Organisation of primary health care in the Asia-Pacific region: developing a prioritised research agenda. (16th August 2019) - Palagyi, Anna; Dodd, Rebecca; Jan, Stephen; Nambiar, Devaki; Joshi, Rohina; Tian, Maoyi; Abimbola, Seye; Peiris, David
Abstract : Health system planners in low- and middle-income countries (LMIC) of the Asia-Pacific region seeking to reorient primary health care (PHC) systems to achieve universal health coverage may be hindered by lack of knowledge of what works in their setting. With limited resources for research available, it is important to identify evidence-based strategies for reorganising PHC delivery, determine where relevant evidence gaps exist and prioritise these for future study. This paper describes an approach for doing this using the best available evidence combined with consultation to establish evidence priorities. We first reviewed PHC organisational interventions in Asia-Pacific LMICs and ascertained evidence gaps. The largest gaps related to interventions to promote access to essential medicines, patient management tools, effective health promotion strategies and service planning and accountability. Evidence from Pacific Island countries was particularly scant. We then engaged an expert panel of 22 PHC stakeholders from seven Asia-Pacific LMICs in a Delphi exercise to identify priority questions for future research. Research priorities were: (1) identifying effective PHC service delivery models for chronic diseases; (2) devising sustainable models of disease integration; (3) optimising task shifting; (4) understanding barriers to care continuity; (5) projecting future PHC needs; and (6) designing appropriate PHC service packages. Notably, stakeholder-determined priorities reflected large, context-dependent system issues, while evidence gaps centred on discrete interventions. Future research on the organisation of PHC services in Asia-Pacific LMICs should incorporate codesign principles to engage researchers and national PHC system stakeholders, and innovative methods that build on existing evidence and account for system complexity.