Delivering Value for Patients and Payers

Data & Measurement

Day 1 – Morning

Michael J. Deegan, M.D., D.M.

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DATA

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Health Care Data Essentials

Sensitivity: the ability to identify a condition

Specificity: the capacity to correctly identify a condition

Timeliness: the availability of data relative to the time of the event

Availability: the ease with which the data is accessed or captured for use

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Data “Cleansing”Validate & Normalize

Align data with a single condition or diagnosis; understand it’s distribution

Clean & Validate

Remove erroneous, incorrect data elements

Extract & Validate

Understand its relevance to condition

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Pitfalls that Inhibit Using Data to Drive PI Lack of timeliness

Reports based on readily available non-relevant data

Failure to adequately analyze and interpret the data

Poor assignment of accountability for indicator performance or improvement

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Pros & Cons of Data Types

Claims Data• Available

• Untimely

• Fragmented

• Insensitive

• Lacks specificity

Clinical Data• Sensitive

• Specific

• Timely

• Longitudinal

• Uneven availability

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Gaining Insight by Using MultipleData Types

Clinical data

Socio-demographic data

Care management data

Claims data

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Non-Clinical Risk Factors

VitreosHealth® Predictive Model

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Uncovering Meaningful Data Patterns

Identify the most seriously ill

Appreciate the influence of socio- demographic & clinical risk factors

Measure cost & outcomes (Value)

Discover cost & utilization drivers

Identify “deviants” ( positive & negative)

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Applying Predictive AnalyticsTo Achieve Greater Value

Most common conditions within population

Patients utilizing the most resources

Most effective treatments

Most effective and efficient caregivers

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“Hidden Opportunity”

“Unknown/Relatively Healthy”

“Critical”

“High Utilizers”

Stat

e-of

-Hea

lth (S

OH)

Risk

High

Low HighMember PMPM Costs

Population Analysis Framework

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A Contemporary Example of Predictive Analytics – VIDEO

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MEASURES

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Deciding Which Measures to Select

> Balanced mix using CVC framework

Patient-oriented process & outcome metrics

Reflects population(s) at risk → practice panel

High leverage to close a care gap

Regulatory or performance requirement

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Measure Selection – Practical Issues Data source availability? - administrative - clinical - survey

Ease of capture?

Comparative data – internal, external?

Benchmarks – risk or case mix adjust?

Inclusion – exclusion criteria defined

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Examples of Measure Types Process - Health Risk Assessment - Colorectal cancer screen - Anti-platelet rx for CAD patient Outcome - Intermediate → HgbA1c - End of episode - Acute → post – MI return to work - Terminal → mortality rate Patient Experience - Access - Overall

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CMS – Measure Types

∙ Process∙ Outcome∙ Intermediate Outcome∙ Patient Reported Outcome∙ Efficiency∙ Cost / Resource Use∙ Structure∙ Composite

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Process of Care Measure Criteria*

1. Sound evidence base the care process leads to improved outcomes

2. Measure accurately captures whether the E-B care process has been provided

3. Process measure has few intervening steps before outcome is realized

4. Measure implementation is unlikely to have unintended consequences

Chassin et al. NEJM, 23 June 2010

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MUC ID Measure Type Program

MUC15-439 Testing for uterine disease prior to obliterative procedure

Process

MIPS

MUC15-1019 Non-recommended PSA-based screening

Process MIPS

MUC15-229 Hep C virus – sustained viral response

Outcome MIPS

MUC15-411 Patient reported outcome > ileo-femoral stent

Patient Reported Outcome

MIPS

MUC15-576 Prevention quality indicator composite

Composite

MIPS, MSSP

CMS- 2015 Measures Under Consideration

See Handout inCoursebook

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Desirable Outcome Measure Features

Outcome Metrics

· Condition specific · Multi-dimensional · Span full care cycle

Cost

· Total costs for full care cycle for condition

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The Outcome Measures Hierarchy*

Long term consequences of treatment

Duration – strength of recovery /Recurrences

Disutility of care or treatment process

Time to Recovery / Normal Activity

Degree of Health or Recovery

Tier 1Health Status Achieved or Retained

Tier 2Process of Recovery

Tier 3Sustainability of Health

Survival

*Porter ME: N Engl J Med 363: 2477, 2010.

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Outcomes Hierarchy – an Example*

Hip Replacement Surgery

Tier 1 – Health Status Achieved – Retained

·Survival………..Mortality rate (inpatient) ·Post-rx care…..Pain management …..Level of physical activity

Tier 2 – Recovery Process

*Porter & Lee: HBR, Oct 2013.

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·Time……..to start treatment …….to return to full physical activity …….to return to work / play (e.g., golf) ·Care Processes…..delays & anxiety …..pain during treatment …..time in hospital …..complications

Tier 3 – Sustainability

·Maintenance of functional status ·Need for revision – replacement ·Long-term consequences

Porter & Lee, HBR, Oct 2013.

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APPLICATIONS

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Measure Selection - Overview

> Balanced mix using CVC framework

Patient-oriented process & outcome metrics

Reflects population(s) at risk → practice panel

High leverage to close a care gap

Regulatory or performance requirement

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Clinical Value Compass*Functional- Physical³- Mental³- Risk status¹

Clinical-Prevention¹-Screening¹-Diagnosis¹-Rx Monitoring¹- Morbidity¹- Mortality¹

Patient Experience- Services -Overall satisfaction³ -Access³- Health benefit(s)³

Cost to Patient- Direct medical²- Indirect personal - social³

modified from Nelson EC, et al. Measuring Outcomes & Costs: The Clinical Value Compass in Practice-Based Learning & Improvement, 2007, JCAHO .

¹ practice report² billing data³ patient self report

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BalancedScorecard

Payer – Patient Mix

PatientExperience

ClinicalProcesses &Outcomes

FunctionalOutcomes

Cost toPatient

Financial Performance

- Access- Overall satisfaction score- Retention rate

- Screening- Prevention- Monitoring- Safety Measures- Care Outcomes

- Full recovery of ability- Return to work- Activities of daily living

- Direct- Indirect, e.g., inability to return to work

- Traditional business – percent & margin- Risk contracts – percent & margin- Operating expenses

- Private / Public (%)- > 65 yo / < 65 yo (%)

Balanced Scorecard for Monitoring Practice

VH MS – MJD – 8 - 14

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Population Health Analysis Framework

“Hidden Opportunity”

“Unknown/Relatively Healthy”

“Critical”

“High Utilizers”

Stat

e-of

-Hea

lth (S

OH)

Risk

High

Low HighMember PMPM Costs

Socio-Economic Related?

Non- Compliance?

Access-to-Care?

Perceived Mental Well-being?

Phase 1 Focus

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QUESTIONS / COMMENTS

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Physician-led Population Health Maturity Cycle

(Where are You?)

FIN

ANCI

AL C

ON

TRIB

UTI

ON

& M

ARGI

N IM

PACT

POPULATION HEALTH MATURITY

Phase II Phase IIIPhase I Phase IV

COPYRIGHT © VITREOSHEALTH ALL RIGHTS RESERVED.

Programs Provider-Driven Patient-EngagementPilots: Payer-driven

S1

S4S7

S6

S5

S2

S3

S1, S2, S3….S7 are Physician Groups

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Factors Driving the Provider-driven Population Health Maturity

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Reliance on Payers

Internal Capabilities

1 2 3 4

Level ofInfluence

PHASES

Progress Toward Functioning as a High Performing PHM Provider Organization

VH MS – MJD – 8 -14