Article Type
Changed
Sat, 04/06/2024 - 18:18

The growth in the hospitalist workforce has been one of the major trends shaping US (and international) inpatient medicine over the last 25 years.1 Hospitalists’ clinical work is typically split among serving as the primary attending for admitted patients (termed “most responsible physician,” or MRP, in Canada), outpatient clinics, medical consults, and comanagement.2,3 Comanagement typically involves the cooperative efforts of hospitalists and subspecialists ranging from general surgery to orthopedics to medical oncology. Comanagement differs from typical medical consultation because comanaging hospitalists are commonly given broad discretion to directly write orders, manage intercurrent medical illness (eg, hyperglycemia), and even discharge patients from the hospital when appropriate. There can be significant heterogeneity in how comanagement is implemented across institutions.4

With respect to hip fractures, literature suggests that subspecialists value comanagement and that comanagement is associated with reductions in hospital length of stay, timelier surgical repair, and potential cost savings for hospitals.5-7 Some studies have found reductions in in-hospital and 1-year mortality (including one meta-analysis on ortho-geriatric comanagement)8 and complications,9 but others have found no such benefits.10,11

In the current issue of the Journal of Hospital Medicine, Maxwell and Mirza used data from the National Surgical Quality Improvement Program (NSQIP) Participant Use Data File (PUF)—specifically, from the Hip Fracture PUF—to investigate the relationship between comanagement and mortality and major morbidity among more than 15,000 patients hospitalized with hip fracture.12 The investigators did not find that comanagement was associated with a reduction in either morbidity or mortality.

Several factors give gravitas to their analysis. First, the NSQIP PUF is an extremely rigorous data source for evaluating surgical outcomes. Originally developed in the US Veterans Health Administration in the 1980’s to standardize data elements needed for quality improvement and hospital benchmarking, today NSQIP involves more than 600 hospitals in 9 different countries submitting hundreds of thousands of cases annually.13 Second, the authors recognized that the comanagement and noncomanagement groups differed substantially and used propensity score matching in an effort to account for these differences. Surprisingly, they found that the comanagement had significantly higher mortality and morbidity than the noncomanagement group, even after propensity score matching.

These results are important in testing the assumption of the inherent “good” of comanagement. Does this study provide definitive evidence that surgical comanagement does not improve outcomes? We would suggest that this study be interpreted in light of certain considerations.

First, comanagement is a broad term including a variety of operationalizations, such as geriatrician vs hospitalist comanagement, involvement before vs after surgery, and varying divisions of responsibility between the surgical and medical services. Research indicates that successful comanagement models tend to incorporate multidisciplinary teams, embrace the “dual primary caregiver” nature of comanagement, and shared goals among primary caregivers, specifically anticipating prevention of complications.5 The NSQIP data do not provide sufficient granularity to allow for investigation of these crucial nuances that may ultimately determine whether comanagement programs are effective. Additionally, comanagement often (but not always) coexists with a care pathway, and so deficiencies in or absence of a care pathway add additional heterogeneity to the comanagement group which is not captured in the NSQIP PUF.

Second, it is important to consider the potential for unmeasured confounding. The propensity score matching did seem to achieve balance in the distribution of most baseline variables between the comanagement and noncomanagement groups, though differences remain for certain covariates. A key assumption in propensity score matching (and in observational research more broadly) is the principle of “no unmeasured confounders” (ie, the assumption that all variables that might influence treatment assignment and outcomes are measured).14 For the NSQIP PUF this absence of unmeasured confounders is clearly not the case because hospital and surgeon variables are omitted from the PUF for reasons of confidentiality. Inclusion of hospital and surgeon variables could well be important because outcomes may vary by hospital or by surgeon, and simultaneously, different hospitals and different surgeons will have different protocols and preferences regarding comanagement. Furthermore, confounding is virtually guaranteed to the extent that hospitals and surgeons do not randomly assign hip fracture patients to comanagement or usual care. The finding of higher mortality in the comanagement group, even after adjustment and matching, suggests the presence of residual confounding. Even if residual confounding is the explanation for the worse outcomes observed in the comanagement group, the finding of a lack of benefit of comanagement is noteworthy and should not be dismissed out of hand.

Limitations aside, these results suggest a need for humility among strong proponents of comanagement, at least in the hip fracture population. While it may still be reasonable to claim that comanagement improves efficiency and may enhance certain aspects of patient or physician satisfaction, the lack of an impact on mortality highlights a need to examine the benefits of these programs more carefully. From a clinical perspective, hospitalists and orthopedic surgeons should consider which hip fracture patients might be most likely to benefit from comanagement.4 From a research perspective, the current study highlights the pressing need for a randomized trial of comanagement to definitively address the effectiveness of these programs.

References

1. Wachter RM, Goldman L. Zero to 50,000 — the 20th anniversary of the hospitalist. N Engl J Med. 2016;375(11):1009-1011. https://doi.org/10.1056/NEJMp1607958
2. Hinami K, Whelan CT, Miller JA, Wolosin RJ, Wetterneck TB; Society of Hospital Medicine Career Satisfaction Task Force. Job characteristics, satisfaction, and burnout across hospitalist practice models. J Hosp Med. 2012;7(5):402-410. https://doi.org/10.1002/jhm.1907
3. Soong C, Eddy Fan, Eric E Howell, et al. Characteristics of hospitalists and hospitalist programs in the United States and Canada. J Clin Outcomes Manag . 2009;16(2):69
4. Siegal EM. Just because you can, doesn’t mean that you should: a call for the rational application of hospitalist comanagement. J Hosp Med. 2008;3(5):398-402. https://doi.org/10.1002/jhm.361
5. Swart E, Vasudeva E, Makhni EC, Macaulay W, Bozic KJ. Dedicated perioperative hip fracture comanagement programs are cost-effective in high-volume centers: an economic analysis. Clin Orthop Relat Res. 2016;474(1):222-233. https://doi.org/10.1007/s11999-015-4494-4
6. Bracey DN, Kiymaz TC, Holst DC, et al. An orthopedic-hospitalist comanaged hip fracture service reduces inpatient length of stay. Geriatr Orthop Surg Rehabil. 2016;7(4):171-177. https://doi.org/10.1177/2151458516661383.
7. Soong C, Cram P, Chezar K, et al. Impact of an integrated hip fracture inpatient program on length of stay and costs. J Orthop Trauma. 2016;30(12):647-652. https://doi.org/10.1097/BOT.0000000000000691
8. Grigoryan KV, Javedan H, Rudolph JL. Ortho-geriatric care models and outcomes in hip fracture patients: a systematic review and meta-analysis. J Orthop Trauma. 2014;28(3):e49-e55. https://doi.org/10.1097/BOT.0b013e3182a5a045
9. Vidán M, Serra JA, Moreno C, Riquelme G, Ortiz J. Efficacy of a comprehensive geriatric intervention in older patients hospitalized for hip fracture: a randomized, controlled trial. J Am Geriatr Soc. 2005;53(9):1476-1482. https://doi.org/10.1111/j.1532-5415.2005.53466.x
10. Gregersen M, Mørch MM, Hougaard K, Damsgaard EM. Geriatric intervention in elderly patients with hip fracture in an orthopedic ward. J Inj Violence Res. 2012;4(2):45-51. https://doi.org/10.5249/jivr.v4i2.96
11. Southern WN, Berger MA, Bellin EY, Hailpern SM, Arnsten JH. Hospitalist care and length of stay in patients requiring complex discharge planning and close clinical monitoring. Arch Intern Med. 2007;167(17):1869-1874. http://doi.org/10.1001/archinte.167.17.1869
12. Maxwell B, Mirza A. Medical comanagement of hip fracture patients is not associated with superior perioperative outcomes: A propensity score matched retrospective cohort analysis of the national surgical quality improvement project. J Hosp Med. 2020;15:468-474. http://doi.org/10.12788/jhm.3343
13. Cohen ME, Ko CY, Bilimoria KY, et al. Optimizing ACS NSQIP modeling for evaluation of surgical quality and risk: patient risk adjustment, procedure mix adjustment, shrinkage adjustment, and surgical focus. J Am Coll Surg. 2013;217(2):336–46.e1. https://doi.org/10.1016/j.jamcollsurg.2013.02.027
14. Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46(3):399–424. https://doi.org/10.1080/00273171.2011.568786

Article PDF
Author and Disclosure Information

1Department of Medicine, University of Toronto, Toronto, Canada; 2Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada; 3Division of General Internal Medicine and Geriatrics, Sinai Health System, Toronto, Canada; 4Division of General Internal Medicine and Geriatrics, University Health Network, Toronto, Canada.

Disclosures

Dr Cram holds funding from the US National Institutes of Health. Dr Vincent has nothing to disclose.

Issue
Journal of Hospital Medicine 15(8)
Publications
Topics
Page Number
510-511
Sections
Author and Disclosure Information

1Department of Medicine, University of Toronto, Toronto, Canada; 2Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada; 3Division of General Internal Medicine and Geriatrics, Sinai Health System, Toronto, Canada; 4Division of General Internal Medicine and Geriatrics, University Health Network, Toronto, Canada.

Disclosures

Dr Cram holds funding from the US National Institutes of Health. Dr Vincent has nothing to disclose.

Author and Disclosure Information

1Department of Medicine, University of Toronto, Toronto, Canada; 2Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada; 3Division of General Internal Medicine and Geriatrics, Sinai Health System, Toronto, Canada; 4Division of General Internal Medicine and Geriatrics, University Health Network, Toronto, Canada.

Disclosures

Dr Cram holds funding from the US National Institutes of Health. Dr Vincent has nothing to disclose.

Article PDF
Article PDF
Related Articles

The growth in the hospitalist workforce has been one of the major trends shaping US (and international) inpatient medicine over the last 25 years.1 Hospitalists’ clinical work is typically split among serving as the primary attending for admitted patients (termed “most responsible physician,” or MRP, in Canada), outpatient clinics, medical consults, and comanagement.2,3 Comanagement typically involves the cooperative efforts of hospitalists and subspecialists ranging from general surgery to orthopedics to medical oncology. Comanagement differs from typical medical consultation because comanaging hospitalists are commonly given broad discretion to directly write orders, manage intercurrent medical illness (eg, hyperglycemia), and even discharge patients from the hospital when appropriate. There can be significant heterogeneity in how comanagement is implemented across institutions.4

With respect to hip fractures, literature suggests that subspecialists value comanagement and that comanagement is associated with reductions in hospital length of stay, timelier surgical repair, and potential cost savings for hospitals.5-7 Some studies have found reductions in in-hospital and 1-year mortality (including one meta-analysis on ortho-geriatric comanagement)8 and complications,9 but others have found no such benefits.10,11

In the current issue of the Journal of Hospital Medicine, Maxwell and Mirza used data from the National Surgical Quality Improvement Program (NSQIP) Participant Use Data File (PUF)—specifically, from the Hip Fracture PUF—to investigate the relationship between comanagement and mortality and major morbidity among more than 15,000 patients hospitalized with hip fracture.12 The investigators did not find that comanagement was associated with a reduction in either morbidity or mortality.

Several factors give gravitas to their analysis. First, the NSQIP PUF is an extremely rigorous data source for evaluating surgical outcomes. Originally developed in the US Veterans Health Administration in the 1980’s to standardize data elements needed for quality improvement and hospital benchmarking, today NSQIP involves more than 600 hospitals in 9 different countries submitting hundreds of thousands of cases annually.13 Second, the authors recognized that the comanagement and noncomanagement groups differed substantially and used propensity score matching in an effort to account for these differences. Surprisingly, they found that the comanagement had significantly higher mortality and morbidity than the noncomanagement group, even after propensity score matching.

These results are important in testing the assumption of the inherent “good” of comanagement. Does this study provide definitive evidence that surgical comanagement does not improve outcomes? We would suggest that this study be interpreted in light of certain considerations.

First, comanagement is a broad term including a variety of operationalizations, such as geriatrician vs hospitalist comanagement, involvement before vs after surgery, and varying divisions of responsibility between the surgical and medical services. Research indicates that successful comanagement models tend to incorporate multidisciplinary teams, embrace the “dual primary caregiver” nature of comanagement, and shared goals among primary caregivers, specifically anticipating prevention of complications.5 The NSQIP data do not provide sufficient granularity to allow for investigation of these crucial nuances that may ultimately determine whether comanagement programs are effective. Additionally, comanagement often (but not always) coexists with a care pathway, and so deficiencies in or absence of a care pathway add additional heterogeneity to the comanagement group which is not captured in the NSQIP PUF.

Second, it is important to consider the potential for unmeasured confounding. The propensity score matching did seem to achieve balance in the distribution of most baseline variables between the comanagement and noncomanagement groups, though differences remain for certain covariates. A key assumption in propensity score matching (and in observational research more broadly) is the principle of “no unmeasured confounders” (ie, the assumption that all variables that might influence treatment assignment and outcomes are measured).14 For the NSQIP PUF this absence of unmeasured confounders is clearly not the case because hospital and surgeon variables are omitted from the PUF for reasons of confidentiality. Inclusion of hospital and surgeon variables could well be important because outcomes may vary by hospital or by surgeon, and simultaneously, different hospitals and different surgeons will have different protocols and preferences regarding comanagement. Furthermore, confounding is virtually guaranteed to the extent that hospitals and surgeons do not randomly assign hip fracture patients to comanagement or usual care. The finding of higher mortality in the comanagement group, even after adjustment and matching, suggests the presence of residual confounding. Even if residual confounding is the explanation for the worse outcomes observed in the comanagement group, the finding of a lack of benefit of comanagement is noteworthy and should not be dismissed out of hand.

Limitations aside, these results suggest a need for humility among strong proponents of comanagement, at least in the hip fracture population. While it may still be reasonable to claim that comanagement improves efficiency and may enhance certain aspects of patient or physician satisfaction, the lack of an impact on mortality highlights a need to examine the benefits of these programs more carefully. From a clinical perspective, hospitalists and orthopedic surgeons should consider which hip fracture patients might be most likely to benefit from comanagement.4 From a research perspective, the current study highlights the pressing need for a randomized trial of comanagement to definitively address the effectiveness of these programs.

The growth in the hospitalist workforce has been one of the major trends shaping US (and international) inpatient medicine over the last 25 years.1 Hospitalists’ clinical work is typically split among serving as the primary attending for admitted patients (termed “most responsible physician,” or MRP, in Canada), outpatient clinics, medical consults, and comanagement.2,3 Comanagement typically involves the cooperative efforts of hospitalists and subspecialists ranging from general surgery to orthopedics to medical oncology. Comanagement differs from typical medical consultation because comanaging hospitalists are commonly given broad discretion to directly write orders, manage intercurrent medical illness (eg, hyperglycemia), and even discharge patients from the hospital when appropriate. There can be significant heterogeneity in how comanagement is implemented across institutions.4

With respect to hip fractures, literature suggests that subspecialists value comanagement and that comanagement is associated with reductions in hospital length of stay, timelier surgical repair, and potential cost savings for hospitals.5-7 Some studies have found reductions in in-hospital and 1-year mortality (including one meta-analysis on ortho-geriatric comanagement)8 and complications,9 but others have found no such benefits.10,11

In the current issue of the Journal of Hospital Medicine, Maxwell and Mirza used data from the National Surgical Quality Improvement Program (NSQIP) Participant Use Data File (PUF)—specifically, from the Hip Fracture PUF—to investigate the relationship between comanagement and mortality and major morbidity among more than 15,000 patients hospitalized with hip fracture.12 The investigators did not find that comanagement was associated with a reduction in either morbidity or mortality.

Several factors give gravitas to their analysis. First, the NSQIP PUF is an extremely rigorous data source for evaluating surgical outcomes. Originally developed in the US Veterans Health Administration in the 1980’s to standardize data elements needed for quality improvement and hospital benchmarking, today NSQIP involves more than 600 hospitals in 9 different countries submitting hundreds of thousands of cases annually.13 Second, the authors recognized that the comanagement and noncomanagement groups differed substantially and used propensity score matching in an effort to account for these differences. Surprisingly, they found that the comanagement had significantly higher mortality and morbidity than the noncomanagement group, even after propensity score matching.

These results are important in testing the assumption of the inherent “good” of comanagement. Does this study provide definitive evidence that surgical comanagement does not improve outcomes? We would suggest that this study be interpreted in light of certain considerations.

First, comanagement is a broad term including a variety of operationalizations, such as geriatrician vs hospitalist comanagement, involvement before vs after surgery, and varying divisions of responsibility between the surgical and medical services. Research indicates that successful comanagement models tend to incorporate multidisciplinary teams, embrace the “dual primary caregiver” nature of comanagement, and shared goals among primary caregivers, specifically anticipating prevention of complications.5 The NSQIP data do not provide sufficient granularity to allow for investigation of these crucial nuances that may ultimately determine whether comanagement programs are effective. Additionally, comanagement often (but not always) coexists with a care pathway, and so deficiencies in or absence of a care pathway add additional heterogeneity to the comanagement group which is not captured in the NSQIP PUF.

Second, it is important to consider the potential for unmeasured confounding. The propensity score matching did seem to achieve balance in the distribution of most baseline variables between the comanagement and noncomanagement groups, though differences remain for certain covariates. A key assumption in propensity score matching (and in observational research more broadly) is the principle of “no unmeasured confounders” (ie, the assumption that all variables that might influence treatment assignment and outcomes are measured).14 For the NSQIP PUF this absence of unmeasured confounders is clearly not the case because hospital and surgeon variables are omitted from the PUF for reasons of confidentiality. Inclusion of hospital and surgeon variables could well be important because outcomes may vary by hospital or by surgeon, and simultaneously, different hospitals and different surgeons will have different protocols and preferences regarding comanagement. Furthermore, confounding is virtually guaranteed to the extent that hospitals and surgeons do not randomly assign hip fracture patients to comanagement or usual care. The finding of higher mortality in the comanagement group, even after adjustment and matching, suggests the presence of residual confounding. Even if residual confounding is the explanation for the worse outcomes observed in the comanagement group, the finding of a lack of benefit of comanagement is noteworthy and should not be dismissed out of hand.

Limitations aside, these results suggest a need for humility among strong proponents of comanagement, at least in the hip fracture population. While it may still be reasonable to claim that comanagement improves efficiency and may enhance certain aspects of patient or physician satisfaction, the lack of an impact on mortality highlights a need to examine the benefits of these programs more carefully. From a clinical perspective, hospitalists and orthopedic surgeons should consider which hip fracture patients might be most likely to benefit from comanagement.4 From a research perspective, the current study highlights the pressing need for a randomized trial of comanagement to definitively address the effectiveness of these programs.

References

1. Wachter RM, Goldman L. Zero to 50,000 — the 20th anniversary of the hospitalist. N Engl J Med. 2016;375(11):1009-1011. https://doi.org/10.1056/NEJMp1607958
2. Hinami K, Whelan CT, Miller JA, Wolosin RJ, Wetterneck TB; Society of Hospital Medicine Career Satisfaction Task Force. Job characteristics, satisfaction, and burnout across hospitalist practice models. J Hosp Med. 2012;7(5):402-410. https://doi.org/10.1002/jhm.1907
3. Soong C, Eddy Fan, Eric E Howell, et al. Characteristics of hospitalists and hospitalist programs in the United States and Canada. J Clin Outcomes Manag . 2009;16(2):69
4. Siegal EM. Just because you can, doesn’t mean that you should: a call for the rational application of hospitalist comanagement. J Hosp Med. 2008;3(5):398-402. https://doi.org/10.1002/jhm.361
5. Swart E, Vasudeva E, Makhni EC, Macaulay W, Bozic KJ. Dedicated perioperative hip fracture comanagement programs are cost-effective in high-volume centers: an economic analysis. Clin Orthop Relat Res. 2016;474(1):222-233. https://doi.org/10.1007/s11999-015-4494-4
6. Bracey DN, Kiymaz TC, Holst DC, et al. An orthopedic-hospitalist comanaged hip fracture service reduces inpatient length of stay. Geriatr Orthop Surg Rehabil. 2016;7(4):171-177. https://doi.org/10.1177/2151458516661383.
7. Soong C, Cram P, Chezar K, et al. Impact of an integrated hip fracture inpatient program on length of stay and costs. J Orthop Trauma. 2016;30(12):647-652. https://doi.org/10.1097/BOT.0000000000000691
8. Grigoryan KV, Javedan H, Rudolph JL. Ortho-geriatric care models and outcomes in hip fracture patients: a systematic review and meta-analysis. J Orthop Trauma. 2014;28(3):e49-e55. https://doi.org/10.1097/BOT.0b013e3182a5a045
9. Vidán M, Serra JA, Moreno C, Riquelme G, Ortiz J. Efficacy of a comprehensive geriatric intervention in older patients hospitalized for hip fracture: a randomized, controlled trial. J Am Geriatr Soc. 2005;53(9):1476-1482. https://doi.org/10.1111/j.1532-5415.2005.53466.x
10. Gregersen M, Mørch MM, Hougaard K, Damsgaard EM. Geriatric intervention in elderly patients with hip fracture in an orthopedic ward. J Inj Violence Res. 2012;4(2):45-51. https://doi.org/10.5249/jivr.v4i2.96
11. Southern WN, Berger MA, Bellin EY, Hailpern SM, Arnsten JH. Hospitalist care and length of stay in patients requiring complex discharge planning and close clinical monitoring. Arch Intern Med. 2007;167(17):1869-1874. http://doi.org/10.1001/archinte.167.17.1869
12. Maxwell B, Mirza A. Medical comanagement of hip fracture patients is not associated with superior perioperative outcomes: A propensity score matched retrospective cohort analysis of the national surgical quality improvement project. J Hosp Med. 2020;15:468-474. http://doi.org/10.12788/jhm.3343
13. Cohen ME, Ko CY, Bilimoria KY, et al. Optimizing ACS NSQIP modeling for evaluation of surgical quality and risk: patient risk adjustment, procedure mix adjustment, shrinkage adjustment, and surgical focus. J Am Coll Surg. 2013;217(2):336–46.e1. https://doi.org/10.1016/j.jamcollsurg.2013.02.027
14. Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46(3):399–424. https://doi.org/10.1080/00273171.2011.568786

References

1. Wachter RM, Goldman L. Zero to 50,000 — the 20th anniversary of the hospitalist. N Engl J Med. 2016;375(11):1009-1011. https://doi.org/10.1056/NEJMp1607958
2. Hinami K, Whelan CT, Miller JA, Wolosin RJ, Wetterneck TB; Society of Hospital Medicine Career Satisfaction Task Force. Job characteristics, satisfaction, and burnout across hospitalist practice models. J Hosp Med. 2012;7(5):402-410. https://doi.org/10.1002/jhm.1907
3. Soong C, Eddy Fan, Eric E Howell, et al. Characteristics of hospitalists and hospitalist programs in the United States and Canada. J Clin Outcomes Manag . 2009;16(2):69
4. Siegal EM. Just because you can, doesn’t mean that you should: a call for the rational application of hospitalist comanagement. J Hosp Med. 2008;3(5):398-402. https://doi.org/10.1002/jhm.361
5. Swart E, Vasudeva E, Makhni EC, Macaulay W, Bozic KJ. Dedicated perioperative hip fracture comanagement programs are cost-effective in high-volume centers: an economic analysis. Clin Orthop Relat Res. 2016;474(1):222-233. https://doi.org/10.1007/s11999-015-4494-4
6. Bracey DN, Kiymaz TC, Holst DC, et al. An orthopedic-hospitalist comanaged hip fracture service reduces inpatient length of stay. Geriatr Orthop Surg Rehabil. 2016;7(4):171-177. https://doi.org/10.1177/2151458516661383.
7. Soong C, Cram P, Chezar K, et al. Impact of an integrated hip fracture inpatient program on length of stay and costs. J Orthop Trauma. 2016;30(12):647-652. https://doi.org/10.1097/BOT.0000000000000691
8. Grigoryan KV, Javedan H, Rudolph JL. Ortho-geriatric care models and outcomes in hip fracture patients: a systematic review and meta-analysis. J Orthop Trauma. 2014;28(3):e49-e55. https://doi.org/10.1097/BOT.0b013e3182a5a045
9. Vidán M, Serra JA, Moreno C, Riquelme G, Ortiz J. Efficacy of a comprehensive geriatric intervention in older patients hospitalized for hip fracture: a randomized, controlled trial. J Am Geriatr Soc. 2005;53(9):1476-1482. https://doi.org/10.1111/j.1532-5415.2005.53466.x
10. Gregersen M, Mørch MM, Hougaard K, Damsgaard EM. Geriatric intervention in elderly patients with hip fracture in an orthopedic ward. J Inj Violence Res. 2012;4(2):45-51. https://doi.org/10.5249/jivr.v4i2.96
11. Southern WN, Berger MA, Bellin EY, Hailpern SM, Arnsten JH. Hospitalist care and length of stay in patients requiring complex discharge planning and close clinical monitoring. Arch Intern Med. 2007;167(17):1869-1874. http://doi.org/10.1001/archinte.167.17.1869
12. Maxwell B, Mirza A. Medical comanagement of hip fracture patients is not associated with superior perioperative outcomes: A propensity score matched retrospective cohort analysis of the national surgical quality improvement project. J Hosp Med. 2020;15:468-474. http://doi.org/10.12788/jhm.3343
13. Cohen ME, Ko CY, Bilimoria KY, et al. Optimizing ACS NSQIP modeling for evaluation of surgical quality and risk: patient risk adjustment, procedure mix adjustment, shrinkage adjustment, and surgical focus. J Am Coll Surg. 2013;217(2):336–46.e1. https://doi.org/10.1016/j.jamcollsurg.2013.02.027
14. Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46(3):399–424. https://doi.org/10.1080/00273171.2011.568786

Issue
Journal of Hospital Medicine 15(8)
Issue
Journal of Hospital Medicine 15(8)
Page Number
510-511
Page Number
510-511
Publications
Publications
Topics
Article Type
Sections
Article Source

© 2020 Society of Hospital Medicine

Disallow All Ads
Correspondence Location
Peter Cram, MD, MBA; Email: peter.cram@uhn.ca; Telephone: 647-767-5508; Twitter: @pmcram.
Content Gating
Gated (full article locked unless allowed per User)
Alternative CME
Disqus Comments
Default
Use ProPublica
Hide sidebar & use full width
render the right sidebar.
Conference Recap Checkbox
Not Conference Recap
Clinical Edge
Display the Slideshow in this Article
Gating Strategy
First Peek Free
Medscape Article
Display survey writer
Reuters content
Disable Inline Native ads
Article PDF Media