The Gordon and Betty Moore Foundation is setting its crosshairs on improving diagnostics as it looks to sharpen accountability and reduce medical errors.
The Foundation focuses on a number of areas, including those outside of healthcare, such as environmental conservation, in the San Francisco Bay Area. It was founded back in 2000 and has an annual budget of around $300 million.
The $85 million earmarked over the next six years for its latest healthcare investment is focused on diagnostics—or, more specifically, lowering errors and delays that are inherent in the system.
Quoting figures from the National Academy of Medicine’s report, Improving Diagnosis in Health Care, the Foundation says that diagnostic errors “are the most common cause of medical errors reported by patients,” accounting for nearly 60% of all errors and an estimated 40,000-80,000 deaths per year.
The Foundation wants to help tackle this through its funding commitment as well as its longstanding Diagnostic Excellence Initiative.
“The initiative aims to reduce harm from erroneous or delayed diagnoses, reduce costs and redundancy in the diagnostic process, improve health outcomes and save lives,” it said in a statement.
First up will be “strengthening accountability for diagnostic excellence,” which essentially means creating new measures for diagnostic performance, which it wants to focus on real-time data.
Currently, the healthcare system is not geared for this, the Foundation argues, which “limits the ability to quantify performance and guide improvements. As the adage goes, ‘you can’t improve what you can’t measure.’”
There will also be a focus on three clinical areas, namely those it sees as the biggest causes of death as a result of diagnosis errors/delays, which are: cardiovascular events, infections and cancers.
“We believe this investment in diagnostic excellence is timely,” said Daniel Yang, M.D., program fellow of the Moore Foundation’s Patient Care Program. “A burgeoning community has attracted new interest in the field; new technologies and artificial intelligence are poised to improve and transform the diagnostic process in important ways; and continuing concern around health care costs are encouraging health care systems to intensify their focus on value and efficiency in both treatment and diagnosis.”