Development and evaluation of a patient-centered quality indicator for the appropriateness of type 2 diabetes management

开发和评估以患者为中心的2型糖尿病管理适宜性质量指标

阅读:1

Abstract

INTRODUCTION: Current diabetes quality measures are agnostic to patient clinical complexity and type of treatment required to achieve it. Our objective was to introduce a patient-centered indicator of appropriate diabetes therapy indicator (ADTI), designed for patients with type 2 diabetes, which is based on hemoglobin A1c (HbA1c) but is also contextualized by patient complexity and treatment intensity. RESEARCH DESIGN AND METHODS: A draft indicator was iteratively refined by a multidisciplinary Delphi panel using existing quality measures, guidelines, and published literature. ADTI performance was then assessed using OptumLabs Data Warehouse data for 2015. Included adults (n=206 279) with type 2 diabetes were categorized as clinically complex based on comorbidities, then categorized as treated appropriately, overtreated, or undertreated based on a matrix of clinical complexity, HbA1c level, and medications used. Associations between ADTI and emergency department/hospital visits for hypoglycemia and hyperglycemia were assessed by calculating event rates for each treatment intensity subset. RESULTS: Overall, 7.4% of patients with type 2 diabetes were overtreated and 21.1% were undertreated. Patients with high complexity were more likely to be overtreated (OR 5.60, 95% CI 5.37 to 5.83) and less likely to be undertreated (OR 0.65, 95% CI 0.62 to 0.68) than patients with low complexity. Overtreated patients had higher rates of hypoglycemia than appropriately treated patients (22.0 vs 6.2 per 1000 people/year), whereas undertreated patients had higher rates of hyperglycemia (8.4 vs 1.9 per 1000 people/year). CONCLUSIONS: The ADTI may facilitate timely, patient-centered treatment intensification/deintensification with the goal of achieving safer evidence-based care.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。