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Does a Code for Acute Myocardial Infarction Mean the Same in All Norwegian Hospitals? A Likelihood Approach to a Medical Record Review

OBJECTIVE: Health registries are important data sources for epidemiology, quality monitoring, and improvement. Acute myocardial infarction (AMI) is a common, serious condition. Little is known about variation in the positive predictive value (PPV) of a coded AMI diagnosis and its association with ho...

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Detalles Bibliográficos
Autores principales: Helgeland, Jon, Kristoffersen, Doris Tove, Skyrud, Katrine Damgaard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577561/
https://www.ncbi.nlm.nih.gov/pubmed/36268007
http://dx.doi.org/10.2147/CLEP.S369763
Descripción
Sumario:OBJECTIVE: Health registries are important data sources for epidemiology, quality monitoring, and improvement. Acute myocardial infarction (AMI) is a common, serious condition. Little is known about variation in the positive predictive value (PPV) of a coded AMI diagnosis and its association with hospital quality indicators. The present study aimed to investigate the relationship between PPV and registry-based 30-day mortality after AMI admission and between-hospital variation in PPV. STUDY DESIGN AND SETTING: An electronic record review was performed in a nationwide sample of Norwegian hospitals. Clinical signs and cardiac troponin measurements were abstracted and analyzed using a mixture model for likelihood ratios and parametric bootstrapping. RESULTS: The overall PPV was estimated to be 97%. We found no statistically significant association between hospital PPV and the classification of hospitals into low, intermediate, and high registry-based 30-day mortality. There was significant variation between hospitals, with a PPV range of 91–100%. CONCLUSION: We found no evidence that variation in PPV of AMI diagnosis can explain variation between hospitals in registry-based 30-day mortality after admission. However, PPV varied significantly between hospitals. We were able to use a very efficient statistical approach to the analysis and handling of various sources of uncertainty.