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Fuhrman, George M.

https://orcid.org/0000-0002-7708-7031

Mayo Clinic

Ochsner Health System

Citations 1

Concordance Between Registry and Administrative Data in the Determination of Comorbidity
Etzioni, David A. , Lessow, Cynthia, Bordeianou, Liliana , Kunitake, Hiroko , Deery, Sarah E. , Papageorge, Christina M. , Fuhrman, George M. , Seiler, Rachel L., Ogilvie, James W. , Habermann, Elizabeth B. , Money, Samuel R., Habermann, Elizabeth , Carchman, Evie H. , Chang, Yu‐Hui

Annals of Surgery | March 3, 2019 | Volume: 272 | Issue: 6 | Pages: 1006-1011

10.1097/sla.0000000000003247 Get It

Objective: To characterize agreement between administrative and registry data in the determination of patient-level comorbidities. Background: Previous research finds poor agreement between these 2 types of data in the determination of outcomes. We hypothesized that concordance between administrative and registry data would also be poor. Methods: A cohort of inpatient operations (length of stay 1 day or greater) was obtained from a consortium of 8 hospitals. Within each hospital, National Surgical Quality Improvement Program (NSQIP) data were merged with intra-institutional inpatient administrative data. Twelve different comorbidities (diabetes, hypertension, congestive heart failure, hemodialysis-dependence, cancer diagnosis, chronic obstructive pulmonary disease, ascites, sepsis, smoking, steroid, congestive heart failure, acute renal failure, and dyspnea) were analyzed in terms of agreement between administrative and NSQIP data. Results: Forty-one thousand four hundred thirty-two inpatient surgical hospitalizations were analyzed in this study. Concordance (Cohen Kappa value) between the 2 data sources varied from 0.79 (diabetes) to 0.02 (dyspnea). Hospital variation in concordance (intersite variation) was quantified using a test of homogeneity. This test found significant intersite variation at a level of P < 0.001 for each of the comorbidities except for dialysis (P = 0.07) and acute renal failure (P = 0.19). These findings imply significant differences between hospitals in their generation of comorbidity data. Conclusion: This study finds significant differences in how administrative versus registry data assess patient-level comorbidity. These differences are of concern to patients, payers, and providers, each of which had a stake in the integrity of these data. Standardized definitions of comorbidity and periodic audits are necessary to ensure data accuracy and minimize bias.