Background: Patients in geriatric care display a high degree of multimorbidity. We aimed to explore and visualise various patterns of multimorbidity in a person-oriented way. We used a register-based closed cohort (n=8104) of patients admitted to geriatric care in Region Stockholm, Sweden, from the year 2016.
Methods: Patients were grouped by their degree of multimorbidity according to the Johns Hopkins Adjusted Clinical Groups® system. Exploration was made using the Expanded Diagnosis Groups, embedded in the system. Statistical analysis was conducted in “R” and results were visualised in Excel.
Results: For half of all patients in the cohort, there were at least twelve diagnoses and at least thirteen active ingredients per patient. The quartile of patients with the highest level of multimorbidity were younger than the quartile of those with the lowest level. Patients with combinations of clusters of diagnoses showed various degrees of multimorbidity. Clusters of diagnoses with administrative character and cardiovascular diseases were present among nearly 80% each of all patients, followed by clusters of neurologic and musculoskeletal disorders with about 70% each. Comparisons between patients’ main diagnosis and all their diagnoses showed a shift to more of musculoskeletal disorders and less of cardiologic clusters when using main diagnoses. The morbidity status of patients measured by registered diagnoses was completed by including data on drugs, and revealed depression, persistent asthma and disorders of lipid metabolism.
Conclusions: Grouping patients by their degree of multimorbidity, based on all their registered concurrent diagnoses and drugs, could illustrate various patterns of mixed multimorbidity, which in turn might lead to a better understanding of the essence of multimorbidity from a patient’s perspective.