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Weaving New Quality Components into the Fabric of Coverage for Pregnant Women and Children
National Association of Medicaid Directors 2015 Fall Conference
November 3, 2015
Enrique Martinez-Vidal
Vice President for State Policy and Technical Assistance
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Today’s Goals Brief overview of child health quality measures
and reporting
National evaluation of the CHIPRA Quality Demonstration
Measuring early elective deliveries and complicated births
Data linkages project
Maternal and Infant Health Initiative Looking to the future
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2015 Child Core SetPreventive CareChlamydia Screening in Women (CHL)
Childhood Immunization Status (CIS)
Well-Child Visits in the First 15 Months of Life (W15)
Immunizations for Adolescents (IMA)
Developmental Screening in the First Three Years of Life (DEV)
Well-Child Visits in the Third, Fourth, Fifth and Sixth Years of Life (W34)
Human Papillomavirus Vaccine for Female Adolescents (HPV)
Adolescent Well-Care Visit (AWC)
Care of Acute and Chronic Conditions Weight Assessment and Counseling for Nutrition and Physical Activity for Children/Adolescents – Body Mass Index Assessment for Children/Adolescents (WCC)
Medication Management for People with Asthma (MMA)
Ambulatory Care – Emergency Department (ED) Visits (AMB)
Experience of Care Consumer Assessment of Healthcare Providers and Systems (CAHPS®) 5.0H (Child Version Including Medicaid and Children with Chronic Conditions Supplemental Items) (CPC)
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2015 Child Core SetMaternal and Perinatal Health Pediatric Central Line-Associated Bloodstream Infections – Neonatal Intensive Care Unit and Pediatric Intensive Care Unit (CLABSI)
PC-02: Cesarean Section (PC02)
Live Births Weighing Less Than 2,500 Grams (LBW)
Frequency of Ongoing Prenatal Care (FPC)
Prenatal & Postpartum Care: Timeliness of Prenatal Care (PPC)
Behavioral Health Risk Assessment (for Pregnant Women) (BHRA)
Behavioral HealthFollow-Up Care for Children Prescribed Attention-Deficit/Hyperactivity Disorder (ADHD) Medication (ADD)
Follow-Up After Hospitalization for Mental Illness (FUH)
Child and Adolescent Major Depressive Disorder: Suicide Risk Assessment (SRA)
Oral Health Prevention: Dental Sealants for 6–9 Year-Old Children at Elevated Caries Risk (SEAL)
Percentage of Eligibles Who Received Preventive Dental Services (PDENT)
Access to CareChild and Adolescents’ Access to Primary Care Practitioners (CAP)
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Measure Specifications
Measures that states report to CMS should include data on entire population of children in Medicaid/CHIP in the state
Two-thirds are based on HEDIS health plan measures Data sources:
– Primarily Medicaid/CHIP administrative data (enrollment and claims or managed care encounters)
– Some measures can use HEDIS hybrid methods (administrative data plus medical chart review)
– Some perinatal measures require vital records data – States can link to other administrative data sources, including
immunization registries – One survey-based measure (CAHPS) – Two EHR measures added in 2013 and 2015
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States’ Quality Measurement and Reporting Strategies
Calculate measures
Use measures to drive QI
Improve quality of care
• Report results to stakeholders• Align QI priorities• Support provider-level improvement
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Child Core Set: Reporting on Child Health Quality (FFY 2013)
All states reported 2 or more measures 33 states reported at least 13 7 states reported 24 measures 2 states (NC & SC) reported 25 measures Median # of measures reported by states: 16 (up
from 12 in 2011) Completeness is improving: 41 states now include
both Medicaid and CHIP populations in at least 1 measure (up from 34 in 2011)
Most frequently reported: access to primary care, well-child visits, use of dental services
Source: 2014 Annual Report on the Quality of Care for Children in Medicaid and CHIP
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Child Core Set Fills a Gap by Providing Uniform State-level Measures for Children Measure set for voluntary annual reporting by
Medicaid and CHIP agencies (24 measures in 2015) Updated annually Includes: access to care, preventive care, maternal &
perinatal care, care of acute & chronic conditions, oral health, experience of care
Data sources: Medicaid/CHIP admin data, HEDIS hybrid methods, vital records data, immunization registries, CAHPS, EHRs
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AHRQ-CMS Pediatric Quality Measures Program (PQMP)
Created under CHIPRA 2009 Following identification of the initial Child Core Set in 2010:
– AHRQ-CMS partnership to:• Develop future enhanced and improved Child Core Sets• Provide for development of new measures for use by others public and
private programs, plans, providers, and patients– Process: Cooperative agreement (grant) awards to:
• 7 AHRQ-CMS PQMP Centers of Excellence• Duration: February 2011-February 2016 (for most)
– Two CHIPRA quality demo grantees (IL, MA) are undertaking new quality measure development as part of their grants
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PQMP Accomplishments: Measures, Science of Measurement, and Dissemination
Multiple measures on different topics– Prenatal care– Children with special health care needs– Mental Health
Science– Publications: http://www.ahrq.gov/policymakers/CHIPRA/chipra-
publications.html– Many conference presentations
Dissemination– Care Coordination Measures for Children with Medical Complexity:
CHIPRA Webinar– Adoption of the updated Child Core Set
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CHIPRA Quality Demonstration Grants
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CHIPRA Quality Demonstration Grants Children’s Health Insurance Program Reauthorization
Act of 2009 – $100 million program– One of the largest federally funded efforts focused on health
care for children 5-year grants awarded by CMS
– 10 grants that included 18 states total– Feb 2010-Feb 2015, with some extensions– Approximately $10 million per grantee
National Evaluation – CMS-funded; Overseen by AHRQ– Mathematica, AcademyHealth, Urban Institute– Aug 2010-Sept 2015, with continuation through mid-2017
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Projects Pursued by Demonstration States (#1)
Quality Measures Reporting (10 states) Service Delivery
– Testing and improving provider-based models (14 states)
– Developing, improving, and sustaining care management entities for children with serious emotional disorders (3 states)
Health Information Technology (14 states)– Developing and enhancing current health IT applications, or
providing incentives for their adoption and use
– Analyzing health IT data, and using analyses to develop QI activities
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Projects Pursued by Demonstration States (#2)
Electronic Health Records (2 states)– Evaluating the model EHR format for children
Other (11 states)– Improve services for youth with complex behavioral needs
– Develop stakeholder collaborations/partnerships
– Focus on School-based Health Centers
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Ten Demo States Implemented Quality Measures Projects
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Measure-focused Demo States Saw Greater Increase in Median # of Reported Measures
0
5
10
15
20
25
FFY 2010 FFY 2011 FFY 2012 FFY 2013
Med
ian
num
ber o
f mea
sure
s
Reporting period
Measure-focused demonstration states (n = 10)Other demonstration states (n = 8)Non-demonstration states and DC (n = 33)
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Demo States Used a Variety of Strategies to Expand Measure Reporting
Hiring dedicated computer programmers for technical aspects of measure calculation
Contracting with Medicaid managed care plans and EQROs to support reporting
Supporting pay-for-reporting programs
Fielding CAHPS more systematically
Developing standard procedures to assemble multiple data files and check their accuracy
Comparing performance with national benchmarks
Establishing statewide group to provide oversight
Identifying variations and monitor changes in performance
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State Experiences: Maine Increased reported measures from
14 in 2010 to 18 in 2014– Used HIE data to calculate measures– Added billing code modifier to
distinguish between global developmental and autism screenings to report rates separately
Formed a stakeholder workgroup, Maine Child Health Improvement Partnership
Disseminated annual reports on 21 measures (18 from Child Core Set)
Implemented strategies to improve measure performance
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State Experiences: Massachusetts Reported on 22 out of 26 measures in
2014– Linked data from demo practices,
health plans, and the state’s database on Medicaid and commercial data
Fielded a survey on caregiver perceptions of care in Medicaid and CHIP (patient experience measure)
Produced quality measure reports for practices, families, Medicaid/CHIP policymakers, and commercially insured patients– Solicited feedback on usability via
interviews with practices and focus groups with families and used info to improve reports
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State Experiences: North Carolina Increased reported measures from 2
in 2010 to 25 in 2014– Leveraged data from various state
agencies Improved existing practice-level
quality reports Using pediatric QI specialists to
analyze network- and practice-level data and work with practices to set QI goals, NC reported:– Improved care quality in over 200
practices– Improved performance on quality
measures statewide in 15 months– Demo staff believe that collaboration
between the QI specialists and practices contributed to the changes
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Demo States Encountered Similar Challenges
Combining data from different programs/sources– Medicaid FFS, Medicaid MCOs, CHIP (if separate
agency)
Linking state data sources– Vital records, state immunization registry
Reporting measures from EHRs Adapting state-level measures to practice-level for
QI activities
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Key Takeaways Calculating the measures took more time and
resources than states anticipated Some measures were more challenging than others
But… States can overcome many of the challenges to
reporting the Child Core Set measures if they invest in data quality and reporting systems, identify staff or contractors who have expertise in quality measurement, and make use of TA and financial support
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Primary Care Providers & Child Health Care Quality Reports
→Survey of pediatricians and family physicians providing care for children in Medicaid & CHIP
→Two demonstration states (NC, PA) and one comparison state (OH)
→Questions about physicians’ experiences with and attitudes toward pediatric quality reports
→727 physicians responded (response rate: 45%)
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Primary Care Providers & Child Health Care Quality Reports
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Primary Care Providers & Child Health Care Quality Reports
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How States Are Using the Child Core Set Measures to Improve Quality
Reporting Results to Stakeholders – Used existing data sources– Created targeted reports for different stakeholders
Aligning Measures and QI Priorities – Formed multi-stakeholder QI workgroups– Encouraged consistent quality reporting standards across programs – Required managed care organizations to meet quality benchmarks
Supporting Provider-Level Engagement– Paid providers for reporting measures and demonstrating
improvement
– Changed reimbursement to support improvements– Hosted learning collaboratives– Provided individualized TA
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Learn More About the CHIPRA Quality Demo
http://www.ahrq.gov/policymakers/chipra/demoeval/index.html
Evaluation Highlights:– How are CHIPRA quality Demonstration States using
quality reports to drive health care improvements for children?
– How are the CHIPRA Quality Demonstration States encouraging health care providers to put quality measures to work?
– How are CHIPRA Quality Demonstration States improving perinatal care?
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Early Elective Deliveries and Complicated Births
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Measuring Early Elective Deliveries in Medicaid
CMS made EEDs a priority measure in the Child Core Set
Medicaid Medical Directors Learning Network Study– 12 states provided Medicaid admin data linked
with vital statistics data– 10 states provided only vital statistics data
EEDs accounted for almost 9% of births paid for by Medicaid
Source: Tara Trudnak Fowler, Jeff Schiff, Mary S. Applegate, Katherine Griffith, and Gerry L. Fairbrother “Early Elective Deliveries Accounted for Nearly 9 Percent of Births Paid For Medicaid” Health Affairs, 33, no.12 (2104)
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Early Elective Deliveries in Medicaid: Policy Implications
Downward trend in EEDs but more reduction needed Policy interventions:
– partnering with hospitals on “hard stop” policies to prohibit EEDs – attached to reporting/ reimbursement
– learning collaboratives – prior authorization requirements – educational and feedback efforts targeting physicians and patients– participating in national initiatives:
• Strong Start for Mothers and Newborns Initiative• Hospital Engagement Networks/CMS Partnership for Patients• Collaborative Improvement and Innovation Network (CoIIN) to Reduce Infant Mortality
(HRSA)
Participating states have common analytic code and protocols to continue monitoring EEDs for quality improvement
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Costs of Complicated Births Birth complications are an especially important area for
Medicaid– 2/3 of adult women Medicaid beneficiaries are of childbearing age– About half of all Medicaid hospital stays are for pregnancy, childbirth,
and newborns – In 2011, Medicaid paid for approximately 45 percent of all births in the
United States and, under ACA expansion, it is increasing…
Avg. cost for complicated newborn increased from 2002-2009 Proportion of complicated births billed to Medicaid increased
from 2006-2009– Increase in proportion in women 15-44 covered by Medicaid– By 2009, Medicaid covered more complicated births than private
insurance (47.5% vs 44.4%)
From 2002-2009, avg cost/admission for complicated newborn stays paid by Medicaid consistently higher than private insured
Source: Fowler TT, et al. Trends in complicated newborn hospital stays & costs, 2002-2009: Implications for the future. Medicare and Medicaid Research Review 2014;4(4):E1-E17
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Leading Diagnoses for Complicated Newborn Stays in 2009
Preterm birth/low birth weight– 23% of diagnoses and 33% of aggregate costs– More likely to be billed to Medicaid
Respiratory distress – 18% of diagnoses and 28% of aggregate costs– More likely to be billed to Medicaid
Jaundice– 10% of diagnoses and 3% of aggregate costs– Less likely to be billed to Medicaid
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Improved Data and Data Linkages Would Improve Study
Maternal-child linkages not possible with HCUP-NIS– Missing key maternal factors that may influence
complicated births (e.g., maternal age, education, smoking, birth history, type of delivery)
Clinical data to determine severity of conditions are lacking in administrative data
Only expected payer source, not actual, given billing or hospital discharge abstract data
Discharges billed to CHIP may not be consistently classified as a specific payer type
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Data Linkages
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Addressing Data Linkage Difficulties: LBW and C-Section Measures
Initiative provided technical assistance to states for measuring & reporting two CMS Child Core Set measures• Rate of low birth weight• Rate of C-section delivery
Technical specs for these measures require linking birth certificate data to Medicaid claims data• Technical assistance to states seeking to expand/improve
quality reporting
• Training to improve technical capacity to build & sustain data linkage infrastructure
Supported by CDC’s Division of Reproductive Health
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Linkage and Reporting Status 13 Phase I States
– AZ, GA, IN, KY, ME, MA, MI, MS, NM, NV, OK, WV, WY– Executed DUA/MOU: 10– Linked data set: 10 (1 previously linked)
6 Phase II States– CT, DE, DC, NE, NJ, VA– Executed DUA/MOU: 2– Linked data set: 1– Expected to submit measures in Fall 2015:
• Yes=1; Maybe=2; No=3
Helped jumpstart other efforts
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Linkages Lessons Learned DUAs, DSAs, and MOUs most important, sensitive, &
time-consuming part (sharing identified data/legal processes)
Think carefully about the needed records & data elements Needed more guidance on Medicaid data Document every step in the process to facilitate future
replication Provide feedback to all partners Consider expanding linkage longitudinally across Medicaid
records for the child (not just mother’s record) Don’t stop! Time and Persistence!http://www.academyhealth.org/datalinkageproject/
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Maternal and Infant Health Initiative
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CMCS’ Maternal and Infant Health Initiative (MIHI)
Launched in July 2014, MIHI aims to:– Increase the rate and content of postpartum visits– Increase the use of contraception among women in
Medicaid and CHIP 14 states/territories are participating:
– AL, CA, CO, DE, IA, KY, MA, MI, MS, MO, NY, Northern Mariana Islands, OR, and WA
Each state/territory receives up to $400,000 total over 4 years– Project period: September 2015 – September 2019
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CMCS’ Maternal and Infant Health Initiative (MIHI)
Uses of funds:– Improve data validation methods/initiatives– Evaluate data sources and measures– Train and educate providers in measure
collection and reporting– Train staff in the use of tools for data collection
and analysis (claims, surveys, EHRs)– Develop a plan to sustain data collection
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Looking to the Future
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Lessons Learned: Gaps (1)
Data Gaps– COEs often can not get State Medicaid data (privacy, state
resources)– National rates not available on a timely basis (challenges of
combining data from different States/programs; CMS resource issues)
Measure Level Gaps (state level vs practice-level)– Child Core Set and COE-developed measures focused
mostly on state-level measures (i.e., to provide a state-level picture of quality, state-to-state comparisons)
– But there is need in the QI Demos (and other QI implementation) for practice-level measures.
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Lessons Learned: Gaps (2)
Capacity Gaps– Variation in capacity to adopt measures across state
Medicaid programs– Led to a situation in which all states, regardless of capacity,
were held to the lowest common denominator (i.e., measures acceptable to all or most States).
Communications Gaps– Between legislative reporting requirements and
programmatic needs/realities– Between silos in HHS (CMCS, CMMI, AHRQ)
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Lessons Learned: Resources Key challenge for CHIPRA 2009 activities was time and
resources– Same people were charged with implementation of multiple new
Obama-era programs: CHIPRA 2009 (multiple programs for enrollment, quality measurement, quality improvement); the early 2009 Investment Act; and ACA in early 2010
– Given pre-existing resources in the Medicaid program, thoughtful, coordinated implementation was a challenge.
Many existing external resources involved in CHIPRA implementation were ready to go on Day 1 with:– Measures (e.g., COEs)– Quality Improvement (e.g., NICHQ, NIPN components, scientific
literature on QI/DI)– National leadership: AHRQ, CMCS, CMMI– State Medicaid leadership
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Recommendations for the Future (1) Capture the lessons learned across all the investments in
children's health care, especially for Medicaid/CHIP Information from quality measure development lessons
and from improvement evaluations could help drive research and program implementation agendas
Designate a single entity at OS level to coordinate children's healthcare quality activities across investments and do continuous quality improvement across HHS, state and private sector programs
Develop a new strategy for federal Medicaid/CHIP and state Medicaid/CHIP programs to work together and with private sector on quality measurement and improvement and equity
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Recommendations for the Future (2) Provide more resources to state Medicaid programs, possibly
contingent on coordinated approach with feds and external experts
Pay for state reporting on quality measures, contingent on accuracy of reporting as a result of additional resources provided
Invest in implementing and using children's healthcare quality measures developed by COEs and through the state quality demonstrations
Don’t stop working on children's healthcare quality even though most of the CHIPRA quality money and activities are ending!
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Thank you!
Enrique Martinez-Vidalenrique.martinez-vidal@academyhealth.org
202-292-6729
AcademyHealthwww.academyhealth.org/
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