Improving Hospital Performance Using AI and Patient Data
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Hospitals and health systems continue to face challenges in rapidly identifying and standardizing care of patients at risk for adverse events.
These events include sepsis as well as those related to medication use, health care-associated infections like Clostridium difficile and other causes of patient deterioration such as respiratory insufficiency and acute myocardial infarction. The opportunity for improvement in these areas is significant, as data have shown.
- On average, the Centers for Disease Control and Prevention reports, one in 31 patients has at least one health care-associated infection.
- 1 in five hospital deaths in the U.S. are caused by sepsis according to a January 2020 report in The Lancet.
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Key Take Aways
Here is what our experts had to say:
With a condition like sepsis, every hour of delay in diagnosis increases mortality by 8%.
Advanced technologies provide real-time, integrated data for clinicians to better monitor patients' conditions.
AI and natural language processing have the ability to marry free text data with structured patient data.
Successful implementation of AI means that it is credible, explainable and reliable.
Speakers
Jonathan B. Perlin, M.D., Ph.D., MSHA, MACP, FACMI
President, Clinical Operations & Chief Medical Officer
HCA Healthcare
Itay Klaz, M.D., MCHI
Medical Director
Wolters Kluwer
Marie Cleary-Fishman, BSN, MS, MBA, CPHQ
Vice President, Clinical Quality, AHA Center for Health Innovation
黑料正能量 Association
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Abstract Overview
Read this abstract to learn about how current demands are impacting the health care workforce.
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