I want to thank each of you for attending today. Accountable Care Organizations and the changes required to implement them is a top of mind issue in healthcare. My goal today is to examine the idea that Accountable Care Organizations require a combination of a Health Information Exchange and Analytics to be successful. One of the challenges of the first generation HIEs was a viable financial model due to the limited capabilities offered by those designs. The inclusion of advanced analytics to manage population health, develop risk models and examine clinical outcomes based on their cost will drive a stronger value proposition and enable accountable care.
Our agenda today is to quickly define what an accountable care organization is, review it’s key components, and define what will make an ACO a success. In addition, we’ll examine the use cases for an ACO, especially the HIE portion – today and in the future. Next, we’ll look at the challenges to adoption and, most importantly, we’ll jump into the architecture of combining the HIE with Analytics to power the successful ACO.
Let’s start with a definition. The challenge is that often the focus of healthcare organizations is bullet #2 – collaboration and coordination of patient care and they are struggling with the payment and quality responsibility part. The shift from traditional fee for service model to the ACO has many physicians worrying about a return to capitation versus risk and cost sharing. The key idea is managing the health of a fixed population of people, generally on a regional basis. In order to manage population health, lots of data analysis will be required – not the traditional retrospective reporting but a predictive, project the trend approach.
Notice that when we look at this list of key components of an ACO taken from CMS literature that Healthcare IT is NOT specifically called out but is implied in nearly every item listed. My favorite is the next to the last bullet – Care Coordination ability and mechanisms to support – clearly that is a Health Information Exchange. The last item is interesting as well – payer partnerships. This component could be challenging due to the lack of data exchange between payers and providers in the past other than billing and claims. It is implied in this component that the provider community will be able to produce quality, efficiency and patient satisfaction analyses to make the ACO work – thus HC analytics.
The reality is that each one of these organizations will need data from outside their organization and the ability to analyze that information. No one will be able to operate independently any more – it is not adequate in an accountable care environment. Today, most ACO discussions are discussing the issue of collaboration internal to the organization and not focused on the external collaboration environment. The debate is in full swing – should the ACO be hospital centric, anchored by a large multi-specialty group practice, led by physicians, independent or, my favorite, virtual. The point is this: there is a place for each type of model, but the key will be the ability to gather, analyze and act on evidence-based clinical information. Many of the current examples are leaders in Healthcare IT and Geisinger Health is well known for their efforts in developing an integrated clinical data repository with a strong data model. Each ACO model has their own idea of how to achieve care coordination and cost effectiveness. Finally, each of these models will do their part to reduce chaos and fragmentation in the current healthcare delivery system.
Let’s not forget the patients!
According to Donald Berwick, John Whittington, and Tom Nolan of the Institute for Healthcare Improvement the strategy for improving the U.S. health care system requires simultaneous pursuit of three aims: improving the experience of care, improving the health of populations, and reducing per capita costs of health care. Preconditions for this include the enrollment of an identified population, a commitment to universality for its members, and the existence of an organization (an "integrator, or HIE") that accepts responsibility for all three aims for that population. The integrator’s role includes at least five components: partnership with individuals and families, redesign of primary care, population health management, financial management, and macro system integration. The integrator required is a “Pay for Population Health Performance System,” which goes beyond medical care to include financial incentives for the equally essential non-medical care determinants of population health. The challenges are even greater than Berwick and colleagues realize for the Triple Aim within medical care; they include agreement on population health measures, financial incentives, ways to avoid unintended consequences, coordination across sectors, and resistance to the reallocation of resources – all of which must have set goals, tracking of actual performance and actionable information for continuous improvement. Setting metrics and driving to the metrics will be the determinant of ACO success – the enabling technology will be using business intelligence tools.
OK, so if we agree that a Health Information Exchange is a key component of an ACO, then what is required? The use case diagram outlines our initial understanding of expectations around an HIE as primarily a clearinghouse of information moving from one organization to another. Note in our earlier view of HIEs, the exchange of population health information was viewed as a Public Health Authority role. While an HIE must meet these basic use cases, there is broader emerging use cases to support the ACO. One of the key trends in HIEs is the shift in focus from state-level efforts to build HIEs to private HIEs built by large IDNs or collaborations of a series of regional IDNs. These regional alliances for HIEs have a common interest – managing their population under the Accountable Care Organization models. Let’s shift from this original view to the current view.
The current view of the Health Information Exchange moves from data interoperability to broadening the data collection about regional populations to support the type of analysis needed to coordinate care and manage costs. Notice the focus on drawing in external databases as well as the clinical information in the previous slide. The major shift is the collection of data about variables impacting on healthcare costs: environmental factors, social/economic conditions, shifts in lifestyle and behavior, health assessments and biometrics. First, note that data will be oriented toward quantifying the variables impacting an individual’s health to provide predictive assessments to avoid costs. In addition, the amount of data collected and analyzed will be exponentially greater – far below the level of HL7 transactions today. Think of capturing your exercise data and it’s impact on blood sugar, your weight and even mood – like Nike + today and then harnessing this remote monitoring to avoid expensive trips to the emergency room or potential hospitalizations. The challenge will be business intelligence systems that can handle “BIG” data, analyze it and recommend a course of action.
The Emerging ACO view is that HC analytics will reside at the HIE level, thus ACO = HIE + Analytics. The key is building analytics on the population being managing by the ACO versus today’s individual silos of care settings. The key in this diagram is the focus on risk and predictive modeling versus the traditional retrospective reporting in healthcare. The shift in focus to preventive medicine and holistic view of the person under population health management versus the patient in the past.
Discussion of Oracle’s “integrated stack” to address these architectural layers.
Population Health Management in an ACO is a platform that aggregates health data across the continuum of care from disparate systems, creating a longitudinal patient record with decision support, quality measurement, and analytics for population management. Upon this platform, programs are built for specific purpose of managing chronic conditions and high priority population health management objectives. The programs feed knowledge and decision support into applications to manage workflow of existing clinical roles and new roles such as health coach, care coordinator and VP of Population Health.
Note that key idea that basic HIE data can be combined with demographic or environmental data to create public health views of the managed population and then use the BPM/SOA capabilities to “take action.”
ACO = HIE + Analytics: Enabling Population Health Management
ACO = HIE + Analytics Martin SizemoreDirector, Healthcare Strategy
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Agenda• Accountable Care Organizations (ACO)• Definition, key components• ACO: Definition of success• ACO HIE requirements – use cases• HIE Current and Emerging views• ACOs require more than EHRs• Challenges to widespread ACO adoption• ACO = HIE + Analytics – Architecture• What are the typical use cases?• Summary
Accountable Care Organization Defined• A healthcare delivery system whose members share responsibility, financial risk and a common goal to improve healthcare delivery and the overall health status for a given population.• Acts collaboratively to coordinate patient care across the continuum and share both the payment and responsibility for quality of care for the covered patients.• Paid a specified amount for the population it manages, rather than a per transaction fee. ACOs can be incented if their quality and patient satisfaction scores are higher than expected; they can also receive decreased reimbursement if scores are lower than expected.* HIMSS ACO FAQ, www.himss.org
Key Components of an ACO• Patient‐centered medical homes• Primary care physicians• Specialists• Minimum of one hospital• Ancillary providers• Minimum of 5,000 Medicare beneficiaries (for Medicare demonstration funding)• Care coordination ability and mechanisms to support• Payer partnerships with reimbursement based on quality, efficiencies and patient satisfaction
Emerging ACO Models ‐ Governance Model Characteristics Current ExamplesIntegrated delivery • Own hospitals, physician practices, perhaps an • Geisinger Health System insurance plan. • Group Health Cooperative of Puget Soundsystems/networks • Aligned financial incentives. • Kaiser Permanente(IDN) • E-health records, team-based care. • Summa Health SystemMultispecialty • Usually own or have strong affiliation with a • Cleveland Clinic hospital. • Marshfield Clinicgroup practices • Contracts with multiple health plans. • Billings Clinic(MSGP) • History of physician leadership. • Virginia Mason Clinic • Mechanisms for coordinated clinical care.Physician-hospital • Nonemployee medical staff. • Greater Newport Physicians (partners with Hoag) • Function like multispecialty group practices. • St. Vincent Healthcare in Billingsorganizations • Reorganize care delivery for cost- • Methodist LeBonheur Healthcare(PHO) effectiveness. • Kettering Health NetworkIndependent Practice • Independent physician practices that jointly • Atrius Health (eastern Massachusetts) contract with health plans • Hill Physicians Group (southern California)Associations • Active in practice redesign, quality • Monarch HealthCare (southern California) improvement.Virtual Physician • Small, independent physician practices, often • Community Care of North Carolina in rural areas. • Grand Junction (Colorado)Organizations • Led by individual physicians, local medical • North Dakota Cooperative Network foundation, or state Medicaid agency. • Structure that provides leadership, infrastructure, resources*Source: Article by Stephen M. Shortell and Lawrence P. Casalino
Performance Measurement in ACOs CURRENT SYSTEM ACO SYSTEM Performance Measurement exclusively at the Measurement at the ACO level, across the individual/group level promotes fragmentation of care team, promotes an emphasis on care coordination and and an emphasis on encounter optimization as taking a long-term, holistic view of wellness. opposed to carrying a longitudinal view. ACO Patient PatientSlide courtesy of Oracle
ACOs from the Patient’s Perspective CURRENT SYSTEM ACO SYSTEM Quality Metrics & Cost Savings Payer Payer ACO Shared Savings Volume & Intensity Care Coordination Rewarded Care Coordination Patient PatientSlide courtesy of Oracle
ACO: Definition of Success Experience Metrics: Improving triple aim™ • Patient satisfaction of Care • PAM Scores (Patient Activation population outcomes Measures) Per Capita Metrics: • Total medical PMPM Costs • Total Medical Trend • Total Rx PMPM • Admissions/1000 Population • Readmission rate Metrics: Health • QUEST outcomes • Select HEDIS metrics • Health status – SF12 • Mortality rates Healthcare Business Intelligence will be the key to success in managing to these metrics* The term triple aim is a trademark of the Institute for Healthcare Improvement
Health Information Exchange (HIE) • Extension of EMRs • Integration or Interoperability role • Primarily data push or pull • Struggles with financial viability • Shifting from state-level efforts to private HIEs • Key element in the integration and coordination of care
HIE: Current View Demographics Rx Claims Demographics Rx Claims Labs Labs Medical Claims Medical Claims Health InformationBiometrics Bio-metrics Exchange Remote monitoring Remote Monitoring Focus: Data collection and Health Integration HRA Environmental Environmental Assessments Factors Lifestyle / Social behavioral /economic Lifestyle / Social / Behavioral Economic
HIE: Emerging ACO View Risk Financial Performance Risk Financial Management Management Performance (vs. paid claimsQualityReporting Quality Reporting Health Clinical Performance Clinical Information Performance Exchange Focus: Population Interventions Health Analysis Risk / predictive and tracking modeling Risk / Predictive Interventions Modeling Care plan Care plan deployment design Care Plan Care Plan Design Deployment
ACOs Require Far More Than EHRsRequirements Data Sources for Mining – Predictive modeling – Medical records – Registries – Clinical outcomes data – EHR interfaces – Patient billing systems – Reminder systems – Payer data – Claims and clinical data – Quality measures warehouses abstracts – Episode of care analysis – Charge master systems – Physician, payer, service – Specifications for integrated line utilization data claims and clinical databases – Infection surveillance – Patient portal options data – Health information – Labor, productivity and exchanges throughput records – Adverse drug events
Challenges to Widespread ACO Adoption• Silos lead to a disconnected business and IT infrastructure• Islands of computing create inefficiencies and underutilized assets• Missing or competing data standards, limited interoperability• Struggle with regulatory compliance, volume of information, data integrity and security• Resource constraints and difficulty managing complexity/change• Volume of data points and quality measures, in widely dispersed locations• Limited use among providers Meaningful Use Stage 2 and 3 to the rescue!
ACO: High-Level Architecture ACO Performance Management will be the key to success
HIEs Require Document Sharing (XDS) Oracle Health Sciences Information Manager (HIM) • First Register and Store ORACLE HIM QUERY AND RESPONSE PROCESS Documents from providers Requestor/ESB OHMPI Registry Repository • Providers Retrieve Documents: – Find Patient – Then Locate Documents Patient Lookup Potential Matches – Then Retrieve Document Display Record Set Documents Supports centralized, Select Patient Associated • Query XDS.b Registry with Patient federated and hybrid data models Display record headers, store pointers Select Extract full Individual Query XDS.b Repository data set/ record/ • HIM facilitates installation Document document and coordination of XDS Displayed Detailed result(s) componentsSlide courtesy of Oracle
Oracle HIE Architecture Oracle Desktop Virtualization Oracle Identity & Access Management Caregiver Mobility SSO User Provisioning LDAPOracle Sun Ray Oracle Portals and ApplicationsThin Client Consumers Clinicians Administrators Consent Mobility Empowerment Oracle Health Sciences Information Gateway Web Service Orchestration Web Service DMZ Gateway Data Center Adapter Oracle Business Process Management Suite Registries CONNECT CONNECT/Direct ESB BPEL Business Process Manager Process Analysis PKI Security Fixed Web Service Orchestration Adaptive Web Service Design & Orchestration Certificate Authorities Oracle Health Sciences SOA-based Integrations Other Health Information Manager Information Other SOA Service Endpoints DMZ Firewall & Internet Organizations’ Web Services & Features Message-based Support Data Center Firewall Secure Health Healthcare Master Health Policy Monitor Email Person Index Health Sciences Integration Engine Health Policy Engine Health Record Locator Healthcare TransactionStandardized Public Key Directory Healthcare Analytics Base“Front Door” EHA: HDWF-- HDM – ORA -- PSCAHIETransactions Oracle Databases, Clusters & Enterprise Manager Enterprise Linux Solaris Containers Oracle VM Database Encryption EXALOGIC Oracle Hardware Servers & Storage EXADATA Slide courtesy of Oracle
Oracle HIE “Edge-Server” Architecture Solving CIO Worries by Providing an Internet “buffer” to PHI data sources Firewall Penetrations Edge Servers for EHR Users Multiple Internal and Desktop Virtualization back channelEnd Users PHI Data Sources Cloud Computing Data Center Web Service DMZ Registries Edge Servers Proxy Servers Electronic PKI Security for the Certificate Health Record Authorities Health Information System(s) Other Health Information Internet Cloud DMZ Firewall & Internet Organizations’ Web Services & Data Center Firewall Secure Health EmailStandardized Edge Servers supports Secure, Controlled Health“Front Door”HIE Information Exchange of PHI to and from the EHRTransactions System(s) Prepared for the future of consumer-oriented healthcare and wellness management Slide courtesy of Oracle
ACO/HIE as a Population Health Platform Research (Evidence-Based De-identified Medicine)People Person HL7, CCD, EDI, P Client Opt HR, Batch, Web Applications In/Out Services Data Clinic Raw Data Enhancing Transformation knowledge Health Coach Claims and Normalization Structured Data translation and the Read byHospital adoption of Clinical Longitudinal Record QxMed evidence- based Primary Care Wellness Analytics Physician practice Master Patient Index Satisfaction Vocabularies IdentifyDevice Master Data Mgmt Predict Organization Prevent or Patient Intervene Home Health Assistant HIE Consent Measure Advanced Analytics Personalized Health Plan VP of Population Health Payer Mgmt
Why Build This Level of Technical Architecture?• Move from retrospective reporting to predictive modeling of population health to manage risk and share savings• Create the data analytics necessary to move to evidence-based medicine and modeling of outcomes, meet coming demand of healthcare consumer analytics• Predictive modeling provides an objective assessment of a patient’s future illness burden and associated health costs based upon their historical conditions as captured through claims and clinical information – key to ACO success! – It is a method for prioritizing members for population health management and care management and stratifying them based upon their morbidity burden and financial risk
HIE + Analytics: What are typical use cases? Use Cases Use CasesDetermine and model total cost of care across all ID risk to patients by looking at environmental factorssettings (acute, ambulatory, home care) by population e.g. asthma, flu breakoutor individualCare coordination New age case management (CRM for patients)Match payer and provider data-verify rollout of ID labor savings. Correlate staffing to predictedpreventative programs demand/activityMeds Mgmt./Reconciliation/Med Therapy Physician attribution and/or care team – qualityMgt./Prescription fill compliance outcomes – patient satisfactionAnalyze population health levels based on various Monitor and track (real time) compliance to regulatorygrouping (geo, facility, provider, etc.) and/or clinical guidelines across settingsUnderstand resource utilizing productivity, throughput Chronic care cost modeling to support payments andand access allocationEvaluate readmission across continuum Support transitions of care through transfer of dataResource planning/physician profitability (contract Aggregate and manage data across all care settingsmanagement, preferences, outcomes (cost, care)Support all 65 ACO measures, not just the initial 33 Comparative Effectiveness / waste reductionMonitor/track patients experience beyond HCAPS Creation of new evidence base for guidelines(coordinate w/workforce, predict experience) 25