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Predictive value of stroke discharge diagnoses in the Danish National Patient Register
Pernille Lühdorf1, Kim Overvad2,3, Erik B Schmidt2
11 Department of Neurology, Aalborg University Hospital, Denmark.
Insights
The Danish National Patient Register shows a limited positive predictive value for stroke diagnoses, with an overall accuracy of 69.3%. This highlights the need for critical use of non-validated register data in stroke research.
Area of Science:
- Epidemiology
- Health Informatics
- Neurology
Background:
- The Danish National Patient Register (DNPR) is a valuable resource for epidemiological research.
- Accurate diagnostic coding is crucial for the validity of register-based studies.
Purpose of the Study:
- To assess the positive predictive values (PPVs) of stroke discharge diagnoses in the DNPR.
- To evaluate the accuracy of coding for subarachnoid hemorrhage, intracerebral hemorrhage, and cerebral infarction.
Main Methods:
- A cohort study (Diet, Cancer and Health) identified patients with stroke discharge diagnoses in the DNPR (1993-2009).
- Medical records were retrieved for validation of these diagnoses.
- Positive predictive values were calculated for overall stroke and specific subtypes.
Main Results:
- The overall PPV for stroke in the DNPR was 69.3% (95% CI 67.8-70.9%).
- PPVs varied significantly by hospital characteristics, ranging from 87.8% in neurology departments to 43.0% in outpatient clinics.
- Specific PPVs for sub-types like subarachnoid hemorrhage, intracerebral hemorrhage, and cerebral infarction were not detailed but contributed to the overall finding.
Conclusions:
- The overall accuracy of stroke discharge diagnoses in the DNPR is limited.
- Researchers should use non-validated DNPR data for stroke research with caution.
- Future research could explore advanced algorithms to improve the predictive value of register data.
Aims:
To determine the positive predictive values for stroke discharge diagnoses, including subarachnoidal haemorrhage, intracerebral haemorrhage and cerebral infarction in the Danish National Patient Register.
Methods:
Participants in the Danish cohort study Diet, Cancer and Health with a stroke discharge diagnosis in the National Patient Register between 1993 and 2009 were identified and their medical records were retrieved for validation of the diagnoses.
Results:
A total of 3326 records of possible cases of stroke were reviewed. The overall positive predictive value for stroke was 69.3% (95% confidence interval (CI) 67.8-70.9%). The predictive values differed according to hospital characteristics, with the highest predictive value of 87.8% (95% CI 85.5-90.1%) found in departments of neurology and the lowest predictive value of 43.0% (95% CI 37.6-48.5%) found in outpatient clinics.
Conclusions:
The overall stroke diagnosis in the Danish National Patient Register had a limited predictive value. We therefore recommend the critical use of non-validated register data for research on stroke. The possibility of optimising the predictive values based on more advanced algorithms should be considered.
