TY - JOUR
T1 - CKD Prevalence in the Military Health System
T2 - Coded Versus Uncoded CKD
AU - Norton, Jenna M.
AU - Grunwald, Lindsay
AU - Banaag, Amanda
AU - Olsen, Cara
AU - Narva, Andrew S.
AU - Marks, Eric
AU - Koehlmoos, Tracey P.
N1 - Funding Information:
This study was funded through the Comparative Effectiveness and Provider-Induced Demand Collaboration (EPIC)/Low-Value Care in the National Capital Region Project, by the United States Defense Health Agency , grant no. HU0001-11-1-0023 . The funding agency played no role in the design, analysis, or interpretation of findings.
Funding Information:
Jenna M. Norton, PhD, MPH, Lindsay Grunwald, MS, Amanda Banaag, MPH, Cara Olsen, MS, DrPH, Andrew S. Narva, MD, Eric Marks, MD, and Tracey P. Koehlmoos, PhD, MHA. Research idea and study design: JMN, TPK, CO, EM, ASN; data acquisition: TPK, LG, AB; data analysis/interpretation: JMN, TPK, LG, AB, CO, EM, ASN; statistical analysis: JMN, TPK, CO, LG, AB; supervision or mentorship: TPK, CO, EM, ASN. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved. This study was funded through the Comparative Effectiveness and Provider-Induced Demand Collaboration (EPIC)/Low-Value Care in the National Capital Region Project, by the United States Defense Health Agency, grant no. HU0001-11-1-0023. The funding agency played no role in the design, analysis, or interpretation of findings. The authors declare that they have no relevant financial interests. The contents, views, or opinions expressed in this presentation are those of the author(s) and do not necessarily reflect official policy or position of Uniformed Services University of the Health Sciences, the Department of Defense, or Departments of the Army, Navy, or Air Force, or the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. Mention of trade names, commercial products, or organizations does not imply endorsement by the US Government. Received October 9, 2020, as a submission to the expedited consideration track with 2 external peer reviews. Direct editorial input from the Statistical Editor, an Associate Editor, and the Editor-in-Chief. Accepted in revised form April 8, 2021. The data that support the findings of this study are available from the United States Defense Health Agency. Restrictions apply to the availability of these data, which were used under federal Data User Agreements for the current study, and so are not publicly available.
Publisher Copyright:
© 2021
PY - 2021/7/1
Y1 - 2021/7/1
N2 - Rationale & Objective: Chronic kidney disease (CKD) is common but often goes unrecorded. Study Design: Cross-sectional. Setting & Participants: Military Health System (MHS) beneficiaries aged 18 to 64 years who received care during fiscal years 2016 to 2018. Predictors: Age, sex, active duty status, race, diabetes, hypertension, and numbers of kidney test results. Outcomes: We defined CKD by International Classification of Diseases, Tenth Revision (ICD-10) code and/or a positive result on a validated electronic phenotype that uses estimated glomerular filtration rate and measures of proteinuria with evidence of chronicity. We defined coded CKD by the presence of an ICD-10 code. We defined uncoded CKD by a positive e-phenotype result without an ICD-10 code. Analytical Approach: We compared coded and uncoded populations using 2-tailed t tests (continuous variables) and Pearson χ2 test for independence (categorical variables). Results: The MHS population included 3,330,893 beneficiaries. Prevalence of CKD was 3.2%, based on ICD code and/or positive e-phenotype result. Of those identified with CKD, 63% were uncoded. Compared with beneficiaries with coded CKD, those with uncoded CKD were younger (aged 45 ± 13 vs 52 ± 11 years), more often women (54.4% vs 37.6%) and active duty (20.2% vs 12.5%), and less often of Black race (18.5% vs 31.5%) or with diabetes (23.5% vs 43.5%) or hypertension (46.6% vs 77.1%; P < 0.001). Beneficiaries with coded (vs uncoded) CKD had greater numbers of kidney test results (P < 0.001). Limitations: Use of cross-sectional administrative data prevents inferences about causality. The CKD e-phenotype may fail to capture CKD in individuals without laboratory data and may underestimate CKD. Conclusions: The prevalence of CKD in the MHS is ~3.2%. Beneficiaries with well-known CKD risk factors, such as older age, male sex, Black race, diabetes, and hypertension, were more likely to be coded, suggesting that clinicians may be missing CKD in groups traditionally considered lower risk, potentially resulting in suboptimal care.
AB - Rationale & Objective: Chronic kidney disease (CKD) is common but often goes unrecorded. Study Design: Cross-sectional. Setting & Participants: Military Health System (MHS) beneficiaries aged 18 to 64 years who received care during fiscal years 2016 to 2018. Predictors: Age, sex, active duty status, race, diabetes, hypertension, and numbers of kidney test results. Outcomes: We defined CKD by International Classification of Diseases, Tenth Revision (ICD-10) code and/or a positive result on a validated electronic phenotype that uses estimated glomerular filtration rate and measures of proteinuria with evidence of chronicity. We defined coded CKD by the presence of an ICD-10 code. We defined uncoded CKD by a positive e-phenotype result without an ICD-10 code. Analytical Approach: We compared coded and uncoded populations using 2-tailed t tests (continuous variables) and Pearson χ2 test for independence (categorical variables). Results: The MHS population included 3,330,893 beneficiaries. Prevalence of CKD was 3.2%, based on ICD code and/or positive e-phenotype result. Of those identified with CKD, 63% were uncoded. Compared with beneficiaries with coded CKD, those with uncoded CKD were younger (aged 45 ± 13 vs 52 ± 11 years), more often women (54.4% vs 37.6%) and active duty (20.2% vs 12.5%), and less often of Black race (18.5% vs 31.5%) or with diabetes (23.5% vs 43.5%) or hypertension (46.6% vs 77.1%; P < 0.001). Beneficiaries with coded (vs uncoded) CKD had greater numbers of kidney test results (P < 0.001). Limitations: Use of cross-sectional administrative data prevents inferences about causality. The CKD e-phenotype may fail to capture CKD in individuals without laboratory data and may underestimate CKD. Conclusions: The prevalence of CKD in the MHS is ~3.2%. Beneficiaries with well-known CKD risk factors, such as older age, male sex, Black race, diabetes, and hypertension, were more likely to be coded, suggesting that clinicians may be missing CKD in groups traditionally considered lower risk, potentially resulting in suboptimal care.
KW - Chronic kidney disease
KW - chronic renal disease
KW - chronic renal insufficiency
KW - electronic health record
KW - electronic phenotype
KW - estimated glomerular filtration rate
KW - medical record
KW - proteinuria
UR - http://www.scopus.com/inward/record.url?scp=85108978139&partnerID=8YFLogxK
U2 - 10.1016/j.xkme.2021.03.015
DO - 10.1016/j.xkme.2021.03.015
M3 - Article
AN - SCOPUS:85108978139
SN - 2590-0595
VL - 3
SP - 586-595.e1
JO - Kidney Medicine
JF - Kidney Medicine
IS - 4
ER -