Big Data and Population Health Management José A. Pagán, PhD SCOTT CONFERENCE CENTER | OMAHA, NEBRASKA INSTITUTE FOR URBAN HEALTH

-Health care payment and delivery systems continue to evolve rapidly as a result of the ACA. -(Big) data  Increasingly available and easier to use/analyze. -(Total) population health (management) is getting some traction. Trends The New York Academy of Medicine | Institute for Urban Health2

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Transition from Fee for Service to Value Based Care The New York Academy of Medicine | Institute for Urban Health4

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Example 9The New York Academy of Medicine | Institute for Urban Health

Population Health Management or Population Health? The New York Academy of Medicine | Institute for Urban Health10

“the iterative process of strategically and proactively managing clinical and financial opportunities to improve health outcomes and patient engagement, while also reducing costs” Symphonycare website example from David Kindig. What Are We Talking About When We Talk About Population Health? Health Affairs Blog. April 6, Population Health Management Definition The New York Academy of Medicine | Institute for Urban Health11

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“the health outcomes of a group of individuals, including the distribution of such outcomes within the group” David Kindig and Greg Stoddart. What Is Population Health? American Journal of Public Health March 2003: Vol. 93, No. 3, pp Population Health Definition The New York Academy of Medicine | Institute for Urban Health13

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-Pre-ACA discussion was mostly about covering the uninsured. -(Almost) everything now is about one leg of the Triple Aim stool – reduce costs. -Population health = f(Health care=g(Primary care, Inpatient, ED,…), Social services, Social/environmental determinants). -Health care expenditures = P1*S1+P2*S2… -Cannot change prices easily so focus on distribution of services (S1, S2…) to achieve targeted cost reductions. Building the evidence for social determinants within a health care delivery context The New York Academy of Medicine | Institute for Urban Health15

What do you see? The New York Academy of Medicine | Institute for Urban Health16

-Increase their visibility of factors that impact population health (i.e., where people live, work, play and learn). -Gain full visibility of health care utilization and costs (e.g., by building strategic partnerships, collaborating, buying out others). -Fully understand geography (local markets) and payment structures to efficiently manage population health. Health care delivery systems are trying to… The New York Academy of Medicine | Institute for Urban Health17

-Focus on cost given a minimum level of quality or population health improvement. -Cost is important but this is not always the case (e.g., some indicators may be more important than others based on individual and organizational goals). -Timeframe window matters (e.g., 1-3 years for health care delivery systems; longer timeframe for highly integrated systems or public health). -Want to get something implemented/adapted? Trial/error, rapid-cycle learning, etc. Evidence thresholds The New York Academy of Medicine | Institute for Urban Health18

Data to Improve Population Health versus Data to Make the Business Case for a Program The New York Academy of Medicine | Institute for Urban Health19

The New York Academy of Medicine | Institute for Urban Health Expected vs. Unexpected Sources of Data 20 Prevailing models of care—or of what impacts health—color where we look for data and how we analyze data Expected sources include income, hospitalizations, obesity rates, air/water quality Unexpected sources include bus routes, social media posts, malpractice suit patterns Focus on the unexpected is likely to lead to new insights and a better understanding of the root causes of a problem

The New York Academy of Medicine | Institute for Urban Health21 Source: The Value of Prevention. Bipartisan Policy Center.

The New York Academy of Medicine | Institute for Urban Health How do we find answers to questions with so much information out there? Partner with experts that may have the data and/or experience analyzing data at your local university or policy organization Potential partners: Community service centers at universities, USDA centers, departments of geography/demography, census/state data centers, National Center for Health Statistics, ResDAC (Medicare/Medicaid data assistance) Partner input may include: sharing analyses, conducting analyses jointly, getting you started on some analyses, pointing you to the right expert 22

The New York Academy of Medicine | Institute for Urban Health23 Example 1: County Health Rankings & Roadmaps

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The New York Academy of Medicine | Institute for Urban Health25 Example 2: DATA2GO.NYC

The New York Academy of Medicine | Institute for Urban Health26 Housing Burden and Fruit/Vegetable Consumption

27 Collaborative Data Projects – Center for Health Innovation The New York Academy of Medicine | Institute for Urban Health

Case 1: Data/PH Medicaid 1115 Waiver and Diabetes Collaborative The New York Academy of Medicine | Institute for Urban Health28

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San Antonio – DSRIP / Diabetes Collaborative The New York Academy of Medicine | Institute for Urban Health30 Adult Population Size1,339,580 Female48.6% Smoking19.3% Had < 150 min/wk of moderate physical activity 64.8% Ate < 5 fruits or vegetables per day76.3% Overweight or obese71.9% Hypertension26.9% High cholesterol29.1% Type 2 diabetes11.6% History of myocardial infarction3.7% History of stroke1.6%

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The New York Academy of Medicine | Institute for Urban Health32 End-Stage Renal Disease Lower Extremity Amputation Proliferative Retinopathy Myocardial Infarction Stroke Total Cost Savings Averted Incidence1,9424,30411,54815,6166,981 Annual Costs (per person) $28,874$16,010$9,003$7,569$8,929 Annual Cost Savings $56,076,644$68,909,409$103,964,070$118,194,921$62,334,403$409,479,447

Case 2: Data/PHM Payment and Delivery System Redesign The New York Academy of Medicine | Institute for Urban Health33

-Childbirth number one reason for hospital admission. -Postpartum care offers opportunity to impact current and future health of vulnerable women. -Low income women have higher: -Maternal mortality/morbidities -Pregnancy complications -Postpartum readmission -Chronic illnesses (e.g., hypertension, diabetes). Redesign payment and delivery systems to address disparities The New York Academy of Medicine | Institute for Urban Health34

-PI: Liz Howell, MD -Preventive medicine, obstetrics/gynecology, public health, social work, patient navigation, systems analysis, health economics, health insurance Project team The New York Academy of Medicine | Institute for Urban Health35

-Postpartum visits -Commercially insured = 80-90% -Healthfirst = 58% -Healthfirst patients with diabetes = 50% -Intervention designed to increase postpartum visit rate. -Delivered by social worker and community health worker. -In-hospital education and post-discharge calls to support self-management, increase access to community resources, reduce barriers to follow-up care. Postpartum visits and intervention The New York Academy of Medicine | Institute for Urban Health36

-Postpartum women, age≥18, insured by Healthfirst, high risk (hypertension, gestational diabetes, late registrants for prenatal care, depressive symptoms). -Enroll 510 women during postpartum hospitalization. -Primary outcome: Timely postpartum visit. -Other outcomes: DM screening, maternal ED visits and hospitalizations, costs, depressive symptoms. -Assessments: baseline, 3 weeks, and 6 months postpartum. Target population and measures The New York Academy of Medicine | Institute for Urban Health37

-Utilization and costs (Mount Sinai, Healthfirst) -Disparities (RWJF) -Meet Healthcare Effectiveness Data and Information Set (HEDIS) criteria (“A member is considered compliant if she receives a postpartum care visit on or between 21 and 56 days (3-8 weeks) after delivery”) (Mount Sinai, Healthfirst) -Impacts health insurance plan ratings, accreditation (NCQA: National Committee for Quality Assurance) Business case angles The New York Academy of Medicine | Institute for Urban Health38

The New York Academy of Medicine | Institute for Urban Health Takeaway Points Data can be effectively used to manage populations as well as to make the business case for programs Many sources of data means that there are multiple ways to analyze data to improve population health Combine several data sources to get interesting insights that can help you manage populations Find collaborators that know how to slice and dice data 39 Thanks!