Construction and validation of a morbidity index based on the International Classification of Primary Care

OBJECTIVES: In epidemiological studies it is often necessary to describe morbidity. The aim of the present study is to construct and validate a morbidity index based on the International Classification of Primary Care (ICPC-2). DESIGN AND SETTING: This is a cohort study based on linked data from national registries. An ICPC morbidity index was constructed based on a list of longstanding health problems in earlier published Scottish data from general practice and adapted to diagnostic ICPC-2 codes recorded in Norwegian general practice 2015 − 2017. SUBJECTS: The index was constructed among Norwegian born people only (N = 4 509 382) and validated in a different population, foreign-born people living in Norway (N = 959 496). MAIN OUTCOME MEASURES: Predictive ability for death in 2018 in these populations was compared with the Charlson index. Multiple logistic regression was used to identify morbidities with the highest odds ratios (OR) for death and predictive ability for different combinations of morbidities was estimated by the area under receiver operating characteristic curves (AUC). RESULTS: An index based on 18 morbidities was found to be optimal, predicting mortality with an AUC of 0.78, slightly better than the Charlson index (AUC 0.77). External validation in a foreign-born population yielded an AUC of 0.76 for the ICPC morbidity index and 0.77 for the Charlson index. CONCLUSIONS: The ICPC morbidity index performs equal to the Charlson index and can be recommended for use in data materials collected in primary health care. KEY POINTS: This is the first morbidity index based on the International Classification of Primary Care, 2(nd) edition (ICPC-2). It predicted mortality equal to the Charlson index and validated acceptably in a different population. The ICPC morbidity index can be used as an adjustment variable in epidemiological research in primary care databases.