11/27/2015. The Importance of Data Analytics in the Creation of a PopHealth Strategy. Conflict of Interest. Social Media Activity

Transcription

1 The Importance of Data Analytics in the Creation of a PopHealth Strategy Jonathan Ware, MD Chief Population Health Officer, Future State Healthcare Medical Director, Population Health Management, IBM Watson Health DISCLAIMER: The views and opinions expressed in this presentation are those of the author and do not necessarily represent official policy or position of HIMSS. Conflict of Interest Jonathan Ware, MD Has no real or apparent conflicts of interest to report. Social Media Activity Jonathan Ware, MD has given permission for the audience to use social media during the presentation Twitter: LinkedIn: linkedin.com/in/jonathanwaremd Facebook: facebook.com/jonathanwaremd Instagram: Instagram.com/jonathanwaremd 1

2 Learning Objectives 1. Define population health and corresponding technologies, processes and tools used to measure and manage patient data. 2. Identify target patient populations which should be monitored and how to identify trends in outcomes. 3. Describe how clinicians can utilize population health data to improve the overall health and quality of care in the communities they serve. Defining Population Health Definition of Population Health The health outcomes of a group of individuals including the distribution of such outcomes within the group 1 - NCQA, The Future of Patient-centered Medical Homes 1 2

3 Definition of (PHM) Population Health Management Holistic approach to healthcare that aims to improve the health status of an entire community Managing all aspects of health from wellness to complex care across the care continuum Right Care at the Right Time by the Right Person in the Right Setting Public Health is a part of Population Health What Does the Population Include? Provider-led PHM An explicit recognition of the powerful cultural change we must implement in order for clinicians to lead a population health revolution 2 - David B. Nash, MD, MBA Founding Dean Jefferson School of Population Health 3

4 Defining Data Definition of Data Pieces of information, such as those collected during a study 3 In medicine and the health sciences, people often speak of "the data" erroneously in the singular. "Data" is a plural noun and takes a plural verb, as in "the data are very convincing." It comes from the Latin "datum", meaning "a thing given. 4 Types of Data Claims data Clinical data Patient-reported data Big data Little data Structured Unstructrured 4

5 Big Data Big Data is what organizations know about people be they customers, citizens, employees, or voters. Data is aggregated from a large number of sources, assembled into a massive data store, and analyzed for patterns. The results are more accurate predictions, more targeted communications, and more personalized services. 5 Extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. 6 Little Data Little Data is what we know about ourselves. What we buy. Who we know. Where we go. How we spend our time. We ve always had a sense for these things after all, it s our lives. But thanks to the combination of mobile, social, and cloud technologies, it s easier than ever to gain insight into our own behavior. 7 Defining Analytics 5

6 Definition of Analytics Analytics is the systematic use of data and related business insights developed through applied analytical disciplines (e.g. statistical, contextual, quantitative, predictive, cognitive, other [including emerging] models) to drive fact-based decision making for planning, management, measurement and learning. 8 - IBM Smarter Planet The Value of Analytics in Healthcare Types of Analytics Descriptive Predictive Prescriptive Descriptive Analytics Descriptive analytics answers the questions what happened and why did it happen. Descriptive analytics looks at past performance and understands that performance by mining historical data to look for the reasons behind past success or failure. 11 6

7 Predictive Analytics Predictive analytics answers the question what will happen. This is when historical performance data is combined with rules, algorithms, and occasionally external data to determine the probable future outcome of an event or the likelihood of a situation occurring. 11 Prescriptive Analytics Goes beyond predicting future outcomes by also suggesting actions to benefit from the predictions and showing the implications of each decision option. Not only anticipates what will happen and when it will happen, but also why it will happen, suggests decision options on how to take advantage of a future opportunity or mitigate a future risk and shows the implication of each decision option. Can continually take in new data to re-predict and re-prescribe, thus automatically improving prediction accuracy and prescribing better decision options. Ingests hybrid data, a combination of structured and unstructured data (videos, images, sounds, texts), and business rules to predict what lies ahead and to prescribe how to take advantage of this predicted future without compromising other priorities. 11 Prescriptive Analytics Source: 12 Modaniel 7

8 Top Performing Pros in Healthcare Share Multiple Characteristics in Their Approach to Analytics Source, IBM Institute for Business Value, Analytics: The new path to value Population Health Strategy Building A Successful PHM Strategy Enables Service Efficiencies Evidence-based Outcomes Patient Safety Positive Impact on Patients Cost Savings 8

9 Pillars of PHM Strengthen and expand the doctor-patient relationship through the care team Reach out beyond the four walls of the office Optimize patient visits Key Components to PHM Strategy Organized system of care Care teams Coordination across care settings Access to primary care Centralized resource planning Continuous care Patient self-management education Focus on health behavior/lifestyle changes Interoperable electronic health records Electronic registries Barriers to PHM Fragmentation of care delivery Misaligned financial incentives Lack of managed-care knowledge Insufficient use of health information technology 9

10 Beginnings of Change Pay-for-performance and disease management have had little impact New models such as PCMH, PCSP, ACO, CIN are more promising Spread and increased use of EHR s opens new possibilities Crucial Role of Automation To have an impact on population health, health care organizations must manage their entire patient populations. To do that effectively, they need electronic automation tools in addition to pure EHR Measure and Manage Management thinker Peter Drucker is often quoted as saying that "you can't manage what you can't measure." Drucker means that you can't know whether or not you are successful unless success is defined and tracked. 9 The original quote "If you can not measure it, you can not improve it." comes from Lord Kelvin. GuavaBox December 5,

11 Measure and Manage? We think that the purpose of our jobs is to hit our marks. We never stop to ask What if a person had a brainstorm that made the marks irrelevant? 10 We talk about breakthrough solutions but we don t believe they really exist. If we did, we d see that our fixation on small measurements is the greatest barrier we could erect to breakthrough solutions, not to mention innovation and collaboration, the other things we say we value but we don t. 10 Forbes August 9, 2015 PHM Technologies Electronic medical records (EHR) EHR registries Spreadsheets & Scorecards Population health software Remote monitoring Telemedicine mhealth PHM Processes Workflow automation Risk stratification Provider adjustment Readmission prevention Financial risk calculations Predictive modeling Turning predictions into actions 11

12 PHM Tools - Automation The Population Health Alliance defines PHM as an approach to care delivery that includes these components: The central care delivery and leadership roles of the primary care physician An emphasis on patient activation, involvement and personal responsibility The patient focus and capacity expansion of care coordination provided through wellness, disease and chronic care management programs PHM Tools - Automation All patients to be managed Not all patients visit their providers Outreach is needed Education for patients is needed Need to stratify Manage highest risk Clinical decision support At visit, which need preventive or chronic care Too expensive to do manual data entry Not at top of license PHM Tools Understanding The Numbers Which systems are you using to gather your data? Do you use clinical, claims or patient-reported data? Combination? Do you have a single source of truth for each data point? Is there standardization as to where that data point is documented? Can you find your data? Can you mine your data? Is it as accurate as possible? Is it automated? Do you share the data with your providers? Care teams? Is the scorecard blinded? Open? 12

13 How Are These Providers Doing? Identifying & Stratifying Target Populations What We Did At Orlando Health 8 Hospitals Academic Medical Center Level 1Trauma Center, Cancer Hospital Pediatric Hospital, Women and Babies Hospital 4 Community Hospitals 3000 Physicians on Staff 600+ Employed Physicians 59 Primary Care Practices 2.1 Million Patient Population 4 ACO s 13

14 Identifying Target Populations Identifying Target Populations 14

15 Risk Stratify Populations Risk Stratify Individual Patients 15

16 Identifying Trends in Outcomes Identifying Trends in Outcomes Care Managing Populations 16

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18 Clinician Utilization of Data Clinician Utilization of Data 18

19 Using Data Analytics in Your PopHealth Strategy Using Analytics in Your PHM Strategy Understand what you want to go in to the system Understand what you want to come out of the system Create standardized documentation protocols Reduce variability in workflows Utilize claims, clinical and patient-reported data Measure only what you need to measure and allow for innovation Manage all patients by automation Present analytics specific to your audience Standardize analytics presentation Give providers and care teams 1-3 metrics at a time to improve on 19

20 Thank You! Questions Jonathan Ware, MD Chief Population Health Officer Future State Healthcare Twitter: LinkedIn: linkedin.com/in/jonathanwaremd Facebook: facebook.com/jonathanwaremd Instagram: Instagram.com/jonathanwaremd Medical Director, Population Health Management IBM Watson Health Sources 1. NCQA, The Future of Patient-centered Medical Homes, accessed on October 20, 2015 at ure_of_pcmh.pdf 2. Richard Hodach, Provider-led Population Health Management. Bloomington, IN: AuthorHouse, Data, The Free Dictionary: Medical Dictionary accessed on October 20, 2015 at 4. Definition of Data, MedicineNet: MedTerms Dictionary accessed on October 20, 2015 at 5. Mark Bonchek, Little Data Makes Big Data More Powerful, Harvard Business Review, May 3, 2013 accessed on October 20, 2015 at 6. Big Data, Google accessed on October 20, 2015 at 7. Mark Bonchek, Little Data Makes Big Data More Powerful, Harvard Business Review, May 3, 2013 accessed on October 20, 2015 at 8. IBM, The value of analytics in healthcare: from insights to outcomes, accessed on October 20, 2015 at df 20

21 Sources 9. Gray MacKenzie, If you can t measure it, you can t improve it, GuavaBox blog accessed on October 20, 2015 at Liz Ryan, If you can t measure it, you can t manage it (False), Forbes August 9, 2015 accessed on October 20, 1970 at Business Analytics, Wikipedia accessed on October 20, 2015 at Modaniel, Own work. Licensed under CC BY-SA 4.0 via Commons. "Three Phases of Analytics, Wikipedia accessed on October 20, 2015 at hree_phases_of_analytics.png 13. IBM, The value of analytics in healthcare: from insights to outcomes, accessed on October 20, 2015 at df 21