Metrics & Scoring Committee October 21, 2016 Waiver Renewal - - PowerPoint PPT Presentation

Metrics & Scoring Committee

October 21, 2016

Waiver Renewal Updates

Waiver renewal application was resubmitted on August 14th with some technical and language revisions: https://www.oregon.gov/oha/OHPB/Pages/health-reform/cms-waiver.aspx CMS public comment period was open through October 1: https://www.medicaid.gov/medicaid-chip-program-information/by- topics/waivers/waivers_faceted.html Community Health Partnership Advisory Council to be convened in October. Reach high level agreement with CMS on specific policy areas by Winter 2016

• Health related services concept paper
• Extension of the tribal uncompensated care program
• Dual eligible opt-out auto enrollment
• Medical policy proposals

Finalize the waiver renewal in early 2017 with implementation beginning July 1, 2017.

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PCPCH Weighting

4

Recap

• With new PCPCH program standards for 2017, CCO incentive

measure formula needs to be adjusted to reflect the new tiers of recognition.

• The Committee initially discussed formula options in August, then

referred the question to the technical advisory workgroup.

• Today, asking for the Committee’s recommendation for the 2017

measure formula, based on TAG feedback, PCPCH program feedback, and a new proposal.

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Option 5 (proposed via email after Committee meeting)

(Tier 1 members *0) + (Tier 2 members *2) + (Tier 3 members *3) + (Tier 4 and 5 STAR members *4) + 5 STAR members (Total CCO enrollment *4 (not including the tier 1s))

Previous Committee Discussion

• Tier 1 should not count toward the PCPCH measure in 2017
• The measure formula should still give weight to higher tiers of

recognition

• The measure formula should give the most benefit to moving clinics to

5 STAR status, with the caveat that it may take time for all site visits to be completed.

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PCPCH Program Feedback

Option 2 (Tier 1 members *1) + (Tier 2 * 2) + (Tier 3 *3) + (Tier 4 * 4) + (5 STAR *5) (Total CCO enrollment * 5) Rationale

• 5 STAR should remain a separate, heavier part of the numerator,

given the effort required to reach this level of certification.

• It would be inconsistent to have separate Tier 4 and 5 STAR

certifications, but then lump them together in the metric (option 1).

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TAG Feedback

Fielded survey after September TAG meeting. Received responses representing 14 CCOs

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3.5 1 7.5 2 Option 1 Option 2 Option 3 Option 4 Other

“…Our recommendation is for Option 4. Options 1 and 3 do not give the desired weight to achieving 5 STAR, and option 2 lowers the rate too drastically and does not give a true impression of PCPCH performance...Option 4 gives the appropriate weight to achieving 5 STAR while not lowering the rates and threshold too greatly.”

TAG Feedback cont.

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The survey also asked CCOs about whether the 60% threshold should be revised to accommodate any changes in the measure formula. Responses varied:

• Benchmark should either remain the same or be lowered depending on if the

denominator is increased to x5.

• Don’t change the threshold until we can look at performance under the new formula

(i.e., CY 2019 measurement)

• Do not change if selecting option 2; could maybe increase if selecting option 4

(potentially set at 80%).

• Maintain current threshold.
• Lower threshold to 40 or 50%, as new formulas (particularly option 2) will drastically

reduce performance scores.

New Proposal

Adopt a phased in approach that eliminates the inclusion of Tier 1 and 2 in the formula, and provide a gradual, but meaningful path to improvement by modifying the denominator, and then target over time.

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Year Formula Threshold 2017

(Tier 3 members *3) + (Tier 4 members *4) + (5 STAR members *5) (Total CCO enrollment *4)

60% 2018

(Tier 3 members *3) + (Tier 4 members *4) + (5 STAR members *5) (Total CCO enrollment *5)

60% 2019

(Tier 3 members *3) + (Tier 4 members *4) + (5 STAR members *5) (Total CCO enrollment *5)

65%

MEASURING SUCCESS IN THE EARLY LEARNING SYSTEM

David Mandell, Acting Early Learning System Director Tom George, Research Specialist, Early Learning Division October 21, 2016

Measuring Success Charter

Advise the Early Learning Council on the issues, challenges, successes and priorities related to measuring the success of the early learning system and ensuring equitable outcomes for all children, including but not limited to the Early Learning Hubs.

Early Learning System Goals

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 Early Learning System is aligned, coordinated and

family‐centered

 Children arrive at school ready to succeed  Children live in healthy, stable & attached families

Focus Populations: Children under the age of six and their families who are furthest from opportunity

Measuring Success Committee Membership

 Early Learning Council members (2‐3)  Hub leadership (2)  Hub operational staff (2)  Individuals from local early learning programs that partner with Hubs (2)  Individuals with expertise in early learning data (including EI/ECSE) and

early learning programs (2)

 Individual with expertise in health data and health system (1)  Individual with expertise in human services data and state human services

system (1)

 Individual with expertise in k12 education data and system (1)  Individuals with expertise in program evaluation and/or design and

implementation of performance metrics (2)

Measuring Success Committee Membership



ELC members: Pam Curtis, Bobbie Weber



Hub leadership: Cade Burnett, Umatilla‐Morrow Head Start; Dorothy Spence, NW Regional ESD; Kristi May, Linn‐Benton‐Lincoln Early Learning Hub



Hub operational staff: Vacant



Early learning Hub partners: Mellie Bukovsky‐Reyes, educational consulting; Emily Berry, Healthy Families, teen parents, youth services



Expertise in early learning data: Debby Jones, Wasco Co. YOUTHINK



Expertise in health data & systems: Collen Reuland, OR Pediatric Improve. Partner.



Expertise in human services data & systems: Sylvia Gillpatrick, SGE



Expertise in k12 education data & systems: Brian Reeder, OR Dept. of Education



Expertise in program evaluation and/or metrics: Andrew Mashburn, PSU; Jennifer Matheson, NW health foundation

Key Early Learning System Policy, Evaluation & Research Questions

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1) Impact of the Early Learning System on Children and Families 2) Access to Early Learning Services 3) Early Learning System Coordination

Impact of the Early Learning System on Children and Families

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Key Question: Are state‐funded and affiliated services improving healthy development for young children and families furthest from opportunity? Sub Questions: 1.1 How have early learning services impacted children’s developmental progress? Has the developmental progress of children under six improved? 1.2 Are all young children needing developmental supports receiving services, and is it improving the lives of children and families? 1.3 How have early learning services impacted children and families from the parents’ perspective, and are parents actively engaged? 1.4 Are early learning services delivered in a culturally relevant manner? 1.5 How have early learning services differentially impacted children and families furthest from

• pportunity and have disparities been reduced?

1.6 What are the processes for programs’ continuous quality improvement? What is the quality

• f programs, and is quality improving?

1.7 How can technical assistance by the ELD be improved to enhance early learning services?

• Coalescing collective ownership of a shared vision

and outcomes for a defined population of children and families.

• Convening partners from across sectors, working

together towards a common vision, based on shared strategies and data.

• Coordinating effective and aligned systems.

Transformative potential of hubs to positively impact children and families

Access to Early Learning Services

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Key Question: Are early learning investments improving the lives of children and families furthest from opportunity? Sub Questions: 2.1 What state funded and affiliated early learning services are available for children and families furthest from opportunity? 2.2 Are early learning investments prioritized to reach those furthest from opportunity? 2.3 Are state funded and affiliated early learning services located in communities with high concentrations of children and families furthest from opportunity? 2.4 How are early learning services engaging children and families furthest from opportunity? 2.5 Are children and families able to seamlessly transition among early learning services? 2.6 What are the barriers that prevent some children and families furthest from opportunity from participating in state‐funded services?

Early Learning System Coordination

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Key Question: Are early learning services aligned, coordinated, and family centered? Sub Questions: 3.1 How do early learning organizations align and coordinate family services? 3.2 Are children and families able to navigate and seamlessly transition among early learning services? 3.3 What are the barriers to an effectively coordinated and aligned early learning system? 3.4 How are resources blended and braided to achieve collective impact within the early learning system? 3.5 Are culturally‐specific community‐based organizations and services effectively integrated partners in the early learning system?

Measuring Success Committee

Incentive Metrics=

• 5% holdback of Hub Coordination funds totaling $514,000.
• Being disbursed in year 2 of biennium.
• Committee charged with developing incentive metrics

recommendations.

• Hub system is still new.
• Hubs have had varying amounts of time to mature.
• Cross‐sector partnerships and strategies that have

been implemented by hubs need more time to accumulate impact and measurable outcomes.

Developmental Stage of Hubs

• New performance metrics, including baselines and targets, are new

in hub contracts this year.

• The Hubs are gaining experience setting targets and determining

ambitious but achievable goals.

• Data sources for many metrics are under development, particularly

cross‐sector work.

• The metrics themselves are being actively field‐tested by hubs.

Current performance metrics and data

Incentive metrics should demonstrate that the Hub and its community partners are taking actions that show collective

• wnership of a shared vision and shared outcomes for a

commonly defined population of children and families.

Eastern Oregon Focused Childcare Networks

Goal

Incentive metrics should:

 Reflect the impact of Hubs in a way that is focused, transformative,

and clear about where the Hubs have impact.

 Reflect the necessity of collective action, fostering engagement

from the community and across sectors.

 Reflect the developmental stage of the Hubs and Hub system.  Have a data source that is readily accessible, reliable and valid.  Be able to be measured/assessed objectively and consistently

across Hubs.

 Should not prioritize one Hub strategy or area of focus over another.

Guiding Principles

Goals of the Kindergarten Assessment

 To provide local and statewide information to state‐level policy makers,

communities, schools, and families about the literacy, math, self‐ regulation, and interpersonal skills of entering kindergarteners.

 To provide essential information on Oregon’s entering kindergarteners’

strengths and to identify gaps in key developmental and academic skills to inform early learning and K‐12 systems decisions and to target instruction, professional development, resources, and supports on the areas of greatest need.

 To provide a consistent tool to be used across the state to identify

• pportunity gaps in order to inform schools, districts, early learning

hubs, communities, and policy‐makers about how to allocate resources to the communities with the greatest need and to measure progress in the years to come.

What does the KA measure?

 Early Literacy (direct assessment)

 Letter names  Letter sounds

 Early Math (direct assessment)

 Numbers and operations

 Approaches to Learning (observational assessment)

 Child Behavior Rating Scale

Self‐Regulation

• Self-regulation is

measured by items 1-10 on the CBRS

• Average is 3.5

(between “sometimes” and “frequently or usually”).

• Nearly a quarter
• f students are

rated below “sometimes.”

Letter names by race/ethnicity

Letter Names average scores range from 10 (Hispanic) to 30 (Asian)

5 10 15 20 25 30 35 Asian African American Hispanic Am Indian/AK Native Multi-racial Pacific Islander White Total

Average Letter Names Score by Race/Ethnicity

 EL Hub scores are lower than state average for every group for every year data is available.  Hispanic children scored the lowest in English Letter Names for two consecutive school years (2014-2015 and 2015-2016)

Hub Communities using Data: Linn, Benton, Lincoln County Hub

 Early Math is the only category where we don't see a clear gender discrepancy.  Native American and Hispanic children consistently score below the Hub and state average.

Pharmacy / MTM Continued

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Proposed Measure

In developing the specifications for today’s discussion, subject matter experts are recommending two changes from what was proposed in September:

• Combination of Comprehensive Medication Review + Targeted Medication

Reviews, rather than just Comprehensive Medication Review, to reach multiple populations in need of pharmacist-provided medication management.

• Move from claims-based measure to chart review, to reflect multiple

platforms and data sources for how these services are provided across the state.

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Public testimony

Preventing obesity in Oregon

Luci Longoria

Health Promotion Manager Oregon Public Health Division

Metrics & Scoring Committee Meeting October 21st, 2016

Leading causes of death in Oregon

7,862 6,523 1,958 1,821 1,796 1,412 1,083 781 Cancer Heart Disease CLRD Stroke Unintent. Injuries Alz. disease Diabetes Suicide

Over 60% of all deaths in Oregon are caused by chronic diseases.

Source: Oregon death certificates (2014)

Actual causes of death in Oregon

Tobacco use Obesity, poor diet, and physical inactivity Alcohol use Other 69% 22%

5%

4%

Source: What is Killing Oregonians? The Public Health Perspective CD Summary 61, no. 15 (July 17, 2012)

Focus on risk factors of chronic disease

Behavior Disease

36% 29% 28% 27% 12% 27% 16% 17% 20% 15%

Obesity Cigarette smoking Physical inactivity Daily sugary drink consumption Binge drinking

Medcaid members General population

Health risk factors among Oregon adults, 2014

Source: 2014 MBRFSS

11% 27%

0% 5% 10% 15% 20% 25% 30%

1990 1994 1998 2002 2006 2010 2014

Obesity among Oregon adults, 1990‐2014

Obesity has increased by nearly 140% since 1990

Percent obese

Source: Oregon Behavioral Risk Factor Surveillance System Note: Vertical dashed line (‐‐‐) indicates change in survey methods (2010). Estimates are age‐adjusted.

7% 13% 7% 11%

0% 4% 8% 12% 16%

2001 2003 2005 2007 2009 2013

Obesity among Oregon youth, 2001‐2015

Percent obese

Source: Oregon Healthy Teens Survey

8th graders 11th graders

14% 26% 34% 34% 40%

Obesity among Oregon adults by race and ethnicity, 2010‐2011

American Indian or Alaska Native Black or African American Latino White Asian or PI

Source: 2010‐2011 Oregon BRFSS Race Oversample Note: Estimate are age‐adjusted. Race and ethnicity categories are mutually exclusive.

20% 31% 30% 27%

Obesity among Oregon adults by education

Less than high school High school graduate Some college College graduate

Source: 2014 Oregon BRFSS Note: Estimate are age‐adjusted.

General population = 27%

33% 38% 39% 39% 42% 43%

Obesity among Oregon adults with selected chronic diseases and risk factors, 2014

Source: Oregon BRFSS Estimates are age‐adjusted.

Diabetes Heart Disease High Blood Pressure Asthma High Cholesterol Arthritis

General population = 27%

41.3% 38.8% 41.0% 40.1% 42.3% 34.3% 32.4% 31.5% 34.2% 38.8% 36.3% 28.0% 40.8% 34.9% 37.8% 34.9% 0% 10% 20% 30% 40% 50%

Yamhill CCO Willamette Valley Community… Western Oregon Advanced Health Umpqua Health Alliance Trillium PrimaryHealth of Josephine County PacificSource ‐ Gorge PacficSource ‐ Central Jackson Care Connect Intercommunitiy Health Network Health Share of Oregon FamilyCare Eastern Oregon Columbia Pacific Cascade Health Alliance AllCare Health Plan

Percent of Medicaid members who are obese by CCO

Source: 2014 Oregon Medicaid BRFSS

10% 36% 39% 40% 44% 46%

Obesity among Oregon adult Medicaid recipients by race and ethnicity

Pacific Islander American Indian or Alaska Native Latino White Asian

Source: 2014 Oregon Medicaid BRFSS Note: Race and ethnicity categories are mutually exclusive.

African American

19% 16%

0% 5% 10% 15% 20% 25%

1996 2002 2006 2010 2014

Physical inactivity (NLTPA) among Oregon adults, 1996‐2013

Percent reporting no physical activity in past 30 days

Source: Oregon Behavioral Risk Factor Surveillance System Note: Vertical dashed line (‐‐‐) indicates change in survey methods (2010). Estimates are age‐adjusted. NLTPA = No Leisure Time Physical Activity

60% 58% 49% 50%

0% 20% 40% 60% 80%

2005 2008 2012 2015

Participation in 1 hour of aerobic physical activity most days (5+) of the week, Oregon youth, 2005‐2015

Percent who get 60 mins of PA 5+ days per week

Source: Oregon Healthy Teens

11th graders 8th graders

15% 13%

0% 5% 10% 15% 20% 25%

2010 2011 2012 2013 2014

Daily soda consumption among Oregon adults, 2010‐2014

Percent consuming 7+ sodas per week

Source: Oregon Behavioral Risk Factor Surveillance System Estimates are age‐adjusted.

17% 18% 19% 21% 24% 24% Daily soda consumption among Oregon adults by selected demographics and health risk factors, 2014

Source: Oregon BRFSS Estimates are age‐adjusted.

Current smoker Less than HS education No health insurance Unemployed Low SES Obese

General population = 13%

What can we do?

Low High

The Health Impact Pyramid

Population impact Individual effort

Low High High Low

Priorities:

• Prevent and reduce

tobacco use

• Slow the increase of
• besity
• Improve oral health
• Reduce harms associated

with substance use

• Prevent deaths from

suicide

• Improve immunization

rates

• Protect the population

from communicable diseases

Population interventions to slow the increase of obesity

Strategy 1: Increase the price of sugary drinks Strategy 2: Increase adoption of standards for healthy foods and beverages, physical activity and breastfeeding Strategy 3: Increase opportunities for physical activity Strategy 4: Improve the availability of affordable and healthy food and beverage choices

Health equity interventions to slow the increase of obesity

Strategy 1: Increase the number of DHS/OHA mental and behavioral health providers that adopt physical activity and nutrition standards Strategy 2: Increase the number of people at high risk for Type 2 diabetes who participate in the National Diabetes Prevention Program Strategy 3: Increase access to parks and recreational facilities Strategy 4: Increase access to healthy foods

Health system interventions to slow the increase of obesity

Strategy 1: Create incentives for plans and providers to decrease the prevalence of obesity Strategy 2: Increase the number of hospitals that meet baby‐friendly standards Strategy 3: Ensure coverage for weight management and chronic disease self‐ management programs Strategy 4: Adopt and implement nutrition standards at plans, clinics and hospitals

SHIP Obesity measures

Obesity prevalence among 2 to 5 year olds Obesity prevalence among youth Obesity prevalence among adults Diabetes prevalence among adults 15.5% 14.5% 10% (8th) 9% (8th) 11% (11th) 10% (11th) 27% 25% 9% 8% Baseline Target (2019)

Recommended measures

Adult obesity

• CCO enrollees aged 18
• r older with a BMI of

30 or above Youth obesity

• CCO enrollees under

the age of 18 with a BMI >=95th percentile

MPOWER Framework

• Monitor outcomes in population
• Promote healthy eating and active living
• Protect people from unhealthful food and unsafe

places

• Offer support for people to manage their weight
• Warn of the dangers of sugary drinks and

unhealthful foods

• Enforce laws that enable healthy eating and active

living

• Raise the price of unhealthful foods and lower the

price of healthful foods

Questions?

Thank you!

Luci Longoria Health Promotion Manager Oregon Public Health Division luci.longoria@state.or.us 971‐673‐1064

NQF Obesity-Related Measures

NQF # Measure Name Data Source 0023 BMI in adults >18

% of adults with valid BMI documentation in past 24 months

EHR

2601 BMI screening & follow up for people with SPMI

% of adults with SPMI with BMI documentation in past 24 months, and follow up for those identified as obese

EHR

1349 Child overweight or obesity status based on parental report of BMI

% of children ages 10-17 who are overweight or obese

National Survey on Children’s Health

0421 / 3039 Preventive care and screening: BMI screening & follow up

% of adults with BMI documentation in past 6 months AND when BMI is

• utside normal parameters, documented follow up plan exists.

EHR / eCQM (Meaningful Use)

0024 Weight assessment & counseling for nutrition and physical activity for children / adolescents

% of children ages 3-17 who had outpatient visit and evidence of: (1) BMI percentile documentation; (2) counseling for nutrition; (3) counseling for physical activity during the measurement year.

EHR / eCMQ (Meaningful Use)

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Developmental Measure: Limiting Gain in BMI

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RAND is developing an obesity measure for Medicare Advantage plans that may be of interest. Rather than focusing on reducing prevalence overall, this new measure focuses on limiting weight gain to within 1.0 BMI unit (~6 lbs) within a 2 year follow-up period. Researchers believe this measure has the potential to go beyond measures of providing advice on diet and physical activity, and help health plans reliably and validly measure success in limiting weight gain among their members. Staff have reached out to the measure developers about using this measure in Oregon.

Next Meeting: December 2nd Retreat November 18th meeting cancelled