ACO = HIE + Analytics: Enabling Population Health Management
1. ACO = HIE + Analytics
Martin Sizemore
Director, Healthcare Strategy
2. About Perficient
Perficient is a leading information technology consulting firm serving clients
throughout North America.
We help clients implement business-driven technology solutions that integrate
business processes, improve worker productivity, increase customer loyalty and
create a more agile enterprise to better respond to new business opportunities.
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5. Our Speaker
Martin Sizemore
• Principal, Healthcare Strategic Advisory Services
• A healthcare strategist, senior consultant and a trusted
C-level advisor for healthcare organizations including
both payers and providers
• Specializes in clinical data warehousing, clinical data
models and healthcare business intelligence for
improving operational efficiencies and clinical
outcomes.
• A TOGAF certified enterprise architect with specialized
skills in enterprise application integration and service
oriented architecture.
6. 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
7. 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
8. 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
9. Emerging ACO Models ‐ Governance
Model Characteristics Current Examples
Integrated delivery • Own hospitals, physician practices, perhaps an • Geisinger Health System
insurance plan. • Group Health Cooperative of Puget Sound
systems/networks
• Aligned financial incentives. • Kaiser Permanente
(IDN) • E-health records, team-based care. • Summa Health System
Multispecialty • Usually own or have strong affiliation with a • Cleveland Clinic
hospital. • Marshfield Clinic
group 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 Billings
organizations
• Reorganize care delivery for cost- • Methodist LeBonheur Healthcare
(PHO) effectiveness. • Kettering Health Network
Independent 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
10. 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 Patient
Slide courtesy of Oracle
11. 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 Patient
Slide courtesy of Oracle
12. 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
13. 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
14. HIE: Current View
Demographics
Rx Claims
Demographics Rx Claims
Labs Labs Medical Claims
Medical
Claims
Health
Information
Biometrics 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
15. HIE: Emerging ACO View
Risk Financial Performance
Risk Financial
Management Management Performance (vs. paid claims
Quality
Reporting
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
16. ACOs Require Far More Than EHRs
Requirements 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
17. 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!
19. 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)
components
Slide courtesy of Oracle
20. Oracle HIE Architecture
Oracle Desktop Virtualization Oracle Identity & Access Management
Caregiver Mobility SSO User Provisioning LDAP
Oracle Sun Ray Oracle Portals and Applications
Thin 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 Transaction
Standardized Public Key Directory Healthcare Analytics
Base
“Front Door” EHA: HDWF-- HDM – ORA -- PSCA
HIE
Transactions Oracle Databases, Clusters & Enterprise Manager
Enterprise Linux Solaris Containers Oracle VM Database Encryption
EXALOGIC Oracle Hardware Servers & Storage EXADATA
Slide courtesy of Oracle
21. 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 channel
End 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
Email
Standardized Edge Servers supports Secure, Controlled Health
“Front Door”
HIE Information Exchange of PHI to and from the EHR
Transactions System(s)
Prepared for the future of consumer-oriented
healthcare and wellness management
Slide courtesy of Oracle
22. 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 by
Hospital adoption of
Clinical Longitudinal Record QxMed
evidence-
based Primary Care
Wellness Analytics Physician
practice
Master Patient Index
Satisfaction Vocabularies Identify
Device 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
23. 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
25. HIE + Analytics: What are typical use cases?
Use Cases Use Cases
Determine and model total cost of care across all ID risk to patients by looking at environmental factors
settings (acute, ambulatory, home care) by population e.g. asthma, flu breakout
or individual
Care coordination New age case management (CRM for patients)
Match payer and provider data-verify rollout of ID labor savings. Correlate staffing to predicted
preventative programs demand/activity
Meds Mgmt./Reconciliation/Med Therapy Physician attribution and/or care team – quality
Mgt./Prescription fill compliance outcomes – patient satisfaction
Analyze population health levels based on various Monitor and track (real time) compliance to regulatory
grouping (geo, facility, provider, etc.) and/or clinical guidelines across settings
Understand resource utilizing productivity, throughput Chronic care cost modeling to support payments and
and access allocation
Evaluate readmission across continuum Support transitions of care through transfer of data
Resource planning/physician profitability (contract Aggregate and manage data across all care settings
management, preferences, outcomes (cost, care)
Support all 65 ACO measures, not just the initial 33 Comparative Effectiveness / waste reduction
Monitor/track patients experience beyond HCAPS Creation of new evidence base for guidelines
(coordinate w/workforce, predict experience) 25
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.”