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Hospitals, payers and physician groups alike are facing changes in healthcare that require their attention. These changes are a result of financial forces that are changing the ways healthcare services are paid, cost of care pressures, ever-changing patient population behaviors, improvements in the science of health care and federal regulations tied to incentives that are soon turning to penalties. Anyone in health care is grappling to understand these changes and chart their strategies to be prepared for the future. The presenters have proven expertise developing their strategies to care for patients in an accountable care model using data to drive their strategies. The presenting organizations will talk through their strategy including their future expectations and early results using data to identify improvement opportunities and to shift the clinical approach to health care. In addition to strategy, they will share solutions and analytic applications critical to the current and future expected results of their strategy.
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Dr. Greg Spencer & Luke Skelley
Data Driven Care: The Key to Accountable Care Delivery from a Physician Group Perspective
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Today’s AgendaWhy a regional physician group is heavily investing in analytics and data warehousing
Crystal Run Healthcare’s strategy to turn data into improved care as well as financial viability in the future
How Crystal Run manages across its patient population who are covered by 24 payer entities
Some of the preliminary challenges and successes engaging clinicians in the use of data
The importance of an adaptive data architecture to turn clinician questions into actionable results
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POLL QUESTION #1
What best describes the group you belong to?Health PlanPhysician GroupProvider OrganizationVendorOther
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Crystal Run Healthcare• Physician owned MSG in NY
State, founded 1996
• 300+ providers, 16 locations
• Joint Venture ASC, Urgent Care, Diagnostic Imaging, Sleep Center, High Complexity Lab, Pathology
• Early adopter EHR (NextGen®) 1999
• Accredited by Joint Commission 2006
• Level 3 NCQA PCMH Recognition 2009, 2012
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Crystal Run Healthcare• Single entity ACO
• April 2012: MSSP participant
• December 2012: NCQA ACO Accreditation
• 25,000 commercial lives at risk
• MSSP
• 10,400 attributed beneficiaries
• 82% primary care services within ACO
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Crystal Run HealthcareThe mission of Crystal Run Healthcare is to improve the quality and availability of, and satisfaction with, health care services in the communities we serve. To accomplish this goal, the practice emphasizes both traditional medical excellence as well as responsiveness to consumer needs through service excellence and patient empowerment.
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The Goal: The Triple AimImprove the health of the population
Enhance the patient experience of care
Reduce, or at least control, the per capita cost of care
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Crystal Run Strategy and ObjectivesEmbrace goals of Triple Aim
Physicians play a crucial role in driving change in healthcare
Focus on providing coordinated care
Population health management is critical
Competition from hospitals and health plans is occurring
Coverage area is expanding, and needs to expand further
Physicians and their teams need to work together for the best of their patients
A strategic pillar is to be the practice of choice for physicians, patients, and employees
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Crystal Run Governance ModelEstablish data warehouse priorities
Set policies for data access, information security and privacy
Develop process for setting data definitions and standards
Coordinate with Partners eCare leadership
JOINT CLINICAL AND FINANCIAL GOVERNANCE MODEL
Hal Teitelbaum, MD, JD, MBAManaging Partner & CEO
Michelle A. Koury, MDChief Operating Officer
Greg Spencer, MDChief Medical &
Chief Medical Info Officer
Mary DeFreitasChief HR Officer
Erlene WashingtonSenior VP of
Finance & Accounting
EDW EXECUTIVE SPONSORS
Greg Spencer, MDCMO & CMIO
Jonathan Nasser, MDMedical Director
Miguel HernandezTechnology Director
Lou CervoneBI Director
EDW Steering Committee
EDW GOVERNANCE
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Crystal Run Care Management StrategiesEmbedding Care Managers at different offices, medical homes and hospitals
Identify high-risk patients from registries and PCP/ team referral
Implement evidence based protocols
Use EHR and mobile / home devices
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Crystal Run Quality Structure27 divisions each headed by its own physician specialist
Manage quality efforts and information
Work with Best Practice Council (quality committee) to define registries
Report to practice-level committee for quality and patient safety
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12
Why Crystal Run is heavily investing in analytics and data warehousing
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POLL QUESTION #2If you are a health plan, physician group, or provider organization, do you currently exchange clinical and claims data with these other constituents?
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Crystal Run Data Analytics StrategyImplementing formal quality improvement methodology
Implementing EDW with multiple data sources
Implementing analytical applications
Daily financial reporting
Order tracking: In-house vs. Sent out
Claims Data Integration
RVUs Standardization
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Crystal Run Analytics Current StateQuality improvements heavily dependent upon data
Using simple analytical tools – Excel, Access, Tableau
Time and effort spent on manual data entry and extraction is excessive and poorly scalable
Decisions about what data to use based on amount of disruption vs. value
Data entry/analysis not done at Top of Licensure
Reporting quality metrics resource intensive – kept it simple
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Physician Dashboard
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Physician Dashboard
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Turning data into improved care & ensuring financial viability in the future
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Dr. J.15 Cases$60,000 Avg. Cost Per Case
Mean Cost per Case = $20,000
$40,000 x 15 cases = $600,000 opportunity Total Opportunity = $600,000
Total Opportunity = $1,475,000$35,000 x 25 cases = $875,000 opportunity
Total Opportunity = $2,360,000
Total Opportunity = $3,960,000
Cost Per Case, Vascular Procedures
Physician Variation Analysis
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Crystal Run ResultsReduced hospital admissions 4+% in one year
Improved mammogram rates from 60-65% to greater than 75%
Achieved less than 9% rate of A1Cs > 9
Blood pressure control in hypertensive patients improved to greater than 75%.
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Improved QualityBreast Cancer Screening
Mammography
1st Quarter 2011
2nd Quarter 2011
3rd Quarter 2011
4th Quarter 2011
1st Quarter 2012
2nd Quarter 2012
3rd Quarter 2012
4th Quarter 2012
1st Quarter 2013
2nd Quarter 2013
3rd Quarter 2013
66.0%
67.0%
68.0%
69.0%
70.0%
71.0%
72.0%
73.0%
74.0%
75.0%
76.0%
CRHC ResultsNCQA Goal
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Outcomes: Avoidable Admissions#
Avo
idab
le A
dmis
sion
s
17%
Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-130
10
20
30
40
Avoidable Admissions
Monthly Quality Trend
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Outcomes: Readmissions
Q2-2012 Q3-2012 Q4-2012 Q1-2013 Q2-2013 Q3-201316.50%
17.00%
17.50%
18.00%
18.50%
19.00%
19.50%
20.00%
CRHCLinear (CRHC)
30 Day Readmission Rate for Medicare
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Total cost difference
2012 pre-pathway
791 patients
$595,920
2013 post-pathway
817 patients
$368,160
TOTAL COST SAVINGS $227, 760
PEG-filgrastim use in Breast cancer patients(equalized as cost per patient treated)
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Reducing Pharmaceutical Costs
Physician A Physician B Physician C Physician D Average $0
$2,000
$4,000
$6,000
$8,000
$10,000
$12,000
$14,000
PEG Filgrastrim cost per patient before and after breast cancer pathway
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A Culture Of Efficiency: Improving Access
• 41,823 fewer visits
• 30,206 more patients
• “Created” 12 physicians
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Variation Reduction Spread Reduction in Charges
DIAGNOSIS DEPARTMENT % CHANGE PP TOTAL $$ CHANGE
CHF Cardiology -6% -$53,457Diabetes PCP/Endocrine -17% -$844,755Thyroid Nodule Endocrinology -26% -$304,224Otitis Externa ENT -2% -$2,373GERD GI -20% -$178,381Cholelithiasis General Surgery -7% -$11,408COPD Hospitalists -20% -$9,215HTN Primary Care -16% -$943,002Hyperlipidemia FP/IM -19% -$1,150,376HA/Migraine Neurology -10% -$208,054Breast Cancer Oncology -7% -$393,622Lateral Epicondylitis Orthopedics -8% -$27,647Asthma Pediatrics -10% -$24,570Asthma Pulmonology +3% +$26,238Renal Mass Urology -4% -$62,812
TOTAL -$4,187,658
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Variation Reduction Spread Improving Access
DIAGNOSIS DEPARTMENT CHANGE IN VISITS CHANGE IN PATIENTS
CHF Cardiology -722 +213Diabetes PCP/Endocrine -3,051 +41Thyroid Nodule Endocrinology -1,971 +132Otitis Externa ENT +70 +65GERD GI -143 +266Cholelithiasis General Surgery -12 +59HTN Primary Care -3,013 +339Hyperlipidemia FP/IM -2,966 -561HA/Migraine Neurology -550 +225Breast Cancer Oncology -278 +16Lateral Epicondylitis Orthopedics -84 -4Asthma Pediatrics -92 -134Asthma Pulmonology -66 +1,132Renal Mass Urology -11 -6
TOTAL -12,889 +1,783
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Managing patient populations across payer entities
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Crystal Run’s payer mix24 Payer Entities
No dominant payer, so little to no leverage for discounts, etc.
No dominant payer, so payers need to contract with Crystal Run to effectively do business in the area
Complicates data analysis due to limited population/statistics by payer
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Payer Challenges Having data-focused payer conversations about shared savings
Need claims data to support risk contracting
Multiple payers limits ability to do valid statistical modeling
Collaborating with multiple plans to develop shared savings model
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Living in Two WorldsImprovements in quality reduces costs to benefit of payer
Reduction in patient visits offset by increase in patient volume
Hospitals acquisition of physicians not based on value but to protect referrals
Triple Aim is a threat to hospitals
Hospitals have to align optimal patient care vs. optimal reimbursement
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Clinician Engagement: Challenges & Successes
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Clinician EngagementData used in physician recruitment and retention
Data also used to support alignment and/or acquisition decisions
Sharing physician performance data helps affect behavior even if no penalty or not tied to a quality effort
• Sharing physician data makes outliers come to consensus
• Not all physician practices focus on value
• Younger physicians sometimes avoid change more than older ones
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It’s All About the DataThe limitation is data.
The doctors need performance data
They have metrics to measure care
~ 80% of Business Intelligence’s time spent gathering versus analyzing data
90/10 of data capture time to analysis time.
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Crystal Run EDW RequirementsFast to implement and fast to ROI
Capable of easily expanding to add new data sources
Library of analytical applications
Vendor with healthcare experience and expertise
Data model conducive to healthcare data
Ability to become self sufficient
Long term business partner
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Adaptive Data Architecture: Turning clinician questions into
actionable results
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Provider-Payer Collaboration
Provider Payer
Case mix analysis
Utilization review
Care management
Regulatory measures
Physician profiling
Prior authorizations
Contracting
Prevent readmissions
Evidence based guidelines
Admission notification
Discharge notification
Risk stratification
Case management
Utilization review
Wellness programs
Consumer transparency
Claims dataClinical data
Care gap notification
Physician profiling
Case management
Evidence based guidelines
Wellness programs
Consumer transparency
Regulatory measures
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Provider Payer Data Sharing
Provider Payer
Case mix analysis
Utilization review
Care management
Regulatory measures
Physician profiling
Prior authorizations
Contracting
Prevent readmissions
Evidence based guidelines
Admission notification
Discharge notification
Risk stratification
Case management
Utilization review
Wellness programs
Consumer transparency
Care gap notification
Physician profiling
Case management
Evidence based guidelines
Wellness programs
Consumer transparency
Regulatory measures
Claims data
Clinical data
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Crystal Run EDW Architecture
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Catalyst Apps and Claims Data
Key Process Analysis Executive Dashboard Integration Tool
Cohort Builder
Comorbidity Analyzer
Readmissions Explorer Population Explorer
Claims Data
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• Driven by business and clinical need
• Rapid development and deployment of data sources
• Built incrementally (i.e., less expensive)
• Ownership transferred to client with technical support as needed
• Align with access roles and data stewardship jurisdictions
• Applications support Healthcare Analytics Adoption Model
Catalyst Data Warehouse Advantages
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Healthcare Analytic Adoption ModelLevel 8 Personalized Medicine
& Prescriptive AnalyticsTailoring patient care based on population outcomes and genetic data. Fee-for-quality rewards health maintenance.
Level 7 Clinical Risk Intervention& Predictive Analytics
Organizational processes for intervention are supported with predictive risk models. Fee-for-quality includes fixed per capita payment.
Level 6 Population Health Management& Suggestive Analytics
Tailoring patient care based upon population metrics. Fee-for-quality includes bundled per case payment.
Level 5 Waste & Care Variability Reduction Reducing variability in care processes. Focusing on internal optimization and waste reduction.
Level 4 Automated External Reporting Efficient, consistent production of reports and adaptability to changing requirements.
Level 3 Automated Internal Reporting Efficient, consistent production of reports and widespread availability in the organization.
Level 2 Standardized Vocabulary& Patient Registries Relating and organizing the core data content.
Level 1 Enterprise Data Warehouse Collecting and integrating the core data content.
Level 0 Fragmented Point Solutions Inefficient, inconsistent versions of the truth. Cumbersome internal and external reporting.
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POLL QUESTION #3On a scale of 1-5, with 5 being very advanced, how far along is your organization in using data to guide your quality and cost initiatives?
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Organizational Structure Goals
Provides steady state domain oversight
GUIDANCE TEAM
Refines Work Group output and leads implementation
CLINICALIMPLEMENTATIO
NTEAM
Provides clinical forum to develop clinical content and analytics feedback
WORKGROUP
Supports development
of clinical content and
analytics feedback
CONTENT AND
ANALYTICSTEAM
Provides overall governance and prioritization of initiatives
SENIOR EXECUTIVE
LEADERSHIP TEAM
ENSURETHAT…
• Workgroups are created with institutional priority• Appropriate leadership is engaged in prioritization• Organizational barriers between team members are
removed
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Organizational Teams
Women & Children’s Clinical Program Guidance Team
Pregnancy SAM
PregnancyMD LeadRN SME
Knowledge Manager
DataArchitect
Application Administrator
RN, Clinical Ops Director
Guidance Team MD lead(e.g., Pregnancy MD Lead)
Subject Matter ExpertData CaptureData Provisioning & VisualizationData Analysis
Normal Newborn SAM
Normal Newborn MD LeadRN SME
GynecologySAM
GynecologyMD LeadRN SME
Permanent Teams
Integrated Clinical and Technical members
Supports Multiple Care Process Families
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Workgroup RolesDATA CAPTURE
• Acquire key data elements• Assure data quality• Integrate data capture into
operational workflow
DATA ANALYSIS
• Interpret data• Discover new information in the data
(data mining)• Evaluate data quality
DATA PROVISIONING
• Move data from transactional systems into the EDW
• Build visualization for use by clinicians
Knowledge Managers
Data Architects(Analysis)
Knowledge Managers
Data Architects(infrastructure)
Data Architects(Visualization)
Application Administrators (e.g., EMR Administrators, Financial System Administrators)
Subject MatterExpert
Data CaptureWorkflow Analysis
Data Provisioning
Data Analysis
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Crystal Run EDW TeamsEDW data acquisition
● Systems programmers● Database administrator● Clinical SME’s
EDW data architecture and integration services● BI director● Data architects● Business development● Project manager● Clinical SME’s
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Catalyst Resource Deployment
Installation Improvement Independence
Engagement Time
Level of Engagement
Technical Director
Engagement Executive
Primary owner
Secondary owner
SOW#1
SOW#2
SOW#3
SOW#4
SOW#5+
Support
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The Analytic Organization’s Journey
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http://www.healthcatalyst.com/
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AHIP Institute 2014
June 11-13, 2014 in Seattle, WA
AHIP’s Data Analytics Forum will provide valuable insights on how stakeholders in the health care system utilize big data to enhance care quality, reduce costs, make better business decisions, and streamline operational processes.
Please join Luke Skelly and Health Catalyst at Booth #911
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Questions?
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Seed Questions
What are some of the barriers you’ve run across in acquiring claims from payers?
What internal challenges do you see payers or providers facing in developing a data driven culture?
How does Health Catalyst support a population health management approach using claims data from non-acute care settings (home health, skilled nursing facilities, etc.)
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Contact InformationDr. Greg Spencer, CMOCrystal Run Healthcarewww.crystalrunhealthcare.com
Luke Skelley, VPHealth Catalyst
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Survey Questions
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