Integrating Payer and Provider Data across the Enterprise to Achieve Accountable Care

Transcription

1 Integrating Payer and Provider Data across the Enterprise to Achieve Accountable Care 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.

2 Conflict of Interest Disclosure Rasu Shrestha, MD MBA Vice President, Medical Information Technology, UPMC Medical Director, Interoperability & Imaging Informatics Medical Advisory Board, Nuance Medical Advisory Board, Vital Images Inc. Editorial Board, Applied Radiology Advisory Board, KLAS Research 2012 HIMSS

3 Conflict of Interest Disclosure Rasu Shrestha, MD MBA Salary: None Royalty: None Receipt of Intellectual Property Rights/Patent Holder: None Consulting Fees (e.g., advisory boards): None Fees for Non-CME Services Received Directly from a Commercial Interest or their Agents (e.g., speakers bureau): None Contracted Research: None Ownership Interest (stocks, stock options or other ownership interest excluding diversified mutual funds): None Other: Advisory Roles only 2012 HIMSS

4 Conflict of Interest Disclosure Anne Boland Docimo, MD, MBA Chief Medical Officer, UPMC Health Plan Medical Director, UPMC Corporate Care Management Catholic Charities Free Health Care Clinic: Board Member Strategic Advisory Council, McKesson Corporation: Member 2012 HIMSS

5 Conflict of Interest Disclosure Anne Boland Docimo, MD, MBA Salary: None Royalty: None Receipt of Intellectual Property Rights/Patent Holder: None Consulting Fees (e.g., advisory boards): None Fees for Non-CME Services Received Directly from a Commercial Interest or their Agents (e.g., speakers bureau): None Contracted Research: None Ownership Interest (stocks, stock options or other ownership interest excluding diversified mutual funds): None Other: Advisory Roles only 2012 HIMSS

6 Learning Objectives Appreciate both the value and challenges of integrating payer and provider information from disparate systems, across enterprises Understand the process that UPMC has undertaken to achieve data integration between payers and providers in order to deliver clinical intelligence to physicians and nurses at the point of care. Discuss specific, strategic ideas to their own healthcare organization to accelerate progress towards connected, accountable care.

7 Empowering Change at UPMC

8 UPMC Today: Snapshot $9 billion integrated global health enterprise 50,000 employees 20 academic, community, and regional hospitals with more than 4,200 licensed beds More than 187,000 inpatient admissions and 165,000 surgeries performed annually Each year, more than 4.5 million outpatient visits and 480,000 emergency visits More than 40 UPMC Cancer Centers with 180 affiliated oncologists UPMC Health Plan: 1.4 million total members, a network of more than 125 hospitals and other facilities and more than 11,500 physicians

9 UPMC Growth UPMC s erecord applications are advancing the quality of patient care and enhancing the effectiveness and efficiency of the organization 33,418 16, % Increase 9

10 UPMC Growth erecord makes physicians and clinicians more productive by simplifying the important patient-facing elements of care delivery % Increase 47 10

11 Why Connected Healthcare Matters to UPMC ,000 8,757,578 80% 31 Petabytes of data Users Patient records Medications semantically grouped Clinical source systems integrated Change is coming health delivery redesign Patient centered record versus episodic record Building strong analytics for accountability Tighter integration between payor and provider Filtering the noise - smarter information

12 Look at UPMC

13 Building a Foundation for Accountable Care

14 Why do we need more information technology (IT) in healthcare? Quality not as good as it could be (McGlynn, 2003; NCQA, 2009; Schoen, 2009) Safety IOM errors report found up to 98,000 deaths per year (Kohn, 2000) Cost rising costs not sustainable; US spends more but gets less (Angrisano, 2007) Inaccessible information missing information frequent in primary care (Smith, 2005)

15 Return on Investment from HIT Improved Patient Safety Reduced Complications Rates Reduced Cost per Patient Episode of Care Enhanced cost & quality performance accountability Improved Quality Performance Lower Costs Better Outcomes Population Health Improve Community Health Surveillance

16 The U.S. spends more on health care per capita than other OECD* countries Price and Performance Concerns U.S. ranks in the bottom 25% of those countries on life expectancy by Jeff Levin-Scherz Source: Harvard Business Review, April 2010 *Organization for Economic Co-operation and Development

17 On a Glide Path to Insolvency CBO 1 Projected Health Spending Proportion of GDP 50% 46% Without delivery system reform, health spending projected to account for almost half of U.S. economy by % 25% 22% 16% 13% 6% 0% Total Health Spending Medicare and Medicaid 1 Congressional Budget Office. Source: Congressional Budget Office, The Long-Term Budget Outlook, June 2009; Innovations Center interviews and analysis.

18 Cumulative Changes in Health Insurance Premiums Workers Contribution to Premiums, Inflation, and Workers Earnings, Source: Kaiser/HRET Survey of Employer-Sponsored Health Benefits, Bureau of Labor Statistics, Consumer Price Index, U.S. City Average of Annual Inflation (April to April), ; Bureau of Labor Statistics, Seasonally Adjusted Data from the Current Employment Statistics Survey, (April to April). 18

19 Chronic Care Costs 75% Acute Care Costs 25%

20 Healthcare Reform Will Attempt to Reduce Costs and Improve Quality: What s Coming The Patient Protection and Affordable Care Act H.R One Hundred Eleventh Congress of the United States of America An Act Entitled The Patient Protection and Affordable Care Act. Be it enacted by the Senate and House of Representatives of the United States of America in Congress assembled The following groups of providers are eligible to participate as an ACO: Physicians and other health practitioners in group practice arrangements Networks of individual practices of ACO professionals Partnerships or JVs between hospitals and ACO professionals Hospitals employing ACO professionals Others as determined by Secretary Source: US House of Representatives, Amendment in the Nature of a Substitute to H.R. 4872, as Reported, March 18, 2010; US Senate, The Patient Protection and Affordable Care Act and the Health Care and Education Reconciliation Act, December 24, 2009; Health Care Advisory Board interviews and analysis.

21 Accountable Care Organization Providers are accountable for the cost and quality of care delivered to a defined group of patients. CMS released final rule for ACO s to form and share in potential savings. States are piloting accountable care models. Commercial insurers are developing models. Integrated delivery systems and PHO s are changing care models to become ACO s.

22 Degree of Shared Risk Accountable Care Translates into Payment Performance Accountability Expanding Across the Care Continuum Capitation/Shared Savings Models Episodic Bundling Hospital-Physician Bundling Pay-for- Performance Care Continuum

23 IT Solutions Needed for ACO Source: KLAS Report, August 2011: Accountable Care Providers Forge the ACO Trail

24 Interoperability Leading the ACO Charge Drives Patient Safety and Cost Reductions Provides evidenced-based clinical decision support at point of care Standardizes medical practice with uniform application of clinical pathways Reduces adverse drug events and injuries related to healthcare delivery Reduces duplicative tests, hospitalizations, lengths of stay Enhances disease management capabilities Improves tracking and collection of quality performance measures Increase patient, provider and payor satisfaction

25 Point of Care Systems Analytical Systems Transaction Systems Clinical Data Repository Data Warehouses External Data Data Information Knowledge Patient Level Administrative systems (scheduling, ADT) Clinical observations, assessment, plan Orders tied to protocols, w/ decision support Tests, results, documentation of care (emar) Capture outcomes, key process variables Error / near-miss reporting Population Level Analytical models, risk adjustment Ad hoc query tools exploratory analysis, hypothesis generation/testing Comparative data, best practices Support for quality improvement teams Practice profile reports for clinicians Real Time: Deploy Improved Practice Retrospective: Develop Improved Practice

26 Building a Foundation for Accountable Care

27 What Accountable Systems of Care Are Not Accountable Care Organizations are not gatekeepers so patients can seek care from specialists without referrals. Accountable Care Organizations do not require member lock-in however the ACO will be required to assume financial responsibility for all care.

28 UPMC Health Plan Patient-Centered Medical Home Data Warehousing & Mining Specialty Care Prevention Home Care Acute Care Medical Home Patient/Family Supports Pharmacy Urgicare Patient & Provider Portals Data Registries Supportive/ Palliative Care Telehealth Community Health Lifestyle Coaching Long Term Care EHR Connectivity & Interoperability Benefits/Network Designs & Incentives 28

29 Providing Value ACO s need timely, patient specific information. ACO s will be required to hit quality targets: Close gaps in care for patients with chronic illnesses Track immunizations, preventive measures To successfully coordinate care and reduce costs: Avoid duplicative evaluations and testing Medication Reconciliation Compliance with Care Plan Transitions in Care Providers will need access to care delivered outside of their own EMR system. ACOs will also need to work with their payers to get claims data on care provided outside of their organization.

30 Semantics Supports True Analytics

31 Meaningful Data in Healthcare Meaning Data Data Meaningful Data Document Healthcare data usage often is data-centric 31 Healthcare data collection is often document-centric

32 Semantics Harmonizes Data from Diverse Systems Data gathered from diverse sources needs to be stored and reviewed in one consistent form Data needs to be normalized/standardized The data s content needs to be preserved: its context in time, space and in relationship with other data allowing EMRs to remain viable data sources UMLS LOINC NDC RxNorm ICD-9-CM Mapping data from different source systems to national standards ICD-10-CM ICD-10-PCS DRG APC APDRG Harmonization between UPMC systems 32 CPT Creation HCFA HCPCS of ontologies to CDT support business SNOMED cases CTof HL7 NLP, meaningful use and disease management OMB Commercial Provider Revenue HL7 CVX Race/Ethnicity Interface Taxonomy Codes Standards Terminologies

33 Heuristics Heuristics are indispensible in medicine Clinicians must make quick judgments about how to treat a patient Often on the basis of a few, potentially serious symptoms Patient with high fever Sharp pain in RLQ Abdomen Appendicitis? Clinician immediately sends the patient for imaging and contacts the surgeon on call Just as heuristics can help doctors save lives, they can also lead to grave errors Think: decision support systems, systems integration, data flow, semantics, smart alerts, smart watch

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35 Justification for Interoperability: Medical Errors Estimated annual mortality: Air travel deaths 300 AIDS 16,500 Breast cancer 43,000 Highway fatalities 43,500 Preventable medical errors 44,000-98,000 (1 jet crash/day) Costs of Preventable Medical Errors: $29 billion/year overall 1999 Institute of Medicine (IOM) Report To Err is Human: Building a Safer Health System 2011 IOM Report: Calls for federal watchdog agency to oversee the safety of health information technology (HIT) and investigate adverse events related to HIT. IOM acknowledges that some components of HIT have improved the quality of healthcare and reduced medical errors, patient safety overall has not improved to the extent that the organization had hoped for.

36 Adverse Drug Events Error Stage for Preventable ADEs Category Percentage Medication Errors ADEs Ordering 59% Dispensing 5% Administration 13% Preventable Monitoring 80% Gurwitz et al. Am J Med 2005;118:251-8.

37 Clinical Knowledge Management at the Point of Care: Medications High-severity drug interactions Potentially problematic laboratory test results Early identification of adverse drug effects through increased monitoring Recommendations regarding geriatric-appropriate dosing Recommendations for prophylactic measures

38 Integrating Payer and Provider Data Across UPMC

39 Integrating Data Across the Health System UPMC physicians have the ability to access information on patients services received inside & outside of the UPMC network via the UPMC Health Plan Clinicians can access integrated provider and UPMC Health Plan data Access encounter information from outside the healthcare network Clinicians start with a loaded EHR Enhanced ability to find abusers Access to Health Plan predictive models for proactive medicine Health Plan Staff Health Plan Health Plan & Provider Provider Clinical Staff EMPI 39 dbmotion Health Plan Node dbmotion Provider Node

40 Integrating Data Across the Health System Clinicians Clinicians can access integrated provider and UPMC Health Plan data Access encounter information from outside the healthcare network Clinicians start with a loaded EHR Enhanced ability to find abusers Access to Health Plan predictive models for proactive medicine Health Plan staff have access to UPMCHP member information that is not available through claims, but is required to improve NCQA 1 HEDIS 2 scores and CMS 3 star ratings. Examples are PA Childhood Immunization Data and Blood Pressure data. Almost all 35 metrics of CMS star ratings could benefit from text data mining. This could impact star ratings and quality to achieve four stars or better, resulting in a 2014 quality bonus of nearly $40-50 million dollars. Health Plan Staff 1 National Committee for Quality Assurance 2 Healthcare Effectiveness Data and Information Set 3 Centers for Medicare & Medicaid Services 40

41 The Impact of Integrated Data at the Point of Care 41

42 smrx paptest engage_aod phary ng addnf 1 rclaims rneeded art ASMNF1 uri ASMNF2 kidney combo_3 ppc2 cdcldl3 ppc1 rmdnurse a1ctest ey e mh7d bloodp BP130 well15m colorec chlamy di pbh rhp UPMC HEDIS 2010 vs #1 Plan HPHC HEDIS 2009 Commercial HMO/POS (% points difference: positive is favorable) HEDIS 2011 HEDIS 2012 HEDIS 2013

43 UPMC HP HEDIS measures PCMH vs. RON* *RON= Rest of Network

44 Challenges to Integrating Claims and Clinical Data Claims data contains different information from clinical data Need to educate clinical staff about the differences Self-pay data flagged not to flow back to 3 rd party or health plan Health plan data and clinical data need to be stored separately cannot be stored in same server UPMC and the UPMC Health Plan are separate entities under HIPAA and as such data should not be comingle, unless authorized by HIPAA or state laws.

45 The Impact of Integrated Data at the Point of Care 45

46 The Impact of Integrated Data at the Point of Care 46

47 The Impact of Integrated Data at the Point of Care 47

48 The Impact of Integrated Data at the Point of Care 48

49 The Impact of Integrated Data at the Point of Care 0 49

50 Accountable Care and Analytics

51 ACO: Cost vs. Quality Cost Internal Analytics Monitoring of risk adjusted claims relative to payer benchmarks Risk adjusted claims by service line and clinician Fine grain monitoring cost centers For at-risk ACOs: true patientlevel cost accounting ACO Quality Monitoring performance metrics Gaps in care identification Point of Care Real Time Clinical Surveillance Development of internal metrics & benchmarks Physician Performance Care team/facility performance 51

52 Barriers to analytics Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. Copyright Massachusetts Institute of Technology

53 Analytics Current State Chaos Future State Access Semantic Data Warehouse Retrospective reporting based on STAR schema Cognos enabled IBM Statistical Scoring enabled Agnostic integration to other Data Warehouses Population Health Search within patient record Gaps in Care highlighted Population awareness Key measures

54 Analytic Solutions Hospitals Identify opportunities to improve outcomes Population Management Risk Management Physicians & Ambulatory Point of care physician tool External Reporting Real-time clinical surveillance for hospitals ACO Provider Performance Measurement / Management Identification of gaps in care

55 Towards Truly Connected Healthcare

56 Clinical Connect - Western Pennsylvania HIE National Health Information Network (NHIN) Altoona Regional Hospital Immunizations PA SIIS VA Hospital Quest/Labcorp State of PA The Washington Hospital* WPA HIE dbmotion dbmotion UPMC* Armstrong County Hospital 56 Butler Hospital* Siemens EHR Meditech EHR Epic EHR Eclipsys EHR Excela Health System McKesson EHR GE Centricity Allscripts My Way Allscripts Enterprise Actionable Data Heritage Valley Health System** *HIE or HIE Capable **In EHR Vendor Selection eclinical Works EpicCare Medent Jefferson Regional Hospital emd Mobile MD St. Clair Hospital* CCD Publish CCD Consume Database Sync Clinical Viewer

57 Clinical Connect - Acute Hospital Locations in WPA

58 Formula for Success: The Five Rights The Right Information at the Right Point in the Workflow Meaningful Contextual Information at the Point of Care to the Right Stakeholder through the Right Channel in the Right Format

59 Closing the loop: Relevant Data at the Point of Care Direct delivery Relevant data exchange back to the EMR EHR Agent + Collaborate Peripheral applications

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62 Personalized Medicine Analytics at the point of care Clinical Context Intelligent Healthcare Patient centric Patient Level Role based alerts Disease/ Population Level Transformation Ontology, Logic Harmonization Semantic interoperability Aggregation Syntactic interoperability Customizability, Design Vocabulary Identification

63 Q&A Thank you!