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COVER STORY · DATA ANALYTICS


Analytics for Population Health and Clinical Transformation: Moving


Forward on the Journey of 1,000 Miles The data analytics pioneers aren’t stopping for a moment— they’re moving forward on all cylinders, and providing templates for everyone to follow By Mark Hagland


hat seemed incredibly messy and poorly defi ned even fi ve years ago, is gradually now coming into focus, and that is the question of where the entire “journey of 1,000 miles” around leveraging data and analytics for popula- tion health management and clinical trans- formation, is headed. What’s clear now, as the leaders of pioneering patient care organizations plow ahead on that road, is that things are moving towards both big-picture coordination of masses of data to improve the health status of entire com- munities, and at the same time, towards smaller-picture pinpointing of gaps in care delivery and effectiveness, across entire integrated health systems. Among the larger integrated health sys- tems, certainly, the senior leaders at UC San Diego Health in San Diego are steaming full-speed ahead. And helping to lead the


W


charge there is Amy Sitapati, M.D., a prac- ticing internal medicine physician and the chief medical information offi cer for popu- lation health for the organization (in fact, UCSD Health has three CMIOs—one for population health, one for inpatient care, and one for outpatient care). Dr. Sitipati, who looks at the overall U.S. healthcare sys- tem and says, “We’re still in kindergarten in terms of U.S. health- care system-wide efforts,” also says that “We’re mid-fi eld now in terms of the


Amy Sitapati, M.D.


way an individual health system thinks about this.” In fact, she reports that, at UCSD Health, “We’re using complex risk stratifi cation


4 hcinnovationgroup.com | NOVEMBER/DECEMBER 2021


to match each patient to our Healthy Places Index, based on zip code, to better under- stand the community base a patient might come from, and how that might


inform our work. We’re focused on equity, so when we run a report on hypertension for hypertension control, since 97 percent of our patients have com- pleted racial information, we can identify Black patients, for example, and can iden- tify who the patients are, in terms of the Healthy Patients Index. And if patients are interested and it’s applicable, we can reach out to individuals who are facing structural barriers. So now we can say to them, we have this program to offer healthy food


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