Claims-based informational and management continuity analyses should control for the number of visits: an observational model performance comparison on a claims dataset of elderly German insured

Abstract Empirical research using claims data has found that continuity of care (COC) is associated with a number of important health economic and medication appropriateness-related outcomes (MARO), such as polypharmacy and potentially inappropriate medications (PIM). However, there is no consensus in the literature on whether claims-based COC analyses should control for the number of visits and the number of providers. In this paper, we investigate how controlling for the number of visits impacts regression model performance and estimates. We also perform additional exploratory analyses to investigate the presence of an interaction between COC and the number of visits and of nonlinear effects of COC and the number of visits. In our main analysis, we used multivariate logistic regression models on a dataset of over 30,000 elderly individuals in Germany, based on claims data from statutory health insurance providers, with extreme polypharmacy (10+ distinct medications) as the outcome and the Herfindahl–Hirschman Index (HHI) as the key predictor, controlling for age, sex and morbidity. We reported regression coefficients, standard errors and p-values and used the Akaike Information Criterion (AIC), Tjur’s $${R}^{2}$$ , area under the receiver operating characteristic (ROC) curve, cross-validation (accuracy/correct classification rate and Brier’s score) as well as a residual analysis to compare models. In robustness checks, we excluded outliers with a high number of visits, used the Bice-Boxerman Continuity of Care Index (BBCOCI) as the key predictor and used PIM as the outcome. In exploratory analyses, we included interaction terms and nonlinear (quadratic) terms for the number of visits and the HHI/BBCOCI. In the main analysis and all robustness checks, models including the number of visits performed better than models excluding the number of visits. Failing to include the number of visits led to inflated estimates of the association between the HHI/BBCOCI and MARO. The exploratory analyses revealed significant interaction terms and nonlinearities. Based on our findings, we recommend that researchers control for the number of visits in claims-based COC analyses, at least when investigating informational/management continuity. Furthermore, where possible, researchers should consider investigating the interaction between the number of visits and the HHI/BBCOCI and allowing for nonlinearity for these variables.