Development of MDS-Based Predication Model for COPD Severity in Nursing Home Residents.

BACKGROUND: Assessing chronic obstructive pulmonary disease (COPD) severity is challenging in nursing home (NH) residents due to incomplete symptom assessments and exacerbation history. OBJECTIVE: The objective of this study was to predict COPD severity in NH residents using the Minimum Data Set (MDS), a clinical assessment of functional capabilities and health needs. METHODS: A cohort analysis of prospectively collected longitudinal data was conducted. Residents from geographically varied Medicare-certified NHs with age ≥60 years, COPD diagnosis, and ≥6 months NH residence at enrollment were included. Residents with severe cognitive impairment were excluded. Demographic characteristics, medical history, and MDS variables were extracted from medical records. The care provider-completed COPD Assessment Test (CAT) and COPD exacerbation history were used to categorize residents by Global Initiative for Chronic Lung Disease (GOLD) A to D groups. Multivariate multinomial logit models mapped the MDS to GOLD A to D groups with stepwise selection of variables. RESULTS: Nursing home residents (N = 175) were 64% women and had a mean age of 77.9 years. Among residents, GOLD B was most common (A = 13.1%; B = 44.0%; C = 5.7%; D = 37.1%). Any long-acting bronchodilator (LABD) use and any dyspnea were significant predictors of GOLD A to D groups. The predicted MDS-GOLD group (A = 6.9%; B = 52.6%; C = 4.6%; D = 36.0%) showed good model fit (correctly predicted = 60.6%). Nursing home residents may underuse group-recommended LABD treatment (no LABD: B = 53.2%; C = 80.0%; D = 40.0%). CONCLUSION AND RELEVANCE: The MDS, completed routinely for US NH residents, could potentially be used to estimate COPD severity. Predicted COPD severity with additional validation could provide a map to evidence-based treatment guidelines and may help to individualize treatment pathways for NH residents.