Ambulatory Healthcare Use Profiles of Patients With Diabetes and Their Association With Quality of Care: A Cross-Sectional Study

Abstract

Background: Despite the growing burden of diabetes worldwide, evidence regarding the optimal models of care to improve the quality of diabetes care remains equivocal. This study aimed to identify profiles of patients with distinct ambulatory care use patterns and to examine the association of these profiles with the quality of diabetes care.

Methods: We performed a cross-sectional study of the baseline data of 550 non-institutionalized adults included in a prospective, community-based, cohort study on diabetes care conducted in Switzerland. Clusters of participants with distinct patterns of ambulatory healthcare use were identified using discrete mixture models. To measure the quality of diabetes care, we used both processes of care indicators (eye and foot examination, microalbuminuria screening, blood cholesterol and glycated hemoglobin measurement [HbA1c], influenza immunization, blood pressure measurement, physical activity and diet advice) and outcome indicators (12-Item Short-Form Health Survey [SF-12], Audit of Diabetes-Dependent Quality of Life [ADDQoL], Patient Assessment of Chronic Illness Care [PACIC], Diabetes Self-Efficacy Scale, HbA1c value, and blood pressure <140/90 mmHg). For each profile of ambulatory healthcare use, we calculated adjusted probabilities of receiving processes of care and estimated adjusted outcomes of care using logistic and linear regression models, respectively.

Results: Four profiles of ambulatory healthcare use were identified: participants with more visits to the general practitioner [GP] than to the diabetologist and receiving concomitant podiatry care ("GP & podiatrist", n=86); participants visiting almost exclusively their GP ("GP only", n=195); participants with a substantially higher use of all ambulatory services ("High users", n=96); and participants reporting more visits to the diabetologist and less visits to the GP than other profiles ("Diabetologist first", n=173). Whereas participants belonging to the "GP only" profile were less likely to report most processes related to the quality of diabetes care, outcomes of care were relatively comparable across all ambulatory healthcare use profiles.

Conclusions: Slight differences in quality of diabetes care appear across the four ambulatory healthcare use profiles identified in this study. Overall, however, results suggest that room for improvement exists in all profiles, and further investigation is necessary to determine whether individual characteristics (like diabetes-related factors) and/or healthcare factors contribute to the differences observed between profiles.

Keywords: ambulatory care; cluster analysis; diabetes mellitus; outcome assessment; process assessment; profiles; quality of health care.

Figure 1

Mean number of visits in the past 12 months, by provider and healthcare use profile. GP, general practitioner.

Figure 2

Adjusted probabilities of receiving recommended processes of care, by healthcare use profile. GP, general practitioner. HbA1c, glycated hemoglobin. BP, blood pressure. Probabilities estimated from logistic regression models (predictive margins). Adjustment: age, sex, living arrangement status, residential location, education level, mandatory health insurance model, subsidies for mandatory health insurance, and diabetes-related complications. *Only participants who have already heard about HbA1c. †Among the following: eye examination, foot examination, microalbuminuria screening, blood cholesterol measurement, and influenza immunization. ‡Among the following: eye examination, foot examination, microalbuminuria screening, blood cholesterol measurement, influenza immunization, and HbA1c measurement.

Figure 3

Adjusted outcomes of care, by healthcare use profile. GP, general practitioner; SF-12, 12-Item Short-Form Health Survey; ADDQoL, Audit of Diabetes-Dependent Quality of Life; PACIC, Patient Assessment of Chronic Illness Care; HbA1c, glycated hemoglobin; BP, blood pressure. Means (or probabilities) estimated from linear (or logistic) regression models (predictive margins). Adjustment: age, sex, living arrangement status, residential location, education level, mandatory health insurance model, subsidies for mandatory health insurance, and diabetes-related complications. *Only participants of the 2017 recruitment phase. † Only participants who have already heard about HbA1c.