MeetaliKakad
Meetali Kakad
2015-2016 Harkness Fellow
Director (CMIO) of EHealth
Department for Technology and EHealth View Fellows
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Placement: Brigham and Women’s Hospital

Mentor: David Bates, M.D., M.Sc. (Brigham and Women’s Hospital and Harvard School of Public Health)

Project: Using Big Data to Transform Healthcare Outcomes: Lessons from the Field

Meetali Kakad, M.B.Ch.B., M.P.H., M.F.P.H., is a 2015–16 Norwegian Harkness/Research Council of Norway Fellow in Health Care Policy and Practice. She is a public health physician and director of EHealth in the Department for Technology and EHealth at South-Eastern Norway Regional Health Authority. Kakad has worked at all levels of health policy, from the global down to the regional. She has worked at the United Nations World Health Organization, the National Health Service in the U.K., and in the hospital sector in Norway. She was also the youngest member of the third Norwegian Commission on Priority-Setting, convened by the Minister of Health in order to review criteria and mechanisms for prioritization within the Norwegian health system. Kakad received a bachelor’s of medicine from the University of Birmingham and a master’s of public health from the University of Cambridge.

Project Abstract

The term “big-data” has gained considerable attention over recent years, referring to large amounts of different types of data that are continually being generated and flowing into an organization at high speeds. Predictive analytics refers to the act of identifying trends and patterns from big data and using these to predict outcomes. In healthcare, predictive analytics can be used to identify individuals or populations at higher risk of an adverse event or those more likely to benefit from a particular intervention. This allows patients and health care professionals to act earlier and more appropriately, resulting in high value care and better health. Most health care organizations are still a long way from using these approaches systematically and at scale. Kakad’s project will compare learnings across organizations that have utilized predictive analytics to improve health outcomes and quality of care. As the study will focus on factors related to successful introduction and implementation of these approaches, qualitative research methods such as structured interviews and case studies will be used. Specifically, Kakad will identify ‘use cases' for predictive analytics and their expected benefits, key characteristics of organizations that have successfully implemented predictive analytics, pinpoint critical factors and potential pitfalls for successful implementation and uptake, and finally, conclude how the policy environment influences use of big data and uptake of predictive analytics in health care. The study findings will inform healthcare organizations in the U.S. in how to better build a business case for up-scaling the use of predictive analytics and in devising plans for successful implementation. Simultaneously, the research will influence Norwegian policy, as decision makers are currently devising a roadmap for a common, nationwide electronic medical record with analytic capabilities.

Career Activity since Fellowship:

Current Position: Ph.D. Candidate, Akershus University Hospital (updated 04/2017)

Email: meetalikakad@gmail.com

Harkness Related Publications:

M. Kakad, R. Rozenblum, DW Bates. “Ten steps to precision delivery – a user’s guide to successful implementation of predictive analytics,” Harvard Business Review. 2017.

R.B. Parikh, M. Kakad, D.W. Bates. “Integrating Predictive Analytics into High Value Care,” JAMA Viewpoint. 2016.

 

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