This year marks the 20th anniversary of the Africa Energy Forum (AEF), which gathers together representatives from national energy utilities, government regulators, power project developers, engineering contractors and design firms, equity investors, commercial and development banks, law firms, multilateral donors, and technology providers to discuss the present and future of providing power to Africa’s emerging economies. It’s been a great opportunity to reflect on how much has changed in 20 years. But it’s an equally great opportunity to reflect on the challenges that remain.
There is widespread belief in the health policy community that alternative payment models (APMs) can help the U.S. achieve the goals of lower health care costs and higher quality care. By tying payments to quality and performance, rather than to volume of services, and by requiring coordination and communication between providers, APMs incentivize efficient resource use and improve health outcomes.
The media have been abuzz lately with coverage on fake news and the misuse of data by popular social networking sites. This issue about using social media data for questionable purposes has raised users’ concerns over data privacy and has made researchers wary of using these data as a reliable information source.
Researchers are rightfully cautious. Social media continues to evolve and generates vast quantities of data. Navigating these changes and wading through so much information have made conducting rigorous research around social media data difficult.
This post was originally published on the Global Health Council blog.
Rising costs are plaguing health care systems around the world, and payers are exploring payment reforms to reduce those costs. Private and public payers alike are experimenting with ways to link payments to the quality and value of care provided, rather than the volume of services. By paying per unit of care provided without accounting for quality of care, the traditional fee-for-service (FFS) payment system incentivizes volume of services, which may contribute to high healthcare costs.
One in five individuals who try heroin will develop an addiction to opioids. Why are some individuals more susceptible to opioid addiction than others? And why do some individuals respond differently than others to treatment?