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January 11, 2023
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From the November 2022 issue of HealthCare Business News magazine
UPMC partners with Microsoft, using clinical analytics to improve care
The University of Pittsburgh Medical Center said in July that it integrated Microsoft’s cloud computing, AI and machine-learning tools into its clinical analytics operations to adjust care protocols and foster better health outcomes.
Outlined in a five-year agreement, UPMC will use these solutions to mine more than 13 petabytes of structured clinical data and 18 petabytes of imaging data to develop care insights.
Using clinical data to adjust COVID-19 treatments, the hospital reduced in-hospital mortality during the pandemic and is now applying the same concept to other areas, including diabetes mellitus and post-surgical adverse outcomes.
“We’re on a quest to become a true data-driven organization, a ‘learning health system’. We can do this only if analytics are embedded in everything that we do — from the executive suite to our clinicians at the bedside,” said Dr. Oscar Marroquin, chief healthcare data and analytics officer, in a statement.
During the pandemic, UPMC used clinical and financial data to reduce in-hospital mortality month-to-month. It has replicated these efforts with diabetes mellitus, which is associated with a higher risk for other conditions and adverse outcomes, especially in those with poor control of their disease.
Using historical data from more than 170,000 diabetic patients, the analytics team built a machine-learning model to predict those at highest risk before they reach that point, enabling endocrinologists to offer these patients diabetes educators.
UPMC partners with Microsoft, using clinical analytics to improve care
The University of Pittsburgh Medical Center said in July that it integrated Microsoft’s cloud computing, AI and machine-learning tools into its clinical analytics operations to adjust care protocols and foster better health outcomes.
Outlined in a five-year agreement, UPMC will use these solutions to mine more than 13 petabytes of structured clinical data and 18 petabytes of imaging data to develop care insights.
Using clinical data to adjust COVID-19 treatments, the hospital reduced in-hospital mortality during the pandemic and is now applying the same concept to other areas, including diabetes mellitus and post-surgical adverse outcomes.
“We’re on a quest to become a true data-driven organization, a ‘learning health system’. We can do this only if analytics are embedded in everything that we do — from the executive suite to our clinicians at the bedside,” said Dr. Oscar Marroquin, chief healthcare data and analytics officer, in a statement.
During the pandemic, UPMC used clinical and financial data to reduce in-hospital mortality month-to-month. It has replicated these efforts with diabetes mellitus, which is associated with a higher risk for other conditions and adverse outcomes, especially in those with poor control of their disease.
Using historical data from more than 170,000 diabetic patients, the analytics team built a machine-learning model to predict those at highest risk before they reach that point, enabling endocrinologists to offer these patients diabetes educators.
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