TY - JOUR
T1 - Chronic kidney disease identification in a high-risk urban population
T2 - Does automated eGFR reporting make a difference?
AU - Plantinga, Laura C.
AU - Tuot, Delphine S.
AU - Grubbs, Vanessa
AU - Hsu, Chi Yuan
AU - Powe, Neil R.
N1 - Funding Information:
We thank the patients and providers of the San Francisco Department of Community Health Network. Ms. Plantinga and Dr. Powe were partially supported by K24DK02643, Dr. Hsu was partially supported by K24DK92291, and Drs. Hsu and Powe were partially supported by R34DK093992, all from the National Institute of Diabetes, Digestive and Kidney Diseases, Bethesda, MD. Dr. Tuot was partially supported by UCSF KL2 RR024130 and an American Kidney Fund Clinical Scientist in Nephrology grant. Dr. Grubbs is supported by the National Institutes of Health/National Institute of Diabetes and Digestive and Renal Diseases Diversity Supplement to R01 DK70939.
PY - 2012/12
Y1 - 2012/12
N2 - Whether automated estimated glomerular filtration rate (eGFR) reporting for patients is associated with improved provider recognition of chronic kidney disease (CKD), as measured by diagnostic coding of CKD in those with laboratory evidence of the disease, has not been explored in a poor, ethnically diverse, high-risk urban patient population. A retrospective cohort of 237 adult patients (≥20 years) with incident CKD (≥1 eGFR ≥60 ml/min/1.73 m2, followed by ≥2 eGFRs <60 ml/min/1.73 m2 ≥3 months apart)-pre- or postautomated eGFR reporting-was identified within the San Francisco Department of Public Health Community Health Network (January 2005-July 2009). Patients were considered coded if any ICD-9-CM diagnostic codes for CKD (585.x), other kidney disease (580.x-581.x, 586.x), or diabetes (250.4) or hypertension (403.x, 404.x) CKD were present in the medical record within 6 months of incident CKD. Multivariable logistic regression was used to obtain adjusted odds ratios (ORs) for CKD coding. We found that, pre-eGFR reporting, 42.5 % of incident CKD patients were coded for CKD. Female gender, increased age, and non-Black race were associated with lower serum creatinine and lower prevalence of coding but comparable eGFR. Prevalence of coding was not statistically significantly higher overall (49.6 %, P = 0.27) or in subgroups after the institution of automated eGFR reporting. However, gaps in coding by age and gender were narrowed post-eGFR, even after adjustment for sociodemographic and clinical characteristics: 47.9 % of those <65 and 30.3 % of those ≥65 were coded pre-eGFR, compared to 49.0 % and 52.0 % post-eGFR (OR = 0.43 and 1.16); similarly, 53.2 % of males and 25.4 % of females were coded pre-eGFR compared to 52.8 % and 44.0 % post-eGFR (OR 0.28 vs. 0.64). Blacks were more likely to be coded in the post-eGFR period: OR = 1.08 and 1.43 (P interaction > 0.05). Automated eGFR reporting may help improve CKD recognition, but it is not sufficient to resolve underidentification of CKD by safety net providers.
AB - Whether automated estimated glomerular filtration rate (eGFR) reporting for patients is associated with improved provider recognition of chronic kidney disease (CKD), as measured by diagnostic coding of CKD in those with laboratory evidence of the disease, has not been explored in a poor, ethnically diverse, high-risk urban patient population. A retrospective cohort of 237 adult patients (≥20 years) with incident CKD (≥1 eGFR ≥60 ml/min/1.73 m2, followed by ≥2 eGFRs <60 ml/min/1.73 m2 ≥3 months apart)-pre- or postautomated eGFR reporting-was identified within the San Francisco Department of Public Health Community Health Network (January 2005-July 2009). Patients were considered coded if any ICD-9-CM diagnostic codes for CKD (585.x), other kidney disease (580.x-581.x, 586.x), or diabetes (250.4) or hypertension (403.x, 404.x) CKD were present in the medical record within 6 months of incident CKD. Multivariable logistic regression was used to obtain adjusted odds ratios (ORs) for CKD coding. We found that, pre-eGFR reporting, 42.5 % of incident CKD patients were coded for CKD. Female gender, increased age, and non-Black race were associated with lower serum creatinine and lower prevalence of coding but comparable eGFR. Prevalence of coding was not statistically significantly higher overall (49.6 %, P = 0.27) or in subgroups after the institution of automated eGFR reporting. However, gaps in coding by age and gender were narrowed post-eGFR, even after adjustment for sociodemographic and clinical characteristics: 47.9 % of those <65 and 30.3 % of those ≥65 were coded pre-eGFR, compared to 49.0 % and 52.0 % post-eGFR (OR = 0.43 and 1.16); similarly, 53.2 % of males and 25.4 % of females were coded pre-eGFR compared to 52.8 % and 44.0 % post-eGFR (OR 0.28 vs. 0.64). Blacks were more likely to be coded in the post-eGFR period: OR = 1.08 and 1.43 (P interaction > 0.05). Automated eGFR reporting may help improve CKD recognition, but it is not sufficient to resolve underidentification of CKD by safety net providers.
KW - African American
KW - Chronic kidney disease
KW - Diagnostic coding
KW - Estimated glomerular filtration rate
KW - Female
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U2 - 10.1007/s11524-012-9726-2
DO - 10.1007/s11524-012-9726-2
M3 - Article
C2 - 22684427
AN - SCOPUS:84878497579
SN - 1099-3460
VL - 89
SP - 965
EP - 976
JO - Journal of Urban Health
JF - Journal of Urban Health
IS - 6
ER -