The Relationship Between Multimorbidity and Patients’ Ratings of Communication

BACKGROUND The growing interest in pay-for-performance and other quality improvement programs has generated concerns about potential performance measurement penalties for providers who care for more complex patients, such as patients with more chronic conditions. Few data are available on how multimorbidity affects common performance metrics. OBJECTIVE To examine the relationship between multimorbidity and patients’ ratings of communication, a common performance metric. DESIGN Cross-sectional study SETTING Nationally representative sample of U.S. residents PARTICIPANTS A total of 15,709 noninstitutionalized adults living in the United States participated in a telephone interview. MEASUREMENTS We used 2 different measures of multimorbidity: 1) “individual conditions” approach disregards similarities/concordance among chronic conditions and 2) “condition-groups” approach considers similarities/concordance among conditions. We used a composite measure of patients’ ratings of patient–physician communication. RESULTS A higher number of individual conditions is associated with lower ratings of communication, although the magnitude of the relationship is small (adjusted average communication scores: 0 conditions, 12.20; 1–2 conditions, 12.06; 3+ conditions, 11.90; scale range 5 = worst, 15 = best). This relationship remains statistically significant when concordant relationships among conditions are considered (0 condition groups 12.19; 1–2 condition groups 12.03; 3+ condition groups 11.94). CONCLUSIONS In our nationally representative sample, patients with more chronic conditions gave their doctors modestly lower patient–doctor communication scores than their healthier counterparts. Accounting for concordance among conditions does not widen the difference in communication scores. Concerns about performance measurement penalty related to patient complexity cannot be entirely addressed by adjusting for multimorbidity. Future studies should focus on other aspects of clinical complexity (e.g., severity, specific combinations of conditions).