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Prevalence of Staphylococcus aureus and Use of Antistaphylococcal Therapy in Children Hospitalized with Pneumonia
Although Staphylococcus aureus pneumonia is common in children with cystic fibrosis and those with healthcare-associated infections (eg, ventilator-associated pneumonia),1,2 S. aureus is an uncommon cause of community-acquired pneumonia in children. In recent years, concerns have arisen about the increasing frequency and severity of staphylococcal pneumonia, largely fueled by the emergence of community-associated methicillin-resistant S. aureus (MRSA).3,4 Thus, therapy with clindamycin or vancomycin, both active against MRSA, has been recommended when S. aureus is suspected.5 Given the lack of rapid and sensitive approaches to the detection of the etiologies of pneumonia, antibiotic selection is most often empirical, contributing to overuse of anti-MRSA antibiotics. In addition, resistance against these antibiotics, especially clindamycin, has been increasing.6,7
A better understanding of the likelihood of staphylococcal pneumonia would help to optimize empirical antibiotic selection, allowing for judicious use of antistaphylococcal antibiotics, while also avoiding poor outcomes due to delays in effective treatment when S. aureus is present.8 Using data from a multicenter, population-based study of pneumonia hospitalizations in children, we sought to describe the prevalence, clinical characteristics, and in-hospital outcomes of staphylococcal pneumonia and the prevalence of antistaphylococcal antibiotic use.
METHODS
The Etiology of Pneumonia in the Community (EPIC) study was a prospective, active, population-based surveillance study of pneumonia hospitalizations among children (age <18 years) conducted between 2010 and 2012 at three children’s hospitals, including two in Tennessee and one in Utah.9 Children hospitalized with clinical evidence of pneumonia and radiographic evidence confirmed by a blinded review by study radiologists were enrolled. Etiologic assessments included blood analysis for bacterial culture, serology for eight respiratory viruses, pneumococcal and group A streptococcal polymerase chain reaction (PCR), and naso/oro-pharyngeal swabs for PCR for 13 respiratory viruses, Mycoplasma pneumoniae, and Chlamydophila pneumoniae. Data from other clinical specimens (pleural fluid, high-quality endotracheal aspirate, or quantified bronchoalveolar lavage fluid) were also recorded. For this study, we included only children with at least one bacterial culture and complete information about antibiotic use. Those with confirmed fungal pneumonia were excluded. Additional details regarding the study population and methods have been published previously.9
Staphylococcal pneumonia was defined based on the detection of S. aureus by culture (any site) or PCR (pleural fluid only), regardless of codetection of other pathogens. Antibiotic susceptibility profiles were used to classify S. aureus isolates as MRSA or methicillin-sensitive S. aureus (MSSA). The remaining children were classified as nonstaphylococcal pneumonia including children with other bacterial pathogens detected (classified as other bacterial pneumonia, excludes atypical bacteria), atypical bacteria, viruses, and no pathogens detected.
Use of anti-MRSA antibiotics (vancomycin, clindamycin, linezolid, doxycycline, and trimethoprim-sulfamethoxazole) and any antistaphylococcal antibiotics (anti-MRSA agents plus oxacillin, nafcillin, and cefazolin) during and after the first two calendar days of admission was identified by medical record review.
Descriptive statistics included number (%) and median (interquartile range, [IQR]) for categorical and continuous variables, respectively. Baseline clinical characteristics and outcomes were compared between children with staphylococcal versus nonstaphylococcal pneumonia, those with staphylococcal versus other bacterial pneumonia, and those with MRSA versus MSSA pneumonia using Wilcoxon rank-sum and Pearson’s chi-square tests where appropriate. To account for multiple comparisons, we used a Bonferroni corrected P value threshold of <.001 to determine statistical significance.
RESULTS
Of the 2,358 children enrolled in the EPIC study hospitalized with radiographically confirmed pneumonia, 2,146 (91.0%) had ≥1 bacterial culture obtained. Two children with Histoplasma capsulatum fungal infection and six children with incomplete antibiotic utilization data were excluded, yielding a final study population of 2,138 children. Among these, blood samples were obtained from 2,134 (>99%) children for culture, pleural fluid from 87 (4%) children, bronchoalveolar lavage fluid from 31 (1%) children, and endotracheal aspirate from 80 (4%) children. Across all culture types, there were 2,332 initial cultures; 2,150 (92%) were collected within the first 24 hours.
Staphylococcal pneumonia was detected in 23 of the 2,138 children (1% [95% CI 0.7, 1.6]; 17 MRSA, 6 MSSA). Of these, 6/23 (26%) had bacteremia, 12/23 (52%) had a positive pleural fluid, and 9/23 (39%) had a positive culture from bronchoalveolar lavage fluid or endotracheal aspirate; 4/23 (17%) children had S. aureus detected from more than one site. Three children (13%) with S. aureus had a viral codetection, including two with influenza.
Compared with children with nonstaphylococcal pneumonia, those with staphylococcal pneumonia were more likely to have a parapneumonic effusion (78% vs 12%, P < .001), but less likely to have cough (78% vs 95%, P < .001). Other baseline characteristics were similar between the two groups. Children with staphylococcal pneumonia had more adverse outcomes than those without (Table), including longer median length of stay (10 vs 3 days, P < .001), more frequent admission to intensive care (83% vs 21%, P < .001), and more frequent invasive mechanical ventilation (65% vs 7%, P < .001). Similar findings were noted when staphylococcal pneumonia was compared with pneumonia caused due to other bacterial pathogens (n = 124). There were no significant differences in baseline characteristics or clinical course between children with MRSA and MSSA pneumonia, although the numbers were small. Overall, S. aureus was detected in 18/267 (7%) children with parapneumonic effusion and 19/462 (4%) children admitted to intensive care. Importantly, there were no confirmed S. aureus cases among children with less severe pneumonia, defined as lacking both parapneumonic effusion and intensive care admission (n = 1,488).
Overall, 519 children (24%) received antistaphylococcal therapy during their hospitalization (512/519, 99% received anti-MRSA therapy), including 22 of the 23 children with S. aureus detected (the only child without antistaphylococcal therapy had S. aureus detected from a high-quality endotracheal tube aspirate only and also had respiratory syncytial virus detected). Clindamycin was most often used (n = 266, 51%), followed by vancomycin (n = 128, 24%), clindamycin plus vancomycin (n = 83, 16%), and others (n = 42, 8%). During the first two days of hospitalization, 479 children (22%) received antistaphylococcal therapy (477 received anti-MRSA therapy). After the first two days, 351 children (16%) received antistaphylococcal therapy (346/351, 99% received anti-MRSA therapy). Use of antistaphylococcal therapy was very common in those admitted to intensive care (182/462, 39%; all but two received anti-MRSA therapy) and in those requiring invasive mechanical ventilation (103/159, 65%). Among those lacking both parapneumonic effusion and intensive care admission (n = 1488), 232 (16%) received antistaphylococcal therapy.
DISCUSSION
In our large, population-based study of >2,000 children hospitalized with community-acquired pneumonia, S. aureus was identified in only 1% of children. Compared with children with other pneumonia etiologies, staphylococcal pneumonia was associated with increased disease severity. Among the small numbers studied, no differences in outcomes were found between children with MRSA and MSSA disease. Despite the low prevalence of staphylococcal pneumonia, almost 1 in 4 children received antistaphylococcal antibiotic therapy; anti-MRSA therapy was used almost exclusively.
The severity of staphylococcal pneumonia was striking, with >80% of children with S. aureus detected being admitted to intensive care, about 65% requiring invasive mechanical ventilation, and >75% with parapneumonic effusion. These findings are similar to those of prior retrospective studies.4,10 The association between staphylococcal pneumonia and adverse outcomes underscores the importance of prompt institution of antimicrobial therapy targeting S. aureus in high-risk patients. This is noteworthy given recent epidemiological data demonstrating increases in MSSA relative to MRSA infections in children,6 and the known superiority of beta-lactam versus vancomycin for MSSA infections, including pneumonia.11
Although detection of staphylococcal infection was rare, almost a quarter of children received antistaphylococcal therapy; nearly all of these children received anti-MRSA therapy. Confirming a bacterial etiology of pneumonia, however, is challenging. Given the severity associated with staphylococcal pneumonia, it is not surprising that use of antistaphylococcal therapy outpaced staphylococcal detections. Antistaphylococcal therapy was especially common in those with severe pneumonia, suggesting that disease severity is an important factor that influences initial antibiotic treatment decisions. Even so, two children with MRSA detected did not initially receive anti-MRSA therapy, highlighting the challenge of balancing judicious antibiotic selection along with ensuring effective treatment. Perhaps more striking is the finding that 16% of children received antistaphylococcal therapy beyond the first two days of hospitalization, presumably after the initial culture results were available. This suggests that clinicians are reluctant to stop antistaphylococcal therapy when the etiology is unknown, although certain features, such as negative cultures, rapid clinical improvement, and lack of risk factors for staphylococcal disease, may provide important clues to support de-escalation of empiric antibiotic therapy. It is also possible that some antibiotics with antistaphylococcal activity were used for alternative indications (eg, clindamycin for penicillin allergy or concern for aspiration pneumonia).
A simple strategy for tailoring antibiotic treatment is maximizing opportunities to identify a causative pathogen. Despite the very low yield of blood cultures in children with pneumonia overall, bacteremia is more common in children with severe pneumonia and those with parapneumonic effusion, especially when cultures are obtained prior to antibiotic use.12,13 Similarly, obtaining pleural fluid is often therapeutic and significantly improves the chances of identifying a bacterial pathogen.14 Moreover, at least one study suggests that S. aureus is much less likely in cases of culture-negative parapneumonic effusions.15 Institutional guidelines, order sets, and antimicrobial stewardship teams are also effective strategies that can facilitate judicious antibiotic use. In particular, stewardship experts can be very useful in assisting clinicians around de-escalation of therapy.16 Use of procalcitonin, a biomarker associated with bacterial infections,17 and prognostic tools to identify risk for adverse outcomes,18 may also inform treatment decisions and are deserving of further study.
Our study must be considered in
Our study demonstrates a very low prevalence of S. aureus detection among children hospitalized with pneumonia and highlights the association between staphylococcal disease and adverse in-hospital outcomes. We also document important discrepancies between disease prevalence and utilization of antistaphylococcal therapy, especially anti-MRSA therapy. Improved approaches are needed to minimize overuse of antistaphylococcal antibiotics while also ensuring adequate therapy for those who need it.
Disclosures
Drs. Zhu, Edwards, Self, Ampofo, Arnold, McCullers, and Williams report grants from the Centers for Disease Control and Prevention during the conduct of the study. Ms. Frush has nothing to disclose. Dr. Jain has nothing to disclose. Dr. Grijalva reports other from Merck, grants and other from Sanofi, other from Pfizer, grants from CDC, grants from AHRQ, grants from NIH, and grants from Campbell Alliance, outside the submitted work. Dr. Self reports grants from CDC, during the conduct of the study; personal fees from Cempra Pharmaceuticals, grants and personal fees from Ferring Pharmaceuticals, personal fees from BioTest AG, personal fees from Abbott Point of Care, personal fees from Gilead Pharmaceuticals, personal fees from Pfizer, grants from Merck, outside the submitted work. Dr. Thomsen has nothing to disclose. Dr. Ampofo reports grants from CDC, during the conduct of the study; other from GlaxoSmithKline, other from Cubist Pharmaceuticals outside the submitted work; and KA collaborate with BioFire Diagnostics, Inc. (formerly Idaho Technology, Inc.) on several NIH grants. Dr. Pavia reports grants from NAID/NIH, grants from NAID/NIH, grants from CDC, personal fees from WebMD, personal fees from Antimicrobial Therapy Inc., outside the submitted work.
Funding
This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number K23AI104779 to D.J.W. and Award 1K23AI113150 to I.P.T., the National Institute of General Medical Sciences under Award K23GM110469 to W.H.S., and the Agency for Healthcare Research and Quality under Award R03HS022342 to C.G.G. The EPIC study was supported by the Influenza Division in the National Center for Immunizations and Respiratory Diseases at the Centers for Disease Control and Prevention through cooperative agreements with each study site and was based on a competitive research funding opportunity. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute of Allergy and Infectious Diseases, the National Institute of General Medical Sciences, the Agency for Healthcare Research and Quality, or the Centers for Disease Control and Prevention.
1. Akil N, Muhlebach MS. Biology and management of methicillin resistant Staphylococcus aureus in cystic fibrosis. Pediatr Pulmonol. 2018. doi: 10.1002/ppul.24139. PubMed
2. Srinivasan R, Asselin J, Gildengorin G, Wiener-Kronish J, Flori HR. A prospective study of ventilator-associated pneumonia in children. Pediatrics.
2009;123(4):1108-1115. doi: 10.1542/peds.2008-1211. PubMed
3. Gonzalez BE, Martinez-Aguilar G, Hulten KG, et al. Severe Staphylococcal sepsis in adolescents in the era of community-acquired methicillin-resistant Staphylococcus aureus. Pediatrics. 2005;115(3):642-648. doi: 10.1542/peds.2004-2300. PubMed
4. Carrillo-Marquez MA, Hulten KG, Hammerman W, Lamberth L, Mason EO, Kaplan SL. Staphylococcus aureus pneumonia in children in the era of community-acquired methicillin-resistance at Texas Children’s Hospital. Pediatr Infect Dis J. 2011;30(7):545-550. doi: 10.1097/INF.0b013e31821618be. PubMed
5. Bradley JS, Byington CL, Shah SS, et al. The management of community-acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the pediatric infectious diseases society and the infectious diseases society of America. Clin Infect Dis. 2011;53(7):e25-e76. doi: 10.1093/cid/cir531. PubMed
6. Sutter DE, Milburn E, Chukwuma U, Dzialowy N, Maranich AM, Hospenthal DR. Changing susceptibility of Staphylococcus aureus in a US pediatric population. Pediatrics. 2016;137(4):e20153099–e20153099. doi: 10.1542/peds.2015-3099. PubMed
7. Sakoulas G, Moellering RC, Jr. Increasing antibiotic resistance among methicillin-resistant Staphylococcus aureus strains. Clin Infect Dis. 2008;46(Suppl 5):S360-S367. doi: 10.1086/533592. PubMed
8. Rubinstein E, Kollef MH, Nathwani D. Pneumonia caused by methicillin-resistant
Staphylococcus aureus. Clin Infect Dis. 2008;46(Suppl 5):S378-S385. doi: 10.1086/533594. PubMed
9. Jain S, Williams DJ, Arnold SR, et al. Community-acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372(9):835-845. doi: 10.1056/NEJMoa1405870. PubMed
10. Kallen AJ, Reed C, Patton M, Arnold KE, Finelli L, Hageman J. Staphylococcus aureus community-onset pneumonia in patients admitted to children’s hospitals during autumn and winter of 2006-2007. Epidemiol Infect. 2010;138(5):666-672. doi: 10.1017/S095026880999135X. PubMed
11. González C, Rubio M, Romero-Vivas J, González M, Picazo JJ. Bacteremic pneumonia due to Staphylococcus aureus: A comparison of disease caused by methicillin-resistant and methicillin-susceptible organisms. Clin Infect Dis. 1999;29(5):1171-1177. doi: 10.1086/313440. PubMed
12. Myers AL, Hall M, Williams DJ, et al. Prevalence of bacteremia in hospitalized pediatric patients with community-acquired pneumonia. Pediatr Infect Dis J. 2013;32(7):736-740. doi: 10.1097/INF.0b013e318290bf63. PubMed
13. Iroh Tam PY, Bernstein E, Ma X, Ferrieri P. Blood culture in evaluation of pediatric community-acquired pneumonia: A systematic review and meta-analysis. Hosp Pediatr. 2015;5(6):324-336. doi: 10.1542/hpeds.2014-0138. PubMed
14. Byington CL, Spencer LY, Johnson TA, et al. An epidemiological investigation of a sustained high rate of pediatric parapneumonic empyema: risk factors and microbiological associations. Clin Infect Dis. 2002;34(4):434-440. doi: 10.1086/338460. PubMed
15. Blaschke AJ, Heyrend C, Byington CL, et al. Molecular analysis improves pathogen identifi cation and epidemiologic study of pediatric parapneumonic empyema. Pediatr Infect Dis J. 2011;30(4):289-294. doi: 10.1097/INF.0b013e3182002d14. PubMed
16. Banerjee R, Teng CB, Cunningham SA, et al. Randomized trial of rapid multiplex polymerase chain reaction-based blood culture identifi cation and susceptibility testing. Clin Infect Dis. 2015;61(7):1071-1080. doi: 10.1093/cid/civ447. PubMed
17. Stockmann C, Ampofo K, Killpack J, et al. Procalcitonin accurately identifies hospitalized children with low risk of bacterial community-acquired pneumonia. J Pediatr Infect Dis Soc. 2018;7(1):46–53. doi: 10.1093/jpids/piw091. PubMed
18. Williams DJ, Zhu Y, Grijalva CG, et al. Predicting severe pneumonia outcomes in children. Pediatrics. 2016;138(4). doi: 10.1542/peds.2016-1019. PubMed
19. Brogan TV, Hall M, Williams DJ, et al. Variability in processes of care and outcomes among children hospitalized with community-acquired pneumonia. Pediatr Infect Dis J. 2012;31(10):1036-1041. doi: 10.1097/INF.0b013e-31825f2b10. PubMed
Although Staphylococcus aureus pneumonia is common in children with cystic fibrosis and those with healthcare-associated infections (eg, ventilator-associated pneumonia),1,2 S. aureus is an uncommon cause of community-acquired pneumonia in children. In recent years, concerns have arisen about the increasing frequency and severity of staphylococcal pneumonia, largely fueled by the emergence of community-associated methicillin-resistant S. aureus (MRSA).3,4 Thus, therapy with clindamycin or vancomycin, both active against MRSA, has been recommended when S. aureus is suspected.5 Given the lack of rapid and sensitive approaches to the detection of the etiologies of pneumonia, antibiotic selection is most often empirical, contributing to overuse of anti-MRSA antibiotics. In addition, resistance against these antibiotics, especially clindamycin, has been increasing.6,7
A better understanding of the likelihood of staphylococcal pneumonia would help to optimize empirical antibiotic selection, allowing for judicious use of antistaphylococcal antibiotics, while also avoiding poor outcomes due to delays in effective treatment when S. aureus is present.8 Using data from a multicenter, population-based study of pneumonia hospitalizations in children, we sought to describe the prevalence, clinical characteristics, and in-hospital outcomes of staphylococcal pneumonia and the prevalence of antistaphylococcal antibiotic use.
METHODS
The Etiology of Pneumonia in the Community (EPIC) study was a prospective, active, population-based surveillance study of pneumonia hospitalizations among children (age <18 years) conducted between 2010 and 2012 at three children’s hospitals, including two in Tennessee and one in Utah.9 Children hospitalized with clinical evidence of pneumonia and radiographic evidence confirmed by a blinded review by study radiologists were enrolled. Etiologic assessments included blood analysis for bacterial culture, serology for eight respiratory viruses, pneumococcal and group A streptococcal polymerase chain reaction (PCR), and naso/oro-pharyngeal swabs for PCR for 13 respiratory viruses, Mycoplasma pneumoniae, and Chlamydophila pneumoniae. Data from other clinical specimens (pleural fluid, high-quality endotracheal aspirate, or quantified bronchoalveolar lavage fluid) were also recorded. For this study, we included only children with at least one bacterial culture and complete information about antibiotic use. Those with confirmed fungal pneumonia were excluded. Additional details regarding the study population and methods have been published previously.9
Staphylococcal pneumonia was defined based on the detection of S. aureus by culture (any site) or PCR (pleural fluid only), regardless of codetection of other pathogens. Antibiotic susceptibility profiles were used to classify S. aureus isolates as MRSA or methicillin-sensitive S. aureus (MSSA). The remaining children were classified as nonstaphylococcal pneumonia including children with other bacterial pathogens detected (classified as other bacterial pneumonia, excludes atypical bacteria), atypical bacteria, viruses, and no pathogens detected.
Use of anti-MRSA antibiotics (vancomycin, clindamycin, linezolid, doxycycline, and trimethoprim-sulfamethoxazole) and any antistaphylococcal antibiotics (anti-MRSA agents plus oxacillin, nafcillin, and cefazolin) during and after the first two calendar days of admission was identified by medical record review.
Descriptive statistics included number (%) and median (interquartile range, [IQR]) for categorical and continuous variables, respectively. Baseline clinical characteristics and outcomes were compared between children with staphylococcal versus nonstaphylococcal pneumonia, those with staphylococcal versus other bacterial pneumonia, and those with MRSA versus MSSA pneumonia using Wilcoxon rank-sum and Pearson’s chi-square tests where appropriate. To account for multiple comparisons, we used a Bonferroni corrected P value threshold of <.001 to determine statistical significance.
RESULTS
Of the 2,358 children enrolled in the EPIC study hospitalized with radiographically confirmed pneumonia, 2,146 (91.0%) had ≥1 bacterial culture obtained. Two children with Histoplasma capsulatum fungal infection and six children with incomplete antibiotic utilization data were excluded, yielding a final study population of 2,138 children. Among these, blood samples were obtained from 2,134 (>99%) children for culture, pleural fluid from 87 (4%) children, bronchoalveolar lavage fluid from 31 (1%) children, and endotracheal aspirate from 80 (4%) children. Across all culture types, there were 2,332 initial cultures; 2,150 (92%) were collected within the first 24 hours.
Staphylococcal pneumonia was detected in 23 of the 2,138 children (1% [95% CI 0.7, 1.6]; 17 MRSA, 6 MSSA). Of these, 6/23 (26%) had bacteremia, 12/23 (52%) had a positive pleural fluid, and 9/23 (39%) had a positive culture from bronchoalveolar lavage fluid or endotracheal aspirate; 4/23 (17%) children had S. aureus detected from more than one site. Three children (13%) with S. aureus had a viral codetection, including two with influenza.
Compared with children with nonstaphylococcal pneumonia, those with staphylococcal pneumonia were more likely to have a parapneumonic effusion (78% vs 12%, P < .001), but less likely to have cough (78% vs 95%, P < .001). Other baseline characteristics were similar between the two groups. Children with staphylococcal pneumonia had more adverse outcomes than those without (Table), including longer median length of stay (10 vs 3 days, P < .001), more frequent admission to intensive care (83% vs 21%, P < .001), and more frequent invasive mechanical ventilation (65% vs 7%, P < .001). Similar findings were noted when staphylococcal pneumonia was compared with pneumonia caused due to other bacterial pathogens (n = 124). There were no significant differences in baseline characteristics or clinical course between children with MRSA and MSSA pneumonia, although the numbers were small. Overall, S. aureus was detected in 18/267 (7%) children with parapneumonic effusion and 19/462 (4%) children admitted to intensive care. Importantly, there were no confirmed S. aureus cases among children with less severe pneumonia, defined as lacking both parapneumonic effusion and intensive care admission (n = 1,488).
Overall, 519 children (24%) received antistaphylococcal therapy during their hospitalization (512/519, 99% received anti-MRSA therapy), including 22 of the 23 children with S. aureus detected (the only child without antistaphylococcal therapy had S. aureus detected from a high-quality endotracheal tube aspirate only and also had respiratory syncytial virus detected). Clindamycin was most often used (n = 266, 51%), followed by vancomycin (n = 128, 24%), clindamycin plus vancomycin (n = 83, 16%), and others (n = 42, 8%). During the first two days of hospitalization, 479 children (22%) received antistaphylococcal therapy (477 received anti-MRSA therapy). After the first two days, 351 children (16%) received antistaphylococcal therapy (346/351, 99% received anti-MRSA therapy). Use of antistaphylococcal therapy was very common in those admitted to intensive care (182/462, 39%; all but two received anti-MRSA therapy) and in those requiring invasive mechanical ventilation (103/159, 65%). Among those lacking both parapneumonic effusion and intensive care admission (n = 1488), 232 (16%) received antistaphylococcal therapy.
DISCUSSION
In our large, population-based study of >2,000 children hospitalized with community-acquired pneumonia, S. aureus was identified in only 1% of children. Compared with children with other pneumonia etiologies, staphylococcal pneumonia was associated with increased disease severity. Among the small numbers studied, no differences in outcomes were found between children with MRSA and MSSA disease. Despite the low prevalence of staphylococcal pneumonia, almost 1 in 4 children received antistaphylococcal antibiotic therapy; anti-MRSA therapy was used almost exclusively.
The severity of staphylococcal pneumonia was striking, with >80% of children with S. aureus detected being admitted to intensive care, about 65% requiring invasive mechanical ventilation, and >75% with parapneumonic effusion. These findings are similar to those of prior retrospective studies.4,10 The association between staphylococcal pneumonia and adverse outcomes underscores the importance of prompt institution of antimicrobial therapy targeting S. aureus in high-risk patients. This is noteworthy given recent epidemiological data demonstrating increases in MSSA relative to MRSA infections in children,6 and the known superiority of beta-lactam versus vancomycin for MSSA infections, including pneumonia.11
Although detection of staphylococcal infection was rare, almost a quarter of children received antistaphylococcal therapy; nearly all of these children received anti-MRSA therapy. Confirming a bacterial etiology of pneumonia, however, is challenging. Given the severity associated with staphylococcal pneumonia, it is not surprising that use of antistaphylococcal therapy outpaced staphylococcal detections. Antistaphylococcal therapy was especially common in those with severe pneumonia, suggesting that disease severity is an important factor that influences initial antibiotic treatment decisions. Even so, two children with MRSA detected did not initially receive anti-MRSA therapy, highlighting the challenge of balancing judicious antibiotic selection along with ensuring effective treatment. Perhaps more striking is the finding that 16% of children received antistaphylococcal therapy beyond the first two days of hospitalization, presumably after the initial culture results were available. This suggests that clinicians are reluctant to stop antistaphylococcal therapy when the etiology is unknown, although certain features, such as negative cultures, rapid clinical improvement, and lack of risk factors for staphylococcal disease, may provide important clues to support de-escalation of empiric antibiotic therapy. It is also possible that some antibiotics with antistaphylococcal activity were used for alternative indications (eg, clindamycin for penicillin allergy or concern for aspiration pneumonia).
A simple strategy for tailoring antibiotic treatment is maximizing opportunities to identify a causative pathogen. Despite the very low yield of blood cultures in children with pneumonia overall, bacteremia is more common in children with severe pneumonia and those with parapneumonic effusion, especially when cultures are obtained prior to antibiotic use.12,13 Similarly, obtaining pleural fluid is often therapeutic and significantly improves the chances of identifying a bacterial pathogen.14 Moreover, at least one study suggests that S. aureus is much less likely in cases of culture-negative parapneumonic effusions.15 Institutional guidelines, order sets, and antimicrobial stewardship teams are also effective strategies that can facilitate judicious antibiotic use. In particular, stewardship experts can be very useful in assisting clinicians around de-escalation of therapy.16 Use of procalcitonin, a biomarker associated with bacterial infections,17 and prognostic tools to identify risk for adverse outcomes,18 may also inform treatment decisions and are deserving of further study.
Our study must be considered in
Our study demonstrates a very low prevalence of S. aureus detection among children hospitalized with pneumonia and highlights the association between staphylococcal disease and adverse in-hospital outcomes. We also document important discrepancies between disease prevalence and utilization of antistaphylococcal therapy, especially anti-MRSA therapy. Improved approaches are needed to minimize overuse of antistaphylococcal antibiotics while also ensuring adequate therapy for those who need it.
Disclosures
Drs. Zhu, Edwards, Self, Ampofo, Arnold, McCullers, and Williams report grants from the Centers for Disease Control and Prevention during the conduct of the study. Ms. Frush has nothing to disclose. Dr. Jain has nothing to disclose. Dr. Grijalva reports other from Merck, grants and other from Sanofi, other from Pfizer, grants from CDC, grants from AHRQ, grants from NIH, and grants from Campbell Alliance, outside the submitted work. Dr. Self reports grants from CDC, during the conduct of the study; personal fees from Cempra Pharmaceuticals, grants and personal fees from Ferring Pharmaceuticals, personal fees from BioTest AG, personal fees from Abbott Point of Care, personal fees from Gilead Pharmaceuticals, personal fees from Pfizer, grants from Merck, outside the submitted work. Dr. Thomsen has nothing to disclose. Dr. Ampofo reports grants from CDC, during the conduct of the study; other from GlaxoSmithKline, other from Cubist Pharmaceuticals outside the submitted work; and KA collaborate with BioFire Diagnostics, Inc. (formerly Idaho Technology, Inc.) on several NIH grants. Dr. Pavia reports grants from NAID/NIH, grants from NAID/NIH, grants from CDC, personal fees from WebMD, personal fees from Antimicrobial Therapy Inc., outside the submitted work.
Funding
This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number K23AI104779 to D.J.W. and Award 1K23AI113150 to I.P.T., the National Institute of General Medical Sciences under Award K23GM110469 to W.H.S., and the Agency for Healthcare Research and Quality under Award R03HS022342 to C.G.G. The EPIC study was supported by the Influenza Division in the National Center for Immunizations and Respiratory Diseases at the Centers for Disease Control and Prevention through cooperative agreements with each study site and was based on a competitive research funding opportunity. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute of Allergy and Infectious Diseases, the National Institute of General Medical Sciences, the Agency for Healthcare Research and Quality, or the Centers for Disease Control and Prevention.
Although Staphylococcus aureus pneumonia is common in children with cystic fibrosis and those with healthcare-associated infections (eg, ventilator-associated pneumonia),1,2 S. aureus is an uncommon cause of community-acquired pneumonia in children. In recent years, concerns have arisen about the increasing frequency and severity of staphylococcal pneumonia, largely fueled by the emergence of community-associated methicillin-resistant S. aureus (MRSA).3,4 Thus, therapy with clindamycin or vancomycin, both active against MRSA, has been recommended when S. aureus is suspected.5 Given the lack of rapid and sensitive approaches to the detection of the etiologies of pneumonia, antibiotic selection is most often empirical, contributing to overuse of anti-MRSA antibiotics. In addition, resistance against these antibiotics, especially clindamycin, has been increasing.6,7
A better understanding of the likelihood of staphylococcal pneumonia would help to optimize empirical antibiotic selection, allowing for judicious use of antistaphylococcal antibiotics, while also avoiding poor outcomes due to delays in effective treatment when S. aureus is present.8 Using data from a multicenter, population-based study of pneumonia hospitalizations in children, we sought to describe the prevalence, clinical characteristics, and in-hospital outcomes of staphylococcal pneumonia and the prevalence of antistaphylococcal antibiotic use.
METHODS
The Etiology of Pneumonia in the Community (EPIC) study was a prospective, active, population-based surveillance study of pneumonia hospitalizations among children (age <18 years) conducted between 2010 and 2012 at three children’s hospitals, including two in Tennessee and one in Utah.9 Children hospitalized with clinical evidence of pneumonia and radiographic evidence confirmed by a blinded review by study radiologists were enrolled. Etiologic assessments included blood analysis for bacterial culture, serology for eight respiratory viruses, pneumococcal and group A streptococcal polymerase chain reaction (PCR), and naso/oro-pharyngeal swabs for PCR for 13 respiratory viruses, Mycoplasma pneumoniae, and Chlamydophila pneumoniae. Data from other clinical specimens (pleural fluid, high-quality endotracheal aspirate, or quantified bronchoalveolar lavage fluid) were also recorded. For this study, we included only children with at least one bacterial culture and complete information about antibiotic use. Those with confirmed fungal pneumonia were excluded. Additional details regarding the study population and methods have been published previously.9
Staphylococcal pneumonia was defined based on the detection of S. aureus by culture (any site) or PCR (pleural fluid only), regardless of codetection of other pathogens. Antibiotic susceptibility profiles were used to classify S. aureus isolates as MRSA or methicillin-sensitive S. aureus (MSSA). The remaining children were classified as nonstaphylococcal pneumonia including children with other bacterial pathogens detected (classified as other bacterial pneumonia, excludes atypical bacteria), atypical bacteria, viruses, and no pathogens detected.
Use of anti-MRSA antibiotics (vancomycin, clindamycin, linezolid, doxycycline, and trimethoprim-sulfamethoxazole) and any antistaphylococcal antibiotics (anti-MRSA agents plus oxacillin, nafcillin, and cefazolin) during and after the first two calendar days of admission was identified by medical record review.
Descriptive statistics included number (%) and median (interquartile range, [IQR]) for categorical and continuous variables, respectively. Baseline clinical characteristics and outcomes were compared between children with staphylococcal versus nonstaphylococcal pneumonia, those with staphylococcal versus other bacterial pneumonia, and those with MRSA versus MSSA pneumonia using Wilcoxon rank-sum and Pearson’s chi-square tests where appropriate. To account for multiple comparisons, we used a Bonferroni corrected P value threshold of <.001 to determine statistical significance.
RESULTS
Of the 2,358 children enrolled in the EPIC study hospitalized with radiographically confirmed pneumonia, 2,146 (91.0%) had ≥1 bacterial culture obtained. Two children with Histoplasma capsulatum fungal infection and six children with incomplete antibiotic utilization data were excluded, yielding a final study population of 2,138 children. Among these, blood samples were obtained from 2,134 (>99%) children for culture, pleural fluid from 87 (4%) children, bronchoalveolar lavage fluid from 31 (1%) children, and endotracheal aspirate from 80 (4%) children. Across all culture types, there were 2,332 initial cultures; 2,150 (92%) were collected within the first 24 hours.
Staphylococcal pneumonia was detected in 23 of the 2,138 children (1% [95% CI 0.7, 1.6]; 17 MRSA, 6 MSSA). Of these, 6/23 (26%) had bacteremia, 12/23 (52%) had a positive pleural fluid, and 9/23 (39%) had a positive culture from bronchoalveolar lavage fluid or endotracheal aspirate; 4/23 (17%) children had S. aureus detected from more than one site. Three children (13%) with S. aureus had a viral codetection, including two with influenza.
Compared with children with nonstaphylococcal pneumonia, those with staphylococcal pneumonia were more likely to have a parapneumonic effusion (78% vs 12%, P < .001), but less likely to have cough (78% vs 95%, P < .001). Other baseline characteristics were similar between the two groups. Children with staphylococcal pneumonia had more adverse outcomes than those without (Table), including longer median length of stay (10 vs 3 days, P < .001), more frequent admission to intensive care (83% vs 21%, P < .001), and more frequent invasive mechanical ventilation (65% vs 7%, P < .001). Similar findings were noted when staphylococcal pneumonia was compared with pneumonia caused due to other bacterial pathogens (n = 124). There were no significant differences in baseline characteristics or clinical course between children with MRSA and MSSA pneumonia, although the numbers were small. Overall, S. aureus was detected in 18/267 (7%) children with parapneumonic effusion and 19/462 (4%) children admitted to intensive care. Importantly, there were no confirmed S. aureus cases among children with less severe pneumonia, defined as lacking both parapneumonic effusion and intensive care admission (n = 1,488).
Overall, 519 children (24%) received antistaphylococcal therapy during their hospitalization (512/519, 99% received anti-MRSA therapy), including 22 of the 23 children with S. aureus detected (the only child without antistaphylococcal therapy had S. aureus detected from a high-quality endotracheal tube aspirate only and also had respiratory syncytial virus detected). Clindamycin was most often used (n = 266, 51%), followed by vancomycin (n = 128, 24%), clindamycin plus vancomycin (n = 83, 16%), and others (n = 42, 8%). During the first two days of hospitalization, 479 children (22%) received antistaphylococcal therapy (477 received anti-MRSA therapy). After the first two days, 351 children (16%) received antistaphylococcal therapy (346/351, 99% received anti-MRSA therapy). Use of antistaphylococcal therapy was very common in those admitted to intensive care (182/462, 39%; all but two received anti-MRSA therapy) and in those requiring invasive mechanical ventilation (103/159, 65%). Among those lacking both parapneumonic effusion and intensive care admission (n = 1488), 232 (16%) received antistaphylococcal therapy.
DISCUSSION
In our large, population-based study of >2,000 children hospitalized with community-acquired pneumonia, S. aureus was identified in only 1% of children. Compared with children with other pneumonia etiologies, staphylococcal pneumonia was associated with increased disease severity. Among the small numbers studied, no differences in outcomes were found between children with MRSA and MSSA disease. Despite the low prevalence of staphylococcal pneumonia, almost 1 in 4 children received antistaphylococcal antibiotic therapy; anti-MRSA therapy was used almost exclusively.
The severity of staphylococcal pneumonia was striking, with >80% of children with S. aureus detected being admitted to intensive care, about 65% requiring invasive mechanical ventilation, and >75% with parapneumonic effusion. These findings are similar to those of prior retrospective studies.4,10 The association between staphylococcal pneumonia and adverse outcomes underscores the importance of prompt institution of antimicrobial therapy targeting S. aureus in high-risk patients. This is noteworthy given recent epidemiological data demonstrating increases in MSSA relative to MRSA infections in children,6 and the known superiority of beta-lactam versus vancomycin for MSSA infections, including pneumonia.11
Although detection of staphylococcal infection was rare, almost a quarter of children received antistaphylococcal therapy; nearly all of these children received anti-MRSA therapy. Confirming a bacterial etiology of pneumonia, however, is challenging. Given the severity associated with staphylococcal pneumonia, it is not surprising that use of antistaphylococcal therapy outpaced staphylococcal detections. Antistaphylococcal therapy was especially common in those with severe pneumonia, suggesting that disease severity is an important factor that influences initial antibiotic treatment decisions. Even so, two children with MRSA detected did not initially receive anti-MRSA therapy, highlighting the challenge of balancing judicious antibiotic selection along with ensuring effective treatment. Perhaps more striking is the finding that 16% of children received antistaphylococcal therapy beyond the first two days of hospitalization, presumably after the initial culture results were available. This suggests that clinicians are reluctant to stop antistaphylococcal therapy when the etiology is unknown, although certain features, such as negative cultures, rapid clinical improvement, and lack of risk factors for staphylococcal disease, may provide important clues to support de-escalation of empiric antibiotic therapy. It is also possible that some antibiotics with antistaphylococcal activity were used for alternative indications (eg, clindamycin for penicillin allergy or concern for aspiration pneumonia).
A simple strategy for tailoring antibiotic treatment is maximizing opportunities to identify a causative pathogen. Despite the very low yield of blood cultures in children with pneumonia overall, bacteremia is more common in children with severe pneumonia and those with parapneumonic effusion, especially when cultures are obtained prior to antibiotic use.12,13 Similarly, obtaining pleural fluid is often therapeutic and significantly improves the chances of identifying a bacterial pathogen.14 Moreover, at least one study suggests that S. aureus is much less likely in cases of culture-negative parapneumonic effusions.15 Institutional guidelines, order sets, and antimicrobial stewardship teams are also effective strategies that can facilitate judicious antibiotic use. In particular, stewardship experts can be very useful in assisting clinicians around de-escalation of therapy.16 Use of procalcitonin, a biomarker associated with bacterial infections,17 and prognostic tools to identify risk for adverse outcomes,18 may also inform treatment decisions and are deserving of further study.
Our study must be considered in
Our study demonstrates a very low prevalence of S. aureus detection among children hospitalized with pneumonia and highlights the association between staphylococcal disease and adverse in-hospital outcomes. We also document important discrepancies between disease prevalence and utilization of antistaphylococcal therapy, especially anti-MRSA therapy. Improved approaches are needed to minimize overuse of antistaphylococcal antibiotics while also ensuring adequate therapy for those who need it.
Disclosures
Drs. Zhu, Edwards, Self, Ampofo, Arnold, McCullers, and Williams report grants from the Centers for Disease Control and Prevention during the conduct of the study. Ms. Frush has nothing to disclose. Dr. Jain has nothing to disclose. Dr. Grijalva reports other from Merck, grants and other from Sanofi, other from Pfizer, grants from CDC, grants from AHRQ, grants from NIH, and grants from Campbell Alliance, outside the submitted work. Dr. Self reports grants from CDC, during the conduct of the study; personal fees from Cempra Pharmaceuticals, grants and personal fees from Ferring Pharmaceuticals, personal fees from BioTest AG, personal fees from Abbott Point of Care, personal fees from Gilead Pharmaceuticals, personal fees from Pfizer, grants from Merck, outside the submitted work. Dr. Thomsen has nothing to disclose. Dr. Ampofo reports grants from CDC, during the conduct of the study; other from GlaxoSmithKline, other from Cubist Pharmaceuticals outside the submitted work; and KA collaborate with BioFire Diagnostics, Inc. (formerly Idaho Technology, Inc.) on several NIH grants. Dr. Pavia reports grants from NAID/NIH, grants from NAID/NIH, grants from CDC, personal fees from WebMD, personal fees from Antimicrobial Therapy Inc., outside the submitted work.
Funding
This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number K23AI104779 to D.J.W. and Award 1K23AI113150 to I.P.T., the National Institute of General Medical Sciences under Award K23GM110469 to W.H.S., and the Agency for Healthcare Research and Quality under Award R03HS022342 to C.G.G. The EPIC study was supported by the Influenza Division in the National Center for Immunizations and Respiratory Diseases at the Centers for Disease Control and Prevention through cooperative agreements with each study site and was based on a competitive research funding opportunity. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute of Allergy and Infectious Diseases, the National Institute of General Medical Sciences, the Agency for Healthcare Research and Quality, or the Centers for Disease Control and Prevention.
1. Akil N, Muhlebach MS. Biology and management of methicillin resistant Staphylococcus aureus in cystic fibrosis. Pediatr Pulmonol. 2018. doi: 10.1002/ppul.24139. PubMed
2. Srinivasan R, Asselin J, Gildengorin G, Wiener-Kronish J, Flori HR. A prospective study of ventilator-associated pneumonia in children. Pediatrics.
2009;123(4):1108-1115. doi: 10.1542/peds.2008-1211. PubMed
3. Gonzalez BE, Martinez-Aguilar G, Hulten KG, et al. Severe Staphylococcal sepsis in adolescents in the era of community-acquired methicillin-resistant Staphylococcus aureus. Pediatrics. 2005;115(3):642-648. doi: 10.1542/peds.2004-2300. PubMed
4. Carrillo-Marquez MA, Hulten KG, Hammerman W, Lamberth L, Mason EO, Kaplan SL. Staphylococcus aureus pneumonia in children in the era of community-acquired methicillin-resistance at Texas Children’s Hospital. Pediatr Infect Dis J. 2011;30(7):545-550. doi: 10.1097/INF.0b013e31821618be. PubMed
5. Bradley JS, Byington CL, Shah SS, et al. The management of community-acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the pediatric infectious diseases society and the infectious diseases society of America. Clin Infect Dis. 2011;53(7):e25-e76. doi: 10.1093/cid/cir531. PubMed
6. Sutter DE, Milburn E, Chukwuma U, Dzialowy N, Maranich AM, Hospenthal DR. Changing susceptibility of Staphylococcus aureus in a US pediatric population. Pediatrics. 2016;137(4):e20153099–e20153099. doi: 10.1542/peds.2015-3099. PubMed
7. Sakoulas G, Moellering RC, Jr. Increasing antibiotic resistance among methicillin-resistant Staphylococcus aureus strains. Clin Infect Dis. 2008;46(Suppl 5):S360-S367. doi: 10.1086/533592. PubMed
8. Rubinstein E, Kollef MH, Nathwani D. Pneumonia caused by methicillin-resistant
Staphylococcus aureus. Clin Infect Dis. 2008;46(Suppl 5):S378-S385. doi: 10.1086/533594. PubMed
9. Jain S, Williams DJ, Arnold SR, et al. Community-acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372(9):835-845. doi: 10.1056/NEJMoa1405870. PubMed
10. Kallen AJ, Reed C, Patton M, Arnold KE, Finelli L, Hageman J. Staphylococcus aureus community-onset pneumonia in patients admitted to children’s hospitals during autumn and winter of 2006-2007. Epidemiol Infect. 2010;138(5):666-672. doi: 10.1017/S095026880999135X. PubMed
11. González C, Rubio M, Romero-Vivas J, González M, Picazo JJ. Bacteremic pneumonia due to Staphylococcus aureus: A comparison of disease caused by methicillin-resistant and methicillin-susceptible organisms. Clin Infect Dis. 1999;29(5):1171-1177. doi: 10.1086/313440. PubMed
12. Myers AL, Hall M, Williams DJ, et al. Prevalence of bacteremia in hospitalized pediatric patients with community-acquired pneumonia. Pediatr Infect Dis J. 2013;32(7):736-740. doi: 10.1097/INF.0b013e318290bf63. PubMed
13. Iroh Tam PY, Bernstein E, Ma X, Ferrieri P. Blood culture in evaluation of pediatric community-acquired pneumonia: A systematic review and meta-analysis. Hosp Pediatr. 2015;5(6):324-336. doi: 10.1542/hpeds.2014-0138. PubMed
14. Byington CL, Spencer LY, Johnson TA, et al. An epidemiological investigation of a sustained high rate of pediatric parapneumonic empyema: risk factors and microbiological associations. Clin Infect Dis. 2002;34(4):434-440. doi: 10.1086/338460. PubMed
15. Blaschke AJ, Heyrend C, Byington CL, et al. Molecular analysis improves pathogen identifi cation and epidemiologic study of pediatric parapneumonic empyema. Pediatr Infect Dis J. 2011;30(4):289-294. doi: 10.1097/INF.0b013e3182002d14. PubMed
16. Banerjee R, Teng CB, Cunningham SA, et al. Randomized trial of rapid multiplex polymerase chain reaction-based blood culture identifi cation and susceptibility testing. Clin Infect Dis. 2015;61(7):1071-1080. doi: 10.1093/cid/civ447. PubMed
17. Stockmann C, Ampofo K, Killpack J, et al. Procalcitonin accurately identifies hospitalized children with low risk of bacterial community-acquired pneumonia. J Pediatr Infect Dis Soc. 2018;7(1):46–53. doi: 10.1093/jpids/piw091. PubMed
18. Williams DJ, Zhu Y, Grijalva CG, et al. Predicting severe pneumonia outcomes in children. Pediatrics. 2016;138(4). doi: 10.1542/peds.2016-1019. PubMed
19. Brogan TV, Hall M, Williams DJ, et al. Variability in processes of care and outcomes among children hospitalized with community-acquired pneumonia. Pediatr Infect Dis J. 2012;31(10):1036-1041. doi: 10.1097/INF.0b013e-31825f2b10. PubMed
1. Akil N, Muhlebach MS. Biology and management of methicillin resistant Staphylococcus aureus in cystic fibrosis. Pediatr Pulmonol. 2018. doi: 10.1002/ppul.24139. PubMed
2. Srinivasan R, Asselin J, Gildengorin G, Wiener-Kronish J, Flori HR. A prospective study of ventilator-associated pneumonia in children. Pediatrics.
2009;123(4):1108-1115. doi: 10.1542/peds.2008-1211. PubMed
3. Gonzalez BE, Martinez-Aguilar G, Hulten KG, et al. Severe Staphylococcal sepsis in adolescents in the era of community-acquired methicillin-resistant Staphylococcus aureus. Pediatrics. 2005;115(3):642-648. doi: 10.1542/peds.2004-2300. PubMed
4. Carrillo-Marquez MA, Hulten KG, Hammerman W, Lamberth L, Mason EO, Kaplan SL. Staphylococcus aureus pneumonia in children in the era of community-acquired methicillin-resistance at Texas Children’s Hospital. Pediatr Infect Dis J. 2011;30(7):545-550. doi: 10.1097/INF.0b013e31821618be. PubMed
5. Bradley JS, Byington CL, Shah SS, et al. The management of community-acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the pediatric infectious diseases society and the infectious diseases society of America. Clin Infect Dis. 2011;53(7):e25-e76. doi: 10.1093/cid/cir531. PubMed
6. Sutter DE, Milburn E, Chukwuma U, Dzialowy N, Maranich AM, Hospenthal DR. Changing susceptibility of Staphylococcus aureus in a US pediatric population. Pediatrics. 2016;137(4):e20153099–e20153099. doi: 10.1542/peds.2015-3099. PubMed
7. Sakoulas G, Moellering RC, Jr. Increasing antibiotic resistance among methicillin-resistant Staphylococcus aureus strains. Clin Infect Dis. 2008;46(Suppl 5):S360-S367. doi: 10.1086/533592. PubMed
8. Rubinstein E, Kollef MH, Nathwani D. Pneumonia caused by methicillin-resistant
Staphylococcus aureus. Clin Infect Dis. 2008;46(Suppl 5):S378-S385. doi: 10.1086/533594. PubMed
9. Jain S, Williams DJ, Arnold SR, et al. Community-acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372(9):835-845. doi: 10.1056/NEJMoa1405870. PubMed
10. Kallen AJ, Reed C, Patton M, Arnold KE, Finelli L, Hageman J. Staphylococcus aureus community-onset pneumonia in patients admitted to children’s hospitals during autumn and winter of 2006-2007. Epidemiol Infect. 2010;138(5):666-672. doi: 10.1017/S095026880999135X. PubMed
11. González C, Rubio M, Romero-Vivas J, González M, Picazo JJ. Bacteremic pneumonia due to Staphylococcus aureus: A comparison of disease caused by methicillin-resistant and methicillin-susceptible organisms. Clin Infect Dis. 1999;29(5):1171-1177. doi: 10.1086/313440. PubMed
12. Myers AL, Hall M, Williams DJ, et al. Prevalence of bacteremia in hospitalized pediatric patients with community-acquired pneumonia. Pediatr Infect Dis J. 2013;32(7):736-740. doi: 10.1097/INF.0b013e318290bf63. PubMed
13. Iroh Tam PY, Bernstein E, Ma X, Ferrieri P. Blood culture in evaluation of pediatric community-acquired pneumonia: A systematic review and meta-analysis. Hosp Pediatr. 2015;5(6):324-336. doi: 10.1542/hpeds.2014-0138. PubMed
14. Byington CL, Spencer LY, Johnson TA, et al. An epidemiological investigation of a sustained high rate of pediatric parapneumonic empyema: risk factors and microbiological associations. Clin Infect Dis. 2002;34(4):434-440. doi: 10.1086/338460. PubMed
15. Blaschke AJ, Heyrend C, Byington CL, et al. Molecular analysis improves pathogen identifi cation and epidemiologic study of pediatric parapneumonic empyema. Pediatr Infect Dis J. 2011;30(4):289-294. doi: 10.1097/INF.0b013e3182002d14. PubMed
16. Banerjee R, Teng CB, Cunningham SA, et al. Randomized trial of rapid multiplex polymerase chain reaction-based blood culture identifi cation and susceptibility testing. Clin Infect Dis. 2015;61(7):1071-1080. doi: 10.1093/cid/civ447. PubMed
17. Stockmann C, Ampofo K, Killpack J, et al. Procalcitonin accurately identifies hospitalized children with low risk of bacterial community-acquired pneumonia. J Pediatr Infect Dis Soc. 2018;7(1):46–53. doi: 10.1093/jpids/piw091. PubMed
18. Williams DJ, Zhu Y, Grijalva CG, et al. Predicting severe pneumonia outcomes in children. Pediatrics. 2016;138(4). doi: 10.1542/peds.2016-1019. PubMed
19. Brogan TV, Hall M, Williams DJ, et al. Variability in processes of care and outcomes among children hospitalized with community-acquired pneumonia. Pediatr Infect Dis J. 2012;31(10):1036-1041. doi: 10.1097/INF.0b013e-31825f2b10. PubMed
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<root generator="drupal.xsl" gversion="1.7"> <header> <fileName>Frush0328</fileName> <TBEID>0C018036.SIG</TBEID> <TBUniqueIdentifier>NJ_0C018036</TBUniqueIdentifier> <newsOrJournal>Journal</newsOrJournal> <publisherName>Frontline Medical Communications Inc.</publisherName> <storyname/> <articleType>1</articleType> <TBLocation>Copyfitting-JHM</TBLocation> <QCDate/> <firstPublished>20181008T141143</firstPublished> <LastPublished>20181008T141143</LastPublished> <pubStatus qcode="stat:"/> <embargoDate/> <killDate/> <CMSDate>20181008T141143</CMSDate> <articleSource/> <facebookInfo/> <meetingNumber/> <byline/> <bylineText> Jennifer M. Frush, BA1, Yuwei Zhu, MD, MS2, Kathryn M. Edwards, MD3, Carlos G. Grijalva, MD, MPH4, Isaac P. Thomsen, MD, MSCI3, Wesley H. Self, MD, MPH5, Seema Jain, MD6, Evan J. Anderson, MD7, Krow Ampofo, MD8, Andrew T. Pavia, MD8, Sandra R. Arnold MD9, Jonathan A. McCullers MD9, Derek J. Williams, MD, MPH10* </bylineText> <bylineFull/> <bylineTitleText/> <USOrGlobal/> <wireDocType/> <newsDocType/> <journalDocType/> <linkLabel/> <pageRange/> <citation/> <quizID/> <indexIssueDate/> <itemClass qcode="ninat:text"/> <provider qcode="provider:"> <name/> <rightsInfo> <copyrightHolder> <name/> </copyrightHolder> <copyrightNotice/> </rightsInfo> </provider> <abstract>Within a cohort of >2,000 children hospitalized with community-acquired pneumonia, staphylococcal pneumonia was rare (1%) but associated with adverse in-hospital outcomes. Despite this low prevalence, use of antistaphylococcal antibiotics was common (24%). Efforts are needed to minimize overuse of antistaphylococcal antibiotics while also ensuring adequate treatment for pathogen-specific diseases.</abstract> <metaDescription>*Address for correspondence: Derek J. Williams, MD, MPH, Vanderbilt University Medical Center, DOT11205, 2200 Children’s Way, Nashville, TN 37232-9000; E-mail: </metaDescription> <articlePDF/> <teaserImage/> <title>Prevalence of Staphylococcus aureus and Use of Antistaphylococcal Therapy in Children Hospitalized with Pneumonia</title> <deck/> <eyebrow>online first october 31, 2018—BRIEF REPORT</eyebrow> <disclaimer/> <AuthorList> <Author> <FirstName/> <MiddleName/> <LastName/> <Suffix/> <Affiliation/> </Author> </AuthorList> <articleURL/> <doi>10.12788/jhm.3093</doi> <pubMedID/> <publishXMLStatus/> <publishXMLVersion>1</publishXMLVersion> <useEISSN>0</useEISSN> <urgency/> <pubPubdateYear/> <pubPubdateMonth/> <pubPubdateDay/> <pubVolume/> <pubNumber/> <wireChannels/> <primaryCMSID/> <CMSIDs/> <keywords/> <seeAlsos/> <publications_g> <publicationData> <publicationCode>jhm</publicationCode> <pubIssueName/> <pubArticleType/> <pubTopics/> <pubCategories/> <pubSections/> <journalTitle/> <journalFullTitle/> <copyrightStatement/> </publicationData> </publications_g> <publications> <term canonical="true">27312</term> </publications> <sections> <term>28090</term> <term canonical="true">27619</term> </sections> <topics> <term canonical="true">327</term> </topics> <links/> </header> <itemSet> <newsItem> <itemMeta> <itemRole>Main</itemRole> <itemClass>text</itemClass> <title>Prevalence of Staphylococcus aureus and Use of Antistaphylococcal Therapy in Children Hospitalized with Pneumonia</title> <deck/> </itemMeta> <itemContent> <p class="affiliation"><sup>1</sup>Duke University School of Medicine, Durham, North Carolina; <sup>2</sup>Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee; <sup>3</sup>Division of Infectious Diseases, Monroe Carell Jr. Children’s Hospital and the Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee; <sup>4</sup>Department of Health Policy, Vanderbilt University School of Medicine, Nashville, Tennessee; <sup>5</sup>Department of Emergency Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee; <sup>6</sup>Centers for Disease Control and Prevention, Atlanta, Georgia; <sup>7</sup>Division of Infectious Diseases, Departments of Medicine and Pediatrics, Emory University School of Medicine, Atlanta, Georgia; <sup>8</sup>Division of Infectious Diseases, Primary Children’s Medical Center and the Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah; <sup>9</sup>Division of Infectious Diseases, LeBonheur Children’s Hospital and the Department of Pediatrics, University of Tennessee Health Sciences Center, Memphis, Tennessee; <sup>10</sup>Division of Hospital Medicine, Monroe Carell Jr. Children’s Hospital and the Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee.</p> <p class="abstract"> Journal of Hospital Medicine 2018;13:XXX-XXX. © 2018 Society of Hospital Medicine</p> <p>*Address for correspondence: Derek J. Williams, MD, MPH, Vanderbilt University Medical Center, DOT11205, 2200 Children’s Way, Nashville, TN 37232-9000; E-mail: derek.williams@vumc.org</p> <p>Received: June 4, 2018; Revised: August 21, 2018; Accepted: September 3, 2018<br/><br/><strong>©</strong><strong>2018 Society of Hospital Medicine DOI 10.12788/jhm.3093</strong></p> <p>Although Staphylococcus aureus pneumonia is common in children with cystic fibrosis and those with healthcare-associated infections (eg, ventilator-associated pneumonia),<sup>1,2</sup> S. aureus is an uncommon cause of community-acquired pneumonia in children. In recent years, concerns have arisen about the increasing frequency and severity of staphylococcal pneumonia, largely fueled by the emergence of community-associated methicillin-resistant S. aureus (MRSA).<sup>3,4 </sup>Thus, therapy with clindamycin or vancomycin, both active against MRSA, has been recommended when S. aureus is suspected.<sup>5</sup> Given the lack of rapid and sensitive approaches to the detection of the etiologies of pneumonia, antibiotic selection is most often empirical, contributing to overuse of anti-MRSA antibiotics. In addition, resistance against these antibiotics, especially clindamycin, has been increasing.<sup>6,7</sup></p> <p>A better understanding of the likelihood of staphylococcal pneumonia would help to optimize empirical antibiotic selection, allowing for judicious use of antistaphylococcal antibiotics, while also avoiding poor outcomes due to delays in effective treatment when S. aureus is present.<sup>8</sup> Using data from a multicenter, population-based study of pneumonia hospitalizations in children, we sought to describe the prevalence, clinical characteristics, and in-hospital outcomes of staphylococcal pneumonia and the prevalence of antistaphylococcal antibiotic use.</p> <h2>METHODS</h2> <p>The Etiology of Pneumonia in the Community (EPIC) study was a prospective, active, population-based surveillance study of pneumonia hospitalizations among children (age <18 years) conducted between 2010 and 2012 at three children’s hospitals, including two in Tennessee and one in Utah.<sup>9</sup> Children hospitalized with clinical evidence of pneumonia and radiographic evidence confirmed by a blinded review by study radiologists were enrolled. Etiologic assessments included blood analysis for bacterial culture, serology for eight respiratory viruses, pneumococcal and group A streptococcal polymerase chain reaction (PCR), and naso/oro-pharyngeal swabs for PCR for 13 respiratory viruses, Mycoplasma pneumoniae, and Chlamydophila pneumoniae. Data from other clinical specimens (pleural fluid, high-quality endotracheal aspirate, or quantified bronchoalveolar lavage fluid) were also recorded. For this study, we included only children with at least one bacterial culture and complete information about antibiotic use. Those with confirmed fungal pneumonia were excluded. Additional details regarding the study population and methods have been published previously.<sup>9</sup></p> <p>Staphylococcal pneumonia was defined based on the detection of S. aureus by culture (any site) or PCR (pleural fluid only), regardless of codetection of other pathogens. Antibiotic susceptibility profiles were used to classify S. aureus isolates as MRSA or methicillin-sensitive S. aureus (MSSA). The remaining children were classified as nonstaphylococcal pneumonia including children with other bacterial pathogens detected (classified as other bacterial pneumonia, excludes atypical bacteria), atypical bacteria, viruses, and no pathogens detected. <br/><br/>Use of anti-MRSA antibiotics (vancomycin, clindamycin, linezolid, doxycycline, and trimethoprim-sulfamethoxazole) and any antistaphylococcal antibiotics (anti-MRSA agents plus oxacillin, nafcillin, and cefazolin) during and after the first two calendar days of admission was identified by medical record review. <br/><br/>Descriptive statistics included number (%) and median (interquartile range, [IQR]) for categorical and continuous variables, respectively. Baseline clinical characteristics and outcomes were compared between children with staphylococcal versus nonstaphylococcal pneumonia, those with staphylococcal versus other bacterial pneumonia, and those with MRSA versus MSSA pneumonia using Wilcoxon rank-sum and Pearson’s chi-square tests where appropriate. To account for multiple comparisons, we used a Bonferroni corrected P value threshold of <.001 to determine statistical significance.</p> <h2>RESULTS</h2> <p>Of the 2,358 children enrolled in the EPIC study hospitalized with radiographically confirmed pneumonia, 2,146 (91.0%) had ≥1 bacterial culture obtained. Two children with Histoplasma capsulatum fungal infection and six children with incomplete antibiotic utilization data were excluded, yielding a final study population of 2,138 children. Among these, blood samples were obtained from 2,134 (>99%) children for culture, pleural fluid from 87 (4%) children, bronchoalveolar lavage fluid from 31 (1%) children, and endotracheal aspirate from 80 (4%) children. Across all culture types, there were 2,332 initial cultures; 2,150 (92%) were collected within the first 24 hours.</p> <p>Staphylococcal pneumonia was detected in 23 of the 2,138 children (1% [95% CI 0.7, 1.6]; 17 MRSA, 6 MSSA). Of these, 6/23 (26%) had bacteremia, 12/23 (52%) had a positive pleural fluid, and 9/23 (39%) had a positive culture from bronchoalveolar lavage fluid or endotracheal aspirate; 4/23 (17%) children had S. aureus detected from more than one site. Three children (13%) with S. aureus had a viral codetection, including two with influenza.<br/><br/>Compared with children with nonstaphylococcal pneumonia, those with staphylococcal pneumonia were more likely to have a parapneumonic effusion (78% vs 12%, P < .001), but less likely to have cough (78% vs 95%, P < .001). Other baseline characteristics were similar between the two groups. Children with staphylococcal pneumonia had more adverse outcomes than those without (Table), including longer median length of stay (10 vs 3 days, P < .001), more frequent admission to intensive care (83% vs 21%, P < .001), and more frequent invasive mechanical ventilation (65% vs 7%, P < .001). Similar findings were noted when staphylococcal pneumonia was compared with pneumonia caused due to other bacterial pathogens (n = 124). There were no significant differences in baseline characteristics or clinical course between children with MRSA and MSSA pneumonia, although the numbers were small. Overall, S. aureus was detected in 18/267 (7%) children with parapneumonic effusion and 19/462 (4%) children admitted to intensive care. Importantly, there were no confirmed S. aureus cases among children with less severe pneumonia, defined as lacking both parapneumonic effusion and intensive care admission (n = 1,488). <br/><br/>Overall, 519 children (24%) received antistaphylococcal therapy during their hospitalization (512/519, 99% received anti-MRSA therapy), including 22 of the 23 children with S. aureus detected (the only child without antistaphylococcal therapy had S. aureus detected from a high-quality endotracheal tube aspirate only and also had respiratory syncytial virus detected). Clindamycin was most often used (n = 266, 51%), followed by vancomycin (n = 128, 24%), clindamycin plus vancomycin (n = 83, 16%), and others (n = 42, 8%). During the first two days of hospitalization, 479 children (22%) received antistaphylococcal therapy (477 received anti-MRSA therapy). After the first two days, 351 children (16%) received antistaphylococcal therapy (346/351, 99% received anti-MRSA therapy). Use of antistaphylococcal therapy was very common in those admitted to intensive care (182/462, 39%; all but two received anti-MRSA therapy) and in those requiring invasive mechanical ventilation (103/159, 65%). Among those lacking both parapneumonic effusion and intensive care admission (n = 1488), 232 (16%) received antistaphylococcal therapy.</p> <h2>DISCUSSION</h2> <p>In our large, population-based study of >2,000 children hospitalized with community-acquired pneumonia, S. aureus was identified in only 1% of children. Compared with children with other pneumonia etiologies, staphylococcal pneumonia was associated with increased disease severity. Among the small numbers studied, no differences in outcomes were found between children with MRSA and MSSA disease. Despite the low prevalence of staphylococcal pneumonia, almost 1 in 4 children received antistaphylococcal antibiotic therapy; anti-MRSA therapy was used almost exclusively. </p> <p>The severity of staphylococcal pneumonia was striking, with >80% of children with S. aureus detected being admitted to intensive care, about 65% requiring invasive mechanical ventilation, and >75% with parapneumonic effusion. These findings are similar to those of prior retrospective studies.<sup>4,10</sup> The association between staphylococcal pneumonia and adverse outcomes underscores the importance of prompt institution of antimicrobial therapy targeting S. aureus in high-risk patients. This is noteworthy given recent epidemiological data demonstrating increases in MSSA relative to MRSA infections in children,<sup>6</sup> and the known superiority of beta-lactam versus vancomycin for MSSA infections, including pneumonia.<sup>11<br/><br/></sup>Although detection of staphylococcal infection was rare, almost a quarter of children received antistaphylococcal therapy; nearly all of these children received anti-MRSA therapy. Confirming a bacterial etiology of pneumonia, however, is challenging. Given the severity associated with staphylococcal pneumonia, it is not surprising that use of antistaphylococcal therapy outpaced staphylococcal detections. Antistaphylococcal therapy was especially common in those with severe pneumonia, suggesting that disease severity is an important factor that influences initial antibiotic treatment decisions. Even so, two children with MRSA detected did not initially receive anti-MRSA therapy, highlighting the challenge of balancing judicious antibiotic selection along with ensuring effective treatment. Perhaps more striking is the finding that 16% of children received antistaphylococcal therapy beyond the first two days of hospitalization, presumably after the initial culture results were available. This suggests that clinicians are reluctant to stop antistaphylococcal therapy when the etiology is unknown, although certain features, such as negative cultures, rapid clinical improvement, and lack of risk factors for staphylococcal disease, may provide important clues to support de-escalation of empiric antibiotic therapy. It is also possible that some antibiotics with antistaphylococcal activity were used for alternative indications (eg, clindamycin for penicillin allergy or concern for aspiration pneumonia).<br/><br/>A simple strategy for tailoring antibiotic treatment is maximizing opportunities to identify a causative pathogen. Despite the very low yield of blood cultures in children with pneumonia overall, bacteremia is more common in children with severe pneumonia and those with parapneumonic effusion, especially when cultures are obtained prior to antibiotic use.<sup>12,13</sup> Similarly, obtaining pleural fluid is often therapeutic and significantly improves the chances of identifying a bacterial pathogen.<sup>14</sup> Moreover, at least one study suggests that S. aureus is much less likely in cases of culture-negative parapneumonic effusions.<sup>15</sup> Institutional guidelines, order sets, and antimicrobial stewardship teams are also effective strategies that can facilitate judicious antibiotic use. In particular, stewardship experts can be very useful in assisting clinicians around de-escalation of therapy.<sup>16</sup> Use of procalcitonin, a biomarker associated with bacterial infections,<sup>17</sup> and prognostic tools to identify risk for adverse outcomes,<sup>18</sup> may also inform treatment decisions and are deserving of further study. <br/><br/>Our study must be considered in <hl name="19"/>the light of its strengths and limitations. Analysis was derived from a population-based surveillance study of community-acquired pneumonia hospitalizations in three children’s hospitals and may not be generalizable to other settings. Nevertheless, the antibiotic-prescribing practices identified in our study are consistent with those from a larger network of children’s hospitals in the United States.<sup>19</sup> The relatively small number of children with S. aureus identified limited our ability to control for potential confounding factors. Some cases of staphylococcal pneumonia may not have been identified. All study children, however, were prospectively enrolled and had samples systematically collected and tested for etiology, likely leading to few cases of misclassification for this pathogen. <br/><br/>Our study demonstrates a very low prevalence of S. aureus detection among children hospitalized with pneumonia and highlights the association between staphylococcal disease and adverse in-hospital outcomes. We also document important discrepancies between disease prevalence and utilization of antistaphylococcal therapy, especially anti-MRSA therapy. Improved approaches are needed to minimize overuse of antistaphylococcal antibiotics while also ensuring adequate therapy for those who need it. </p> <p>Disclosures: Drs. Zhu, Edwards, Self, Ampofo, Arnold, McCullers, and Williams report grants from the Centers for Disease Control and Prevention during the conduct of the study. Ms. Frush has nothing to disclose. Dr. Jain has nothing to disclose. Dr. Grijalva reports other from Merck, grants and other from Sanofi, other from Pfizer, grants from CDC, grants from AHRQ, grants from NIH, and grants from Campbell Alliance, outside the submitted work. Dr. Self reports grants from CDC, during the conduct of the study; personal fees from Cempra Pharmaceuticals, grants and personal fees from Ferring Pharmaceuticals, personal fees from BioTest AG, personal fees from Abbott Point of Care, personal fees from Gilead Pharmaceuticals, personal fees from Pfizer, grants from Merck, outside the submitted work. Dr. Thomsen has nothing to disclose. Dr. Ampofo reports grants from CDC, during the conduct of the study; other from GlaxoSmithKline, other from Cubist Pharmaceuticals outside the submitted work; and KA collaborate with BioFire Diagnostics, Inc. (formerly Idaho Technology, Inc.) on several NIH grants. Dr. Pavia reports grants from NAID/NIH, grants from NAID/NIH, grants from CDC, personal fees from WebMD, personal fees from Antimicrobial Therapy Inc., outside the submitted work.</p> <p>Funding: This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number K23AI104779 to D.J.W. and Award 1K23AI113150 to I.P.T., the National Institute of General Medical Sciences under Award K23GM110469 to W.H.S., and the Agency for Healthcare Research and Quality under Award R03HS022342 to C.G.G. The EPIC study was supported by the Influenza Division in the National Center for Immunizations and Respiratory Diseases at the Centers for Disease Control and Prevention through cooperative agreements with each study site and was based on a competitive research funding opportunity. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute of Allergy and Infectious Diseases, the National Institute of General Medical Sciences, the Agency for Healthcare Research and Quality, or the Centers for Disease Control and Prevention.</p> <p class="references">1. Akil N, Muhlebach MS. Biology and management of methicillin resistant Staphylococcus aureus in cystic fibrosis. Pediatr Pulmonol. 2018. doi: 10.1002/ppul.24139.</p> </itemContent> </newsItem> </itemSet></root>
©2018 Society of Hospital Medicine
Impact of Pneumonia Guidelines
Overutilization of resources is a significant, yet underappreciated, problem in medicine. Many interventions target underutilization (eg, immunizations) or misuse (eg, antibiotic prescribing for viral pharyngitis), yet overutilization remains as a significant contributor to healthcare waste.[1] In an effort to reduce waste, the Choosing Wisely campaign created a work group to highlight areas of overutilization, specifically noting both diagnostic tests and therapies for common pediatric conditions with no proven benefit and possible harm to the patient.[2] Respiratory illnesses have been a target of many quality‐improvement efforts, and pneumonia represents a common diagnosis in pediatrics.[3] The use of diagnostic testing for pneumonia is an area where care can be optimized and aligned with evidence.
Laboratory testing and diagnostic imaging are routinely used for the management of children with community‐acquired pneumonia (CAP). Several studies have documented substantial variability in the use of these resources for pneumonia management, with higher resource use associated with a higher chance of hospitalization after emergency department (ED) evaluation and a longer length of stay among those requiring hospitalization.[4, 5] This variation in diagnostic resource utilization has been attributed, at least in part, to a lack of consensus on the management of pneumonia. There is wide variability in diagnostic testing, and due to potential consequences for patients presenting with pneumonia, efforts to standardize care offer an opportunity to improve healthcare value.
In August 2011, the first national, evidence‐based consensus guidelines for the management of childhood CAP were published jointly by the Pediatric Infectious Diseases Society (PIDS) and the Infectious Diseases Society of America (IDSA).[6] A primary focus of these guidelines was the recommendation for the use of narrow spectrum antibiotics for the management of uncomplicated pneumonia. Previous studies have assessed the impact of the publication of the PIDS/IDSA guidelines on empiric antibiotic selection for the management of pneumonia.[7, 8] In addition, the guidelines provided recommendations regarding diagnostic test utilization, in particular discouraging blood tests (eg, complete blood counts) and radiologic studies for nontoxic, fully immunized children treated as outpatients, as well as repeat testing for children hospitalized with CAP who are improving.
Although single centers have demonstrated changes in utilization patterns based on clinical practice guidelines,[9, 10, 11, 12] whether these guidelines have impacted diagnostic test utilization among US children with CAP in a larger scale remains unknown. Therefore, we sought to determine the impact of the PIDS/IDSA guidelines on the use of diagnostic testing among children with CAP using a national sample of US children's hospitals. Because the guidelines discourage repeat diagnostic testing in patients who are improving, we also evaluated the association between repeat diagnostic studies and severity of illness.
METHODS
This retrospective cohort study used data from the Pediatric Health Information System (PHIS) (Children's Hospital Association, Overland Park, KS). The PHIS database contains deidentified administrative data, detailing demographic, diagnostic, procedure, and billing data from 47 freestanding, tertiary care children's hospitals. This database accounts for approximately 20% of all annual pediatric hospitalizations in the United States. Data quality is ensured through a joint effort between the Children's Hospital Association and participating hospitals.
Patient Population
Data from 32 (of the 47) hospitals included in PHIS with complete inpatient and ED data were used to evaluate hospital‐level resource utilization for children 1 to 18 years of age discharged January 1, 2008 to June 30, 2014 with a diagnosis of pneumonia (International Classification of Diseases, 9th Revision [ICD‐9] codes 480.x‐486.x, 487.0).[13] Our goal was to identify previously healthy children with uncomplicated pneumonia, so we excluded patients with complex chronic conditions,[14] billing charges for intensive care management and/or pleural drainage procedure (IDC‐9 codes 510.0, 510.9, 511.0, 511.1, 511.8, 511.9, 513.x) on day of admission or the next day, or prior pneumonia admission in the last 30 days. We studied 2 mutually exclusive populations: children with pneumonia treated in the ED (ie, patients who were evaluated in the ED and discharged to home), and children hospitalized with pneumonia, including those admitted through the ED.
Guideline Publication and Study Periods
For an exploratory before and after comparison, patients were grouped into 2 cohorts based on a guideline online publication date of August 1, 2011: preguideline (January 1, 2008 to July 31, 2011) and postguideline (August 1, 2011 to June 30, 2014).
Study Outcomes
The measured outcomes were the monthly proportion of pneumonia patients for whom specific diagnostic tests were performed, as determined from billing data. The diagnostic tests evaluated were complete blood count (CBC), blood culture, C‐reactive protein (CRP), and chest radiograph (CXR). Standardized costs were also calculated from PHIS charges as previously described to standardize the cost of the individual tests and remove interhospital cost variation.[3]
Relationship of Repeat Testing and Severity of Illness
Because higher illness severity and clinical deterioration may warrant repeat testing, we also explored the association of repeat diagnostic testing for inpatients with severity of illness by using the following variables as measures of severity: length of stay (LOS), transfer to intensive care unit (ICU), or pleural drainage procedure after admission (>2 calendar days after admission). Repeat diagnostic testing was stratified by number of tests.
Statistical Analysis
The categorical demographic characteristics of the pre‐ and postguideline populations were summarized using frequencies and percentages, and compared using 2 tests. Continuous demographics were summarized with medians and interquartile ranges (IQRs) and compared with the Wilcoxon rank sum test. Segmented regression, clustered by hospital, was used to assess trends in monthly resource utilization as well as associated standardized costs before and after guidelines publication. To estimate the impact of the guidelines overall, we compared the observed diagnostic resource use at the end of the study period with expected use projected from trends in the preguidelines period (ie, if there were no new guidelines). Individual interrupted time series were also built for each hospital. From these models, we assessed which hospitals had a significant difference between the rate observed at the end of the study and that estimated from their preguideline trajectory. To assess the relationship between the number of positive improvements at a hospital and hospital characteristics, we used Spearman's correlation and Kruskal‐Wallis tests. All analyses were performed with SAS version 9.3 (SAS Institute, Inc., Cary, NC), and P values <0.05 were considered statistically significant. In accordance with the policies of the Cincinnati Children's Hospital Medical Center Institutional Review Board, this research, using a deidentified dataset, was not considered human subjects research.
RESULTS
There were 275,288 hospital admissions meeting study inclusion criteria of 1 to 18 years of age with a diagnosis of pneumonia from 2008 to 2014. Of these, 54,749 met exclusion criteria (1874 had pleural drainage procedure on day 0 or 1, 51,306 had complex chronic conditions, 1569 were hospitalized with pneumonia in the last 30 days). Characteristics of the remaining 220,539 patients in the final sample are shown in Table 1. The median age was 4 years (IQR, 27 years); a majority of the children were male (53%) and had public insurance (58%). There were 128,855 patients in the preguideline period (January 1, 2008 to July 31, 2011) and 91,684 in the post guideline period (August 1, 2011June 30, 2014).
| Overall | Preguideline | Postguideline | P | |
|---|---|---|---|---|
| ||||
| No. of discharges | 220,539 | 128,855 | 91,684 | |
| Type of encounter | ||||
| ED only | 150,215 (68.1) | 88,790 (68.9) | 61,425 (67) | <0.001 |
| Inpatient | 70,324 (31.9) | 40,065 (31.1) | 30,259 (33) | |
| Age | ||||
| 14 years | 129,360 (58.7) | 77,802 (60.4) | 51,558 (56.2) | <0.001 |
| 59 years | 58,609 (26.6) | 32,708 (25.4) | 25,901 (28.3) | |
| 1018 years | 32,570 (14.8) | 18,345 (14.2) | 14,225 (15.5) | |
| Median [IQR] | 4 [27] | 3 [27] | 4 [27] | <0.001 |
| Gender | ||||
| Male | 116,718 (52.9) | 68,319 (53) | 48,399 (52.8) | 00.285 |
| Female | 103,813 (47.1) | 60,532 (47) | 43,281 (47.2) | |
| Race | ||||
| Non‐Hispanic white | 84,423 (38.3) | 47,327 (36.7) | 37,096 (40.5) | <0.001 |
| Non‐Hispanic black | 60,062 (27.2) | 35,870 (27.8) | 24,192 (26.4) | |
| Hispanic | 51,184 (23.2) | 31,167 (24.2) | 20,017 (21.8) | |
| Asian | 6,444 (2.9) | 3,691 (2.9) | 2,753 (3) | |
| Other | 18,426 (8.4) | 10,800 (8.4) | 7,626 (8.3) | |
| Payer | ||||
| Government | 128,047 (58.1) | 70,742 (54.9) | 57,305 (62.5) | <0.001 |
| Private | 73,338 (33.3) | 44,410 (34.5) | 28,928 (31.6) | |
| Other | 19,154 (8.7) | 13,703 (10.6) | 5,451 (5.9) | |
| Disposition | ||||
| HHS | 684 (0.3) | 411 (0.3) | 273 (0.3) | <0.001 |
| Home | 209,710 (95.1) | 123,236 (95.6) | 86,474 (94.3) | |
| Other | 9,749 (4.4) | 4,962 (3.9) | 4,787 (5.2) | |
| SNF | 396 (0.2) | 246 (0.2) | 150 (0.2) | |
| Season | ||||
| Spring | 60,171 (27.3) | 36,709 (28.5) | 23,462 (25.6) | <0.001 |
| Summer | 29,891 (13.6) | 17,748 (13.8) | 12,143 (13.2) | |
| Fall | 52,161 (23.7) | 28,332 (22) | 23,829 (26) | |
| Winter | 78,316 (35.5) | 46,066 (35.8) | 32,250 (35.2) | |
| LOS | ||||
| 13 days | 204,812 (92.9) | 119,497 (92.7) | 85,315 (93.1) | <0.001 |
| 46 days | 10,454 (4.7) | 6,148 (4.8) | 4,306 (4.7) | |
| 7+ days | 5,273 (2.4) | 3,210 (2.5) | 2,063 (2.3) | |
| Median [IQR] | 1 [11] | 1 [11] | 1 [11] | 0.144 |
| Admitted patients, median [IQR] | 2 [13] | 2 [13] | 2 [13] | <0.001 |
Discharged From the ED
Throughout the study, utilization of CBC, blood cultures, and CRP was <20%, whereas CXR use was >75%. In segmented regression analysis, CRP utilization was relatively stable before the guidelines publication. However, by the end of the study period, the projected estimate of CRP utilization without guidelines (expected) was 2.9% compared with 4.8% with the guidelines (observed) (P < 0.05) (Figure 1). A similar pattern of higher rates of diagnostic utilization after the guidelines compared with projected estimates without the guidelines was also seen in the ED utilization of CBC, blood cultures, and CXR (Figure 1); however, these trends did not achieve statistical significance. Table 2 provides specific values. Using a standard cost of $19.52 for CRP testing, annual costs across all hospitals increased $11,783 for ED evaluation of CAP.
Baseline (%) | Preguideline Trend | Level Change at Guideline | Change in Trend After Guideline | Estimates at End of Study* | |||
|---|---|---|---|---|---|---|---|
Without Guideline (%) | With Guideline (%) | P | |||||
| |||||||
| ED‐only encounters | |||||||
| Blood culture | 14.6 | 0.1 | 0.8 | 0.1 | 5.5 | 8.6 | NS |
| CBC | 19.2 | 0.1 | 0.4 | 0.1 | 10.7 | 14.0 | NS |
| CRP | 5.4 | 0.0 | 0.6 | 0.1 | 2.9 | 4.8 | <0.05 |
| Chest x‐ray | 85.4 | 0.1 | 0.1 | 0.0 | 80.9 | 81.1 | NS |
| Inpatient encounters | |||||||
| Blood culture | 50.6 | 0.0 | 1.7 | 0.2 | 49.2 | 41.4 | <0.05 |
| Repeat blood culture | 6.5 | 0.0 | 1.0 | 0.1 | 8.9 | 5.8 | NS |
| CBC | 65.2 | 0.0 | 3.1 | 0.0 | 65.0 | 62.2 | NS |
| Repeat CBC | 23.4 | 0.0 | 4.2 | 0.0 | 20.8 | 16.0 | NS |
| CRP | 25.7 | 0.0 | 1.1 | 0.0 | 23.8 | 23.5 | NS |
| Repeat CRP | 12.5 | 0.1 | 2.2 | 0.1 | 7.1 | 7.3 | NS |
| Chest x‐ray | 89.4 | 0.1 | 0.7 | 0.0 | 85.4 | 83.9 | NS |
| Repeat chest x‐ray | 25.5 | 0.0 | 2.0 | 0.1 | 24.1 | 17.7 | <0.05 |
Inpatient Encounters
In the segmented regression analysis of children hospitalized with CAP, guideline publication was associated with changes in the monthly use of some diagnostic tests. For example, by the end of the study period, the use of blood culture was 41.4% (observed), whereas the projected estimated use in the absence of the guidelines was 49.2% (expected) (P < 0.05) (Figure 2). Table 2 includes the data for the other tests, CBC, CRP, and CXR, in which similar patterns are noted with lower utilization rates after the guidelines, compared with expected utilization rates without the guidelines; however, these trends did not achieve statistical significance. Evaluating the utilization of repeat testing for inpatients, only repeat CXR achieved statistical significance (P < 0.05), with utilization rates of 17.7% with the guidelines (actual) compared with 24.1% without the guidelines (predicted).
To better understand the use of repeat testing, a comparison of severity outcomesLOS, ICU transfer, and pleural drainage procedureswas performed between patients with no repeat testing (70%) and patients with 1 or more repeat tests (30%). Patients with repeat testing had longer LOS (no repeat testing LOS 1 [IQR, 12]) versus 1 repeat test LOS 3 ([IQR, 24] vs 2+ repeat tests LOS 5 [IQR, 38]), higher rate of ICU transfer (no repeat testing 4.6% vs 1 repeat test 14.6% vs 2+ repeat test 35.6%), and higher rate of pleural drainage (no repeat testing 0% vs 1 repeat test 0.1% vs 2+ repeat test 5.9%] (all P < 0.001).
Using standard costs of $37.57 for blood cultures and $73.28 for CXR, annual costs for children with CAP across all hospitals decreased by $91,512 due to decreased utilization of blood cultures, and by $146,840 due to decreased utilization of CXR.
Hospital‐Level Variation in the Impact of the National Guideline
Figure 3 is a visual representation (heat map) of the impact of the guidelines at the hospital level at the end of the study from the individual interrupted time series. Based on this heat map (Figure 3), there was wide variability between hospitals in the impact of the guideline on each test in different settings (ED or inpatient). By diagnostic testing, 7 hospitals significantly decreased utilization of blood cultures for inpatients, and 5 hospitals significantly decreased utilization for repeat blood cultures and repeat CXR. Correlation between the number of positive improvements at a hospital and region (P = 0.974), number of CAP cases (P = 0.731), or percentage of public insurance (P = 0.241) were all nonsignificant.
DISCUSSION
This study complements previous assessments by evaluating the impact of the 2011 IDSA/PIDS consensus guidelines on the management of children with CAP cared for at US children's hospitals. Prior studies have shown increased use of narrow‐spectrum antibiotics for children with CAP after the publication of these guidelines.[7] The current study focused on diagnostic testing for CAP before and after the publication of the 2011 guidelines. In the ED setting, use of some diagnostic tests (blood culture, CBC, CXR, CRP) was declining prior to guideline publication, but appeared to plateau and/or increase after 2011. Among children admitted with CAP, use of diagnostic testing was relatively stable prior to 2011, and use of these tests (blood culture, CBC, CXR, CRP) declined after guideline publication. Overall, changes in diagnostic resource utilization 3 years after publication were modest, with few changes achieving statistical significance. There was a large variability in the impact of guidelines on test use between hospitals.
For outpatients, including those managed in the ED, the PIDS/IDSA guidelines recommend limited laboratory testing in nontoxic, fully immunized patients. The guidelines discourage the use of diagnostic testing among outpatients because of their low yield (eg, blood culture), and because test results may not impact management (eg, CBC).[6] In the years prior to guideline publication, there was already a declining trend in testing rates, including blood cultures, CBC, and CRP, for patients in the ED. After guideline publication, the rate of blood cultures, CBC, and CRP increased, but only the increase in CRP utilization achieved statistical significance. We would not expect utilization for common diagnostic tests (eg, CBC for outpatients with CAP) to be at or close to 0% because of the complexity of clinical decision making regarding admission that factors in aspects of patient history, exam findings, and underlying risk.[15] ED utilization of blood cultures was <10%, CBC <15%, and CRP <5% after guideline publication, which may represent the lowest testing limit that could be achieved.
CXRs obtained in the ED did not decrease over the entire study period. The rates of CXR use (close to 80%) seen in our study are similar to prior ED studies.[5, 16] Management of children with CAP in the ED might be different than outpatient primary care management because (1) unlike primary care providers, ED providers do not have an established relationship with their patients and do not have the opportunity for follow‐up and serial exams, making them less likely to tolerate diagnostic uncertainty; and (2) ED providers may see sicker patients. However, use of CXR in the ED does represent an opportunity for further study to understand if decreased utilization is feasible without adversely impacting clinical outcomes.
The CAP guidelines provide a strong recommendation to obtain blood culture in moderate to severe pneumonia. Despite this, blood culture utilization declined after guideline publication. Less than 10% of children hospitalized with uncomplicated CAP have positive blood cultures, which calls into question the utility of blood cultures for all admitted patients.[17, 18, 19] The recent EPIC (Epidemiology of Pneumonia in the Community) study showed that a majority of children hospitalized with pneumonia do not have growth of bacteria in culture, but there may be a role for blood cultures in patients with a strong suspicion of complicated CAP or in the patient with moderate to severe disease.[20] In addition to blood cultures, the guidelines also recommend CBC and CXR in moderate to severely ill children. This observed decline in testing in CBC and CXR may be related to individual physician assessments of which patients are moderately to severely ill, as the guidelines do not recommend testing for children with less severe disease. Our exclusion of patients requiring intensive care management or pleural drainage on admission might have selected children with a milder course of illness, although still requiring admission.
The guidelines discourage repeat diagnostic testing among children hospitalized with CAP who are improving. In this study, repeat CXR and CBC occurred in approximately 20% of patients, but repeat blood culture and CRP was much lower. As with initial diagnostic testing for inpatients with CAP, the rates of some repeat testing decreased with the guidelines. However, those with repeat testing had longer LOS and were more likely to require ICU transfer or a pleural drainage procedure compared to children without repeat testing. This suggests that repeat testing is used more often in children with a severe presentation or a worsening clinical course, and not done routinely on hospitalized patients.
The financial impact of decreased testing is modest, because the tests themselves are relatively inexpensive. However, the lack of substantial cost savings should not preclude efforts to continue to improve adherence to the guidelines. Not only is increased testing associated with higher hospitalization rates,[5] potentially yielding higher costs and family stress, increased testing may also lead to patient discomfort and possibly increased radiation exposure through chest radiography.
Many of the diagnostic testing recommendations in the CAP guidelines are based on weak evidence, which may contribute to the lack of substantial adoption. Nevertheless, adherence to guideline recommendations requires sustained effort on the part of individual physicians that should be encouraged through institutional support.[21] Continuous education and clinical decision support, as well as reminders in the electronic medical record, would make guideline recommendations more visible and may help overcome the inertia of previous practice.[15] The hospital‐level heat map (Figure 3) included in this study demonstrates that the impact of the guidelines was variable across sites. Although a few sites had decreased diagnostic testing in many areas with no increased testing in any category, there were several sites that had no improvement in any diagnostic testing category. In addition, hospital‐level factors like size, geography, and insurance status were not associated with number of improvements. To better understand drivers of change at individual hospitals, future studies should evaluate specific strategies utilized by the rapid guideline adopters.
This study is subject to several limitations. The use of ICD‐9 codes to identify patients with CAP may not capture all patients with this diagnosis; however, these codes have been previously validated.[13] Additionally, because patients were identified using ICD‐9 coding assigned at the time of discharge, testing performed in the ED setting may not reflect care for a child with known pneumonia, but rather may reflect testing for a child with fever or other signs of infection. PHIS collects data from freestanding children's hospitals, which care for a majority of children with CAP in the US, but our findings may not be generalizable to other hospitals. In addition, we did not examine drivers of trends within individual institutions. We did not have detailed information to examine whether the PHIS hospitals in our study had actively worked to adopt the CAP guidelines. We were also unable to assess physician's familiarity with guidelines or the level of disagreement with the recommendations. Furthermore, the PHIS database does not permit detailed correlation of diagnostic testing with clinical parameters. In contrast to the diagnostic testing evaluated in this study, which is primarily discouraged by the IDSA/PIDS guidelines, respiratory viral testing for children with CAP is recommended but could not be evaluated, as data on such testing are not readily available in PHIS.
CONCLUSION
Publication of the IDSA/PIDS evidence‐based guidelines for the management of CAP was associated with modest, variable changes in use of diagnostic testing. Further adoption of the CAP guidelines should reduce variation in care and decrease unnecessary resource utilization in the management of CAP. Our study demonstrates that efforts to promote decreased resource utilization should target specific situations (eg, repeat testing for inpatients who are improving). Adherence to guidelines may be improved by the adoption of local practices that integrate and improve daily workflow, like order sets and clinical decision support tools.
Disclosure: Nothing to report.
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- , , , . Emergency department management of childhood pneumonia in the United States prior to publication of national guidelines. Acad Emerg Med. 2013;20(3):240–246.
- , , , et al. Prevalence of bacteremia in hospitalized pediatric patients with community‐acquired pneumonia. Pediatr Infect Dis J. 2013;32(7):736–740.
- , , , , . The prevalence of bacteremia in pediatric patients with community‐acquired pneumonia: guidelines to reduce the frequency of obtaining blood cultures. Hosp Pediatr. 2013;3(2):92–96.
- . Do all children hospitalized with community‐acquired pneumonia require blood cultures? Hosp Pediatr. 2013;3(2):177–179.
- , , , et al.; CDC EPIC Study Team. Community‐acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372(9):835–845.
- , , , et al. Influence of hospital guidelines on management of children hospitalized with pneumonia. Pediatrics. 2012;130(5):e823–e830.
Overutilization of resources is a significant, yet underappreciated, problem in medicine. Many interventions target underutilization (eg, immunizations) or misuse (eg, antibiotic prescribing for viral pharyngitis), yet overutilization remains as a significant contributor to healthcare waste.[1] In an effort to reduce waste, the Choosing Wisely campaign created a work group to highlight areas of overutilization, specifically noting both diagnostic tests and therapies for common pediatric conditions with no proven benefit and possible harm to the patient.[2] Respiratory illnesses have been a target of many quality‐improvement efforts, and pneumonia represents a common diagnosis in pediatrics.[3] The use of diagnostic testing for pneumonia is an area where care can be optimized and aligned with evidence.
Laboratory testing and diagnostic imaging are routinely used for the management of children with community‐acquired pneumonia (CAP). Several studies have documented substantial variability in the use of these resources for pneumonia management, with higher resource use associated with a higher chance of hospitalization after emergency department (ED) evaluation and a longer length of stay among those requiring hospitalization.[4, 5] This variation in diagnostic resource utilization has been attributed, at least in part, to a lack of consensus on the management of pneumonia. There is wide variability in diagnostic testing, and due to potential consequences for patients presenting with pneumonia, efforts to standardize care offer an opportunity to improve healthcare value.
In August 2011, the first national, evidence‐based consensus guidelines for the management of childhood CAP were published jointly by the Pediatric Infectious Diseases Society (PIDS) and the Infectious Diseases Society of America (IDSA).[6] A primary focus of these guidelines was the recommendation for the use of narrow spectrum antibiotics for the management of uncomplicated pneumonia. Previous studies have assessed the impact of the publication of the PIDS/IDSA guidelines on empiric antibiotic selection for the management of pneumonia.[7, 8] In addition, the guidelines provided recommendations regarding diagnostic test utilization, in particular discouraging blood tests (eg, complete blood counts) and radiologic studies for nontoxic, fully immunized children treated as outpatients, as well as repeat testing for children hospitalized with CAP who are improving.
Although single centers have demonstrated changes in utilization patterns based on clinical practice guidelines,[9, 10, 11, 12] whether these guidelines have impacted diagnostic test utilization among US children with CAP in a larger scale remains unknown. Therefore, we sought to determine the impact of the PIDS/IDSA guidelines on the use of diagnostic testing among children with CAP using a national sample of US children's hospitals. Because the guidelines discourage repeat diagnostic testing in patients who are improving, we also evaluated the association between repeat diagnostic studies and severity of illness.
METHODS
This retrospective cohort study used data from the Pediatric Health Information System (PHIS) (Children's Hospital Association, Overland Park, KS). The PHIS database contains deidentified administrative data, detailing demographic, diagnostic, procedure, and billing data from 47 freestanding, tertiary care children's hospitals. This database accounts for approximately 20% of all annual pediatric hospitalizations in the United States. Data quality is ensured through a joint effort between the Children's Hospital Association and participating hospitals.
Patient Population
Data from 32 (of the 47) hospitals included in PHIS with complete inpatient and ED data were used to evaluate hospital‐level resource utilization for children 1 to 18 years of age discharged January 1, 2008 to June 30, 2014 with a diagnosis of pneumonia (International Classification of Diseases, 9th Revision [ICD‐9] codes 480.x‐486.x, 487.0).[13] Our goal was to identify previously healthy children with uncomplicated pneumonia, so we excluded patients with complex chronic conditions,[14] billing charges for intensive care management and/or pleural drainage procedure (IDC‐9 codes 510.0, 510.9, 511.0, 511.1, 511.8, 511.9, 513.x) on day of admission or the next day, or prior pneumonia admission in the last 30 days. We studied 2 mutually exclusive populations: children with pneumonia treated in the ED (ie, patients who were evaluated in the ED and discharged to home), and children hospitalized with pneumonia, including those admitted through the ED.
Guideline Publication and Study Periods
For an exploratory before and after comparison, patients were grouped into 2 cohorts based on a guideline online publication date of August 1, 2011: preguideline (January 1, 2008 to July 31, 2011) and postguideline (August 1, 2011 to June 30, 2014).
Study Outcomes
The measured outcomes were the monthly proportion of pneumonia patients for whom specific diagnostic tests were performed, as determined from billing data. The diagnostic tests evaluated were complete blood count (CBC), blood culture, C‐reactive protein (CRP), and chest radiograph (CXR). Standardized costs were also calculated from PHIS charges as previously described to standardize the cost of the individual tests and remove interhospital cost variation.[3]
Relationship of Repeat Testing and Severity of Illness
Because higher illness severity and clinical deterioration may warrant repeat testing, we also explored the association of repeat diagnostic testing for inpatients with severity of illness by using the following variables as measures of severity: length of stay (LOS), transfer to intensive care unit (ICU), or pleural drainage procedure after admission (>2 calendar days after admission). Repeat diagnostic testing was stratified by number of tests.
Statistical Analysis
The categorical demographic characteristics of the pre‐ and postguideline populations were summarized using frequencies and percentages, and compared using 2 tests. Continuous demographics were summarized with medians and interquartile ranges (IQRs) and compared with the Wilcoxon rank sum test. Segmented regression, clustered by hospital, was used to assess trends in monthly resource utilization as well as associated standardized costs before and after guidelines publication. To estimate the impact of the guidelines overall, we compared the observed diagnostic resource use at the end of the study period with expected use projected from trends in the preguidelines period (ie, if there were no new guidelines). Individual interrupted time series were also built for each hospital. From these models, we assessed which hospitals had a significant difference between the rate observed at the end of the study and that estimated from their preguideline trajectory. To assess the relationship between the number of positive improvements at a hospital and hospital characteristics, we used Spearman's correlation and Kruskal‐Wallis tests. All analyses were performed with SAS version 9.3 (SAS Institute, Inc., Cary, NC), and P values <0.05 were considered statistically significant. In accordance with the policies of the Cincinnati Children's Hospital Medical Center Institutional Review Board, this research, using a deidentified dataset, was not considered human subjects research.
RESULTS
There were 275,288 hospital admissions meeting study inclusion criteria of 1 to 18 years of age with a diagnosis of pneumonia from 2008 to 2014. Of these, 54,749 met exclusion criteria (1874 had pleural drainage procedure on day 0 or 1, 51,306 had complex chronic conditions, 1569 were hospitalized with pneumonia in the last 30 days). Characteristics of the remaining 220,539 patients in the final sample are shown in Table 1. The median age was 4 years (IQR, 27 years); a majority of the children were male (53%) and had public insurance (58%). There were 128,855 patients in the preguideline period (January 1, 2008 to July 31, 2011) and 91,684 in the post guideline period (August 1, 2011June 30, 2014).
| Overall | Preguideline | Postguideline | P | |
|---|---|---|---|---|
| ||||
| No. of discharges | 220,539 | 128,855 | 91,684 | |
| Type of encounter | ||||
| ED only | 150,215 (68.1) | 88,790 (68.9) | 61,425 (67) | <0.001 |
| Inpatient | 70,324 (31.9) | 40,065 (31.1) | 30,259 (33) | |
| Age | ||||
| 14 years | 129,360 (58.7) | 77,802 (60.4) | 51,558 (56.2) | <0.001 |
| 59 years | 58,609 (26.6) | 32,708 (25.4) | 25,901 (28.3) | |
| 1018 years | 32,570 (14.8) | 18,345 (14.2) | 14,225 (15.5) | |
| Median [IQR] | 4 [27] | 3 [27] | 4 [27] | <0.001 |
| Gender | ||||
| Male | 116,718 (52.9) | 68,319 (53) | 48,399 (52.8) | 00.285 |
| Female | 103,813 (47.1) | 60,532 (47) | 43,281 (47.2) | |
| Race | ||||
| Non‐Hispanic white | 84,423 (38.3) | 47,327 (36.7) | 37,096 (40.5) | <0.001 |
| Non‐Hispanic black | 60,062 (27.2) | 35,870 (27.8) | 24,192 (26.4) | |
| Hispanic | 51,184 (23.2) | 31,167 (24.2) | 20,017 (21.8) | |
| Asian | 6,444 (2.9) | 3,691 (2.9) | 2,753 (3) | |
| Other | 18,426 (8.4) | 10,800 (8.4) | 7,626 (8.3) | |
| Payer | ||||
| Government | 128,047 (58.1) | 70,742 (54.9) | 57,305 (62.5) | <0.001 |
| Private | 73,338 (33.3) | 44,410 (34.5) | 28,928 (31.6) | |
| Other | 19,154 (8.7) | 13,703 (10.6) | 5,451 (5.9) | |
| Disposition | ||||
| HHS | 684 (0.3) | 411 (0.3) | 273 (0.3) | <0.001 |
| Home | 209,710 (95.1) | 123,236 (95.6) | 86,474 (94.3) | |
| Other | 9,749 (4.4) | 4,962 (3.9) | 4,787 (5.2) | |
| SNF | 396 (0.2) | 246 (0.2) | 150 (0.2) | |
| Season | ||||
| Spring | 60,171 (27.3) | 36,709 (28.5) | 23,462 (25.6) | <0.001 |
| Summer | 29,891 (13.6) | 17,748 (13.8) | 12,143 (13.2) | |
| Fall | 52,161 (23.7) | 28,332 (22) | 23,829 (26) | |
| Winter | 78,316 (35.5) | 46,066 (35.8) | 32,250 (35.2) | |
| LOS | ||||
| 13 days | 204,812 (92.9) | 119,497 (92.7) | 85,315 (93.1) | <0.001 |
| 46 days | 10,454 (4.7) | 6,148 (4.8) | 4,306 (4.7) | |
| 7+ days | 5,273 (2.4) | 3,210 (2.5) | 2,063 (2.3) | |
| Median [IQR] | 1 [11] | 1 [11] | 1 [11] | 0.144 |
| Admitted patients, median [IQR] | 2 [13] | 2 [13] | 2 [13] | <0.001 |
Discharged From the ED
Throughout the study, utilization of CBC, blood cultures, and CRP was <20%, whereas CXR use was >75%. In segmented regression analysis, CRP utilization was relatively stable before the guidelines publication. However, by the end of the study period, the projected estimate of CRP utilization without guidelines (expected) was 2.9% compared with 4.8% with the guidelines (observed) (P < 0.05) (Figure 1). A similar pattern of higher rates of diagnostic utilization after the guidelines compared with projected estimates without the guidelines was also seen in the ED utilization of CBC, blood cultures, and CXR (Figure 1); however, these trends did not achieve statistical significance. Table 2 provides specific values. Using a standard cost of $19.52 for CRP testing, annual costs across all hospitals increased $11,783 for ED evaluation of CAP.
Baseline (%) | Preguideline Trend | Level Change at Guideline | Change in Trend After Guideline | Estimates at End of Study* | |||
|---|---|---|---|---|---|---|---|
Without Guideline (%) | With Guideline (%) | P | |||||
| |||||||
| ED‐only encounters | |||||||
| Blood culture | 14.6 | 0.1 | 0.8 | 0.1 | 5.5 | 8.6 | NS |
| CBC | 19.2 | 0.1 | 0.4 | 0.1 | 10.7 | 14.0 | NS |
| CRP | 5.4 | 0.0 | 0.6 | 0.1 | 2.9 | 4.8 | <0.05 |
| Chest x‐ray | 85.4 | 0.1 | 0.1 | 0.0 | 80.9 | 81.1 | NS |
| Inpatient encounters | |||||||
| Blood culture | 50.6 | 0.0 | 1.7 | 0.2 | 49.2 | 41.4 | <0.05 |
| Repeat blood culture | 6.5 | 0.0 | 1.0 | 0.1 | 8.9 | 5.8 | NS |
| CBC | 65.2 | 0.0 | 3.1 | 0.0 | 65.0 | 62.2 | NS |
| Repeat CBC | 23.4 | 0.0 | 4.2 | 0.0 | 20.8 | 16.0 | NS |
| CRP | 25.7 | 0.0 | 1.1 | 0.0 | 23.8 | 23.5 | NS |
| Repeat CRP | 12.5 | 0.1 | 2.2 | 0.1 | 7.1 | 7.3 | NS |
| Chest x‐ray | 89.4 | 0.1 | 0.7 | 0.0 | 85.4 | 83.9 | NS |
| Repeat chest x‐ray | 25.5 | 0.0 | 2.0 | 0.1 | 24.1 | 17.7 | <0.05 |
Inpatient Encounters
In the segmented regression analysis of children hospitalized with CAP, guideline publication was associated with changes in the monthly use of some diagnostic tests. For example, by the end of the study period, the use of blood culture was 41.4% (observed), whereas the projected estimated use in the absence of the guidelines was 49.2% (expected) (P < 0.05) (Figure 2). Table 2 includes the data for the other tests, CBC, CRP, and CXR, in which similar patterns are noted with lower utilization rates after the guidelines, compared with expected utilization rates without the guidelines; however, these trends did not achieve statistical significance. Evaluating the utilization of repeat testing for inpatients, only repeat CXR achieved statistical significance (P < 0.05), with utilization rates of 17.7% with the guidelines (actual) compared with 24.1% without the guidelines (predicted).
To better understand the use of repeat testing, a comparison of severity outcomesLOS, ICU transfer, and pleural drainage procedureswas performed between patients with no repeat testing (70%) and patients with 1 or more repeat tests (30%). Patients with repeat testing had longer LOS (no repeat testing LOS 1 [IQR, 12]) versus 1 repeat test LOS 3 ([IQR, 24] vs 2+ repeat tests LOS 5 [IQR, 38]), higher rate of ICU transfer (no repeat testing 4.6% vs 1 repeat test 14.6% vs 2+ repeat test 35.6%), and higher rate of pleural drainage (no repeat testing 0% vs 1 repeat test 0.1% vs 2+ repeat test 5.9%] (all P < 0.001).
Using standard costs of $37.57 for blood cultures and $73.28 for CXR, annual costs for children with CAP across all hospitals decreased by $91,512 due to decreased utilization of blood cultures, and by $146,840 due to decreased utilization of CXR.
Hospital‐Level Variation in the Impact of the National Guideline
Figure 3 is a visual representation (heat map) of the impact of the guidelines at the hospital level at the end of the study from the individual interrupted time series. Based on this heat map (Figure 3), there was wide variability between hospitals in the impact of the guideline on each test in different settings (ED or inpatient). By diagnostic testing, 7 hospitals significantly decreased utilization of blood cultures for inpatients, and 5 hospitals significantly decreased utilization for repeat blood cultures and repeat CXR. Correlation between the number of positive improvements at a hospital and region (P = 0.974), number of CAP cases (P = 0.731), or percentage of public insurance (P = 0.241) were all nonsignificant.
DISCUSSION
This study complements previous assessments by evaluating the impact of the 2011 IDSA/PIDS consensus guidelines on the management of children with CAP cared for at US children's hospitals. Prior studies have shown increased use of narrow‐spectrum antibiotics for children with CAP after the publication of these guidelines.[7] The current study focused on diagnostic testing for CAP before and after the publication of the 2011 guidelines. In the ED setting, use of some diagnostic tests (blood culture, CBC, CXR, CRP) was declining prior to guideline publication, but appeared to plateau and/or increase after 2011. Among children admitted with CAP, use of diagnostic testing was relatively stable prior to 2011, and use of these tests (blood culture, CBC, CXR, CRP) declined after guideline publication. Overall, changes in diagnostic resource utilization 3 years after publication were modest, with few changes achieving statistical significance. There was a large variability in the impact of guidelines on test use between hospitals.
For outpatients, including those managed in the ED, the PIDS/IDSA guidelines recommend limited laboratory testing in nontoxic, fully immunized patients. The guidelines discourage the use of diagnostic testing among outpatients because of their low yield (eg, blood culture), and because test results may not impact management (eg, CBC).[6] In the years prior to guideline publication, there was already a declining trend in testing rates, including blood cultures, CBC, and CRP, for patients in the ED. After guideline publication, the rate of blood cultures, CBC, and CRP increased, but only the increase in CRP utilization achieved statistical significance. We would not expect utilization for common diagnostic tests (eg, CBC for outpatients with CAP) to be at or close to 0% because of the complexity of clinical decision making regarding admission that factors in aspects of patient history, exam findings, and underlying risk.[15] ED utilization of blood cultures was <10%, CBC <15%, and CRP <5% after guideline publication, which may represent the lowest testing limit that could be achieved.
CXRs obtained in the ED did not decrease over the entire study period. The rates of CXR use (close to 80%) seen in our study are similar to prior ED studies.[5, 16] Management of children with CAP in the ED might be different than outpatient primary care management because (1) unlike primary care providers, ED providers do not have an established relationship with their patients and do not have the opportunity for follow‐up and serial exams, making them less likely to tolerate diagnostic uncertainty; and (2) ED providers may see sicker patients. However, use of CXR in the ED does represent an opportunity for further study to understand if decreased utilization is feasible without adversely impacting clinical outcomes.
The CAP guidelines provide a strong recommendation to obtain blood culture in moderate to severe pneumonia. Despite this, blood culture utilization declined after guideline publication. Less than 10% of children hospitalized with uncomplicated CAP have positive blood cultures, which calls into question the utility of blood cultures for all admitted patients.[17, 18, 19] The recent EPIC (Epidemiology of Pneumonia in the Community) study showed that a majority of children hospitalized with pneumonia do not have growth of bacteria in culture, but there may be a role for blood cultures in patients with a strong suspicion of complicated CAP or in the patient with moderate to severe disease.[20] In addition to blood cultures, the guidelines also recommend CBC and CXR in moderate to severely ill children. This observed decline in testing in CBC and CXR may be related to individual physician assessments of which patients are moderately to severely ill, as the guidelines do not recommend testing for children with less severe disease. Our exclusion of patients requiring intensive care management or pleural drainage on admission might have selected children with a milder course of illness, although still requiring admission.
The guidelines discourage repeat diagnostic testing among children hospitalized with CAP who are improving. In this study, repeat CXR and CBC occurred in approximately 20% of patients, but repeat blood culture and CRP was much lower. As with initial diagnostic testing for inpatients with CAP, the rates of some repeat testing decreased with the guidelines. However, those with repeat testing had longer LOS and were more likely to require ICU transfer or a pleural drainage procedure compared to children without repeat testing. This suggests that repeat testing is used more often in children with a severe presentation or a worsening clinical course, and not done routinely on hospitalized patients.
The financial impact of decreased testing is modest, because the tests themselves are relatively inexpensive. However, the lack of substantial cost savings should not preclude efforts to continue to improve adherence to the guidelines. Not only is increased testing associated with higher hospitalization rates,[5] potentially yielding higher costs and family stress, increased testing may also lead to patient discomfort and possibly increased radiation exposure through chest radiography.
Many of the diagnostic testing recommendations in the CAP guidelines are based on weak evidence, which may contribute to the lack of substantial adoption. Nevertheless, adherence to guideline recommendations requires sustained effort on the part of individual physicians that should be encouraged through institutional support.[21] Continuous education and clinical decision support, as well as reminders in the electronic medical record, would make guideline recommendations more visible and may help overcome the inertia of previous practice.[15] The hospital‐level heat map (Figure 3) included in this study demonstrates that the impact of the guidelines was variable across sites. Although a few sites had decreased diagnostic testing in many areas with no increased testing in any category, there were several sites that had no improvement in any diagnostic testing category. In addition, hospital‐level factors like size, geography, and insurance status were not associated with number of improvements. To better understand drivers of change at individual hospitals, future studies should evaluate specific strategies utilized by the rapid guideline adopters.
This study is subject to several limitations. The use of ICD‐9 codes to identify patients with CAP may not capture all patients with this diagnosis; however, these codes have been previously validated.[13] Additionally, because patients were identified using ICD‐9 coding assigned at the time of discharge, testing performed in the ED setting may not reflect care for a child with known pneumonia, but rather may reflect testing for a child with fever or other signs of infection. PHIS collects data from freestanding children's hospitals, which care for a majority of children with CAP in the US, but our findings may not be generalizable to other hospitals. In addition, we did not examine drivers of trends within individual institutions. We did not have detailed information to examine whether the PHIS hospitals in our study had actively worked to adopt the CAP guidelines. We were also unable to assess physician's familiarity with guidelines or the level of disagreement with the recommendations. Furthermore, the PHIS database does not permit detailed correlation of diagnostic testing with clinical parameters. In contrast to the diagnostic testing evaluated in this study, which is primarily discouraged by the IDSA/PIDS guidelines, respiratory viral testing for children with CAP is recommended but could not be evaluated, as data on such testing are not readily available in PHIS.
CONCLUSION
Publication of the IDSA/PIDS evidence‐based guidelines for the management of CAP was associated with modest, variable changes in use of diagnostic testing. Further adoption of the CAP guidelines should reduce variation in care and decrease unnecessary resource utilization in the management of CAP. Our study demonstrates that efforts to promote decreased resource utilization should target specific situations (eg, repeat testing for inpatients who are improving). Adherence to guidelines may be improved by the adoption of local practices that integrate and improve daily workflow, like order sets and clinical decision support tools.
Disclosure: Nothing to report.
Overutilization of resources is a significant, yet underappreciated, problem in medicine. Many interventions target underutilization (eg, immunizations) or misuse (eg, antibiotic prescribing for viral pharyngitis), yet overutilization remains as a significant contributor to healthcare waste.[1] In an effort to reduce waste, the Choosing Wisely campaign created a work group to highlight areas of overutilization, specifically noting both diagnostic tests and therapies for common pediatric conditions with no proven benefit and possible harm to the patient.[2] Respiratory illnesses have been a target of many quality‐improvement efforts, and pneumonia represents a common diagnosis in pediatrics.[3] The use of diagnostic testing for pneumonia is an area where care can be optimized and aligned with evidence.
Laboratory testing and diagnostic imaging are routinely used for the management of children with community‐acquired pneumonia (CAP). Several studies have documented substantial variability in the use of these resources for pneumonia management, with higher resource use associated with a higher chance of hospitalization after emergency department (ED) evaluation and a longer length of stay among those requiring hospitalization.[4, 5] This variation in diagnostic resource utilization has been attributed, at least in part, to a lack of consensus on the management of pneumonia. There is wide variability in diagnostic testing, and due to potential consequences for patients presenting with pneumonia, efforts to standardize care offer an opportunity to improve healthcare value.
In August 2011, the first national, evidence‐based consensus guidelines for the management of childhood CAP were published jointly by the Pediatric Infectious Diseases Society (PIDS) and the Infectious Diseases Society of America (IDSA).[6] A primary focus of these guidelines was the recommendation for the use of narrow spectrum antibiotics for the management of uncomplicated pneumonia. Previous studies have assessed the impact of the publication of the PIDS/IDSA guidelines on empiric antibiotic selection for the management of pneumonia.[7, 8] In addition, the guidelines provided recommendations regarding diagnostic test utilization, in particular discouraging blood tests (eg, complete blood counts) and radiologic studies for nontoxic, fully immunized children treated as outpatients, as well as repeat testing for children hospitalized with CAP who are improving.
Although single centers have demonstrated changes in utilization patterns based on clinical practice guidelines,[9, 10, 11, 12] whether these guidelines have impacted diagnostic test utilization among US children with CAP in a larger scale remains unknown. Therefore, we sought to determine the impact of the PIDS/IDSA guidelines on the use of diagnostic testing among children with CAP using a national sample of US children's hospitals. Because the guidelines discourage repeat diagnostic testing in patients who are improving, we also evaluated the association between repeat diagnostic studies and severity of illness.
METHODS
This retrospective cohort study used data from the Pediatric Health Information System (PHIS) (Children's Hospital Association, Overland Park, KS). The PHIS database contains deidentified administrative data, detailing demographic, diagnostic, procedure, and billing data from 47 freestanding, tertiary care children's hospitals. This database accounts for approximately 20% of all annual pediatric hospitalizations in the United States. Data quality is ensured through a joint effort between the Children's Hospital Association and participating hospitals.
Patient Population
Data from 32 (of the 47) hospitals included in PHIS with complete inpatient and ED data were used to evaluate hospital‐level resource utilization for children 1 to 18 years of age discharged January 1, 2008 to June 30, 2014 with a diagnosis of pneumonia (International Classification of Diseases, 9th Revision [ICD‐9] codes 480.x‐486.x, 487.0).[13] Our goal was to identify previously healthy children with uncomplicated pneumonia, so we excluded patients with complex chronic conditions,[14] billing charges for intensive care management and/or pleural drainage procedure (IDC‐9 codes 510.0, 510.9, 511.0, 511.1, 511.8, 511.9, 513.x) on day of admission or the next day, or prior pneumonia admission in the last 30 days. We studied 2 mutually exclusive populations: children with pneumonia treated in the ED (ie, patients who were evaluated in the ED and discharged to home), and children hospitalized with pneumonia, including those admitted through the ED.
Guideline Publication and Study Periods
For an exploratory before and after comparison, patients were grouped into 2 cohorts based on a guideline online publication date of August 1, 2011: preguideline (January 1, 2008 to July 31, 2011) and postguideline (August 1, 2011 to June 30, 2014).
Study Outcomes
The measured outcomes were the monthly proportion of pneumonia patients for whom specific diagnostic tests were performed, as determined from billing data. The diagnostic tests evaluated were complete blood count (CBC), blood culture, C‐reactive protein (CRP), and chest radiograph (CXR). Standardized costs were also calculated from PHIS charges as previously described to standardize the cost of the individual tests and remove interhospital cost variation.[3]
Relationship of Repeat Testing and Severity of Illness
Because higher illness severity and clinical deterioration may warrant repeat testing, we also explored the association of repeat diagnostic testing for inpatients with severity of illness by using the following variables as measures of severity: length of stay (LOS), transfer to intensive care unit (ICU), or pleural drainage procedure after admission (>2 calendar days after admission). Repeat diagnostic testing was stratified by number of tests.
Statistical Analysis
The categorical demographic characteristics of the pre‐ and postguideline populations were summarized using frequencies and percentages, and compared using 2 tests. Continuous demographics were summarized with medians and interquartile ranges (IQRs) and compared with the Wilcoxon rank sum test. Segmented regression, clustered by hospital, was used to assess trends in monthly resource utilization as well as associated standardized costs before and after guidelines publication. To estimate the impact of the guidelines overall, we compared the observed diagnostic resource use at the end of the study period with expected use projected from trends in the preguidelines period (ie, if there were no new guidelines). Individual interrupted time series were also built for each hospital. From these models, we assessed which hospitals had a significant difference between the rate observed at the end of the study and that estimated from their preguideline trajectory. To assess the relationship between the number of positive improvements at a hospital and hospital characteristics, we used Spearman's correlation and Kruskal‐Wallis tests. All analyses were performed with SAS version 9.3 (SAS Institute, Inc., Cary, NC), and P values <0.05 were considered statistically significant. In accordance with the policies of the Cincinnati Children's Hospital Medical Center Institutional Review Board, this research, using a deidentified dataset, was not considered human subjects research.
RESULTS
There were 275,288 hospital admissions meeting study inclusion criteria of 1 to 18 years of age with a diagnosis of pneumonia from 2008 to 2014. Of these, 54,749 met exclusion criteria (1874 had pleural drainage procedure on day 0 or 1, 51,306 had complex chronic conditions, 1569 were hospitalized with pneumonia in the last 30 days). Characteristics of the remaining 220,539 patients in the final sample are shown in Table 1. The median age was 4 years (IQR, 27 years); a majority of the children were male (53%) and had public insurance (58%). There were 128,855 patients in the preguideline period (January 1, 2008 to July 31, 2011) and 91,684 in the post guideline period (August 1, 2011June 30, 2014).
| Overall | Preguideline | Postguideline | P | |
|---|---|---|---|---|
| ||||
| No. of discharges | 220,539 | 128,855 | 91,684 | |
| Type of encounter | ||||
| ED only | 150,215 (68.1) | 88,790 (68.9) | 61,425 (67) | <0.001 |
| Inpatient | 70,324 (31.9) | 40,065 (31.1) | 30,259 (33) | |
| Age | ||||
| 14 years | 129,360 (58.7) | 77,802 (60.4) | 51,558 (56.2) | <0.001 |
| 59 years | 58,609 (26.6) | 32,708 (25.4) | 25,901 (28.3) | |
| 1018 years | 32,570 (14.8) | 18,345 (14.2) | 14,225 (15.5) | |
| Median [IQR] | 4 [27] | 3 [27] | 4 [27] | <0.001 |
| Gender | ||||
| Male | 116,718 (52.9) | 68,319 (53) | 48,399 (52.8) | 00.285 |
| Female | 103,813 (47.1) | 60,532 (47) | 43,281 (47.2) | |
| Race | ||||
| Non‐Hispanic white | 84,423 (38.3) | 47,327 (36.7) | 37,096 (40.5) | <0.001 |
| Non‐Hispanic black | 60,062 (27.2) | 35,870 (27.8) | 24,192 (26.4) | |
| Hispanic | 51,184 (23.2) | 31,167 (24.2) | 20,017 (21.8) | |
| Asian | 6,444 (2.9) | 3,691 (2.9) | 2,753 (3) | |
| Other | 18,426 (8.4) | 10,800 (8.4) | 7,626 (8.3) | |
| Payer | ||||
| Government | 128,047 (58.1) | 70,742 (54.9) | 57,305 (62.5) | <0.001 |
| Private | 73,338 (33.3) | 44,410 (34.5) | 28,928 (31.6) | |
| Other | 19,154 (8.7) | 13,703 (10.6) | 5,451 (5.9) | |
| Disposition | ||||
| HHS | 684 (0.3) | 411 (0.3) | 273 (0.3) | <0.001 |
| Home | 209,710 (95.1) | 123,236 (95.6) | 86,474 (94.3) | |
| Other | 9,749 (4.4) | 4,962 (3.9) | 4,787 (5.2) | |
| SNF | 396 (0.2) | 246 (0.2) | 150 (0.2) | |
| Season | ||||
| Spring | 60,171 (27.3) | 36,709 (28.5) | 23,462 (25.6) | <0.001 |
| Summer | 29,891 (13.6) | 17,748 (13.8) | 12,143 (13.2) | |
| Fall | 52,161 (23.7) | 28,332 (22) | 23,829 (26) | |
| Winter | 78,316 (35.5) | 46,066 (35.8) | 32,250 (35.2) | |
| LOS | ||||
| 13 days | 204,812 (92.9) | 119,497 (92.7) | 85,315 (93.1) | <0.001 |
| 46 days | 10,454 (4.7) | 6,148 (4.8) | 4,306 (4.7) | |
| 7+ days | 5,273 (2.4) | 3,210 (2.5) | 2,063 (2.3) | |
| Median [IQR] | 1 [11] | 1 [11] | 1 [11] | 0.144 |
| Admitted patients, median [IQR] | 2 [13] | 2 [13] | 2 [13] | <0.001 |
Discharged From the ED
Throughout the study, utilization of CBC, blood cultures, and CRP was <20%, whereas CXR use was >75%. In segmented regression analysis, CRP utilization was relatively stable before the guidelines publication. However, by the end of the study period, the projected estimate of CRP utilization without guidelines (expected) was 2.9% compared with 4.8% with the guidelines (observed) (P < 0.05) (Figure 1). A similar pattern of higher rates of diagnostic utilization after the guidelines compared with projected estimates without the guidelines was also seen in the ED utilization of CBC, blood cultures, and CXR (Figure 1); however, these trends did not achieve statistical significance. Table 2 provides specific values. Using a standard cost of $19.52 for CRP testing, annual costs across all hospitals increased $11,783 for ED evaluation of CAP.
Baseline (%) | Preguideline Trend | Level Change at Guideline | Change in Trend After Guideline | Estimates at End of Study* | |||
|---|---|---|---|---|---|---|---|
Without Guideline (%) | With Guideline (%) | P | |||||
| |||||||
| ED‐only encounters | |||||||
| Blood culture | 14.6 | 0.1 | 0.8 | 0.1 | 5.5 | 8.6 | NS |
| CBC | 19.2 | 0.1 | 0.4 | 0.1 | 10.7 | 14.0 | NS |
| CRP | 5.4 | 0.0 | 0.6 | 0.1 | 2.9 | 4.8 | <0.05 |
| Chest x‐ray | 85.4 | 0.1 | 0.1 | 0.0 | 80.9 | 81.1 | NS |
| Inpatient encounters | |||||||
| Blood culture | 50.6 | 0.0 | 1.7 | 0.2 | 49.2 | 41.4 | <0.05 |
| Repeat blood culture | 6.5 | 0.0 | 1.0 | 0.1 | 8.9 | 5.8 | NS |
| CBC | 65.2 | 0.0 | 3.1 | 0.0 | 65.0 | 62.2 | NS |
| Repeat CBC | 23.4 | 0.0 | 4.2 | 0.0 | 20.8 | 16.0 | NS |
| CRP | 25.7 | 0.0 | 1.1 | 0.0 | 23.8 | 23.5 | NS |
| Repeat CRP | 12.5 | 0.1 | 2.2 | 0.1 | 7.1 | 7.3 | NS |
| Chest x‐ray | 89.4 | 0.1 | 0.7 | 0.0 | 85.4 | 83.9 | NS |
| Repeat chest x‐ray | 25.5 | 0.0 | 2.0 | 0.1 | 24.1 | 17.7 | <0.05 |
Inpatient Encounters
In the segmented regression analysis of children hospitalized with CAP, guideline publication was associated with changes in the monthly use of some diagnostic tests. For example, by the end of the study period, the use of blood culture was 41.4% (observed), whereas the projected estimated use in the absence of the guidelines was 49.2% (expected) (P < 0.05) (Figure 2). Table 2 includes the data for the other tests, CBC, CRP, and CXR, in which similar patterns are noted with lower utilization rates after the guidelines, compared with expected utilization rates without the guidelines; however, these trends did not achieve statistical significance. Evaluating the utilization of repeat testing for inpatients, only repeat CXR achieved statistical significance (P < 0.05), with utilization rates of 17.7% with the guidelines (actual) compared with 24.1% without the guidelines (predicted).
To better understand the use of repeat testing, a comparison of severity outcomesLOS, ICU transfer, and pleural drainage procedureswas performed between patients with no repeat testing (70%) and patients with 1 or more repeat tests (30%). Patients with repeat testing had longer LOS (no repeat testing LOS 1 [IQR, 12]) versus 1 repeat test LOS 3 ([IQR, 24] vs 2+ repeat tests LOS 5 [IQR, 38]), higher rate of ICU transfer (no repeat testing 4.6% vs 1 repeat test 14.6% vs 2+ repeat test 35.6%), and higher rate of pleural drainage (no repeat testing 0% vs 1 repeat test 0.1% vs 2+ repeat test 5.9%] (all P < 0.001).
Using standard costs of $37.57 for blood cultures and $73.28 for CXR, annual costs for children with CAP across all hospitals decreased by $91,512 due to decreased utilization of blood cultures, and by $146,840 due to decreased utilization of CXR.
Hospital‐Level Variation in the Impact of the National Guideline
Figure 3 is a visual representation (heat map) of the impact of the guidelines at the hospital level at the end of the study from the individual interrupted time series. Based on this heat map (Figure 3), there was wide variability between hospitals in the impact of the guideline on each test in different settings (ED or inpatient). By diagnostic testing, 7 hospitals significantly decreased utilization of blood cultures for inpatients, and 5 hospitals significantly decreased utilization for repeat blood cultures and repeat CXR. Correlation between the number of positive improvements at a hospital and region (P = 0.974), number of CAP cases (P = 0.731), or percentage of public insurance (P = 0.241) were all nonsignificant.
DISCUSSION
This study complements previous assessments by evaluating the impact of the 2011 IDSA/PIDS consensus guidelines on the management of children with CAP cared for at US children's hospitals. Prior studies have shown increased use of narrow‐spectrum antibiotics for children with CAP after the publication of these guidelines.[7] The current study focused on diagnostic testing for CAP before and after the publication of the 2011 guidelines. In the ED setting, use of some diagnostic tests (blood culture, CBC, CXR, CRP) was declining prior to guideline publication, but appeared to plateau and/or increase after 2011. Among children admitted with CAP, use of diagnostic testing was relatively stable prior to 2011, and use of these tests (blood culture, CBC, CXR, CRP) declined after guideline publication. Overall, changes in diagnostic resource utilization 3 years after publication were modest, with few changes achieving statistical significance. There was a large variability in the impact of guidelines on test use between hospitals.
For outpatients, including those managed in the ED, the PIDS/IDSA guidelines recommend limited laboratory testing in nontoxic, fully immunized patients. The guidelines discourage the use of diagnostic testing among outpatients because of their low yield (eg, blood culture), and because test results may not impact management (eg, CBC).[6] In the years prior to guideline publication, there was already a declining trend in testing rates, including blood cultures, CBC, and CRP, for patients in the ED. After guideline publication, the rate of blood cultures, CBC, and CRP increased, but only the increase in CRP utilization achieved statistical significance. We would not expect utilization for common diagnostic tests (eg, CBC for outpatients with CAP) to be at or close to 0% because of the complexity of clinical decision making regarding admission that factors in aspects of patient history, exam findings, and underlying risk.[15] ED utilization of blood cultures was <10%, CBC <15%, and CRP <5% after guideline publication, which may represent the lowest testing limit that could be achieved.
CXRs obtained in the ED did not decrease over the entire study period. The rates of CXR use (close to 80%) seen in our study are similar to prior ED studies.[5, 16] Management of children with CAP in the ED might be different than outpatient primary care management because (1) unlike primary care providers, ED providers do not have an established relationship with their patients and do not have the opportunity for follow‐up and serial exams, making them less likely to tolerate diagnostic uncertainty; and (2) ED providers may see sicker patients. However, use of CXR in the ED does represent an opportunity for further study to understand if decreased utilization is feasible without adversely impacting clinical outcomes.
The CAP guidelines provide a strong recommendation to obtain blood culture in moderate to severe pneumonia. Despite this, blood culture utilization declined after guideline publication. Less than 10% of children hospitalized with uncomplicated CAP have positive blood cultures, which calls into question the utility of blood cultures for all admitted patients.[17, 18, 19] The recent EPIC (Epidemiology of Pneumonia in the Community) study showed that a majority of children hospitalized with pneumonia do not have growth of bacteria in culture, but there may be a role for blood cultures in patients with a strong suspicion of complicated CAP or in the patient with moderate to severe disease.[20] In addition to blood cultures, the guidelines also recommend CBC and CXR in moderate to severely ill children. This observed decline in testing in CBC and CXR may be related to individual physician assessments of which patients are moderately to severely ill, as the guidelines do not recommend testing for children with less severe disease. Our exclusion of patients requiring intensive care management or pleural drainage on admission might have selected children with a milder course of illness, although still requiring admission.
The guidelines discourage repeat diagnostic testing among children hospitalized with CAP who are improving. In this study, repeat CXR and CBC occurred in approximately 20% of patients, but repeat blood culture and CRP was much lower. As with initial diagnostic testing for inpatients with CAP, the rates of some repeat testing decreased with the guidelines. However, those with repeat testing had longer LOS and were more likely to require ICU transfer or a pleural drainage procedure compared to children without repeat testing. This suggests that repeat testing is used more often in children with a severe presentation or a worsening clinical course, and not done routinely on hospitalized patients.
The financial impact of decreased testing is modest, because the tests themselves are relatively inexpensive. However, the lack of substantial cost savings should not preclude efforts to continue to improve adherence to the guidelines. Not only is increased testing associated with higher hospitalization rates,[5] potentially yielding higher costs and family stress, increased testing may also lead to patient discomfort and possibly increased radiation exposure through chest radiography.
Many of the diagnostic testing recommendations in the CAP guidelines are based on weak evidence, which may contribute to the lack of substantial adoption. Nevertheless, adherence to guideline recommendations requires sustained effort on the part of individual physicians that should be encouraged through institutional support.[21] Continuous education and clinical decision support, as well as reminders in the electronic medical record, would make guideline recommendations more visible and may help overcome the inertia of previous practice.[15] The hospital‐level heat map (Figure 3) included in this study demonstrates that the impact of the guidelines was variable across sites. Although a few sites had decreased diagnostic testing in many areas with no increased testing in any category, there were several sites that had no improvement in any diagnostic testing category. In addition, hospital‐level factors like size, geography, and insurance status were not associated with number of improvements. To better understand drivers of change at individual hospitals, future studies should evaluate specific strategies utilized by the rapid guideline adopters.
This study is subject to several limitations. The use of ICD‐9 codes to identify patients with CAP may not capture all patients with this diagnosis; however, these codes have been previously validated.[13] Additionally, because patients were identified using ICD‐9 coding assigned at the time of discharge, testing performed in the ED setting may not reflect care for a child with known pneumonia, but rather may reflect testing for a child with fever or other signs of infection. PHIS collects data from freestanding children's hospitals, which care for a majority of children with CAP in the US, but our findings may not be generalizable to other hospitals. In addition, we did not examine drivers of trends within individual institutions. We did not have detailed information to examine whether the PHIS hospitals in our study had actively worked to adopt the CAP guidelines. We were also unable to assess physician's familiarity with guidelines or the level of disagreement with the recommendations. Furthermore, the PHIS database does not permit detailed correlation of diagnostic testing with clinical parameters. In contrast to the diagnostic testing evaluated in this study, which is primarily discouraged by the IDSA/PIDS guidelines, respiratory viral testing for children with CAP is recommended but could not be evaluated, as data on such testing are not readily available in PHIS.
CONCLUSION
Publication of the IDSA/PIDS evidence‐based guidelines for the management of CAP was associated with modest, variable changes in use of diagnostic testing. Further adoption of the CAP guidelines should reduce variation in care and decrease unnecessary resource utilization in the management of CAP. Our study demonstrates that efforts to promote decreased resource utilization should target specific situations (eg, repeat testing for inpatients who are improving). Adherence to guidelines may be improved by the adoption of local practices that integrate and improve daily workflow, like order sets and clinical decision support tools.
Disclosure: Nothing to report.
- , . Eliminating waste in US health care. JAMA. 2012;307(14):1513–1516.
- , , , et al. Choosing wisely in pediatric hospital medicine: five opportunities for improved healthcare value. J Hosp Med. 2013;8(9):479–485.
- , , , et al.; Pediatric Research in Inpatient Settings (PRIS) Network. Prioritization of comparative effectiveness research topics in hospital pediatrics. Arch Pediatr Adolesc Med. 2012;166(12):1155–1164.
- , , , et al. Variability in processes of care and outcomes among children hospitalized with community‐acquired pneumonia. Pediatr Infect Dis J. 2012;31(10):1036–1041.
- , , , , . Variation in emergency department diagnostic testing and disposition outcomes in pneumonia. Pediatrics. 2013;132(2):237–244.
- , , , et al.; Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. The management of community‐acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. Clin Infect Dis. 2011;53(7):e25–e76.
- , , , et al., Impact of Infectious Diseases Society of America/Pediatric Infectious Diseases Society guidelines on treatment of community‐acquired pneumonia in hospitalized children. Clin Infect Dis. 2014;58(6):834–838.
- , , , et al. Antibiotic choice for children hospitalized with pneumonia and adherence to national guidelines. Pediatrics. 2015;136(1):44–52.
- , , , et al. Quality improvement methods increase appropriate antibiotic prescribing for childhood pneumonia. Pediatrics. 2013;131(5):e1623–e1631.
- , , , et al. Improvement methodology increases guideline recommended blood cultures in children with pneumonia. Pediatrics. 2015;135(4):e1052–e1059.
- , , , , , . Impact of a guideline on management of children hospitalized with community‐acquired pneumonia. Pediatrics. 2012;129(3):e597–e604.
- , , , . Effectiveness of antimicrobial guidelines for community‐acquired pneumonia in children. Pediatrics. 2012;129(5):e1326–e1333.
- , , , et al. Identifying pediatric community‐acquired pneumonia hospitalizations: accuracy of administrative billing codes. JAMA Pediatr. 2013;167(9):851–858.
- , , , , . Pediatric complex chronic conditions classification system version 2: updated for ICD‐10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199.
- , . Establishing superior benchmarks of care in clinical practice: a proposal to drive achievable health care value. JAMA Pediatr. 2015;169(4):301–302.
- , , , . Emergency department management of childhood pneumonia in the United States prior to publication of national guidelines. Acad Emerg Med. 2013;20(3):240–246.
- , , , et al. Prevalence of bacteremia in hospitalized pediatric patients with community‐acquired pneumonia. Pediatr Infect Dis J. 2013;32(7):736–740.
- , , , , . The prevalence of bacteremia in pediatric patients with community‐acquired pneumonia: guidelines to reduce the frequency of obtaining blood cultures. Hosp Pediatr. 2013;3(2):92–96.
- . Do all children hospitalized with community‐acquired pneumonia require blood cultures? Hosp Pediatr. 2013;3(2):177–179.
- , , , et al.; CDC EPIC Study Team. Community‐acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372(9):835–845.
- , , , et al. Influence of hospital guidelines on management of children hospitalized with pneumonia. Pediatrics. 2012;130(5):e823–e830.
- , . Eliminating waste in US health care. JAMA. 2012;307(14):1513–1516.
- , , , et al. Choosing wisely in pediatric hospital medicine: five opportunities for improved healthcare value. J Hosp Med. 2013;8(9):479–485.
- , , , et al.; Pediatric Research in Inpatient Settings (PRIS) Network. Prioritization of comparative effectiveness research topics in hospital pediatrics. Arch Pediatr Adolesc Med. 2012;166(12):1155–1164.
- , , , et al. Variability in processes of care and outcomes among children hospitalized with community‐acquired pneumonia. Pediatr Infect Dis J. 2012;31(10):1036–1041.
- , , , , . Variation in emergency department diagnostic testing and disposition outcomes in pneumonia. Pediatrics. 2013;132(2):237–244.
- , , , et al.; Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. The management of community‐acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. Clin Infect Dis. 2011;53(7):e25–e76.
- , , , et al., Impact of Infectious Diseases Society of America/Pediatric Infectious Diseases Society guidelines on treatment of community‐acquired pneumonia in hospitalized children. Clin Infect Dis. 2014;58(6):834–838.
- , , , et al. Antibiotic choice for children hospitalized with pneumonia and adherence to national guidelines. Pediatrics. 2015;136(1):44–52.
- , , , et al. Quality improvement methods increase appropriate antibiotic prescribing for childhood pneumonia. Pediatrics. 2013;131(5):e1623–e1631.
- , , , et al. Improvement methodology increases guideline recommended blood cultures in children with pneumonia. Pediatrics. 2015;135(4):e1052–e1059.
- , , , , , . Impact of a guideline on management of children hospitalized with community‐acquired pneumonia. Pediatrics. 2012;129(3):e597–e604.
- , , , . Effectiveness of antimicrobial guidelines for community‐acquired pneumonia in children. Pediatrics. 2012;129(5):e1326–e1333.
- , , , et al. Identifying pediatric community‐acquired pneumonia hospitalizations: accuracy of administrative billing codes. JAMA Pediatr. 2013;167(9):851–858.
- , , , , . Pediatric complex chronic conditions classification system version 2: updated for ICD‐10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199.
- , . Establishing superior benchmarks of care in clinical practice: a proposal to drive achievable health care value. JAMA Pediatr. 2015;169(4):301–302.
- , , , . Emergency department management of childhood pneumonia in the United States prior to publication of national guidelines. Acad Emerg Med. 2013;20(3):240–246.
- , , , et al. Prevalence of bacteremia in hospitalized pediatric patients with community‐acquired pneumonia. Pediatr Infect Dis J. 2013;32(7):736–740.
- , , , , . The prevalence of bacteremia in pediatric patients with community‐acquired pneumonia: guidelines to reduce the frequency of obtaining blood cultures. Hosp Pediatr. 2013;3(2):92–96.
- . Do all children hospitalized with community‐acquired pneumonia require blood cultures? Hosp Pediatr. 2013;3(2):177–179.
- , , , et al.; CDC EPIC Study Team. Community‐acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372(9):835–845.
- , , , et al. Influence of hospital guidelines on management of children hospitalized with pneumonia. Pediatrics. 2012;130(5):e823–e830.
© 2015 Society of Hospital Medicine
TCS Among Children with Pneumonia
National guidelines for the management of childhood pneumonia highlight the need for the development of objective outcome measures to inform clinical decision making, establish benchmarks of care, and compare treatments and interventions.[1] Time to clinical stability (TCS) is a measure reported in adult pneumonia studies that incorporates vital signs, ability to eat, and mental status to objectively assess readiness for discharge.[2, 3, 4] TCS has not been validated among children as it has in adults,[5, 6, 7, 8] although such measures could prove useful for assessing discharge readiness with applications in both clinical and research settings. The objective of our study was to test the performance of pediatric TCS measures among children hospitalized with pneumonia.
METHODS
Study Population
We studied children hospitalized with community‐acquired pneumonia at Monroe Carell Jr. Children's Hospital at Vanderbilt between January 6, 2010 and May 9, 2011. Study children were enrolled as part of the Centers for Disease Control & Prevention (CDC) Etiology of Pneumonia in the Community (EPIC) study, a prospective, population‐based study of community‐acquired pneumonia hospitalizations. Detailed enrollment criteria for the EPIC study were reported previously.[9] Institutional review boards at Vanderbilt University and the CDC approved this study. Informed consent was obtained from enrolled families.
Data Elements and Study Definitions
Baseline data, including demographics, illness history, comorbidities, and clinical outcomes (eg, length of stay [LOS], intensive care admission), were systematically and prospectively collected. Additionally, data for 4 physiologic parameters, including temperature, heart rate, respiratory rate, and use of supplemental oxygen were obtained from the electronic medical record. These parameters were measured at least every 6 hours from admission through discharge as part of routine care. Readmissions within 7 calendar days of discharge were also obtained from the electronic medical record.
Stability for each parameter was defined as follows: normal temperature (36.037.9C), normal respiratory and heart rates in accordance with Pediatric Advanced Life Support age‐based values (see Supporting Table 1 in the online version of this article),[10] and no administration of supplemental oxygen. If the last recorded value for a given parameter was abnormal, that parameter was considered unstable at discharge. Otherwise, the time and date of the last abnormal value for each parameter was subtracted from admission time and date to determine TCS for that parameter in hours.
To determine overall stability, we evaluated 4 combination TCS measures, each incorporating 2 individual parameters. All combinations included respiratory rate and need for supplemental oxygen, as these parameters are the most explicit clinical indicators of pneumonia. Stability for each combination measure was defined as normalization of all included measures.
Clinical Outcomes for the Combined TCS Measures
The 4 combined TCS measures were compared against clinical outcomes including hospital LOS (measured in hours) and an ordinal severity scale. The ordinal scale categorized children into 3 mutually exclusive groups as follows: nonsevere (hospitalization without need for intensive care or empyema requiring drainage), severe (intensive care admission without invasive mechanical ventilation or vasopressor support and no empyema requiring drainage), and very severe (invasive mechanical ventilation, vasopressor support, or empyema requiring drainage).
Statistical Analysis
Categorical and continuous variables were summarized using frequencies and percentages and median and interquartile range (IQR) values, respectively. Analyses were stratified by age (<2 years, 24 years, 517 years). We also plotted summary statistics for the combined measures and LOS, and computed the median absolute difference between these measures for each level of the ordinal severity scale. Analyses were conducted using Stata 13 (StataCorp, College Station, TX).
RESULTS
Study Population
Among 336 children enrolled in the EPIC study at Vanderbilt during the study period, 334 (99.4%) with complete data were included. Median age was 33 months (IQR, 1480). Median LOS was 56.4 hours (IQR, 41.591.7). There were 249 (74.5%) children classified as nonsevere, 39 (11.7) as severe, and 46 (13.8) as very severe (for age‐based characteristics see Supporting Table 2 in the online version of this article). Overall, 12 (3.6%) children were readmitted within 7 days of discharge.
Individual Stability Parameters
Overall, 323 (96.7%) children had 1 parameter abnormal on admission. Respiratory rate (81.4%) was the most common abnormal parameter, followed by abnormal temperature (71.4%), use of supplemental oxygen (63.8%), and abnormal heart rate (54.4%). Overall, use of supplemental oxygen had the longest TCS, followed by respiratory rate (Table 1). In comparison, heart rate and temperature stabilized relatively quickly.
| Parameter | <2 Years, n=130 | 24 Years, n=90 | 517 Years, n=101 | |||
|---|---|---|---|---|---|---|
| No. (%)* | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | |
| ||||||
| Respiratory rate | 97 (74.6) | 38.6 (18.768.9) | 63 (70.0) | 31.6 (9.561.9) | 63 (62.4) | 24.3 (10.859.2) |
| Oxygen | 90 (69.2) | 39.5 (19.273.6) | 58 (64.4) | 44.2 (2477.6) | 61 (60.4) | 38.3 (1870.6) |
| Heart rate | 21 (16.2) | 4.5 (0.318.4) | 73 (81.1) | 21.8 (5.751.9) | 62 (61.4) | 18 (5.842.2) |
| Temperature | 101 (77.7) | 14.5 (4.545.3) | 61 (67.8) | 18.4 (2.842.8) | 62 (61.4) | 10.6 (0.834) |
Seventy children (21.0%) had 1 parameter abnormal at discharge, including abnormal respiratory rate in 13.7%, heart rate in 7.0%, and temperature in 3.3%. One child (0.3%) was discharged with supplemental oxygen. Ten children (3.0%) had 2 parameters abnormal at discharge. There was no difference in 7‐day readmissions for children with 1 parameter abnormal at discharge (1.4%) compared to those with no abnormal parameters at discharge (4.4%, P=0.253).
Combination TCS Measures
Within each age group, the percentage of children achieving stability was relatively consistent across the 4 combined TCS measures (Table 2); however, more children were considered unstable at discharge (and fewer classified as stable on admission) as the number of included parameters increased. More children <5 years of age reached stability (range, 80.0%85.6%) compared to children 5 years of age (range, 68.3%72.3%). We also noted increasing median TCS with increasing disease severity (Figure 1, P<0.01) (see Supporting Fig. 1AC in the online version of this article); TCS was only slightly shorter than LOS across all 3 levels of the severity scale.
| TCS Measures | <2 Years, n=130 | 24 Years, n=90 | 517 Years, n=101 | P Value | |||
|---|---|---|---|---|---|---|---|
| No. (%)* | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | ||
| |||||||
| RR+O2 | 108 (83.1) | 40.5 (20.175.0) | 72 (80.0) | 39.6 (15.679.2) | 69 (68.3) | 30.4 (14.759.2) | 0.08 |
| RR+O2+HR | 109 (83.8) | 40.2 (19.573.9) | 73 (81.1) | 35.9 (15.977.6) | 68 (67.3) | 29.8 (17.256.6) | 0.11 |
| RR+O2+T | 110 (84.6) | 40.5 (20.770.1) | 77 (85.6) | 39.1 (18.477.6) | 73 (72.3) | 28.2 (14.744.7) | 0.03 |
| RR+O2+HR+T | 110 (84.6) | 40.5 (20.770.1) | 72 (80.0) | 39.7 (20.177.5) | 71 (70.3) | 29.2 (18.254) | 0.05 |
DISCUSSION
Our study demonstrates that longitudinal TCS measures consisting of routinely collected physiologic parameters may be useful for objectively assessing disease recovery and clinical readiness for discharge among children hospitalized with pneumonia. A simple TCS measure incorporating respiratory rate and oxygen requirement performed similarly to the more complex combinations and classified fewer children as unstable at discharge. However, we also note several challenges that deserve additional study prior to the application of a pediatric TCS measure in clinical and research settings.
Vital signs and supplemental oxygen use are used clinically to assess disease severity and response to therapy among children with acute respiratory illness. Because these objective parameters are routinely collected among hospitalized children, the systematization of these data could inform clinical decision making around hospital discharge. Similar to early warning scores used to detect impending clinical deterioration,[11] TCS measures, by signaling normalization of stability parameters in a consistent and objective manner, could serve as an early signal of readiness for discharge. However, maximizing the clinical utility of TCS would require embedding the process within the electronic health record, a tool that could also have implications for the Centers for Medicare and Medicaid Services' meaningful use regulations.[12]
TCS could also serve as an outcome measure in research and quality efforts. Increased disease severity was associated with longer TCS for the 4 combined measures; TCS also demonstrated strong agreement with LOS. Furthermore, TCS minimizes the influence of factors unrelated to disease that may impact LOS (eg, frequency of hospital rounds, transportation difficulties, or social impediments to discharge), an advantage when studying outcomes for research and quality benchmarking.
The percentage of children reaching stability and the median TCS for the combined measures demonstrated little variation within each age group, likely because respiratory rate and need for supplemental oxygen, 2 of the parameters with the longest individual time to stability, were also included in each of the combination measures. This suggests that less‐complex measures incorporating only respiratory rate and need for supplemental oxygen may be sufficient to assess clinical stability, particularly because these parameters are objectively measured and possess a direct physiological link to pneumonia. In contrast, the other parameters may be more often influenced by factors unrelated to disease severity.
Our study also highlights several shortcomings of the pediatric TCS measures. Despite use of published, age‐based reference values,[13] we noted wide variation in the achievement of stability across individual parameters, especially for children 5 years old. Overall, 21% of children had 1 abnormal parameter at discharge. Even the simplest combined measure classified 13.4% of children as unstable at discharge. Discharge with unstable parameters was not associated with 7‐day readmission, although our study was underpowered to detect small differences. Additional study is therefore needed to evaluate less restrictive cutoff values on calculated TCS and the impact of hospital discharge prior to reaching stability. In particular, relaxing the upper limit for normal respiratory rate in adolescents (16 breaths per minute) to more closely approximate the adult TCS parameter (24 breaths per minute) should be explored. Refinement and standardization of age‐based vital sign reference values specific to hospitalized children may also improve the performance of these measures.[14]
Several limitations deserve discussion. TCS parameters and readmission data were abstracted retrospectively from a single institution, and our findings may not be generalizable. Although clinical staff routinely measured these data, measurement variation likely exists. Nevertheless, such variation is likely systematic, limiting the impact of potential misclassification. TCS was calculated based on the last abnormal value for each parameter; prior fluctuations between normal and abnormal periods of stability were not captured. We were unable to assess room air oxygen saturations. Instead, supplemental oxygen use served as a surrogate for hypoxia. At our institution, oxygen therapy is provided for children with pneumonia to maintain oxygen saturations of 90% to 92%. We did not assess work of breathing (a marker of severe pneumonia) or ability to eat (a component of adult TCS measures). We initially considered the evaluation of intravenous fluids as a proxy for ability to eat (addition of this parameter to the 4 parameter TCS resulted in a modest increase in median time to stability, data not shown); however, we felt the lack of institutional policy and subjective nature of this parameter detracted from our study's objectives. Finally, we were not able to determine clinical readiness for discharge beyond the measurement of vital sign parameters. Therefore, prospective evaluation of the proposed pediatric TCS measures in broader populations will be important to build upon our findings, refine stability parameters, and test the utility of new parameters (eg, ability to eat, work of breathing) prior to use in clinical settings.
Our study provides an initial evaluation of TCS measures for assessing severity and recovery among children hospitalized with pneumonia. Similar to adults, such validated TCS measures may ultimately prove useful for improving the quality of both clinical care and research, although additional study to more clearly define stability criteria is needed prior to implementation.
Disclosures
This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number K23AI104779 to Dr. Williams. The EPIC study was supported by the Influenza Division in the National Center for Immunizations and Respiratory Diseases at the Centers for Disease Control and Prevention through cooperative agreements with each study site and was based on a competitive research funding opportunity. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention or the National Institutes of Health. Dr. Grijalva serves as a consultant to Glaxo‐Smith‐Kline and Pfizer outside of the scope of this article. Dr. Edwards is supported through grants from Novartis for the conduction of a Group B strep vaccine study and serves as the Chair of the Data Safety and Monitoring Data Committee for Influenza Study outside the scope of this article. Dr. Self reports grants from CareFusion, BioMerieux, Affinium Pharmaceuticals, Astute Medical, Crucell Holland BV, BRAHMS GmbH, Pfizer, Rapid Pathogen Screening, Venaxis, BioAegis Inc., Sphingotec GmbH, and Cempra Pharmaceuticals; personal fees from BioFire Diagnostics and Venaxis, Inc; and patent 13/632,874 (Sterile Blood Culture Collection System) pending; all outside the scope of this article.
- Healthcare Cost and Utilization Project. Available at: http://www.ahrq.gov/research/data/hcup/index.html. Accessed February 1, 2014.
- , , , et al. Time to clinical stability in patients hospitalized with community‐acquired pneumonia: implications for practice guidelines. JAMA. 1998;279:1452–1457.
- , , , et al.; Neumofail Group. Reaching stability in community‐acquired pneumonia: the effects of the severity of disease, treatment, and the characteristics of patients. Clin Infect Dis. 2004;39:1783–1790.
- , , , et al.; Community‐Acquired Pneumonia Organization. The pneumonia severity index predicts time to clinical stability in patients with community‐acquired pneumonia. Int J Tuberc Lung Dis. 2006;10:739–743.
- , , , , . Efficacy of corticosteroids in community‐acquired pneumonia: a randomized double‐blinded clinical trial. Am J Respir Crit Care Med. 2010;181:975–982.
- , , , et al. Early administration of antibiotics does not shorten time to clinical stability in patients with moderate‐to‐severe community‐acquired pneumonia. Chest 2003;124:1798–1804.
- , , , . A comparison between time to clinical stability in community‐acquired aspiration pneumonia and community‐acquired pneumonia. Intern Emerg Med. 2014;9:143–150.
- , , , et al.; Community‐Acquired Pneumonia Organization (CAPO) Investigators. A worldwide perspective of atypical pathogens in community‐acquired pneumonia. Am J Respir Crit Care Med. 2007;175:1086–1093.
- , , , et al.; CDC EPIC Study Team. Community‐acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372:835–845.
- American Heart Association. 2005 American Heart Association (AHA) guidelines for cardiopulmonary resuscitation (CPR) and emergency cardiovascular care (ECC) of pediatric and neonatal patients: pediatric basic life support. Pediatrics. 2006;117:e989–e1004.
- , , . Development and initial validation of the Bedside Paediatric Early Warning System score. Crit Care. 2009;13:R135.
- Centers for Medicare and Medicaid Services. Regulations and guidance. EHR incentive programs. Available at: http://www.cms.gov/Regulations‐and‐Guidance/Legislation/EHRIncentivePrograms/index.html. Accessed February 20, 2015
- , , , , , . Development of heart and respiratory rate percentile curves for hospitalized children. Pediatrics. 2013;131:e1150–e1157.
- , , , et al. Length of stay after reaching clinical stability drives hospital costs associated with adult community‐acquired pneumonia. Scand J Infect Dis. 2013;45:219–226.
National guidelines for the management of childhood pneumonia highlight the need for the development of objective outcome measures to inform clinical decision making, establish benchmarks of care, and compare treatments and interventions.[1] Time to clinical stability (TCS) is a measure reported in adult pneumonia studies that incorporates vital signs, ability to eat, and mental status to objectively assess readiness for discharge.[2, 3, 4] TCS has not been validated among children as it has in adults,[5, 6, 7, 8] although such measures could prove useful for assessing discharge readiness with applications in both clinical and research settings. The objective of our study was to test the performance of pediatric TCS measures among children hospitalized with pneumonia.
METHODS
Study Population
We studied children hospitalized with community‐acquired pneumonia at Monroe Carell Jr. Children's Hospital at Vanderbilt between January 6, 2010 and May 9, 2011. Study children were enrolled as part of the Centers for Disease Control & Prevention (CDC) Etiology of Pneumonia in the Community (EPIC) study, a prospective, population‐based study of community‐acquired pneumonia hospitalizations. Detailed enrollment criteria for the EPIC study were reported previously.[9] Institutional review boards at Vanderbilt University and the CDC approved this study. Informed consent was obtained from enrolled families.
Data Elements and Study Definitions
Baseline data, including demographics, illness history, comorbidities, and clinical outcomes (eg, length of stay [LOS], intensive care admission), were systematically and prospectively collected. Additionally, data for 4 physiologic parameters, including temperature, heart rate, respiratory rate, and use of supplemental oxygen were obtained from the electronic medical record. These parameters were measured at least every 6 hours from admission through discharge as part of routine care. Readmissions within 7 calendar days of discharge were also obtained from the electronic medical record.
Stability for each parameter was defined as follows: normal temperature (36.037.9C), normal respiratory and heart rates in accordance with Pediatric Advanced Life Support age‐based values (see Supporting Table 1 in the online version of this article),[10] and no administration of supplemental oxygen. If the last recorded value for a given parameter was abnormal, that parameter was considered unstable at discharge. Otherwise, the time and date of the last abnormal value for each parameter was subtracted from admission time and date to determine TCS for that parameter in hours.
To determine overall stability, we evaluated 4 combination TCS measures, each incorporating 2 individual parameters. All combinations included respiratory rate and need for supplemental oxygen, as these parameters are the most explicit clinical indicators of pneumonia. Stability for each combination measure was defined as normalization of all included measures.
Clinical Outcomes for the Combined TCS Measures
The 4 combined TCS measures were compared against clinical outcomes including hospital LOS (measured in hours) and an ordinal severity scale. The ordinal scale categorized children into 3 mutually exclusive groups as follows: nonsevere (hospitalization without need for intensive care or empyema requiring drainage), severe (intensive care admission without invasive mechanical ventilation or vasopressor support and no empyema requiring drainage), and very severe (invasive mechanical ventilation, vasopressor support, or empyema requiring drainage).
Statistical Analysis
Categorical and continuous variables were summarized using frequencies and percentages and median and interquartile range (IQR) values, respectively. Analyses were stratified by age (<2 years, 24 years, 517 years). We also plotted summary statistics for the combined measures and LOS, and computed the median absolute difference between these measures for each level of the ordinal severity scale. Analyses were conducted using Stata 13 (StataCorp, College Station, TX).
RESULTS
Study Population
Among 336 children enrolled in the EPIC study at Vanderbilt during the study period, 334 (99.4%) with complete data were included. Median age was 33 months (IQR, 1480). Median LOS was 56.4 hours (IQR, 41.591.7). There were 249 (74.5%) children classified as nonsevere, 39 (11.7) as severe, and 46 (13.8) as very severe (for age‐based characteristics see Supporting Table 2 in the online version of this article). Overall, 12 (3.6%) children were readmitted within 7 days of discharge.
Individual Stability Parameters
Overall, 323 (96.7%) children had 1 parameter abnormal on admission. Respiratory rate (81.4%) was the most common abnormal parameter, followed by abnormal temperature (71.4%), use of supplemental oxygen (63.8%), and abnormal heart rate (54.4%). Overall, use of supplemental oxygen had the longest TCS, followed by respiratory rate (Table 1). In comparison, heart rate and temperature stabilized relatively quickly.
| Parameter | <2 Years, n=130 | 24 Years, n=90 | 517 Years, n=101 | |||
|---|---|---|---|---|---|---|
| No. (%)* | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | |
| ||||||
| Respiratory rate | 97 (74.6) | 38.6 (18.768.9) | 63 (70.0) | 31.6 (9.561.9) | 63 (62.4) | 24.3 (10.859.2) |
| Oxygen | 90 (69.2) | 39.5 (19.273.6) | 58 (64.4) | 44.2 (2477.6) | 61 (60.4) | 38.3 (1870.6) |
| Heart rate | 21 (16.2) | 4.5 (0.318.4) | 73 (81.1) | 21.8 (5.751.9) | 62 (61.4) | 18 (5.842.2) |
| Temperature | 101 (77.7) | 14.5 (4.545.3) | 61 (67.8) | 18.4 (2.842.8) | 62 (61.4) | 10.6 (0.834) |
Seventy children (21.0%) had 1 parameter abnormal at discharge, including abnormal respiratory rate in 13.7%, heart rate in 7.0%, and temperature in 3.3%. One child (0.3%) was discharged with supplemental oxygen. Ten children (3.0%) had 2 parameters abnormal at discharge. There was no difference in 7‐day readmissions for children with 1 parameter abnormal at discharge (1.4%) compared to those with no abnormal parameters at discharge (4.4%, P=0.253).
Combination TCS Measures
Within each age group, the percentage of children achieving stability was relatively consistent across the 4 combined TCS measures (Table 2); however, more children were considered unstable at discharge (and fewer classified as stable on admission) as the number of included parameters increased. More children <5 years of age reached stability (range, 80.0%85.6%) compared to children 5 years of age (range, 68.3%72.3%). We also noted increasing median TCS with increasing disease severity (Figure 1, P<0.01) (see Supporting Fig. 1AC in the online version of this article); TCS was only slightly shorter than LOS across all 3 levels of the severity scale.
| TCS Measures | <2 Years, n=130 | 24 Years, n=90 | 517 Years, n=101 | P Value | |||
|---|---|---|---|---|---|---|---|
| No. (%)* | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | ||
| |||||||
| RR+O2 | 108 (83.1) | 40.5 (20.175.0) | 72 (80.0) | 39.6 (15.679.2) | 69 (68.3) | 30.4 (14.759.2) | 0.08 |
| RR+O2+HR | 109 (83.8) | 40.2 (19.573.9) | 73 (81.1) | 35.9 (15.977.6) | 68 (67.3) | 29.8 (17.256.6) | 0.11 |
| RR+O2+T | 110 (84.6) | 40.5 (20.770.1) | 77 (85.6) | 39.1 (18.477.6) | 73 (72.3) | 28.2 (14.744.7) | 0.03 |
| RR+O2+HR+T | 110 (84.6) | 40.5 (20.770.1) | 72 (80.0) | 39.7 (20.177.5) | 71 (70.3) | 29.2 (18.254) | 0.05 |
DISCUSSION
Our study demonstrates that longitudinal TCS measures consisting of routinely collected physiologic parameters may be useful for objectively assessing disease recovery and clinical readiness for discharge among children hospitalized with pneumonia. A simple TCS measure incorporating respiratory rate and oxygen requirement performed similarly to the more complex combinations and classified fewer children as unstable at discharge. However, we also note several challenges that deserve additional study prior to the application of a pediatric TCS measure in clinical and research settings.
Vital signs and supplemental oxygen use are used clinically to assess disease severity and response to therapy among children with acute respiratory illness. Because these objective parameters are routinely collected among hospitalized children, the systematization of these data could inform clinical decision making around hospital discharge. Similar to early warning scores used to detect impending clinical deterioration,[11] TCS measures, by signaling normalization of stability parameters in a consistent and objective manner, could serve as an early signal of readiness for discharge. However, maximizing the clinical utility of TCS would require embedding the process within the electronic health record, a tool that could also have implications for the Centers for Medicare and Medicaid Services' meaningful use regulations.[12]
TCS could also serve as an outcome measure in research and quality efforts. Increased disease severity was associated with longer TCS for the 4 combined measures; TCS also demonstrated strong agreement with LOS. Furthermore, TCS minimizes the influence of factors unrelated to disease that may impact LOS (eg, frequency of hospital rounds, transportation difficulties, or social impediments to discharge), an advantage when studying outcomes for research and quality benchmarking.
The percentage of children reaching stability and the median TCS for the combined measures demonstrated little variation within each age group, likely because respiratory rate and need for supplemental oxygen, 2 of the parameters with the longest individual time to stability, were also included in each of the combination measures. This suggests that less‐complex measures incorporating only respiratory rate and need for supplemental oxygen may be sufficient to assess clinical stability, particularly because these parameters are objectively measured and possess a direct physiological link to pneumonia. In contrast, the other parameters may be more often influenced by factors unrelated to disease severity.
Our study also highlights several shortcomings of the pediatric TCS measures. Despite use of published, age‐based reference values,[13] we noted wide variation in the achievement of stability across individual parameters, especially for children 5 years old. Overall, 21% of children had 1 abnormal parameter at discharge. Even the simplest combined measure classified 13.4% of children as unstable at discharge. Discharge with unstable parameters was not associated with 7‐day readmission, although our study was underpowered to detect small differences. Additional study is therefore needed to evaluate less restrictive cutoff values on calculated TCS and the impact of hospital discharge prior to reaching stability. In particular, relaxing the upper limit for normal respiratory rate in adolescents (16 breaths per minute) to more closely approximate the adult TCS parameter (24 breaths per minute) should be explored. Refinement and standardization of age‐based vital sign reference values specific to hospitalized children may also improve the performance of these measures.[14]
Several limitations deserve discussion. TCS parameters and readmission data were abstracted retrospectively from a single institution, and our findings may not be generalizable. Although clinical staff routinely measured these data, measurement variation likely exists. Nevertheless, such variation is likely systematic, limiting the impact of potential misclassification. TCS was calculated based on the last abnormal value for each parameter; prior fluctuations between normal and abnormal periods of stability were not captured. We were unable to assess room air oxygen saturations. Instead, supplemental oxygen use served as a surrogate for hypoxia. At our institution, oxygen therapy is provided for children with pneumonia to maintain oxygen saturations of 90% to 92%. We did not assess work of breathing (a marker of severe pneumonia) or ability to eat (a component of adult TCS measures). We initially considered the evaluation of intravenous fluids as a proxy for ability to eat (addition of this parameter to the 4 parameter TCS resulted in a modest increase in median time to stability, data not shown); however, we felt the lack of institutional policy and subjective nature of this parameter detracted from our study's objectives. Finally, we were not able to determine clinical readiness for discharge beyond the measurement of vital sign parameters. Therefore, prospective evaluation of the proposed pediatric TCS measures in broader populations will be important to build upon our findings, refine stability parameters, and test the utility of new parameters (eg, ability to eat, work of breathing) prior to use in clinical settings.
Our study provides an initial evaluation of TCS measures for assessing severity and recovery among children hospitalized with pneumonia. Similar to adults, such validated TCS measures may ultimately prove useful for improving the quality of both clinical care and research, although additional study to more clearly define stability criteria is needed prior to implementation.
Disclosures
This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number K23AI104779 to Dr. Williams. The EPIC study was supported by the Influenza Division in the National Center for Immunizations and Respiratory Diseases at the Centers for Disease Control and Prevention through cooperative agreements with each study site and was based on a competitive research funding opportunity. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention or the National Institutes of Health. Dr. Grijalva serves as a consultant to Glaxo‐Smith‐Kline and Pfizer outside of the scope of this article. Dr. Edwards is supported through grants from Novartis for the conduction of a Group B strep vaccine study and serves as the Chair of the Data Safety and Monitoring Data Committee for Influenza Study outside the scope of this article. Dr. Self reports grants from CareFusion, BioMerieux, Affinium Pharmaceuticals, Astute Medical, Crucell Holland BV, BRAHMS GmbH, Pfizer, Rapid Pathogen Screening, Venaxis, BioAegis Inc., Sphingotec GmbH, and Cempra Pharmaceuticals; personal fees from BioFire Diagnostics and Venaxis, Inc; and patent 13/632,874 (Sterile Blood Culture Collection System) pending; all outside the scope of this article.
National guidelines for the management of childhood pneumonia highlight the need for the development of objective outcome measures to inform clinical decision making, establish benchmarks of care, and compare treatments and interventions.[1] Time to clinical stability (TCS) is a measure reported in adult pneumonia studies that incorporates vital signs, ability to eat, and mental status to objectively assess readiness for discharge.[2, 3, 4] TCS has not been validated among children as it has in adults,[5, 6, 7, 8] although such measures could prove useful for assessing discharge readiness with applications in both clinical and research settings. The objective of our study was to test the performance of pediatric TCS measures among children hospitalized with pneumonia.
METHODS
Study Population
We studied children hospitalized with community‐acquired pneumonia at Monroe Carell Jr. Children's Hospital at Vanderbilt between January 6, 2010 and May 9, 2011. Study children were enrolled as part of the Centers for Disease Control & Prevention (CDC) Etiology of Pneumonia in the Community (EPIC) study, a prospective, population‐based study of community‐acquired pneumonia hospitalizations. Detailed enrollment criteria for the EPIC study were reported previously.[9] Institutional review boards at Vanderbilt University and the CDC approved this study. Informed consent was obtained from enrolled families.
Data Elements and Study Definitions
Baseline data, including demographics, illness history, comorbidities, and clinical outcomes (eg, length of stay [LOS], intensive care admission), were systematically and prospectively collected. Additionally, data for 4 physiologic parameters, including temperature, heart rate, respiratory rate, and use of supplemental oxygen were obtained from the electronic medical record. These parameters were measured at least every 6 hours from admission through discharge as part of routine care. Readmissions within 7 calendar days of discharge were also obtained from the electronic medical record.
Stability for each parameter was defined as follows: normal temperature (36.037.9C), normal respiratory and heart rates in accordance with Pediatric Advanced Life Support age‐based values (see Supporting Table 1 in the online version of this article),[10] and no administration of supplemental oxygen. If the last recorded value for a given parameter was abnormal, that parameter was considered unstable at discharge. Otherwise, the time and date of the last abnormal value for each parameter was subtracted from admission time and date to determine TCS for that parameter in hours.
To determine overall stability, we evaluated 4 combination TCS measures, each incorporating 2 individual parameters. All combinations included respiratory rate and need for supplemental oxygen, as these parameters are the most explicit clinical indicators of pneumonia. Stability for each combination measure was defined as normalization of all included measures.
Clinical Outcomes for the Combined TCS Measures
The 4 combined TCS measures were compared against clinical outcomes including hospital LOS (measured in hours) and an ordinal severity scale. The ordinal scale categorized children into 3 mutually exclusive groups as follows: nonsevere (hospitalization without need for intensive care or empyema requiring drainage), severe (intensive care admission without invasive mechanical ventilation or vasopressor support and no empyema requiring drainage), and very severe (invasive mechanical ventilation, vasopressor support, or empyema requiring drainage).
Statistical Analysis
Categorical and continuous variables were summarized using frequencies and percentages and median and interquartile range (IQR) values, respectively. Analyses were stratified by age (<2 years, 24 years, 517 years). We also plotted summary statistics for the combined measures and LOS, and computed the median absolute difference between these measures for each level of the ordinal severity scale. Analyses were conducted using Stata 13 (StataCorp, College Station, TX).
RESULTS
Study Population
Among 336 children enrolled in the EPIC study at Vanderbilt during the study period, 334 (99.4%) with complete data were included. Median age was 33 months (IQR, 1480). Median LOS was 56.4 hours (IQR, 41.591.7). There were 249 (74.5%) children classified as nonsevere, 39 (11.7) as severe, and 46 (13.8) as very severe (for age‐based characteristics see Supporting Table 2 in the online version of this article). Overall, 12 (3.6%) children were readmitted within 7 days of discharge.
Individual Stability Parameters
Overall, 323 (96.7%) children had 1 parameter abnormal on admission. Respiratory rate (81.4%) was the most common abnormal parameter, followed by abnormal temperature (71.4%), use of supplemental oxygen (63.8%), and abnormal heart rate (54.4%). Overall, use of supplemental oxygen had the longest TCS, followed by respiratory rate (Table 1). In comparison, heart rate and temperature stabilized relatively quickly.
| Parameter | <2 Years, n=130 | 24 Years, n=90 | 517 Years, n=101 | |||
|---|---|---|---|---|---|---|
| No. (%)* | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | |
| ||||||
| Respiratory rate | 97 (74.6) | 38.6 (18.768.9) | 63 (70.0) | 31.6 (9.561.9) | 63 (62.4) | 24.3 (10.859.2) |
| Oxygen | 90 (69.2) | 39.5 (19.273.6) | 58 (64.4) | 44.2 (2477.6) | 61 (60.4) | 38.3 (1870.6) |
| Heart rate | 21 (16.2) | 4.5 (0.318.4) | 73 (81.1) | 21.8 (5.751.9) | 62 (61.4) | 18 (5.842.2) |
| Temperature | 101 (77.7) | 14.5 (4.545.3) | 61 (67.8) | 18.4 (2.842.8) | 62 (61.4) | 10.6 (0.834) |
Seventy children (21.0%) had 1 parameter abnormal at discharge, including abnormal respiratory rate in 13.7%, heart rate in 7.0%, and temperature in 3.3%. One child (0.3%) was discharged with supplemental oxygen. Ten children (3.0%) had 2 parameters abnormal at discharge. There was no difference in 7‐day readmissions for children with 1 parameter abnormal at discharge (1.4%) compared to those with no abnormal parameters at discharge (4.4%, P=0.253).
Combination TCS Measures
Within each age group, the percentage of children achieving stability was relatively consistent across the 4 combined TCS measures (Table 2); however, more children were considered unstable at discharge (and fewer classified as stable on admission) as the number of included parameters increased. More children <5 years of age reached stability (range, 80.0%85.6%) compared to children 5 years of age (range, 68.3%72.3%). We also noted increasing median TCS with increasing disease severity (Figure 1, P<0.01) (see Supporting Fig. 1AC in the online version of this article); TCS was only slightly shorter than LOS across all 3 levels of the severity scale.
| TCS Measures | <2 Years, n=130 | 24 Years, n=90 | 517 Years, n=101 | P Value | |||
|---|---|---|---|---|---|---|---|
| No. (%)* | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | No. (%) | Median (IQR) TCS, h | ||
| |||||||
| RR+O2 | 108 (83.1) | 40.5 (20.175.0) | 72 (80.0) | 39.6 (15.679.2) | 69 (68.3) | 30.4 (14.759.2) | 0.08 |
| RR+O2+HR | 109 (83.8) | 40.2 (19.573.9) | 73 (81.1) | 35.9 (15.977.6) | 68 (67.3) | 29.8 (17.256.6) | 0.11 |
| RR+O2+T | 110 (84.6) | 40.5 (20.770.1) | 77 (85.6) | 39.1 (18.477.6) | 73 (72.3) | 28.2 (14.744.7) | 0.03 |
| RR+O2+HR+T | 110 (84.6) | 40.5 (20.770.1) | 72 (80.0) | 39.7 (20.177.5) | 71 (70.3) | 29.2 (18.254) | 0.05 |
DISCUSSION
Our study demonstrates that longitudinal TCS measures consisting of routinely collected physiologic parameters may be useful for objectively assessing disease recovery and clinical readiness for discharge among children hospitalized with pneumonia. A simple TCS measure incorporating respiratory rate and oxygen requirement performed similarly to the more complex combinations and classified fewer children as unstable at discharge. However, we also note several challenges that deserve additional study prior to the application of a pediatric TCS measure in clinical and research settings.
Vital signs and supplemental oxygen use are used clinically to assess disease severity and response to therapy among children with acute respiratory illness. Because these objective parameters are routinely collected among hospitalized children, the systematization of these data could inform clinical decision making around hospital discharge. Similar to early warning scores used to detect impending clinical deterioration,[11] TCS measures, by signaling normalization of stability parameters in a consistent and objective manner, could serve as an early signal of readiness for discharge. However, maximizing the clinical utility of TCS would require embedding the process within the electronic health record, a tool that could also have implications for the Centers for Medicare and Medicaid Services' meaningful use regulations.[12]
TCS could also serve as an outcome measure in research and quality efforts. Increased disease severity was associated with longer TCS for the 4 combined measures; TCS also demonstrated strong agreement with LOS. Furthermore, TCS minimizes the influence of factors unrelated to disease that may impact LOS (eg, frequency of hospital rounds, transportation difficulties, or social impediments to discharge), an advantage when studying outcomes for research and quality benchmarking.
The percentage of children reaching stability and the median TCS for the combined measures demonstrated little variation within each age group, likely because respiratory rate and need for supplemental oxygen, 2 of the parameters with the longest individual time to stability, were also included in each of the combination measures. This suggests that less‐complex measures incorporating only respiratory rate and need for supplemental oxygen may be sufficient to assess clinical stability, particularly because these parameters are objectively measured and possess a direct physiological link to pneumonia. In contrast, the other parameters may be more often influenced by factors unrelated to disease severity.
Our study also highlights several shortcomings of the pediatric TCS measures. Despite use of published, age‐based reference values,[13] we noted wide variation in the achievement of stability across individual parameters, especially for children 5 years old. Overall, 21% of children had 1 abnormal parameter at discharge. Even the simplest combined measure classified 13.4% of children as unstable at discharge. Discharge with unstable parameters was not associated with 7‐day readmission, although our study was underpowered to detect small differences. Additional study is therefore needed to evaluate less restrictive cutoff values on calculated TCS and the impact of hospital discharge prior to reaching stability. In particular, relaxing the upper limit for normal respiratory rate in adolescents (16 breaths per minute) to more closely approximate the adult TCS parameter (24 breaths per minute) should be explored. Refinement and standardization of age‐based vital sign reference values specific to hospitalized children may also improve the performance of these measures.[14]
Several limitations deserve discussion. TCS parameters and readmission data were abstracted retrospectively from a single institution, and our findings may not be generalizable. Although clinical staff routinely measured these data, measurement variation likely exists. Nevertheless, such variation is likely systematic, limiting the impact of potential misclassification. TCS was calculated based on the last abnormal value for each parameter; prior fluctuations between normal and abnormal periods of stability were not captured. We were unable to assess room air oxygen saturations. Instead, supplemental oxygen use served as a surrogate for hypoxia. At our institution, oxygen therapy is provided for children with pneumonia to maintain oxygen saturations of 90% to 92%. We did not assess work of breathing (a marker of severe pneumonia) or ability to eat (a component of adult TCS measures). We initially considered the evaluation of intravenous fluids as a proxy for ability to eat (addition of this parameter to the 4 parameter TCS resulted in a modest increase in median time to stability, data not shown); however, we felt the lack of institutional policy and subjective nature of this parameter detracted from our study's objectives. Finally, we were not able to determine clinical readiness for discharge beyond the measurement of vital sign parameters. Therefore, prospective evaluation of the proposed pediatric TCS measures in broader populations will be important to build upon our findings, refine stability parameters, and test the utility of new parameters (eg, ability to eat, work of breathing) prior to use in clinical settings.
Our study provides an initial evaluation of TCS measures for assessing severity and recovery among children hospitalized with pneumonia. Similar to adults, such validated TCS measures may ultimately prove useful for improving the quality of both clinical care and research, although additional study to more clearly define stability criteria is needed prior to implementation.
Disclosures
This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under Award Number K23AI104779 to Dr. Williams. The EPIC study was supported by the Influenza Division in the National Center for Immunizations and Respiratory Diseases at the Centers for Disease Control and Prevention through cooperative agreements with each study site and was based on a competitive research funding opportunity. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention or the National Institutes of Health. Dr. Grijalva serves as a consultant to Glaxo‐Smith‐Kline and Pfizer outside of the scope of this article. Dr. Edwards is supported through grants from Novartis for the conduction of a Group B strep vaccine study and serves as the Chair of the Data Safety and Monitoring Data Committee for Influenza Study outside the scope of this article. Dr. Self reports grants from CareFusion, BioMerieux, Affinium Pharmaceuticals, Astute Medical, Crucell Holland BV, BRAHMS GmbH, Pfizer, Rapid Pathogen Screening, Venaxis, BioAegis Inc., Sphingotec GmbH, and Cempra Pharmaceuticals; personal fees from BioFire Diagnostics and Venaxis, Inc; and patent 13/632,874 (Sterile Blood Culture Collection System) pending; all outside the scope of this article.
- Healthcare Cost and Utilization Project. Available at: http://www.ahrq.gov/research/data/hcup/index.html. Accessed February 1, 2014.
- , , , et al. Time to clinical stability in patients hospitalized with community‐acquired pneumonia: implications for practice guidelines. JAMA. 1998;279:1452–1457.
- , , , et al.; Neumofail Group. Reaching stability in community‐acquired pneumonia: the effects of the severity of disease, treatment, and the characteristics of patients. Clin Infect Dis. 2004;39:1783–1790.
- , , , et al.; Community‐Acquired Pneumonia Organization. The pneumonia severity index predicts time to clinical stability in patients with community‐acquired pneumonia. Int J Tuberc Lung Dis. 2006;10:739–743.
- , , , , . Efficacy of corticosteroids in community‐acquired pneumonia: a randomized double‐blinded clinical trial. Am J Respir Crit Care Med. 2010;181:975–982.
- , , , et al. Early administration of antibiotics does not shorten time to clinical stability in patients with moderate‐to‐severe community‐acquired pneumonia. Chest 2003;124:1798–1804.
- , , , . A comparison between time to clinical stability in community‐acquired aspiration pneumonia and community‐acquired pneumonia. Intern Emerg Med. 2014;9:143–150.
- , , , et al.; Community‐Acquired Pneumonia Organization (CAPO) Investigators. A worldwide perspective of atypical pathogens in community‐acquired pneumonia. Am J Respir Crit Care Med. 2007;175:1086–1093.
- , , , et al.; CDC EPIC Study Team. Community‐acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372:835–845.
- American Heart Association. 2005 American Heart Association (AHA) guidelines for cardiopulmonary resuscitation (CPR) and emergency cardiovascular care (ECC) of pediatric and neonatal patients: pediatric basic life support. Pediatrics. 2006;117:e989–e1004.
- , , . Development and initial validation of the Bedside Paediatric Early Warning System score. Crit Care. 2009;13:R135.
- Centers for Medicare and Medicaid Services. Regulations and guidance. EHR incentive programs. Available at: http://www.cms.gov/Regulations‐and‐Guidance/Legislation/EHRIncentivePrograms/index.html. Accessed February 20, 2015
- , , , , , . Development of heart and respiratory rate percentile curves for hospitalized children. Pediatrics. 2013;131:e1150–e1157.
- , , , et al. Length of stay after reaching clinical stability drives hospital costs associated with adult community‐acquired pneumonia. Scand J Infect Dis. 2013;45:219–226.
- Healthcare Cost and Utilization Project. Available at: http://www.ahrq.gov/research/data/hcup/index.html. Accessed February 1, 2014.
- , , , et al. Time to clinical stability in patients hospitalized with community‐acquired pneumonia: implications for practice guidelines. JAMA. 1998;279:1452–1457.
- , , , et al.; Neumofail Group. Reaching stability in community‐acquired pneumonia: the effects of the severity of disease, treatment, and the characteristics of patients. Clin Infect Dis. 2004;39:1783–1790.
- , , , et al.; Community‐Acquired Pneumonia Organization. The pneumonia severity index predicts time to clinical stability in patients with community‐acquired pneumonia. Int J Tuberc Lung Dis. 2006;10:739–743.
- , , , , . Efficacy of corticosteroids in community‐acquired pneumonia: a randomized double‐blinded clinical trial. Am J Respir Crit Care Med. 2010;181:975–982.
- , , , et al. Early administration of antibiotics does not shorten time to clinical stability in patients with moderate‐to‐severe community‐acquired pneumonia. Chest 2003;124:1798–1804.
- , , , . A comparison between time to clinical stability in community‐acquired aspiration pneumonia and community‐acquired pneumonia. Intern Emerg Med. 2014;9:143–150.
- , , , et al.; Community‐Acquired Pneumonia Organization (CAPO) Investigators. A worldwide perspective of atypical pathogens in community‐acquired pneumonia. Am J Respir Crit Care Med. 2007;175:1086–1093.
- , , , et al.; CDC EPIC Study Team. Community‐acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372:835–845.
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