Purchasing is an essential function of any health financing system. One of the challenges is to make it more strategic in order to enhance efficiency, equity and quality in health services access as well as financial protection.
The acceleration of digitization in health financing, including the digitization of the purchaser/provider interaction, is leading to new and growing data sources available to purchasers. If well managed, these data sources can help to appreciate health needs, develop a better knowledge of providers performance, select providers, design the most efficient contracts and inform the learning cycle. One application of these new sources of data is the automation of verification, fraud detection and quality assurance and thus fight Fraud, Waste and Abuse (FWA) in health care. Recent developments in cloud-based analytical and data sciences tools and their uptake in low-and-middle income countries (LMICs) create new opportunities for a usage of “big data” sources by purchasing agencies in Africa.
The PBF and the FAHS communities of practice are launching a global learning agenda on algorithmic verification, fraud detection and quality assurance in purchasing in LMICs.
The objectives of our program of work are:
As a member of the working group, you will be expected to support the facilitation team in developing a global learning agenda on “Improving purchasing for Universal Health Coverage through algorithmic verification, fraud detection and quality of care monitoring”.
Among other tasks, you will have to:
All Collectivity experts can apply to this project. We are particularly interested in people with advanced experience in designing health financing policies, expertise in verification systems in PBF programs or with experience in health insurance information systems. Fluency in English is required for attending the international meeting.