When we think of healthcare, we often think of hospitals, nurses and doctors. But knowledge is an undeniably powerful tool in the medical field. And the more knowledge — the more data — that healthcare entities, research organizations and academic institutions can share, the more effective medical professionals can be in caring for patients.
The latest example of this vital synergy between medicine and research is our COVID-19 data consortium known as CHARGE (Consortium of HCA Healthcare and Academia for Research Generation). Launched just this year, the partnership of public and private research institutions is designed to use HCA Healthcare’s vast amount of data on COVID-19 hospital care not only to improve patient outcomes, but also to increase public knowledge.
“We believe [CHARGE] has the potential to both rapidly produce new evidence to improve the safety and quality of care for people with COVID-19 and serve as a model for the development of a national learning health system,” says Dr. David Meyers, acting director of the federal Agency for Healthcare Research and Quality (AHRQ). The CHARGE institutions — including AHRQ, HCA Healthcare’s own Sarah Cannon Research Institute, Columbia University, Johns Hopkins University, Duke University and Harvard Pilgrim Health Care Institute — will have access to the COVID-19 data in a research program directed by the HCA Healthcare Research Institute.
“Access to [our] vast data repository will greatly accelerate the pace of discovery of new knowledge,” says Dr. Shoshana Herzig, director of Hospital Medicine Research, Beth Israel Deaconess Medical Center in Boston. “To put it succinctly: This initiative will help save lives.”
“Patient care needs to be focused on data when available, and the data needs to be made easily available to practitioners for their use,” says Dr. Russell E. Poland, Ph.D., Clinical Operations Group, and assistant vice president of HCA Healthcare’s Extramural Research and Collaborative Partnerships. “Unfortunately, many decisions are not based on data but on ‘feelings’ — or even worse, bad data.”