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A quality improvement project using statistical process control methods for type 2 diabetes control in a resource-limited setting.
International Journal for Quality in Health Care 2017 August 2
Quality issue: Quality improvement (QI) is a key strategy for improving diabetes care in low- and middle-income countries (LMICs). This study reports on a diabetes QI project in rural Guatemala whose primary aim was to improve glycemic control of a panel of adult diabetes patients.
Initial assessment: Formative research suggested multiple areas for programmatic improvement in ambulatory diabetes care.
Choice of solution: This project utilized the Model for Improvement and Agile Global Health, our organization's complementary healthcare implementation framework.
Implementation: A bundle of improvement activities were implemented at the home, clinic and institutional level.
Evaluation: Control charts of mean hemoglobin A1C (HbA1C) and proportion of patients meeting target HbA1C showed improvement as special cause variation was identified 3 months after the intervention began. Control charts for secondary process measures offered insights into the value of different components of the intervention. Intensity of home-based diabetes education emerged as an important driver of panel glycemic control.
Lessons learned: Diabetes QI work is feasible in resource-limited settings in LMICs and can improve glycemic control. Statistical process control charts are a promising methodology for use with panels or registries of diabetes patients.
Initial assessment: Formative research suggested multiple areas for programmatic improvement in ambulatory diabetes care.
Choice of solution: This project utilized the Model for Improvement and Agile Global Health, our organization's complementary healthcare implementation framework.
Implementation: A bundle of improvement activities were implemented at the home, clinic and institutional level.
Evaluation: Control charts of mean hemoglobin A1C (HbA1C) and proportion of patients meeting target HbA1C showed improvement as special cause variation was identified 3 months after the intervention began. Control charts for secondary process measures offered insights into the value of different components of the intervention. Intensity of home-based diabetes education emerged as an important driver of panel glycemic control.
Lessons learned: Diabetes QI work is feasible in resource-limited settings in LMICs and can improve glycemic control. Statistical process control charts are a promising methodology for use with panels or registries of diabetes patients.
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