Concordance Between Registry and Administrative Data in the Determination of Comorbidity: A Multi-institutional Study.
Journal
Annals of surgery
ISSN: 1528-1140
Titre abrégé: Ann Surg
Pays: United States
ID NLM: 0372354
Informations de publication
Date de publication:
12 2020
12 2020
Historique:
pubmed:
1
3
2019
medline:
15
12
2020
entrez:
1
3
2019
Statut:
ppublish
Résumé
To characterize agreement between administrative and registry data in the determination of patient-level comorbidities. 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. 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. 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. 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.
Sections du résumé
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.
Identifiants
pubmed: 30817356
doi: 10.1097/SLA.0000000000003247
pii: 00000658-202012000-00023
doi:
Types de publication
Journal Article
Multicenter Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
1006-1011Références
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