The ability of primary healthcare (PHC) providers to practice in accordance with evidence-based guidelines and norms is a critical component of improving the quality of primary healthcare. Implementation science seeks to promote the routine use of evidence-based practices by identifying barriers to their implementation and developing strategies, such as audit and feedback (AnF), to overcome them. However, because the effects of AnF show significant heterogeneity across studies, this research focuses on systematically developing an optimized AnF strategy and rigorously evaluating its effectiveness in improving clinical practice compared to no intervention. The development of an optimized AnF strategy involves a preparation phase, which utilizes expert consultation and a Best-Worst Scaling (BWS) survey to identify key candidate components and assess resource constraints, followed by an optimization phase utilizing a 2×2×2×2 factorial design randomized controlled trial (RCT) to determine the most effective combination of AnF components. Subsequently, in the evaluation phase, a two-arm, multicentre RCT will be conducted across four nations (Nepal, Mozambique, Tanzania, and China). Primary healthcare providers (PHPs) will be 1:1 randomly assigned to either the optimized AnF intervention group or a no intervention control group based on randomly permuted blocks (sizes 2, 4, and 6), stratified by country. Care quality will be assessed using the gold standard method of Unannounced Standardized Patients (USPs). The primary outcome is the proportion of completed guideline-recommended quality checklist items for the consultation of hypertension and Type II diabetes cases among all items. This outcome will be expressed as a continuous score ranging from 0% to 100%. Furthermore, a mixed-methods research strategy will be employed to extract Context-Mechanism-Outcome (CMO) elements and construct a Causal Pathway Diagram (CPD). This study will provide a robust empirical foundation for using an optimized AnF strategy to improve the quality of primary healthcare in developing countries. By deconstructing "why, for whom, and under what circumstances" the intervention works through the CMO framework and CPD, this study will provide vital mechanistic evidence for the future scale-up of this model, contributing a comprehensive and universal research paradigm to the field of implementation science.
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A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Quality of care indicators: The proportion of completed guideline-recommended quality checklist items for physical and laboratory exams of hypertension and type II diabetes cases of the PHC providers among all of the items
Timeframe: Through study completion, an average of 1 year