Adjusted morbidity groups and survival: a retrospective cohort study of primary care patients with chronic conditions

Background Chronic conditions are one of the main determinants of frailty, functional disability, loss of quality of life and the number one cause of death worldwide. This study aimed to describe the survival of patients with chronic conditions who were followed up in primary care according to the level of risk by adjusted morbidity groups and to analyse the effects of sex, age, clinician and care factors on survival. Methods This was a longitudinal observational study of a retrospective cohort of patients with chronic conditions identified by the adjusted morbidity group stratifier of the electronic medical records in a primary health centre of the Region of Madrid, which has an assigned population of 18,107 inhabitants. The follow-up period was from June 2015 to June 2018. A description of survival according to the Kaplan–Meier method and Cox proportional hazards multivariate regression model was used to analyse the effects of sex, age, clinician and care factors. Results A total of 9,866 patients with chronic conditions were identified; 77.4% (7,638) had a low risk, 18.1% (1,784) had a medium risk, and 4.5% (444) had a high risk according to the adjusted morbidity groups. A total of 477 patients with chronic conditions died (4.8%). The median survival was 36 months. The factors associated with lower survival were age over 65 years (hazard ratio [HR] = 1.3; 95% confidence interval [CI] = 1.1–1.6), receiving palliative care (HR = 3.4; 95% CI = 2.6–4.5), high versus low risk level (HR = 2.4; 95% CI = 1.60–3.7), five chronic conditions or more (HR = 1.5; 95% CI = 1.2-2), complexity index (HR = 1.01; 95% CI = 1.02–1.04) and polymedication (HR = 2.6; 95% CI = 2.0-3.3). Conclusions There was a gradual and significant decrease in the survival of patients with chronic conditions according to their level of risk as defined by adjusted morbidity groups. Other factors, such as older age, receiving palliative care, high number of chronic conditions, complexity, and polymedication, had a negative effect on survival. The adjusted morbidity groups are useful in explaining survival outcomes and may be valuable for clinical practice, resource planning and public health research.