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.
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.
Authors: Erika R Gehrie; Harmony R Reynolds; Anita Y Chen; Brian H Neelon; Matthew T Roe; W Brian Gibler; E Magnus Ohman; L Kristin Newby; Eric D Peterson; Judith S Hochman Journal: Am Heart J Date: 2009-10 Impact factor: 4.749
Authors: Greg Ridgeway; Mette Nørgaard; Thomas Bøjer Rasmussen; William D Finkle; Lars Pedersen; Hans Erik Bøtker; Henrik Toft Sørensen Journal: Clin Epidemiol Date: 2019-01-04 Impact factor: 4.790