The Crossroads of Health IT and Accountable Care

1. The Crossroads of Health IT and Accountable Care Presented by: Rich Temple, National Practice Director, Beacon Partners February 6, 2014

2. Agenda for Today • Quick Background on Beacon Partners • The Fast-Evolving Healthcare Landscape • Why Data Volumes are Exploding • The Impact of Accountable Care on Healthcare Organizations as a Whole and Healthcare IT Departments • Particular Challenges from Affordable Care • Population Health • Wrap-Up • Questions / Discussion

3. Beacon Partners • Consultancy founded in 1989 • Exclusive focus is healthcare • More than 300 consultants in all types of engagements all over the country and in Canada • Focus on strategic advisory to health systems of all sizes • Successfully completed more than 2,000 engagements with over 600 healthcare clients • HIMSS Platinum member / CHIME Foundation member

4. Timeline of Health IT Over the Decades

5. What Does the Future Hold? Genomics / personalized medicine Predictive Analytics Around Entire Populations Streaming Info from Home Devices Integration across providers, payors, and regulatory agencies Sharing of Huge Diagnostic Images Fitbits Cardiac Monitors Blood pressure Monitors, etc. Increasing need to capture and mine unstructured and semi-structured content

6. Regulatory Mandates Keep Coming ICD-10 CQM Clinical Process of Care PQRS Outcomes Clinical Documentation improvement, financial modeling, code mapping, etc. ACO 33 Efficiency Measures HCAHPS Readmits

7. We Knew Data Needs Were Going to Be Overwhelming… • Prevailing wisdom says that hospital’s data storage needs will double every 18 months • Another way of stating this is that data storage needs will increase tenfold over a five-year period! • There are research papers in circulation that state that this is a very conservative estimate – that the rate of increase could actually be many times higher! _____________________________________ • And this generally doesn’t take into account new repositories to cover data sources and targets such as: • Private HIEs with a centralized structure • Enterprise Data Warehouses (for BI/”big data”) • Data structures built to support the data capture and rendering requirements of Accountable Care Organizations (ACOs)

8. How to Store and Manage All This Data • Cloud Storage (private or public “clouds”) • In-house data storage • Data management strategies • Consider different storage strategies for different types of data • Recent, critical data needs to be captured with the lowest-possible latency • Large percentage of data captured is not directly accessed again – does not need to be in low-latency, easily accessed storage • Archive capabilities for infrequently-used data architected to minimize bandwidth requirements • Data likely to be required for detailed analytics set up separately and architected to be accessible via distributed computing tools such as Hadoop • De-duplication strategies • Redundancy strategies for disaster recovery / business continuity

9. Accountable Care and its “parent”, the “Affordable Care Act”, are huge drivers of these initiatives through wide-ranging data capture, data storage, and through detailed analysis of a myriad of clinical and financial data points

10. What is an ACO? • Accountable Care Organizations (ACOs) are groups of doctors, hospitals, and other health care providers, who come together voluntarily to give coordinated high quality care to their Medicare patients. • The goal of coordinated care is to ensure that patients, especially the chronically ill, get the right care at the right time, while avoiding unnecessary duplication of services and preventing medical errors. • When an ACO succeeds both in both delivering high-quality care and spending health care dollars more wisely, it will share in the savings it achieves for the Medicare program. Definition courtesy of CMS: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ACO/index.html?redirect=/ACO/

11. What Metrics Do ACOs Require? • For starters, all ACOs need to report on the “ACO 33” and demonstrate a high level of quality in the following areas: • Patient/ Caregiver Experience (7 measures) • Care Coordination/ Patient Safety (6 measures) • Preventive Health (8 measures) • At-Risk Populations (12 measures) • Diabetes (6 measures) • Hypertension (1 measure) • Ischemic Vascular Disease (2 measures) • Heart Failure (1 measure) • Coronary Artery Disease (2 measures)

12. What Metrics Do ACOs Require? Patient/Caregiver Experience

13. What Metrics Do ACOs Require? Care Coordination / Patient Safety

14. What Metrics Do ACOs Require? Preventive Health

15. What Metrics Do ACOs Require? At-Risk Populations

16. “groups of doctors, hospitals, and other health care providers, who come together voluntarily to give coordinated high quality care to their Medicare patients." Engine to feed data into in order to establish quality and financial metrics and compare against moving benchmarks Hospitals FQHCs Owned and affiliated physician practices Subacute / LTC facilities Other providers

17. “coordinated care is to ensure that patients, especially the chronically ill, get the right care at the right time” Normalize different system nomenclatures Capture quality indicators across disparate systems Establish compliance with plans of care Weed out excess data points Track cost of care Capture the right data from all sources across many different provider sites and systems • Identity management across disparate systems • EMPI • Aggregate allergy, condition, medication, and other clinical info HIE Patient Surveys Diff physician EHRs Claims Diff hosp EHRs Excel spread-sheets Financial systems PAPER Quality mgmt systems Case mgmt systems Home- devices

18. It’s Not Just Blindly Aggregating Data • Pulling data points from widely disparate systems is challenging enough but… • Profoundly different workflows exist for how data gets entered into these different systems • “Weight” could be entered in many different places even within the same EHR • Algorithms for computing basic metrics (e.g., Length of Stay) may vary across providers • Temperature: Fahrenheit versus Celsius • Essential to do a detailed workflow analysis and standardize across all members of the ACO exactly how data must be entered for proper reporting • Corollary to this is building “error reports” to show what providers are not complying and thus sending over incomplete or inaccurate key metrics

19. Sample ACO Quality Measure Narrative

20. One More ACO Quality Measure Narrative

21. How Do These Metrics Get Built? • There are commercial software packages (more and more every day) that purport to be able to provide these metrics but rigorous upfront preparation is necessary to avoid challenges • Different systems feed data into a repository in different ways • “HL7” is called a standard, but it is really more of a suggestion. HL7 feeds vary widely from system to system • Data normalization • All the “moving parts” necessary to consider when computing exceptions, contraindications, etc. • Data normalization • Data governance across multiple providers and types of systems • Much more…

22. How Do These Metrics Get Built? • Real-time (or near-real-time) feeds from multiple sources • Optimally configured interface engines • Connectivity that maximizes uptime and minimizes latency • Robust error reporting • BI/Analytics to identify problem areas and provide appropriate, targeted interventions, before problems get to the point of reaching a risk for the entire “shared savings” model of the ACO

23. Population Health Management • Borne out of both Accountable Care and the Affordable Care Act, as a whole, Population Health Management (PHM) has become top-of-mind for healthcare organizations • With the financial models for providers changing to reward truly making patients better, providers need to have tools to make sure patients are staying well, even after they leave the hospital or practice site • This is where PHM comes in

24. Population Health Management • Case managers need to be empowered with a multitude of different types of data to identify patients at-risk of readmissions or complications and intervene right away. Besides EHR data, critical data will be: Case Management Systems Medication History Access (e.g., Surescripts) Different types of Decision Support Systems Risk Stratification Systems Payor-type Actuarial Systems (to manage risk)

25. Population Health Management • Registries of patients with different types of potentially risky conditions must be able to be built • Processes for automatic reminders, referrals, etc., need to be in place and adhered to • PHM involves ongoing communication with patients and an awareness of their compliance with post-discharge protocols • Targeted interventions may be needed (e.g., trips to the home) when risks are noted • Ability to document interventions and their success or lack thereof is essential

26. Wrap-Up • Data storage requirements were increasing exponentially before Accountable Care moved into our world • Accountable Care requires a whole new way of thinking about storing and operating on data and has brought Business Intelligence and Analytics to the center of healthcare strategy and operations • Systems have to speak to each other as never before and they don’t always speak anything like the same language • Systems have to support a PHM-type approach and use both data and targeted interventions to keep patients well • Healthcare IT does have the tools to pull it all together, but it requires an understanding of people and process, as well as technology

27. Wrap-Up This is a fact of life now and healthcare organizations must embrace it if they want to survive and thrive in this new world

28. Thank You For more information please contact: Rich Temple, National Practice Director, Beacon Partners rtemple@beaconpartners.com 908-705-7108