Many validation and PPV studies rely on establishing a gold standard by expert judgment and consensus. 23 For definite or probable AMI, the authors found significant differences in PPV between four communities of residence, ranging from 71% to 78%. We know of only one study on the variation in PPV. 14–20 Two systematic reviews 21, 22 reported PPVs greater than 93% in the majority of studies and a range of 70–100%. The positive predictive value (PPV) of a coded AMI diagnosis from administrative health registries has been studied by several authors. 11, 12 The proportion of Type 2 among AMI cases varies widely between studies. Nonischemic myocardial injury may result in elevated cTn and must be distinguished from Type 2 AMI. Type 2 AMI is defined as ischemia caused by acute conditions other than acute coronary atherothrombosis. 9, 10 A loss of oxygen supply to the heart (ischemia) is necessary for AMI diagnosis. For an overview of the diagnosis of AMI and the use of cTn, see e.g. Cardiac troponins (cTns) are proteins that form parts of the heart muscle tissue (myocardium) and are released when heart tissue is damaged. The diagnosis of AMI rests on patient history, clinical information such as electrocardiography (ECG) abnormalities and the presence of chest pain, as well as biochemical markers. 1–8 Addressing these issues is important to further the use of 30D in health system governance and clinical quality improvement. Although 30D is in routine use as a quality indicator in Norway and elsewhere, criticisms have been raised. We may distinguish between two sources of bias when comparing hospitals: first, variation in diagnostic or coding practice, resulting in different medical conditions in the data from different hospitals second, variation in disease severity, which cannot be controlled for by case mix adjustment. To be useful, the indicators must be valid in the sense of having negligible bias and unobserved confounding. Routine publication of quality indicators can potentially be used for quality improvement. The probability of death within 30 days after hospital admission (here denoted 30D), based on coded diagnosis in electronic registries, has been used as a quality indicator for hospitals. Hospital administrative databases are important sources for the study of AMI epidemiology as well as for quality monitoring and improvement. Keywords: health registries, quality indicators, finite mixture models, case fatality, cardiac troponinsĪcute myocardial infarction (AMI) is a serious condition with high short-term mortality and a high rate of subsequent disability among survivors. We were able to use a very efficient statistical approach to the analysis and handling of various sources of uncertainty. However, PPV varied significantly between hospitals. There was significant variation between hospitals, with a PPV range of 91– 100%.Ĭonclusion: We found no evidence that variation in PPV of AMI diagnosis can explain variation between hospitals in registry-based 30-day mortality after admission. We found no statistically significant association between hospital PPV and the classification of hospitals into low, intermediate, and high registry-based 30-day mortality. Results: The overall PPV was estimated to be 97%. Clinical signs and cardiac troponin measurements were abstracted and analyzed using a mixture model for likelihood ratios and parametric bootstrapping. Study Design and Setting: An electronic record review was performed in a nationwide sample of Norwegian hospitals. 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. Little is known about variation in the positive predictive value (PPV) of a coded AMI diagnosis and its association with hospital quality indicators. Acute myocardial infarction (AMI) is a common, serious condition. Objective: Health registries are important data sources for epidemiology, quality monitoring, and improvement. Jon Helgeland, Doris Tove Kristoffersen, Katrine Damgaard Skyrudĭivision for Health Services, Norwegian Institute of Public Health, Oslo, NorwayĬorrespondence: Jon Helgeland, Norwegian Institute of Public Health, PO Box 222 Skøyen, Oslo, 0213, Norway, Tel +47 464 00 443, Email
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