Developing an ACO Measure Set for Maine

Michael Bailit

December 10, 2013

Agenda:

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1. National Measures Landscape: Buying Value Analysis

2. Measure Selection Processes in Other States

3. Key Policy Decisions in Measure Selection

4. Potential Next Steps for Maine’s Measure Selection Process

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The Buying Value study

Buying Value…– is a private purchaser-led project to accelerate

adoption of value purchasing in the private sector;

– believe that selection of appropriate performance measures is fundamental to the success of a value-based payment system, and

– convened a payer and purchaser group to promote measure alignment among private and public purchasers, health plans, providers, and state and federal officials.

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Why is lack of alignment problematic?

The measure misalignment creates what is experienced as “measure chaos” for providers subject to multiple measure sets, with related accountability expectations and sometimes financial implications.

Mixed signals from the market make it difficult for providers to focus their quality improvement efforts and lead them to tune out some payers and some measures.

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Background on the Buying Value analysis

As part of its effort to promote measure alignment, Buying Value commissioned a recent report from Bailit studying the alignment of state-level measure sets.

To complete this analysis, Bailit gathered 48 measure sets used for different program types, and designed for different purposes, across 25 different states and three regional collaboratives. – Program type examples: ACO, PCMH, Medicaid managed

care plan, exchange– Program purpose examples: reporting, payment, reporting

and payment, multi-payer alignment

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Measure sets by state

Reviewed 48 measure sets used by 25 states.

Intentionally gave a closer look at two states: CA and MA.

1. AR

2. CA (7)

3. CO

4. FL

5. IA (2)

6. ID

7. IL

8. LA

9. MA (8)

10. MD

11. ME (2)

12. MI

13. MN (2)

14. MO (3)

15. MT

16. NY

17. OH

18. OK

19. OR

20. PA (4)

21. RI

22. TX

23. UT (2)

24. WA

25. WI

Note: If we reviewed more than one measure set from a state, the number of sets included in the analysis is noted above.

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Analysis included two measure sets from Maine

Systems Core Measure Set obtained from the Maine Health Management Coalition

Measure set used in Maine’s multi-payer PCMH pilot

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Measure sets significantly ranged in size

Note: This is counting the measures as NQF counts them (or if the measure was not NQF-endorsed, as the program counted them).

108 measures

29 measures

3 measures

[max]

[min]

[avg]

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Buying Value study findings

There are many measures in use today.– In total, we identified 1367 measures across the 48 measure

sets.– We identified 509 distinct measures.

Current state and regional measure sets are not aligned. – Only 20% of the 509 distinct measures were used by more

than one program.

Non-alignment persists despite preference for standard measures.– Most measures are from a known source (e.g., NCQA,

AHRQ) and are NQF-endorsed.

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Access, affordability & in-approp care

11%Comm & care coordination

5%Health and well-

being14%

Infrastructure4%

Person- centered11%

Safety19%

Sec. Prevention and Treatment

28%

Utilization8%

Distinct measures by domainn = 509

The distinct measures were evenly distributed across measure domains

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States prefer to use standard measures

Standard59%

Modi-fied17%

Home- grown15%

Undeter-mined6%

Other3%

Measures by measure typen = 1367

Standard: measures from a known source (e.g., NCQA, AHRQ)

Modified: standard measures with a change to the standard specifications

Homegrown: measures that were indicated on the source document as having been created by the developer of the measure set

Undetermined: measures that were not indicated as “homegrown”, but for which the source could not be identified

Other: a measure bundle or composite

Defining Terms

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Finding: programs show a strong preference for NCQA’s HEDIS measures

HEDIS66%

Standard and modified non-

HEDIS11%

Homegrown14%

Undetermined6%

Other3%

NCQA (HEDIS) measures and the types of the non-HEDIS measures

n = 1367

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But only 16% of the distinct measures come from HEDIS

HEDIS16%

Resolution Health

5%

AHRQ4%

CMS4%

AMA- PCPRI3%

Standard source with less than 10 measures

13%

Homegrown39%

Undetermined15%

HEDIS measures and the types of the non-HEDIS measures

n = 509

In other words, the 81 HEDIS

measures are used over and over

again.

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Finding: little alignment across the measure sets

Not shared80%

Shared20%

Number of distinct measures shared by multiple measure sets

n = 509

Very little coordination/ sharing across the measure sets

Of the 1367 measures, 509 were “distinct” measures

Only 20% of these distinct measures were used by more than one program

How often are the “shared measures” shared?

Measures not shared 80%

2 sets; 28; 6%

3-5 sets; 20; 4%6-10 sets; 21; 4%

11-15 sets; 14; 3%

16-30 sets; 19; 4%

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Only 19 measures were shared by at least 1/3 (16+) of the measure sets

Most measures are not shared

Not that often…

6 Preventative Care

Categories of the 19 most frequently used measures

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•Breast Cancer Screening

•Cervical Cancer Screening

•Childhood Immunization Status

•Colorectal Cancer Screening

•Weight Assessment and Counseling for Children and Adolescents

•Tobacco Use: Screening & Cessation Intervention

7 Diabetes Care

•Comprehensive Diabetes Care (CDC): LDL-C Control <100 mg/dL

•CDC: Hemoglobin A1c (HbA1c) Control (<8.0%)

•CDC: Medical Attention for Nephropathy

•CDC: HbA1c Testing

•CDC: HbA1c Poor Control (>9.0%)

•CDC: LDL-C Screening

•CDC: Eye Exam

1 Mental Health/Sub-

stance Abuse

•Follow-up after Hospitalization for Mental Illness

1 Patient Experience

•CAHPS Surveys(various versions)

4 Other Chronic

Conditions

•Controlling High Blood Pressure

•Use of Appropriate Medications for People with Asthma

•Cardiovascular Disease: Blood Pressure Management <140/90 mmHg

•Cholesterol Management for Patients with Cardiovascular Conditions

Programs are selecting different subsets of standard measures

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ProgramA

ProgramB

ProgramC

ProgramD

ProgramE

While the programs may be primarily using standard, NQF-endorsed measures, they are not selecting the same standard measures Not one measure was used by every program

– Breast Cancer Screening was the most frequently used measure and it was used by only 30 of the programs (63%).

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State measure set variation

Regardless of how we cut the data - by program type, program purpose, domain, and within CA and MA - the

programs were not aligned.

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Conclusions from the Buying Value study

1. Measures sets appear to be developed independently without an eye towards alignment with other sets.

2. The diversity in available measures allows states and regions interested in creating measure sets to select measures that they believe best meet their local needs.

3. Even the few who seek to create alignment struggle due to a paucity of tools to facilitate such alignment.

4. Alignment with other programs won’t happen by chance; it must be a goal that is considered throughout the measure set development process.

Agenda:

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1. National Measures Landscape/ Buying Value Analysis

2. Measure Selection Processes in Other States

3. Key Policy Decisions in Measure Selection

4. Potential Next Steps for Maine’s Measure Selection Process

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Measure selection in other states

Bailit has supported multiple states and regions through a measure selection process.

On the next slides we will draw from four of those experiences:– Colorado– Oregon– Pennsylvania (AF4Q South Central Pennsylvania)– Vermont

The slides that follow will provide a brief overview of the different approaches to measure selection and discuss how the factors influenced the unique outcomes.

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Case Example #1: Colorado Medicaid

Status: Measure set in development

Purpose: Key performance indicator measure set for Regional Care Collaborative Organizations (RCCOs) within the Medicaid program

Type of process: Informal internal deliberation, to be followed by external stakeholder vetting

Stakeholders involved: State Medicaid agency staff, thus far

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Case Example #1: Colorado Medicaid

Key criteria for measure selection:– Distribution across target populations and within

domains of interest– Alignment with other state programs– Feasibility

Unique interests:– Coordination of care measures– Social determinants of health measures– Inclusion of “creative” non-standardized measures

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Case Example #2: Oregon Medicaid

Status: Two largely overlapping measure sets implemented 1-1-13: CMS waiver accountability and CCO incentive pool

Purpose: Incentive measure set for Coordinated Care Organizations (CCOs) required by CMS as a part of its Medicaid section 1115 waiver

Type of process: Formal, state-staffed committee process

Stakeholders involved: Legislatively-mandated physician advisory committee. CCO representatives and health services researchers.

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Case Example #2: Oregon Medicaid

Key criteria for measure selection:– Representative of the array of services provided

and beneficiaries served by the CCOs– Measures must be valid and reliable – Reliance on national measure sets whenever

possible

Unique interests:– “Transformative” potential– State-specific opportunities for improvement

relative to national benchmarks

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Case Example #3: AF4Q South Central Pennsylvania

Status: Completed but not implemented

Purpose: Multi-payer aligned commercial measure set for PCMHs in the region

Type of process: Formal committee process managed by AF4Q staff and key stakeholders

Stakeholders involved: One leading payer and one leading hospital system, with intermittent involvement of other local health plans, hospital systems and employers

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Case Example #3: AF4Q South Central Pennsylvania

Key criteria for measure selection:– Distribution across domains of interest– Alignment with federal measure sets– Feasibility

Unique interests:– Alignment with pre-existing stakeholder-developed

measure sets– Relevance for patient-centered medical homes

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Case Example #4: Vermont multi-payer ACO

Status of Project: Completed and slated to be implemented 1-1-14

Purpose: Measure set for coordinated Medicaid and commercial insurer ACO pilot program

Type of process: Formal, state-staffed committee process

Stakeholders involved: Potential ACOs, payers (commercial and Medicaid), consumer advocates, provider associations, quality improvement organization

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Case Example #4: Vermont multi-payer ACO

Key criteria for measure selection:– Representative of the array of services provided and

beneficiaries – NQF-endorsed measures that have relevant

benchmarks whenever possible

Unique interests:– Alignment with Medicare Shared Savings Program– Alignment with HEDIS– State-specific opportunities for improvement relative

to national benchmarks– Use of systems measures, utilization measures and

pending measures

Agenda:

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1. National Measures Landscape/ Buying Value Analysis

2. Measure Selection Processes in Other States

3. Key Policy Decisions in Measure Selection

4. Potential Next Steps for Maine’s Measure Selection Process

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Six Key Policy Decisions in Measure Selection

1. Intended use

2. Standardized vs. transformative/creative measures

3. Data source: clinical data vs. claims vs. survey

4. Operationalizing clinical data measures: electronic capture vs. sampling methodology

5. Areas of importance vs. opportunities for improvement

6. Alignment with other programs vs. program-specific measures

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1. Intended use

Measures can be used for multiple purposes. The first question to ask when forming a measure set is “measurement to what end”?

Measures may be may be more appropriate for some uses and not others at a particular point in time.

Some potential measure uses:– Assessing performance relative to goals and expectations– Qualifying and/or modifying payment– Observing states and trends

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2. Standardized vs. “innovative” measures

Pros Cons

Standard measures

• Measure already vetted for validity and reliability

• Enables comparisons with other programs

• Potentially offers national and/or regional benchmark information

• Often facilitates implementation due to clearly defined specifications

• Facilitates alignment with other measure programs

• May not offer an assessment of a specific performance attribute of interest

Innovative measures

• Enables programs to customize measures to suit their specific needs

• Offers a measurement solution for areas in which there is a dearth of standard measures

• Can be used to develop future standardized measures

• Measures may not be valid or reliable

• Do not support comparisons with other programs, benchmarking or alignment across programs

• May be challenging to implement

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3. Data source: clinical data vs. claims vs. patient survey The source of measures often depends on program

capacity, electronic infrastructure and resources. Pros Cons

Clinical data-based measures

• Provides opportunity to assess clinical processes and outcomes not found in claims

• Requires either sophisticated electronic reporting system or resource-intensive chart review

Claims-based measures

• Relatively easy to implement• Baseline data easier to generate

than for clinical data

• Generally limited to process measures and some outcome measures

Survey measures

• Only mechanism for assessing patient experience

• Resource-intensive• Can be burdensome to

patients if other surveys are commonly administered

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4. Operationalizing clinical data measures: electronic capture vs. sampling methodology

Pros Cons

Electronic capture

• Once infrastructure is in place, can potentially generate a low administrative burden

• Requires implementation of a sophisticated electronic reporting system – especially for ACOs with many independent providers using different EHRs

• Requires substantial upfront investment

Sampling methodology

• Relatively straight-forward to implement

• Most HEDIS measures have established protocols for chart review

• Resource-intensive• Administratively burdensome• Cost is recurring and does

not diminish over time

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5. Areas of importance vs. opportunities for improvement Should the program focus on measures for areas of

importance regardless of baseline performance or focus on known opportunities for improvement?

Pros Cons

Areas of importance (conditions, procedures etc.)

• Assesses what matters most to patient health

• Can facilitate alignment with other measure programs

• If performance is strong, and there aren’t opportunities for improvement, measurement results won’t have operational application.

Opportunities for improvement

• Focus important incentive dollars where they can have an impact on quality

• May lead the program to focus on niche populations

• May create misalignment with other programs

• Requires baseline and benchmark information

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6. Alignment with other programs vs. program-specific measures

Pros Cons

Aligned measures

• Facilitates system reform by focusing providers on specific quality goals through consistent market signals

• Enables comparisons with other programs

• Potentially offers national and/or regional benchmark information

• May not address the priority goals of the program

• May not offer the precise measurement tool desired

Program-focused measures

• Enables programs to encourage providers to focus on areas that would otherwise be forgotten

• Enables programs to select measures to address their specific priorities

• May foster “measure chaos” by sending mixed signals to providers about where they should put their focus

• May be deprioritized or ignored if the populations or related measure incentives are too small

Agenda:

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1. National Measures Landscape/ Buying Value Analysis

2. Measure Selection Processes in Other States

3. Key Policy Decisions in Measure Selection

4. Potential Next Steps for Maine’s Measure Selection Process

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Potential next steps for creating an ACO measure set for Maine

1. Determine the type of process and the stakeholders to be involved.

2. Establish a timeline for completion and create a work plan to meet appropriate deadlines.

3. Agree on the goals/objectives for the measure set.

4. Establish measure selection criteria.

5. Utilize your “measures library” that includes all measure sets currently in use in Maine or recommended for consideration.

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Potential next steps for creating an ACO measure set for Maine

6. Use the selection criteria to remove measures from the library

7. Agree upon a draft measure set

8. Review the draft set to determine whether it achieves the program’s goals, making adjustments as necessary.

9. Finalize the measure set

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Final considerations

Reaching agreement on a core measure set takes considerable time and effort – many facilitated meetings, staff work to prepare for each meeting and a willingness to compromise.

Measure sets are not static. They need to be reviewed each year and modified based on implementation experience, changing clinical standards, changing priorities, and (hopefully) improved performance.

Contact information

Michael Bailit, MBA

• mbailit@bailit-health.com

• 781-453-1166