Patterns of multimorbidity and pharmacotherapy: a total population cross-sectional study

BACKGROUND: Treatment of multimorbid patients can be improved. Development of patient-centred care of high-quality requires context-bound understanding of the multimorbid population’s patterns of demographics, co-morbidities and medication use. OBJECTIVE: The aim of this study was to identify patterns of multimorbidity in the total population of Region Stockholm, Sweden, by exploring demographics, claimed prescription drugs, risk of mortality and non-random association of conditions. METHODS: In this cross-sectional descriptive population-based cohort study, we extracted data from the Swedish VAL database (N = 2 323 667) including all consultations in primary and specialized outpatient care, all inpatient care and all prescriptions claimed during 2017. We report number of chronic conditions and claimed prescription drugs, physical and mental co-morbidity, and 1-year mortality. We stratified the analyses by sex. We examined non-random associations between diseases using cluster analysis. RESULTS: In total, 21.6% had multimorbidity (two or more chronic conditions) and 24.1% had polypharmacy (more than five claimed prescription drugs). Number of claimed drugs, co-occurrence of mental and physical conditions, and 1-year mortality increased as multimorbidity increased. We identified seven multimorbidity clusters with clinically distinct characteristics. The smallest cluster (7% of individuals) had prominent cardiovascular disease, the highest 1-year mortality rate, high levels of multimorbidity and polypharmacy, and was much older. The largest cluster (27% of individuals) was younger and heterogenous, with primarily mental health problems. CONCLUSIONS: Individuals with chronic conditions often show clinical complexity with both concordant and discordant conditions and polypharmacy. This study indicates that clinical guidelines addressing clustering of conditions may be one strategy for managing complexity.