Given name(s)
Marshall H.
Family name
Chin
Degrees
MD, MPH

CKD Awareness in Hospitalized Patients

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Article
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Hospitalized patients frequently unaware of their chronic kidney disease
Author(s)
Milda R. Saunders, MD, MPH
Sharon Dahei Kim, MPP
Nisha Patel, MD
David O. Meltzer, MD, PhD
Marshall H. Chin, MD, MPH

Chronic kidney disease (CKD) affects over 13% of the US population and is associated with increased morbidity, mortality, and healthcare costs.[1] However, only 10% of individuals with CKD are aware of their diagnoses.[2] Even in those with stage 5 CKD, only 60% of individuals are aware of their CKD.[3] To our knowledge, no work has examined CKD awareness in a hospitalized patient population.

Patient awareness of their CKD diagnosis is important because progression of kidney disease can be slowed by patient self‐management of diabetes and hypertension.[4] Patient awareness of CKD may also increase acceptance of preend‐stage renal disease (ESRD) patient education and nephrology referral, which have been shown to delay CKD progression and improve clinical status at dialysis initiation.[5] However, only 60% of patients with advanced CKD have visited a nephrologist in the past year or have seen a nephrologist prior to dialysis initiation.[1]

The hospital is an important site for patient education and linkage to outpatient care for patients with CKD.[6] The hospital serves high‐risk patients who may not be well connected to outpatient care or who have lesswell‐controlled disease.[6, 7] Thus, hospitalization represents an opportunity to identify existing CKD and to use a multidisciplinary approach to preventative care, patient education, and patient‐provider planning for renal replacement therapy needs. In our cross‐sectional study in an urban, minority‐serving hospital, we sought to determine what patient factors were associated with hospitalized patients correctly self‐identifying as having CKD.

METHODS

Subjects and Data

We used data from the University of Chicago Hospitalist Project, a study of hospitalized patient outcomes.[8] Within 48 hours of hospitalization, all general medicine patients or their proxies are approached to enroll. During one‐on‐one inpatient interviews, a trained research assistant obtains demographic, health status, and healthcare utilization information. Participants consent for study staff to review their medical records. More than 80% of general medicine patients enroll.

We obtained data on 1234 general medicine patients discharged between January 1, 2012 and March 31, 2013 with an International Classification of Diseases, Ninth Revision (ICD‐9) code for chronic kidney disease (ICD‐9 codes 585.0585.5, 585.9) in their first 20 admission diagnoses. These codes are highly specific for CKD but have lower sensitivity.[9] We excluded all patients with a history of transplant (996.81, V42.0, n=90) or ESRD (585.6, n=416). We excluded repeat admissions during the study period (n=138). Our final sample included 590 unique patients with ICD‐9 diagnosis of CKD without ESRD.

Demographic, Clinical, and Health Service Utilization Characteristics

Our outcome was CKD awareness, the patient's correct self‐report of kidney disease. Patients selected their chronic medical conditions from a list read to them and were specifically asked if they had kidney problems. Demographic characteristics including age, gender, race/ethnicity, marital status, and education were also obtained. Healthcare utilization variables included how often the patient saw their primary medical care provider in the past year and whether patients had a prior hospitalization in the last year.

Health status variables such as mental status, diabetes, hypertension, and CKD stage were also assessed. Mental status was quantified using the telephone version of the Mini‐Mental State Examination (MMSE), scored from 1 to 22.10 We defined diabetes as ICD‐9 codes 250.0250.00, and hypertension as ICD‐9 codes 401.0, 401.9, 403, 405.09, 405.19, 405.91, 405.99, or by patient self‐report. CKD stage was based on the estimated glomerular filtration rate (eGFR) from the medical record using Kidney Disease Outcomes Quality Initiative guidelines.[11] We used the mode of the eGFR to calculate the appropriate CKD stage for those with more than 1 eGFR value from the hospitalization (576/590, 98%). The eGFR was calculated by the modified Modification of Diet in Renal Disease equation: (GFR (mL/min/1.73 m2)=175 (Screatinine)1.154 (Age)0.203 (0.742 if female) x (1.212 if African American)) recommended by the National Kidney Disease Education Program.[12]

Analysis

We used logistic regression to analyze the influence of the demographic, clinical, and healthcare utilization covariates on the likelihood of a patient reporting kidney problems. For the multivariate analysis, we sequentially added variables in a step‐wise fashion. We adjusted for (1) demographic factors: gender, race, ethnicity, marital status, and education; (2) eGFR‐calculated CKD stage and comorbidities: diabetes, hypertension, and mental status; and (3) healthcare utilization in the last 12 months: any hospitalizations and the number of visits to a health provider.

RESULTS

Patient Characteristics and Bivariable Association With Patient CKD Self‐Report

Table 1 shows demographic, clinical, and health service use characteristics for 590 patients with ICD‐9 coded CKD. In the bivariable model in Table 1, age, race, marital status and comorbidities, were associated with patient self‐report of CKD. Patients older than 80 years with physician‐identified CKD through ICD‐9 coding had 57% lower odds of reporting CKD than their younger counterparts. Patients of other races (nonwhite, non‐African American), married patients, and those with CKD stages 4 and 5 were much more likely to correctly self‐report CKD. Patients with higher MMSE score, diabetes, or hypertension had greater odds of CKD self‐report (all P<0.05).

Overall Patient Characteristics and Patient Factors Associated With Patient Chronic Kidney Disease Self‐Report
Total, N=590 Bivariable Odds Ratio (95% CI) Multivariable With Stepwise Addition (95% CI)
Model 1, Demographic Factors Model 2, Plus CKD Stage and Other Comorbidities Model 3, Plus Health Service Use

  • NOTE: Model 1 demographic factors: gender, race, ethnicity, marital status and education; model 1+CKD stage; model 2+comorbidities: diabetes, hypertension, and mental status; and model 3+healthcare use: hospitalization in the last 12 months and number of visits to a health provider in the last year. Abbreviations: CI, confidence interval; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; ICD‐9, International Classification of Diseases, Ninth Revision. *P<0.05. P<0.01. P<0.001. Includes Asian or mixed race. ‖Diabetes ICD‐9 codes 250.0250.99. Hypertension ICD‐9 codes 401.0, 401.0, 401.9, 403, 405.09, 405.19, 405.91, 405.99. #From Mini‐Mental State Exam telephone version (score 126).

Female 312 (52.98%) 1.21 (0.85‐1.70) 1.64 (1.09‐2.47)* 1.28 (0.79‐2.06) 1.36 (0.75‐2.48)
Age, y
Below 54 138 (23.4%) REF REF REF REF
5466 150 (24.4%) 0.96 (0.59‐1.54) 0.95 (0.56‐1.59) 1.01 (0.56‐1.81) 0.83 (0.41‐1.68)
6779 161 (27.3%) 0.77 (0.48‐1.23) 0.67 (0.39‐1.15) 0.66 (0.35‐1.23) 0.72(0.34‐1.52)
Above 80 141 (23.9%) 0.43 (0.26‐0.74) 0.32 (0.17‐0.60) 0.42 (0.20‐0.91)* 0.37 (0.15‐0.93)*
Race
African American 449 (82.1%) REF REF REF REF
White 75 (13.7%) 1.47 (0.89‐2.42) 1.53 (0.86‐2.71) 1.56 (0.78‐3.12) 1.08 (0.47‐2.49)
Other 23 (4.2%) 3.62 (1.53‐8.54) 5.29 (1.78‐15.73) 6.19 (1.72‐22.29) 11.63 (1.80‐75.21)*
Ethnicity (Hispanic is reference group) 21 (4.0%) 0.97 (0.38‐2.44) 0.43 (0.13‐1.45) 0.71 (0.16‐3.09) 0.46 (0.06‐3.57)
Married 171 (32.6%) 1.49 (1.03‐2.18)* 1.32 (0.85‐2.04) 1.20 (0.73‐1.98) 1.77 (0.94‐3.33)
Education
Less than high school 128 (25.2%) REF REF REF REF
High school grad/some college 296 (58.2%) 1.05 (0.68‐1.63) 0.93 (0.58‐1.49) 0.95 (0.54‐1.67) 0.85 (0.42‐1.72)
College grad or higher 85 (16.7%) 1.13 (0.64‐2.01) 0.96 (0.51‐1.78) 1.07 (0.51‐2.23) 0.69 (0.27‐1.77)
CKD stage (eGFR calculated, mode)
12 115 (20.0%) 0.55 (0.32‐0.95)* 0.52 (0.27‐1.01) 0.28 (0.11‐0.69)
3 300 (52.1%) REF REF REF
4 112 (19.4%) 2.43 (1.55‐3.81) 2.69 (1.52‐4.76) 3.07 (1.56‐6.07)
5 49 (8.5%) 4.50 (2.39‐8.48) 3.94 (1.81‐8.56) 5.16 (1.85‐14.41)
Diabetes (ICD‐9 coded or self‐report)‖ 292 (49.5%) 1.52 (1.07‐2.15)* 1.54 (0.97‐2.45) 1.26 (0.71‐2.26)
Hypertension (ICD‐9 coded or self‐report) 436 (73.9%) 3.36 (2.09‐5.41) 1.53 (0.80‐2.90) 1.26 (0.57‐2.81)
Mini‐Mental State Exam score# 19.7 (2.5) 1.13 (1.03‐1.23) 1.09 (0.98‐1.22) 1.22 (1.06‐1.42)
Hospitalized in last 12 months 253 (46.9%) 1.50 (1.05‐2.13)* 1.12 (0.65‐1.95)
No. of visits to health provider
Once/year or less 80 (18.4%) REF REF
23 times/year 58 (13.3%) 0.80 (0.40‐1.60) 0.44 (0.17‐1.16)
4+ times/year 298 (68.4%) 0.60 (0.36‐0.99)* 0.38 (0.19‐0.74)

Multivariable Associations With Patient CKD Self‐Report

Age, race, and CKD stage remained consistently associated with CKD self‐report, although the magnitude of the effects (odds ratios [ORs]) varied across models (Table 1). Across all the models, patients older than 80 years were still significantly less likely than younger patients to self‐report CKD (ORs ranging from 0.32 to 0.42, all P<0.05). Patients classified as being of other race were found to have a 5.29 to 11.63 greater odds of CKD self‐report than African American patients (all P<0.05).

Patients with CKD stage 4 and 5 were more likely to self‐report than patients with CKD stage 3 (ORs ranging from 2.693.07 for stage 4 and 3.945.16 for stage 5, P<0.05). In the final model, every unit increase in MMSE score increased the odds of CKD self‐report by 22%. In addition, patients who saw their health provider 4 or more times per year were 62% less likely to self‐report CKD than patients who saw their provider 1 or fewer times per year (OR: 0.38, P<0.05).

A large proportion of patients (68.6%) were CKD unspecified by ICD‐9 codes, and only 27% of the unspecified group reported having CKD (Table 2). Examining the eGFR CKD stage of the CKD unspecified group showed that 22.8% were eGFR‐determined CKD stage 1 to 2, 57.1% were CKD stage 3, 14.8% were CKD stage 4, and 5.3% were CKD stage 5. Patients had 2 to 3 times greater odds of correct CKD self‐report if physicians had correctly identified their CKD stage (bivariable OR: 2.42, 95% confidence interval [CI]: 1.57‐3.72, multivariable OR: 3.22, 95% CI: 0.99‐10.46) (analysis not shown).

Patient Chronic Kidney Disease Self‐Report by Physician‐Coded CKD Stage and eGFR Calculated CKD Stage
CKD Stage* Physician (ICD‐9) Coded eGFR Calculated eGFR Coded With ICD‐9 Correct

  • NOTE: Percent correct patient CKD self‐report, patient awareness of CKD, by various methods of CKD stagephysician (ICD‐9) versus eGFR calculated CKD stage versus eGFR calculated stage with concordant ICD‐9 stage. Abbreviations: CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; ICD‐9, International Classification of Diseases, Ninth Revision; K/DOQI, Kidney Disease Outcomes Quality Initiative. *P<0.05, based on 2 comparing physician coded, eGFR calculated, and eGFR coded with correct ICD‐9 codes. CKD stage based on physician coded ICD‐9 data. CKD stage is eGFR calculated using mode CKD stage for hospitalization based on K/DOQI staging guidelines. Cases in which eGFR calculated stage and ICD‐9coded stage are concordant.

Unspecified 110 (27.2%)
12 5 (31.2%) 20 (17.4%) 0
3 25 (27.2%) 83 (27.7%) 17 (29.8%)
4 40 (63.5%) 54 (48.2%) 25 (69.4%)
5 11 (78.6%) 31 (63.3%) 10 (83.3%)

DISCUSSION

Although prior work has examined CKD awareness in the general population and in high‐risk cohorts,[2, 3, 13] this is the first study examining CKD awareness in an urban, underserved hospitalized population. We found that overall patients' CKD awareness was low (32%), but increased as high as 63% for CKD stage 5, even after controlling for patient demographic, clinical characteristics, and healthcare use. Our overall rate of CKD awareness was higher than prior studies overall and at lower CKD stages.[2, 3, 13] Our work is consistent with prior literature that shows increasing CKD awareness with advancing CKD stage.[2, 3, 13]

Older patients (>80 years) had lower awareness of CKD. Older patients are more likely to have a near normal creatinine, despite a markedly reduced eGFR, so their CKD may go unnoticed.[14] Even with appropriate recognition, providers may also feel like their CKD is unlikely to progress to ESRD, given its stability and/or their competing risk of death.[15] Finally, older hospitalized patients may also be less likely to report a CKD diagnosis due to difficulty in recall due to denial, dementia, or delirium.

One limitation is that our case‐finding for CKD was physician ICD‐9 coding, which is highly specific but not sensitive.[9] The majority of patients with physician‐identified CKD were CKD unspecified, perhaps due to poor coding, physician underdocumentation, or physician under‐recognition of CKD stage. Although only 27% of the CKD unspecified group correctly self‐identified as having CKD, over 75% were found to be CKD stage 3 or higher, which should trigger additional monitoring or care based on guidelines.[10] In addition, despite statistical significance, we may not be able to make meaningful inferences about our small other group (nonwhite, non‐African American). Our sample was from 1 hospitalan urban, academic, tertiary care center with a large proportion of African American patientswhich may limit generalizability. The multivariable model will need to be tested in other populations for reproducibility.

Our study significantly contributes to the literature by examining patient awareness of CKD in a high‐risk, urban, hospitalized minority population. Other study strengths include use of basic demographic information, as well as survey and laboratory data for a richer examination of the associations between patient factors and CKD awareness.

CONCLUSION

Hospitalized patients with CKD have a low CKD awareness. Patient awareness of their CKD is increased with physician documentation of CKD severity. Patient awareness of their CKD must be coupled with provider awareness and CKD documentation to link patients to multidisciplinary CKD education and care to slow CKD progression and reduce associated cardiovascular and metabolic complications. Further work is needed across hospitals to determineand improveCKD awareness among both patients and providers.

Disclosures

Dr. Saunders was supported by Pilot and Feasibility Funding from the Chicago Center for Diabetes Translation Research (NIDDK P30 DK092949). Dr. Chin was supported by NIDDK K24 DK071933. Dr. Meltzer was supported by NIA T35 AG029795. Dr. Saunders had full access to all of the study data and takes responsibility for the integrity of the data and accuracy of the data analysis. An abstract of this article was presented at the Society of Hospital Medicine Annual Meeting in Las Vegas, Nevada in March 2014 and at the Society of General Internal Medicine Annual Meeting in San Diego, California in April 2014. The authors report no conflicts of interest.

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References
  1. United States Renal Data System. Annual Data Report: Atlas of Chronic Kidney Disease and End‐Stage Renal Disease in the United States. Bethesda, MD: National Institutes of Health; 2012.
  2. Tuot DS, Plantinga LC, Hsu CY, et al. Chronic kidney disease awareness among individuals with clinical markers of kidney dysfunction. Clin J Am Soc Neph. 2011;6(8):1838–1844.
  3. Kurella Tamura M, Anand S, Li S, et al. Comparison of CKD awareness in a screening population using the Modification of Diet in Renal Disease (MDRD) Study and CKD Epidemiology Collaboration (CKD‐EPI) equations. Am J Kidney Dis. 2011;57(3 suppl 2):S17–S23.
  4. Bakris GL, Williams M, Dworkin L, et al. Preserving renal function in adults with hypertension and diabetes: a consensus approach. Am J Kidney Dis. 2000;36(3):646–661.
  5. Wu IW, Wang SY, Hsu SK, et al. Multidisciplinary predialysis education decreases the incidence of dialysis and reduces mortality—a controlled cohort study based on the NKFDOQI guidelines. Nephrol Dial Transplant. 2009;24(11):3426–3433.
  6. Blunt I, Bardsley M, Strippoli GF. Pre‐dialysis hospital use and late referrals in incident dialysis patients in England: a retrospective cohort study. Nephrol Dial Transplant. 2015;30(1):124–129.
  7. Albert NM, Fonarow G, Abraham W, et al. Do hospitals that provide heart failure patient education prior to discharge also promote continuity of care? A report from OPTIMIZE‐HF. J Card Fail. 2006;12(6 suppl):S111.
  8. Meltzer D, Manning WG, Morrison J, et al. Effects of physician experience on costs and outcomes on an academic general medicine service: results of a trial of hospitalists. Ann Intern Med. 2002;137(11):866–874.
  9. Kern EFO, Maney M, Miller DR, et al. Failure of ICD‐9‐CM codes to identify patients with comorbid chronic kidney disease in diabetes. Health Serv Res. 2006;41(2):564–580.
  10. Roccaforte WH, Burke WJ, Bayer BL, Wengel SP. Validation of a telephone version of the mini‐mental state examination. J Am Geriatr Soc. 1992;40(7):697–702.
  11. National Kidney Foundation. Kidney disease outcomes quality initiative guidelines 2002. Available at: http://www2.kidney.org/professionals/KDOQI/guidelines_ckd/toc.htm. Accessed October 9, 2014.
  12. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Ann Intern Med. 1999;130(6):461–470.
  13. Flessner MF, Wyatt SB, Akylbekova EL, et al. Prevalence and awareness of CKD among African Americans: the Jackson Heart Study. Am J Kidney Dis. 2009;53(2):238–247.
  14. Giannelli SV, Patel KV, Windham BG, Pizzarelli F, Ferrucci L, Guralnik JM. Magnitude of underascertainment of impaired kidney function in older adults with normal serum creatinine. J Am Geriatr Soc. 2007;55(6):816–823.
  15. Anderson S, Halter JB, Hazzard WR, et al. Prediction, Progression, and Outcomes of Chronic Kidney Disease in Older Adults. J Am Soc Neph. 2009;20(6):1199–1209.
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Author(s)
Milda R. Saunders, MD, MPH
Sharon Dahei Kim, MPP
Nisha Patel, MD
David O. Meltzer, MD, PhD
Marshall H. Chin, MD, MPH
Author(s)
Milda R. Saunders, MD, MPH
Sharon Dahei Kim, MPP
Nisha Patel, MD
David O. Meltzer, MD, PhD
Marshall H. Chin, MD, MPH
Files
Supplementary Information (1)
Supplementary Information (2)
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Supplementary Information (1)
Supplementary Information (2)
Article PDF
jhm2395.pdf
Article PDF
jhm2395.pdf

Chronic kidney disease (CKD) affects over 13% of the US population and is associated with increased morbidity, mortality, and healthcare costs.[1] However, only 10% of individuals with CKD are aware of their diagnoses.[2] Even in those with stage 5 CKD, only 60% of individuals are aware of their CKD.[3] To our knowledge, no work has examined CKD awareness in a hospitalized patient population.

Patient awareness of their CKD diagnosis is important because progression of kidney disease can be slowed by patient self‐management of diabetes and hypertension.[4] Patient awareness of CKD may also increase acceptance of preend‐stage renal disease (ESRD) patient education and nephrology referral, which have been shown to delay CKD progression and improve clinical status at dialysis initiation.[5] However, only 60% of patients with advanced CKD have visited a nephrologist in the past year or have seen a nephrologist prior to dialysis initiation.[1]

The hospital is an important site for patient education and linkage to outpatient care for patients with CKD.[6] The hospital serves high‐risk patients who may not be well connected to outpatient care or who have lesswell‐controlled disease.[6, 7] Thus, hospitalization represents an opportunity to identify existing CKD and to use a multidisciplinary approach to preventative care, patient education, and patient‐provider planning for renal replacement therapy needs. In our cross‐sectional study in an urban, minority‐serving hospital, we sought to determine what patient factors were associated with hospitalized patients correctly self‐identifying as having CKD.

METHODS

Subjects and Data

We used data from the University of Chicago Hospitalist Project, a study of hospitalized patient outcomes.[8] Within 48 hours of hospitalization, all general medicine patients or their proxies are approached to enroll. During one‐on‐one inpatient interviews, a trained research assistant obtains demographic, health status, and healthcare utilization information. Participants consent for study staff to review their medical records. More than 80% of general medicine patients enroll.

We obtained data on 1234 general medicine patients discharged between January 1, 2012 and March 31, 2013 with an International Classification of Diseases, Ninth Revision (ICD‐9) code for chronic kidney disease (ICD‐9 codes 585.0585.5, 585.9) in their first 20 admission diagnoses. These codes are highly specific for CKD but have lower sensitivity.[9] We excluded all patients with a history of transplant (996.81, V42.0, n=90) or ESRD (585.6, n=416). We excluded repeat admissions during the study period (n=138). Our final sample included 590 unique patients with ICD‐9 diagnosis of CKD without ESRD.

Demographic, Clinical, and Health Service Utilization Characteristics

Our outcome was CKD awareness, the patient's correct self‐report of kidney disease. Patients selected their chronic medical conditions from a list read to them and were specifically asked if they had kidney problems. Demographic characteristics including age, gender, race/ethnicity, marital status, and education were also obtained. Healthcare utilization variables included how often the patient saw their primary medical care provider in the past year and whether patients had a prior hospitalization in the last year.

Health status variables such as mental status, diabetes, hypertension, and CKD stage were also assessed. Mental status was quantified using the telephone version of the Mini‐Mental State Examination (MMSE), scored from 1 to 22.10 We defined diabetes as ICD‐9 codes 250.0250.00, and hypertension as ICD‐9 codes 401.0, 401.9, 403, 405.09, 405.19, 405.91, 405.99, or by patient self‐report. CKD stage was based on the estimated glomerular filtration rate (eGFR) from the medical record using Kidney Disease Outcomes Quality Initiative guidelines.[11] We used the mode of the eGFR to calculate the appropriate CKD stage for those with more than 1 eGFR value from the hospitalization (576/590, 98%). The eGFR was calculated by the modified Modification of Diet in Renal Disease equation: (GFR (mL/min/1.73 m2)=175 (Screatinine)1.154 (Age)0.203 (0.742 if female) x (1.212 if African American)) recommended by the National Kidney Disease Education Program.[12]

Analysis

We used logistic regression to analyze the influence of the demographic, clinical, and healthcare utilization covariates on the likelihood of a patient reporting kidney problems. For the multivariate analysis, we sequentially added variables in a step‐wise fashion. We adjusted for (1) demographic factors: gender, race, ethnicity, marital status, and education; (2) eGFR‐calculated CKD stage and comorbidities: diabetes, hypertension, and mental status; and (3) healthcare utilization in the last 12 months: any hospitalizations and the number of visits to a health provider.

RESULTS

Patient Characteristics and Bivariable Association With Patient CKD Self‐Report

Table 1 shows demographic, clinical, and health service use characteristics for 590 patients with ICD‐9 coded CKD. In the bivariable model in Table 1, age, race, marital status and comorbidities, were associated with patient self‐report of CKD. Patients older than 80 years with physician‐identified CKD through ICD‐9 coding had 57% lower odds of reporting CKD than their younger counterparts. Patients of other races (nonwhite, non‐African American), married patients, and those with CKD stages 4 and 5 were much more likely to correctly self‐report CKD. Patients with higher MMSE score, diabetes, or hypertension had greater odds of CKD self‐report (all P<0.05).

Overall Patient Characteristics and Patient Factors Associated With Patient Chronic Kidney Disease Self‐Report
Total, N=590 Bivariable Odds Ratio (95% CI) Multivariable With Stepwise Addition (95% CI)
Model 1, Demographic Factors Model 2, Plus CKD Stage and Other Comorbidities Model 3, Plus Health Service Use

  • NOTE: Model 1 demographic factors: gender, race, ethnicity, marital status and education; model 1+CKD stage; model 2+comorbidities: diabetes, hypertension, and mental status; and model 3+healthcare use: hospitalization in the last 12 months and number of visits to a health provider in the last year. Abbreviations: CI, confidence interval; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; ICD‐9, International Classification of Diseases, Ninth Revision. *P<0.05. P<0.01. P<0.001. Includes Asian or mixed race. ‖Diabetes ICD‐9 codes 250.0250.99. Hypertension ICD‐9 codes 401.0, 401.0, 401.9, 403, 405.09, 405.19, 405.91, 405.99. #From Mini‐Mental State Exam telephone version (score 126).

Female 312 (52.98%) 1.21 (0.85‐1.70) 1.64 (1.09‐2.47)* 1.28 (0.79‐2.06) 1.36 (0.75‐2.48)
Age, y
Below 54 138 (23.4%) REF REF REF REF
5466 150 (24.4%) 0.96 (0.59‐1.54) 0.95 (0.56‐1.59) 1.01 (0.56‐1.81) 0.83 (0.41‐1.68)
6779 161 (27.3%) 0.77 (0.48‐1.23) 0.67 (0.39‐1.15) 0.66 (0.35‐1.23) 0.72(0.34‐1.52)
Above 80 141 (23.9%) 0.43 (0.26‐0.74) 0.32 (0.17‐0.60) 0.42 (0.20‐0.91)* 0.37 (0.15‐0.93)*
Race
African American 449 (82.1%) REF REF REF REF
White 75 (13.7%) 1.47 (0.89‐2.42) 1.53 (0.86‐2.71) 1.56 (0.78‐3.12) 1.08 (0.47‐2.49)
Other 23 (4.2%) 3.62 (1.53‐8.54) 5.29 (1.78‐15.73) 6.19 (1.72‐22.29) 11.63 (1.80‐75.21)*
Ethnicity (Hispanic is reference group) 21 (4.0%) 0.97 (0.38‐2.44) 0.43 (0.13‐1.45) 0.71 (0.16‐3.09) 0.46 (0.06‐3.57)
Married 171 (32.6%) 1.49 (1.03‐2.18)* 1.32 (0.85‐2.04) 1.20 (0.73‐1.98) 1.77 (0.94‐3.33)
Education
Less than high school 128 (25.2%) REF REF REF REF
High school grad/some college 296 (58.2%) 1.05 (0.68‐1.63) 0.93 (0.58‐1.49) 0.95 (0.54‐1.67) 0.85 (0.42‐1.72)
College grad or higher 85 (16.7%) 1.13 (0.64‐2.01) 0.96 (0.51‐1.78) 1.07 (0.51‐2.23) 0.69 (0.27‐1.77)
CKD stage (eGFR calculated, mode)
12 115 (20.0%) 0.55 (0.32‐0.95)* 0.52 (0.27‐1.01) 0.28 (0.11‐0.69)
3 300 (52.1%) REF REF REF
4 112 (19.4%) 2.43 (1.55‐3.81) 2.69 (1.52‐4.76) 3.07 (1.56‐6.07)
5 49 (8.5%) 4.50 (2.39‐8.48) 3.94 (1.81‐8.56) 5.16 (1.85‐14.41)
Diabetes (ICD‐9 coded or self‐report)‖ 292 (49.5%) 1.52 (1.07‐2.15)* 1.54 (0.97‐2.45) 1.26 (0.71‐2.26)
Hypertension (ICD‐9 coded or self‐report) 436 (73.9%) 3.36 (2.09‐5.41) 1.53 (0.80‐2.90) 1.26 (0.57‐2.81)
Mini‐Mental State Exam score# 19.7 (2.5) 1.13 (1.03‐1.23) 1.09 (0.98‐1.22) 1.22 (1.06‐1.42)
Hospitalized in last 12 months 253 (46.9%) 1.50 (1.05‐2.13)* 1.12 (0.65‐1.95)
No. of visits to health provider
Once/year or less 80 (18.4%) REF REF
23 times/year 58 (13.3%) 0.80 (0.40‐1.60) 0.44 (0.17‐1.16)
4+ times/year 298 (68.4%) 0.60 (0.36‐0.99)* 0.38 (0.19‐0.74)

Multivariable Associations With Patient CKD Self‐Report

Age, race, and CKD stage remained consistently associated with CKD self‐report, although the magnitude of the effects (odds ratios [ORs]) varied across models (Table 1). Across all the models, patients older than 80 years were still significantly less likely than younger patients to self‐report CKD (ORs ranging from 0.32 to 0.42, all P<0.05). Patients classified as being of other race were found to have a 5.29 to 11.63 greater odds of CKD self‐report than African American patients (all P<0.05).

Patients with CKD stage 4 and 5 were more likely to self‐report than patients with CKD stage 3 (ORs ranging from 2.693.07 for stage 4 and 3.945.16 for stage 5, P<0.05). In the final model, every unit increase in MMSE score increased the odds of CKD self‐report by 22%. In addition, patients who saw their health provider 4 or more times per year were 62% less likely to self‐report CKD than patients who saw their provider 1 or fewer times per year (OR: 0.38, P<0.05).

A large proportion of patients (68.6%) were CKD unspecified by ICD‐9 codes, and only 27% of the unspecified group reported having CKD (Table 2). Examining the eGFR CKD stage of the CKD unspecified group showed that 22.8% were eGFR‐determined CKD stage 1 to 2, 57.1% were CKD stage 3, 14.8% were CKD stage 4, and 5.3% were CKD stage 5. Patients had 2 to 3 times greater odds of correct CKD self‐report if physicians had correctly identified their CKD stage (bivariable OR: 2.42, 95% confidence interval [CI]: 1.57‐3.72, multivariable OR: 3.22, 95% CI: 0.99‐10.46) (analysis not shown).

Patient Chronic Kidney Disease Self‐Report by Physician‐Coded CKD Stage and eGFR Calculated CKD Stage
CKD Stage* Physician (ICD‐9) Coded eGFR Calculated eGFR Coded With ICD‐9 Correct

  • NOTE: Percent correct patient CKD self‐report, patient awareness of CKD, by various methods of CKD stagephysician (ICD‐9) versus eGFR calculated CKD stage versus eGFR calculated stage with concordant ICD‐9 stage. Abbreviations: CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; ICD‐9, International Classification of Diseases, Ninth Revision; K/DOQI, Kidney Disease Outcomes Quality Initiative. *P<0.05, based on 2 comparing physician coded, eGFR calculated, and eGFR coded with correct ICD‐9 codes. CKD stage based on physician coded ICD‐9 data. CKD stage is eGFR calculated using mode CKD stage for hospitalization based on K/DOQI staging guidelines. Cases in which eGFR calculated stage and ICD‐9coded stage are concordant.

Unspecified 110 (27.2%)
12 5 (31.2%) 20 (17.4%) 0
3 25 (27.2%) 83 (27.7%) 17 (29.8%)
4 40 (63.5%) 54 (48.2%) 25 (69.4%)
5 11 (78.6%) 31 (63.3%) 10 (83.3%)

DISCUSSION

Although prior work has examined CKD awareness in the general population and in high‐risk cohorts,[2, 3, 13] this is the first study examining CKD awareness in an urban, underserved hospitalized population. We found that overall patients' CKD awareness was low (32%), but increased as high as 63% for CKD stage 5, even after controlling for patient demographic, clinical characteristics, and healthcare use. Our overall rate of CKD awareness was higher than prior studies overall and at lower CKD stages.[2, 3, 13] Our work is consistent with prior literature that shows increasing CKD awareness with advancing CKD stage.[2, 3, 13]

Older patients (>80 years) had lower awareness of CKD. Older patients are more likely to have a near normal creatinine, despite a markedly reduced eGFR, so their CKD may go unnoticed.[14] Even with appropriate recognition, providers may also feel like their CKD is unlikely to progress to ESRD, given its stability and/or their competing risk of death.[15] Finally, older hospitalized patients may also be less likely to report a CKD diagnosis due to difficulty in recall due to denial, dementia, or delirium.

One limitation is that our case‐finding for CKD was physician ICD‐9 coding, which is highly specific but not sensitive.[9] The majority of patients with physician‐identified CKD were CKD unspecified, perhaps due to poor coding, physician underdocumentation, or physician under‐recognition of CKD stage. Although only 27% of the CKD unspecified group correctly self‐identified as having CKD, over 75% were found to be CKD stage 3 or higher, which should trigger additional monitoring or care based on guidelines.[10] In addition, despite statistical significance, we may not be able to make meaningful inferences about our small other group (nonwhite, non‐African American). Our sample was from 1 hospitalan urban, academic, tertiary care center with a large proportion of African American patientswhich may limit generalizability. The multivariable model will need to be tested in other populations for reproducibility.

Our study significantly contributes to the literature by examining patient awareness of CKD in a high‐risk, urban, hospitalized minority population. Other study strengths include use of basic demographic information, as well as survey and laboratory data for a richer examination of the associations between patient factors and CKD awareness.

CONCLUSION

Hospitalized patients with CKD have a low CKD awareness. Patient awareness of their CKD is increased with physician documentation of CKD severity. Patient awareness of their CKD must be coupled with provider awareness and CKD documentation to link patients to multidisciplinary CKD education and care to slow CKD progression and reduce associated cardiovascular and metabolic complications. Further work is needed across hospitals to determineand improveCKD awareness among both patients and providers.

Disclosures

Dr. Saunders was supported by Pilot and Feasibility Funding from the Chicago Center for Diabetes Translation Research (NIDDK P30 DK092949). Dr. Chin was supported by NIDDK K24 DK071933. Dr. Meltzer was supported by NIA T35 AG029795. Dr. Saunders had full access to all of the study data and takes responsibility for the integrity of the data and accuracy of the data analysis. An abstract of this article was presented at the Society of Hospital Medicine Annual Meeting in Las Vegas, Nevada in March 2014 and at the Society of General Internal Medicine Annual Meeting in San Diego, California in April 2014. The authors report no conflicts of interest.

Chronic kidney disease (CKD) affects over 13% of the US population and is associated with increased morbidity, mortality, and healthcare costs.[1] However, only 10% of individuals with CKD are aware of their diagnoses.[2] Even in those with stage 5 CKD, only 60% of individuals are aware of their CKD.[3] To our knowledge, no work has examined CKD awareness in a hospitalized patient population.

Patient awareness of their CKD diagnosis is important because progression of kidney disease can be slowed by patient self‐management of diabetes and hypertension.[4] Patient awareness of CKD may also increase acceptance of preend‐stage renal disease (ESRD) patient education and nephrology referral, which have been shown to delay CKD progression and improve clinical status at dialysis initiation.[5] However, only 60% of patients with advanced CKD have visited a nephrologist in the past year or have seen a nephrologist prior to dialysis initiation.[1]

The hospital is an important site for patient education and linkage to outpatient care for patients with CKD.[6] The hospital serves high‐risk patients who may not be well connected to outpatient care or who have lesswell‐controlled disease.[6, 7] Thus, hospitalization represents an opportunity to identify existing CKD and to use a multidisciplinary approach to preventative care, patient education, and patient‐provider planning for renal replacement therapy needs. In our cross‐sectional study in an urban, minority‐serving hospital, we sought to determine what patient factors were associated with hospitalized patients correctly self‐identifying as having CKD.

METHODS

Subjects and Data

We used data from the University of Chicago Hospitalist Project, a study of hospitalized patient outcomes.[8] Within 48 hours of hospitalization, all general medicine patients or their proxies are approached to enroll. During one‐on‐one inpatient interviews, a trained research assistant obtains demographic, health status, and healthcare utilization information. Participants consent for study staff to review their medical records. More than 80% of general medicine patients enroll.

We obtained data on 1234 general medicine patients discharged between January 1, 2012 and March 31, 2013 with an International Classification of Diseases, Ninth Revision (ICD‐9) code for chronic kidney disease (ICD‐9 codes 585.0585.5, 585.9) in their first 20 admission diagnoses. These codes are highly specific for CKD but have lower sensitivity.[9] We excluded all patients with a history of transplant (996.81, V42.0, n=90) or ESRD (585.6, n=416). We excluded repeat admissions during the study period (n=138). Our final sample included 590 unique patients with ICD‐9 diagnosis of CKD without ESRD.

Demographic, Clinical, and Health Service Utilization Characteristics

Our outcome was CKD awareness, the patient's correct self‐report of kidney disease. Patients selected their chronic medical conditions from a list read to them and were specifically asked if they had kidney problems. Demographic characteristics including age, gender, race/ethnicity, marital status, and education were also obtained. Healthcare utilization variables included how often the patient saw their primary medical care provider in the past year and whether patients had a prior hospitalization in the last year.

Health status variables such as mental status, diabetes, hypertension, and CKD stage were also assessed. Mental status was quantified using the telephone version of the Mini‐Mental State Examination (MMSE), scored from 1 to 22.10 We defined diabetes as ICD‐9 codes 250.0250.00, and hypertension as ICD‐9 codes 401.0, 401.9, 403, 405.09, 405.19, 405.91, 405.99, or by patient self‐report. CKD stage was based on the estimated glomerular filtration rate (eGFR) from the medical record using Kidney Disease Outcomes Quality Initiative guidelines.[11] We used the mode of the eGFR to calculate the appropriate CKD stage for those with more than 1 eGFR value from the hospitalization (576/590, 98%). The eGFR was calculated by the modified Modification of Diet in Renal Disease equation: (GFR (mL/min/1.73 m2)=175 (Screatinine)1.154 (Age)0.203 (0.742 if female) x (1.212 if African American)) recommended by the National Kidney Disease Education Program.[12]

Analysis

We used logistic regression to analyze the influence of the demographic, clinical, and healthcare utilization covariates on the likelihood of a patient reporting kidney problems. For the multivariate analysis, we sequentially added variables in a step‐wise fashion. We adjusted for (1) demographic factors: gender, race, ethnicity, marital status, and education; (2) eGFR‐calculated CKD stage and comorbidities: diabetes, hypertension, and mental status; and (3) healthcare utilization in the last 12 months: any hospitalizations and the number of visits to a health provider.

RESULTS

Patient Characteristics and Bivariable Association With Patient CKD Self‐Report

Table 1 shows demographic, clinical, and health service use characteristics for 590 patients with ICD‐9 coded CKD. In the bivariable model in Table 1, age, race, marital status and comorbidities, were associated with patient self‐report of CKD. Patients older than 80 years with physician‐identified CKD through ICD‐9 coding had 57% lower odds of reporting CKD than their younger counterparts. Patients of other races (nonwhite, non‐African American), married patients, and those with CKD stages 4 and 5 were much more likely to correctly self‐report CKD. Patients with higher MMSE score, diabetes, or hypertension had greater odds of CKD self‐report (all P<0.05).

Overall Patient Characteristics and Patient Factors Associated With Patient Chronic Kidney Disease Self‐Report
Total, N=590 Bivariable Odds Ratio (95% CI) Multivariable With Stepwise Addition (95% CI)
Model 1, Demographic Factors Model 2, Plus CKD Stage and Other Comorbidities Model 3, Plus Health Service Use

  • NOTE: Model 1 demographic factors: gender, race, ethnicity, marital status and education; model 1+CKD stage; model 2+comorbidities: diabetes, hypertension, and mental status; and model 3+healthcare use: hospitalization in the last 12 months and number of visits to a health provider in the last year. Abbreviations: CI, confidence interval; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; ICD‐9, International Classification of Diseases, Ninth Revision. *P<0.05. P<0.01. P<0.001. Includes Asian or mixed race. ‖Diabetes ICD‐9 codes 250.0250.99. Hypertension ICD‐9 codes 401.0, 401.0, 401.9, 403, 405.09, 405.19, 405.91, 405.99. #From Mini‐Mental State Exam telephone version (score 126).

Female 312 (52.98%) 1.21 (0.85‐1.70) 1.64 (1.09‐2.47)* 1.28 (0.79‐2.06) 1.36 (0.75‐2.48)
Age, y
Below 54 138 (23.4%) REF REF REF REF
5466 150 (24.4%) 0.96 (0.59‐1.54) 0.95 (0.56‐1.59) 1.01 (0.56‐1.81) 0.83 (0.41‐1.68)
6779 161 (27.3%) 0.77 (0.48‐1.23) 0.67 (0.39‐1.15) 0.66 (0.35‐1.23) 0.72(0.34‐1.52)
Above 80 141 (23.9%) 0.43 (0.26‐0.74) 0.32 (0.17‐0.60) 0.42 (0.20‐0.91)* 0.37 (0.15‐0.93)*
Race
African American 449 (82.1%) REF REF REF REF
White 75 (13.7%) 1.47 (0.89‐2.42) 1.53 (0.86‐2.71) 1.56 (0.78‐3.12) 1.08 (0.47‐2.49)
Other 23 (4.2%) 3.62 (1.53‐8.54) 5.29 (1.78‐15.73) 6.19 (1.72‐22.29) 11.63 (1.80‐75.21)*
Ethnicity (Hispanic is reference group) 21 (4.0%) 0.97 (0.38‐2.44) 0.43 (0.13‐1.45) 0.71 (0.16‐3.09) 0.46 (0.06‐3.57)
Married 171 (32.6%) 1.49 (1.03‐2.18)* 1.32 (0.85‐2.04) 1.20 (0.73‐1.98) 1.77 (0.94‐3.33)
Education
Less than high school 128 (25.2%) REF REF REF REF
High school grad/some college 296 (58.2%) 1.05 (0.68‐1.63) 0.93 (0.58‐1.49) 0.95 (0.54‐1.67) 0.85 (0.42‐1.72)
College grad or higher 85 (16.7%) 1.13 (0.64‐2.01) 0.96 (0.51‐1.78) 1.07 (0.51‐2.23) 0.69 (0.27‐1.77)
CKD stage (eGFR calculated, mode)
12 115 (20.0%) 0.55 (0.32‐0.95)* 0.52 (0.27‐1.01) 0.28 (0.11‐0.69)
3 300 (52.1%) REF REF REF
4 112 (19.4%) 2.43 (1.55‐3.81) 2.69 (1.52‐4.76) 3.07 (1.56‐6.07)
5 49 (8.5%) 4.50 (2.39‐8.48) 3.94 (1.81‐8.56) 5.16 (1.85‐14.41)
Diabetes (ICD‐9 coded or self‐report)‖ 292 (49.5%) 1.52 (1.07‐2.15)* 1.54 (0.97‐2.45) 1.26 (0.71‐2.26)
Hypertension (ICD‐9 coded or self‐report) 436 (73.9%) 3.36 (2.09‐5.41) 1.53 (0.80‐2.90) 1.26 (0.57‐2.81)
Mini‐Mental State Exam score# 19.7 (2.5) 1.13 (1.03‐1.23) 1.09 (0.98‐1.22) 1.22 (1.06‐1.42)
Hospitalized in last 12 months 253 (46.9%) 1.50 (1.05‐2.13)* 1.12 (0.65‐1.95)
No. of visits to health provider
Once/year or less 80 (18.4%) REF REF
23 times/year 58 (13.3%) 0.80 (0.40‐1.60) 0.44 (0.17‐1.16)
4+ times/year 298 (68.4%) 0.60 (0.36‐0.99)* 0.38 (0.19‐0.74)

Multivariable Associations With Patient CKD Self‐Report

Age, race, and CKD stage remained consistently associated with CKD self‐report, although the magnitude of the effects (odds ratios [ORs]) varied across models (Table 1). Across all the models, patients older than 80 years were still significantly less likely than younger patients to self‐report CKD (ORs ranging from 0.32 to 0.42, all P<0.05). Patients classified as being of other race were found to have a 5.29 to 11.63 greater odds of CKD self‐report than African American patients (all P<0.05).

Patients with CKD stage 4 and 5 were more likely to self‐report than patients with CKD stage 3 (ORs ranging from 2.693.07 for stage 4 and 3.945.16 for stage 5, P<0.05). In the final model, every unit increase in MMSE score increased the odds of CKD self‐report by 22%. In addition, patients who saw their health provider 4 or more times per year were 62% less likely to self‐report CKD than patients who saw their provider 1 or fewer times per year (OR: 0.38, P<0.05).

A large proportion of patients (68.6%) were CKD unspecified by ICD‐9 codes, and only 27% of the unspecified group reported having CKD (Table 2). Examining the eGFR CKD stage of the CKD unspecified group showed that 22.8% were eGFR‐determined CKD stage 1 to 2, 57.1% were CKD stage 3, 14.8% were CKD stage 4, and 5.3% were CKD stage 5. Patients had 2 to 3 times greater odds of correct CKD self‐report if physicians had correctly identified their CKD stage (bivariable OR: 2.42, 95% confidence interval [CI]: 1.57‐3.72, multivariable OR: 3.22, 95% CI: 0.99‐10.46) (analysis not shown).

Patient Chronic Kidney Disease Self‐Report by Physician‐Coded CKD Stage and eGFR Calculated CKD Stage
CKD Stage* Physician (ICD‐9) Coded eGFR Calculated eGFR Coded With ICD‐9 Correct

  • NOTE: Percent correct patient CKD self‐report, patient awareness of CKD, by various methods of CKD stagephysician (ICD‐9) versus eGFR calculated CKD stage versus eGFR calculated stage with concordant ICD‐9 stage. Abbreviations: CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; ICD‐9, International Classification of Diseases, Ninth Revision; K/DOQI, Kidney Disease Outcomes Quality Initiative. *P<0.05, based on 2 comparing physician coded, eGFR calculated, and eGFR coded with correct ICD‐9 codes. CKD stage based on physician coded ICD‐9 data. CKD stage is eGFR calculated using mode CKD stage for hospitalization based on K/DOQI staging guidelines. Cases in which eGFR calculated stage and ICD‐9coded stage are concordant.

Unspecified 110 (27.2%)
12 5 (31.2%) 20 (17.4%) 0
3 25 (27.2%) 83 (27.7%) 17 (29.8%)
4 40 (63.5%) 54 (48.2%) 25 (69.4%)
5 11 (78.6%) 31 (63.3%) 10 (83.3%)

DISCUSSION

Although prior work has examined CKD awareness in the general population and in high‐risk cohorts,[2, 3, 13] this is the first study examining CKD awareness in an urban, underserved hospitalized population. We found that overall patients' CKD awareness was low (32%), but increased as high as 63% for CKD stage 5, even after controlling for patient demographic, clinical characteristics, and healthcare use. Our overall rate of CKD awareness was higher than prior studies overall and at lower CKD stages.[2, 3, 13] Our work is consistent with prior literature that shows increasing CKD awareness with advancing CKD stage.[2, 3, 13]

Older patients (>80 years) had lower awareness of CKD. Older patients are more likely to have a near normal creatinine, despite a markedly reduced eGFR, so their CKD may go unnoticed.[14] Even with appropriate recognition, providers may also feel like their CKD is unlikely to progress to ESRD, given its stability and/or their competing risk of death.[15] Finally, older hospitalized patients may also be less likely to report a CKD diagnosis due to difficulty in recall due to denial, dementia, or delirium.

One limitation is that our case‐finding for CKD was physician ICD‐9 coding, which is highly specific but not sensitive.[9] The majority of patients with physician‐identified CKD were CKD unspecified, perhaps due to poor coding, physician underdocumentation, or physician under‐recognition of CKD stage. Although only 27% of the CKD unspecified group correctly self‐identified as having CKD, over 75% were found to be CKD stage 3 or higher, which should trigger additional monitoring or care based on guidelines.[10] In addition, despite statistical significance, we may not be able to make meaningful inferences about our small other group (nonwhite, non‐African American). Our sample was from 1 hospitalan urban, academic, tertiary care center with a large proportion of African American patientswhich may limit generalizability. The multivariable model will need to be tested in other populations for reproducibility.

Our study significantly contributes to the literature by examining patient awareness of CKD in a high‐risk, urban, hospitalized minority population. Other study strengths include use of basic demographic information, as well as survey and laboratory data for a richer examination of the associations between patient factors and CKD awareness.

CONCLUSION

Hospitalized patients with CKD have a low CKD awareness. Patient awareness of their CKD is increased with physician documentation of CKD severity. Patient awareness of their CKD must be coupled with provider awareness and CKD documentation to link patients to multidisciplinary CKD education and care to slow CKD progression and reduce associated cardiovascular and metabolic complications. Further work is needed across hospitals to determineand improveCKD awareness among both patients and providers.

Disclosures

Dr. Saunders was supported by Pilot and Feasibility Funding from the Chicago Center for Diabetes Translation Research (NIDDK P30 DK092949). Dr. Chin was supported by NIDDK K24 DK071933. Dr. Meltzer was supported by NIA T35 AG029795. Dr. Saunders had full access to all of the study data and takes responsibility for the integrity of the data and accuracy of the data analysis. An abstract of this article was presented at the Society of Hospital Medicine Annual Meeting in Las Vegas, Nevada in March 2014 and at the Society of General Internal Medicine Annual Meeting in San Diego, California in April 2014. The authors report no conflicts of interest.

References
  1. United States Renal Data System. Annual Data Report: Atlas of Chronic Kidney Disease and End‐Stage Renal Disease in the United States. Bethesda, MD: National Institutes of Health; 2012.
  2. Tuot DS, Plantinga LC, Hsu CY, et al. Chronic kidney disease awareness among individuals with clinical markers of kidney dysfunction. Clin J Am Soc Neph. 2011;6(8):1838–1844.
  3. Kurella Tamura M, Anand S, Li S, et al. Comparison of CKD awareness in a screening population using the Modification of Diet in Renal Disease (MDRD) Study and CKD Epidemiology Collaboration (CKD‐EPI) equations. Am J Kidney Dis. 2011;57(3 suppl 2):S17–S23.
  4. Bakris GL, Williams M, Dworkin L, et al. Preserving renal function in adults with hypertension and diabetes: a consensus approach. Am J Kidney Dis. 2000;36(3):646–661.
  5. Wu IW, Wang SY, Hsu SK, et al. Multidisciplinary predialysis education decreases the incidence of dialysis and reduces mortality—a controlled cohort study based on the NKFDOQI guidelines. Nephrol Dial Transplant. 2009;24(11):3426–3433.
  6. Blunt I, Bardsley M, Strippoli GF. Pre‐dialysis hospital use and late referrals in incident dialysis patients in England: a retrospective cohort study. Nephrol Dial Transplant. 2015;30(1):124–129.
  7. Albert NM, Fonarow G, Abraham W, et al. Do hospitals that provide heart failure patient education prior to discharge also promote continuity of care? A report from OPTIMIZE‐HF. J Card Fail. 2006;12(6 suppl):S111.
  8. Meltzer D, Manning WG, Morrison J, et al. Effects of physician experience on costs and outcomes on an academic general medicine service: results of a trial of hospitalists. Ann Intern Med. 2002;137(11):866–874.
  9. Kern EFO, Maney M, Miller DR, et al. Failure of ICD‐9‐CM codes to identify patients with comorbid chronic kidney disease in diabetes. Health Serv Res. 2006;41(2):564–580.
  10. Roccaforte WH, Burke WJ, Bayer BL, Wengel SP. Validation of a telephone version of the mini‐mental state examination. J Am Geriatr Soc. 1992;40(7):697–702.
  11. National Kidney Foundation. Kidney disease outcomes quality initiative guidelines 2002. Available at: http://www2.kidney.org/professionals/KDOQI/guidelines_ckd/toc.htm. Accessed October 9, 2014.
  12. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Ann Intern Med. 1999;130(6):461–470.
  13. Flessner MF, Wyatt SB, Akylbekova EL, et al. Prevalence and awareness of CKD among African Americans: the Jackson Heart Study. Am J Kidney Dis. 2009;53(2):238–247.
  14. Giannelli SV, Patel KV, Windham BG, Pizzarelli F, Ferrucci L, Guralnik JM. Magnitude of underascertainment of impaired kidney function in older adults with normal serum creatinine. J Am Geriatr Soc. 2007;55(6):816–823.
  15. Anderson S, Halter JB, Hazzard WR, et al. Prediction, Progression, and Outcomes of Chronic Kidney Disease in Older Adults. J Am Soc Neph. 2009;20(6):1199–1209.
References
  1. United States Renal Data System. Annual Data Report: Atlas of Chronic Kidney Disease and End‐Stage Renal Disease in the United States. Bethesda, MD: National Institutes of Health; 2012.
  2. Tuot DS, Plantinga LC, Hsu CY, et al. Chronic kidney disease awareness among individuals with clinical markers of kidney dysfunction. Clin J Am Soc Neph. 2011;6(8):1838–1844.
  3. Kurella Tamura M, Anand S, Li S, et al. Comparison of CKD awareness in a screening population using the Modification of Diet in Renal Disease (MDRD) Study and CKD Epidemiology Collaboration (CKD‐EPI) equations. Am J Kidney Dis. 2011;57(3 suppl 2):S17–S23.
  4. Bakris GL, Williams M, Dworkin L, et al. Preserving renal function in adults with hypertension and diabetes: a consensus approach. Am J Kidney Dis. 2000;36(3):646–661.
  5. Wu IW, Wang SY, Hsu SK, et al. Multidisciplinary predialysis education decreases the incidence of dialysis and reduces mortality—a controlled cohort study based on the NKFDOQI guidelines. Nephrol Dial Transplant. 2009;24(11):3426–3433.
  6. Blunt I, Bardsley M, Strippoli GF. Pre‐dialysis hospital use and late referrals in incident dialysis patients in England: a retrospective cohort study. Nephrol Dial Transplant. 2015;30(1):124–129.
  7. Albert NM, Fonarow G, Abraham W, et al. Do hospitals that provide heart failure patient education prior to discharge also promote continuity of care? A report from OPTIMIZE‐HF. J Card Fail. 2006;12(6 suppl):S111.
  8. Meltzer D, Manning WG, Morrison J, et al. Effects of physician experience on costs and outcomes on an academic general medicine service: results of a trial of hospitalists. Ann Intern Med. 2002;137(11):866–874.
  9. Kern EFO, Maney M, Miller DR, et al. Failure of ICD‐9‐CM codes to identify patients with comorbid chronic kidney disease in diabetes. Health Serv Res. 2006;41(2):564–580.
  10. Roccaforte WH, Burke WJ, Bayer BL, Wengel SP. Validation of a telephone version of the mini‐mental state examination. J Am Geriatr Soc. 1992;40(7):697–702.
  11. National Kidney Foundation. Kidney disease outcomes quality initiative guidelines 2002. Available at: http://www2.kidney.org/professionals/KDOQI/guidelines_ckd/toc.htm. Accessed October 9, 2014.
  12. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Ann Intern Med. 1999;130(6):461–470.
  13. Flessner MF, Wyatt SB, Akylbekova EL, et al. Prevalence and awareness of CKD among African Americans: the Jackson Heart Study. Am J Kidney Dis. 2009;53(2):238–247.
  14. Giannelli SV, Patel KV, Windham BG, Pizzarelli F, Ferrucci L, Guralnik JM. Magnitude of underascertainment of impaired kidney function in older adults with normal serum creatinine. J Am Geriatr Soc. 2007;55(6):816–823.
  15. Anderson S, Halter JB, Hazzard WR, et al. Prediction, Progression, and Outcomes of Chronic Kidney Disease in Older Adults. J Am Soc Neph. 2009;20(6):1199–1209.
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Journal of Hospital Medicine - 10(9)
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Journal of Hospital Medicine - 10(9)
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Hospitalized patients frequently unaware of their chronic kidney disease
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Hospitalized patients frequently unaware of their chronic kidney disease
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Milda R. Saunders, MD, MPH
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Address for correspondence and reprint requests: Milda Saunders, MD, University of Chicago Medical Center, 5841 S. Maryland, MC 5000, Chicago, IL 60637; Telephone: 773‐702‐5941; E‐mail: msaunder@medicine.bsd.uchicago.edu; Fax: 773‐795‐7398
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