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Dr. Greg Spencer & Luke Skelley

Data Driven Care: The Key to Accountable Care Delivery from a Physician Group Perspective

Today’s Agenda

Why 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

POLL QUESTION #1

What best describes the group you belong to?Health PlanPhysician GroupProvider OrganizationVendorOther

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

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

Crystal Run Healthcare

The 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.

The Goal: The Triple Aim

Improve the health of the population

Enhance the patient experience of care

Reduce, or at least control, the per capita cost of care

Crystal Run Strategy and Objectives

Embrace 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

Crystal Run Governance Model

Establish 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, MBA

Managing 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

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

Crystal Run Quality Structure

27 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

Why Crystal Run is heavily investing in analytics and data warehousing

POLL QUESTION #2

If you are a health plan, physician group, or provider organization, do you currently exchange clinical and claims data with these other constituents?

Crystal Run Data Analytics Strategy

Implementing 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

Crystal Run Analytics Current State

Quality 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

Physician Dashboard

Turning data into improved care & ensuring financial viability in the future

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

Cost Per Case, Vascular Procedures

Physician Variation Analysis

Crystal Run Results

Reduced 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%.

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

CRHC ResultsNCQA Goal

Outcomes: Avoidable Admissions#

Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-130

Avoidable Admissions

Monthly Quality Trend

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%

Linear (CRHC)

30 Day Readmission Rate for Medicare

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)

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

A Culture Of Efficiency: Improving Access

• 41,823 fewer visits

• 30,206 more patients

• “Created” 12 physicians

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

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

Managing patient populations across payer entities

Crystal Run’s payer mix

24 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

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

Living in Two Worlds

Improvements 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

Clinician Engagement: Challenges & Successes

Clinician Engagement

Data 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

It’s All About the Data

The 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.

Crystal Run EDW Requirements

Fast 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

Adaptive Data Architecture: Turning clinician questions into

actionable results

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

Wellness programs

Regulatory measures

Provider Payer Data Sharing

Provider Payer

Case mix analysis

Utilization review

Care management

Regulatory measures

Physician profiling

Prior authorizations

Contracting

Prevent readmissions

Admission notification

Discharge notification

Risk stratification

Case management

Utilization review

Wellness programs

Care gap notification

Physician profiling

Case management

Wellness programs

Regulatory measures

Claims data

Clinical data

Crystal Run EDW Architecture

Catalyst Apps and Claims Data

Key Process Analysis Executive Dashboard Integration Tool

Cohort Builder

Comorbidity Analyzer

Readmissions Explorer Population Explorer

Claims Data

• 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

Healthcare Analytic Adoption Model

Level 8 Personalized Medicine& Prescriptive Analytics

Tailoring 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 ReductionReducing variability in care processes. Focusing on internal optimization and waste reduction.

Level 4 Automated External ReportingEfficient, consistent production of reports and adaptability to changing requirements.

Level 3 Automated Internal ReportingEfficient, 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 SolutionsInefficient, inconsistent versions of the truth. Cumbersome internal and external reporting.

POLL QUESTION #3

On 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?

Organizational Structure Goals

Provides steady state domain oversight

GUIDANCE TEAM

Refines Work Group output and leads implementation

CLINICALIMPLEMENTATIO

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

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 Expert

Data Capture

Data Provisioning & Visualization

Data 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

Workgroup Roles

DATA 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

Crystal Run EDW Teams

EDW 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

Catalyst Resource Deployment

Installation Improvement Independence

Engagement Time

Level of Engagement

Technical Director

Engagement Executive

Primary owner

Secondary owner

SOW#5+

Support

The Analytic Organization’s Journey

http://www.healthcatalyst.com/

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

Questions?

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.)

Contact Information

Dr. Greg Spencer, CMOCrystal Run Healthcarewww.crystalrunhealthcare.com

Luke Skelley, VPHealth Catalyst

luke.skelly@healthcatalyst.comwww.healthcatalyst.com

Survey Questions

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