Paving the Way in Data Sharing
Sanford Health is committed to improving the health of our population and exploring new and innovative methods to support this commitment.
The Sanford Data Collaborative drives this commitment forward.
Paving the way in data sharing, we are a first-of-its-kind collaborative data center offering regional researchers the opportunity to access real-life, timely health care data.
Learn more about the Sanford Data Collaborative through recent publications and research:
- Griese, E.R., Hsu, B.S., and Pearce, D.A. (2017, August). Data Sharing: Leading Data-Driven Population Health. South Dakota Medicine, 374-375
- Cohen, J.K. (2017, April 26). Why Sanford Health is sharing patient data with its academic neighbors. Becker’s Health IT & CIO Review
- Hsu, B., Nowak, D., and Smith, J. (2017, June 29) Reframing Analytics: Transforming Insights into Action. NEJM catalyst
About the Data
Sanford is committed to the protection of our patients’ data. Datasets will be limited in nature. Researchers and their associated academic institutions will be required to sign a Data Usage Agreement ensuring the highest level of protection surrounding released data.
The data comes from Sanford Health, one of the largest health care systems in the nation. Headquartered in the Dakotas, the system has received nearly $1 billion in gifts from philanthropist Denny Sanford. These gifts have allowed for several groundbreaking initiatives, including global children's clinics, genomic medicine and specialized centers researching cures for type 1 diabetes, breast cancer and other diseases.
Proposals should consider each of the following priorities within project applications:
- Population health perspective: Projects should look to address clinical behaviors or outcomes from a population health perspective. For instance, identifying potential proxies within clinical and claims data that can incorporate social determinants of health within their analytic plan. Use of de-identified external data to augment the provided data set is encouraged.
- Predictive and prescriptive: Ultimately, the goal of the project should not be to simply provide novel insights but to move findings within the health care system past predictive ability and into prescriptive actions.
- Multidisciplinary approach: Innovation stemming from multiple disciplines, able to bring a truly multidisciplinary approach and impact, will be prioritized in the review process.
- Impact: All projects should identify an actionable impact. Possible impacts include actionable prescriptive algorithms and targeted population segmentations for quality improvement projects.
For more information, watch our webinar on the proposal process.
Past Projects & Publications
Wharton School of Business, University of Pennsylvania
Principle investigator: Guy David, PhD
Project examines provider turnover - identifying individual, system, and patient-level characteristics driving risk for turnover. Application: Prescriptive algorithm able to flag providers at risk for turnover, highlight key drivers to inform targeted intervention.
University of North Dakota, School of Medicine – Population Health
Principal investigator: Yvonne Jonk, PhD
Project aims to predict patient populations at risk for frequent, inappropriate utilization. Application: Prescriptive algorithm able to flag patient populations at risk or rising risk for inappropriate utilization, identify modifiable drivers for intervention/prevention opportunities.
South Dakota State University, Math and Statistics Department
Principle investigator: Semhar Michael, PhD
Project examines patient experience comments (free text portion of Press Ganey surveys) to identify associations between patient experience, provider, and clinic quality outcomes. Application: Leverage natural language processing to identify patients with similar experiences/sentiments, identify associations between patient experience and health outcomes/clinic quality indicators. Models will be able to inform targeted patient experience efforts.
University of South Dakota
Principal investigator: Carole South-Winter, EdD
The team developed a readmission risk algorithm for patients following heart surgery that determines who is at risk and provides insights for care. Previous risk scores did not suggest possible interventions.
Dakota State University
Principal investigator: Yong Wang, PhD
Researchers looked for patterns in how rural and urban patients use various service platforms, including electronic medical records, to search for ways to decrease emergent and urgent care needs.
University of North Dakota, Population Health
Principal investigator: Arielle Selya, PhD
The team developed an algorithm to predict unplanned medical visits for diabetics, taking into account their current disease management behaviors, such as smoking, and other information, and then providing pathways to care.
South Dakota State University
Principal investigator: Surachat Ngorsuraches, PhD
The team developed a patient engagement score using existing patient data. Patient engagement factors into effective management of chronic conditions, but surveys and other tracking methods are time-consuming. This score can help identify and decrease emergency department visits and hospitalizations.
University of North Dakota, School of Medicine
Principal investigator: Jeff Hostetter, MD
The team examined how primary care services can affect patients’ use of preventive behaviors and looked to see how that differs with a team-based approach.
Principal investigator: Susan Hoover, MD, PhD
The Population Health Group created an algorithm based on current patient data to determine who needs screening for C. difficile. The goal was to decrease unnecessary testing and to develop a platform to be used to decide on ordering the test.
Meet Our Team
Emily Griese, PhD
Director of Collaborative Research, Health Services
Associate Scientist, Sanford Research
Dr. Emily Griese is a National Institutes of Health funded investigator with research focusing on longitudinal, person-centered modeling working to identify sources of resilience among at-risk youth. In leading the Sanford Data Collaborative, Dr. Griese brings expertise in data analytics and research methodology, working to examine health care data with the goal of ultimately improving the health outcomes of the populations we serve.
She received her PhD in psychological research in education from the University of Nebraska-Lincoln and completed her postdoctoral work in health disparities and population research at Sanford Research where she is currently an associate scientist. She is also an assistant professor in the Department of Pediatrics at the University of South Dakota Sanford School of Medicine.
David Pearce, PhD
Executive Vice President, Sanford Research
Dr. David Pearce serves as executive vice president of Sanford Research and is a senior scientist with the Sanford Children’s Health Research Center. He is also a professor for the Department of Pediatrics with the University of South Dakota Sanford School of Medicine. He is one of the world’s leading researchers of Batten disease and also established the Coordination of Rare Diseases at Sanford (CoRDS) program.
Benson S. Hsu, MD, MBA, FAAP
Vice President, Enterprise Data and Analytics
Dr. Benson Hsu is responsible for creating and executing transformative strategies for Sanford Health’s data and analytics initiatives. Dr. Hsu obtained his AB degree in economics from Princeton University, his MD from the University of Missouri School of Medicine and his post-graduate training in pediatric critical care at the University of Wisconsin Madison. Dr. Hsu received an MBA from Duke University Fuqua School of Business, graduating with distinction as a Fuqua Scholar. Dr. Hsu continues to practice as a pediatric critical care physician and is an associate professor in pediatrics at the University of South Dakota Sanford School of Medicine with a dual appointment as a secondary assistant scientist at Sanford Research.
Research Project Manager
Cheryl Stansbury is the research project manager for the Sanford Data Collaborative and collaborative projects within the Griese Lab. An employee of Sanford Health since 2012, she has a background in team, program and data management. She received her master of science in healthcare administration from the University of South Dakota.
Kurt Cogswell, PhD
Department Head and Professor of Mathematics and Statistics, South Dakota State University
Mary Nettleman, MD, MS, MACP
Dean, Sanford School of Medicine, University of South Dakota
Michael Lawler, PhD
Dean and Professor, School of Health Sciences, University of South Dakota
Venky Venkatachalam, PhD
Dean, Beacom School of Business, University of South Dakota
Joshua Wynne, MD, MBA, MPH
Dean, School of Medicine and Health Sciences, University of North Dakota
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