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Validity of chronic disease diagnoses in Icelandic healthcare registries
Sæmundur Rögnvaldsson1, Thorir Einarsson Long1,2, Sigrun Thorsteinsdottir1,3
1Faculty of Medicine, University of Iceland, Iceland.
Insights
Icelandic healthcare registry diagnoses for chronic diseases are highly accurate, with strong positive and negative predictive values. This confirms the reliability of registry data for research purposes.
Area of Science:
- Public Health
- Epidemiology
- Medical Informatics
Background:
- Healthcare registries are crucial for epidemiological research.
- Validating diagnostic data ensures the reliability of research findings.
- The accuracy of chronic disease diagnoses in registries requires rigorous assessment.
Purpose of the Study:
- To evaluate the accuracy and validity of recorded chronic disease diagnoses in Icelandic healthcare registries.
- To assess the positive predictive value (PPV) and negative predictive value (NPV) of these diagnoses.
- To determine if diagnoses are supported by objective medical findings.
Main Methods:
- A validation study was conducted using data from the iStopMM trial, encompassing 54% of the Icelandic population born before 1976.
- For eight chronic diseases, 30 patients with and 30 without a diagnosis were randomly selected for physician chart review.
- Predefined criteria were used to validate each case, focusing on accuracy rather than timeliness.
Main Results:
- The overall accuracy of chronic disease diagnoses was 96%, with an estimated 98.5% after weighting for prevalence.
- The overall positive predictive value (PPV) was 93% and the negative predictive value (NPV) was 99%.
- Most diagnoses were supported by objective findings (96%), though PPV varied by disease (e.g., 83% for multiple sclerosis).
Conclusions:
- Diagnosis data from Icelandic healthcare registries demonstrates high accuracy, PPV, and NPV for chronic diseases.
- The majority of recorded diagnoses can be corroborated by objective medical evidence.
- Findings support the reliable use of Icelandic registry data in health research.
Aims:
To evaluate the validity of recorded chronic disease diagnoses in Icelandic healthcare registries.
Methods:
Eight different chronic diseases from multiple sub-specialties of medicine were validated with respect to accuracy, but not to timeliness. For each disease, 30 patients with a recorded diagnosis and 30 patients without the same diagnosis were randomly selected from >80,000 participants in the iStopMM trial, which includes 54% of the Icelandic population born before 1976. Each case was validated by chart review by physicians using predefined criteria.
Results:
The overall accuracy of the chronic disease diagnoses was 96% (95% CI 94-97%), ranging from 92 to 98% for individual diseases. After weighting for disease prevalence, the accuracy was estimated to be 98.5%. The overall positive predictive value (PPV) of chronic disease diagnosis was 93% (95% CI 89-96%) and the overall negative predictive value (NPV) was 99% (95% CI 96-100%). There were disease-specific differences in validity, most notably multiple sclerosis, where the PPV was 83%. Other disorders had PPVs between 93 and 97%. The NPV of most disorders was 100%, except for hypertension and heart failure, where it was 97 and 93%, respectively. Those who had the registered chronic disease had objective findings of disease in 96% of cases.
Conclusions:
When determining the presence of chronic disease, diagnosis data from the Icelandic healthcare registries has a high PPV, NPV and accuracy. Furthermore, most diagnoses can be confirmed by objective findings such as imaging or blood testing. These findings can inform the interpretation of studies using diagnostic data from the Icelandic healthcare registries.
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