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Supplemental Appendixes
Supplemental Appendix 1. Empirical logit transformation and back transformation; Supplemental Appendix 2. Association between quality of diabetes care (process) and the prevalence of diabetes and of diabetes concordant conditions (sensitivity analysis based on QOF scores instead of achievement rates); Supplemental Appendix 3. Association between quality of diabetes care (intermediate outcomes) and the prevalence of diabetes and diabetes-concordant conditions (sensitivity analysis based on QOF scores instead of achivement rates)
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- Supplemental data: Appendixes - PDF file
The Article in Brief
Impact of the Prevalence of Concordant and Discordant Conditions on the Quality of Diabetes Care in Family Practices in England
Ignacio Ricci-Cabello , and colleagues
Background This study sets out to explain the quality of diabetes care in family practices. It assesses the potential impact of the prevalence of diabetes-concordant conditions (conditions with related physiologic processes that may therefore be part of the same care management plan) such as obesity, hypertension, coronary heart disease, chronic kidney disease, stroke, atrial fibrillation and heart failure) and diabetes-discordant conditions (conditions that are not directly related to each other physiologically or in their care management) such as asthma, cancer, chronic obstructive pulmonary disease, dementia, depression, epilepsy, hypothyroidism and severe mental disorders. The study examines whether family practices with a higher proportion of patients with related cardiometabolic conditions may prioritize and more efficiently allocate resources for the management of these conditions. In comparison, practices with a higher proportion of patients with diabetes-discordant conditions might find it more difficult to deliver high-quality diabetes care because of competition for resources and attention from varying conditions.
What This Study Found Although the quality of diabetes care provided in practices is associated with the prevalence of other major chronic conditions, the nature and direction of the associations is only partially explained by the concordant-discordant model. Specifically, prevalence rates for four of seven concordant conditions (obesity, chronic kidney disease, atrial fibrillation and heart failure) were positively associated with quality of diabetes care. Similarly, negative associations were observed as predicted for two of eight discordant conditions examined (epilepsy and mental health). Observations for other concordant and discordant conditions, however, did not match predictions. The prevalence of hypertension and coronary heart failure, for example, were negatively associated with both processes and intermediate outcomes of diabetes. There were strong positive associations for diabetes quality of care and cancer and COPD.
Implications
- The authors conclude that while the concordant-discordant model does not fully explain the patterns of association between the prevalence of chronic conditions and the quality of diabetes care, the prevalence of a number of chronic conditions can be a predictor of quality of care for diabetes. The authors assert that incentive programs should consider the number of chronic conditions when assessing performance of individual clinicians.