Objective: Hospital discharge registers (HDRs) are frequently used in epidemiological research. However, the validity of several important psychiatric diagnostic entities, including bipolar disorder, remains uncertain. Hence, we aimed to develop an optimal algorithm for register-based identification of DSM-IV-TR bipolar disorder.
Method: We identified potential cases in the Swedish national HDR using two separate discharge diagnoses of bipolar disorder according to ICD versions 8-10 during January 1, 1973 to December 31, 2004. In a randomly selected subsample of 135 cases from the county of Sörmland, two senior psychiatrists reassessed the diagnostic status based on patients' medical records. We scrutinized false-positive cases and modified the initial algorithm to improve positive predictive value while minimizing false negatives. Finally, we externally validated resulting caseness algorithms by linking HDR diagnostic data with best-estimate clinical diagnoses from the National Quality Assurance Register for Bipolar Disorder (BipoläR), dispensed lithium prescriptions from the National Prescribed Drug Register, and the ICD-10 diagnoses from the National Outpatient Register respectively.
Results: The algorithm with two discharge diagnoses of bipolar disorder yielded a positive predictive value of 0.81. Modification by excluding individuals diagnosed with ICD-8 296.20 (manic-depressive psychosis, depressed type), and/or ICD-9 296.B (unipolar affective psychosis, melancholic form), gave a positive positive predictive value of 0.92. The modified algorithm also had statistically superior external validity compared with the original algorithm.
Conclusion: Our findings suggest that DSM-IV-TR bipolar disorder caseness based on two inpatient episodes with a bipolar disorder diagnosis is sufficiently sensitive and specific to be used in further epidemiological study of bipolar disorder.
© 2011 John Wiley & Sons A/S.