Multimorbidity clusters and associated health care cost among patients attending psychiatric clinics in Odisha, India

Introduction: There is a dearth of data on common multimorbidity clusters and the healthcare costs for individuals with mental health disorders. This study aimed to identify clinically meaningful physical-mental multimorbidity clusters, frequently occurring clusters of conditions, and healthcare utilization patterns and expenditure among patients attending a psychiatric outpatient clinic. Materials and Methods: Data were collected in the psychiatric outpatient department among patients aged 18 years and above in February-July 2019 (n = 500); follow-up data on non-communicable disease incidence were collected after 18 months. For analysis, morbidity clusters were defined using two approaches: 1) agglomerative hierarchical clustering method to identify clusters of diseases; and 2) non-hierarchical cluster k mean analysis to identify clusters of patients. Self-reported healthcare costs in these clusters were also calculated. Result: Two disease clusters were identified: using the 1st approach were; 1) hypertension, diabetes, and mood disorder; 2) Neurotic, stress-related, and somatoform disorders, and acid peptic disease. Three clusters of patients identified using the 2nd approach were identified: 1) those with mood disorders and cardiometabolic, musculoskeletal, and thyroid diseases; 2) those with neurotic, substance use, and organic mental disorders, cancer, and epilepsy; and 3) those with Schizophrenia. Patients in Cluster 1 were taking more than six medicines and had more hospital visits. Within 18 months, 41 participants developed either one or two chronic conditions, most commonly diabetes, hypertension, or thyroid disease. Conclusion: Cardiometabolic diseases are most commonly clustered with mood disorders. There is a need for blood pressure and sugar measurement in psychiatric clinics and mood disorder screening in cardiac, endocrinology, and primary care clinics.