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Data and Methodologies Used in
the
Evaluation of Health Reform at
the State Level
Donna Spencer, PhD
State Health Access Data Assistance Center
University of Minnesota, Twin Cities
AEA: Evaluation 2013
Washington, DC
October 18, 2013
Supported by a grant from The Robert Wood Johnson Foundation
Agenda
• State Health Access Reform Evaluation
(SHARE) Grant Program
• Systematic review of grant methods and data
• Data sources used in health reform research
and evaluation
–
–
–
–
–

Federal surveys
State surveys
Administrative data
Medical claims data
Qualitative methods

• Lessons learned from the SHARE program
2
About SHARE
• National Program of the Robert Wood Johnson Foundation
(RWJF) since 2006
• Goals:
– support the evaluation of health policy reform at the state level
– develop an evidence-based resource to inform health reform efforts in
the future

• Focus: State-level reform and state implementation of national
reform
• Operated out of the State Health Access Data Assistance Center
(SHADAC) in the Division of Health Policy and Management,
School of Public Health, University of Minnesota.
• Collaborators on this presentation:
– Kelsey Avery (Graduate Research Assistant)
– Carrie Au-Yueng, MPH (Research Fellow)
– Lynn Blewett, PhD (SHADAC and SHARE Principal Investigator)
3
About SHARE
• 3 rounds of grant awards
– 33 grants funded to date
– 9 currently in the field

• Over $7 million in research and evaluation funding to
date
• Projects have ranged from 3-30 months in duration
• Grantee institutions: mostly universities but also private
research organizations and state agencies
• States studied:
– Single-state (14 grants)
– Multi-state (10 grants)
– All states/national (9 grants)
4
States Studied by SHARE Grants

Studied by one or more
single- or multi-state
share grant(s)

Map excludes all-state/national studies.
5
Policies and Programs Studied

Grants may be assigned to more than one policy and/or program.
6
Topics and Outcomes Studied

Grants may be assigned to more than one topic and/or outcome.
7
Systematic Review of Grants: Approach
• Excel-based abstraction tool
• Data abstracted:
–
–
–
–
–

Type of study/evaluation
Quantitative/qualitative methods
Types of data used and data sources
Facilitators/obstacles in research/evaluation
Methodological lessons learned

• Grant documents used in review:
– Proposals
– Grant progress reports
– Grant deliverables (presentations, publications, substantive
reports, briefs)
8
Types of Data Used by Grantees*

* Grants may be assigned to more than one data type.
** Administrative data includes eligibility data and enrollment data.

9
Federal and State Surveys Used

10
Survey Data Lessons
Federal Surveys

State Surveys

•

•

•
•
•

Existing data
– Time and $ resource
efficient
Some have good state sample
sizes
Can facilitate state
comparisons
No one survey offers it all in
terms of policy-relevant
content and ample state data

•
•

•
•

Larger state-specific sample
sizes (in some cases)
Targeted oversampling
Questionnaire more easily
modified and relevant for local
policy environment
Inconsistency/uncertainty in
funding
Own methodological limitations

11
Medical Claims Data Used

12
Claims Data Lessons
• Ideal for measuring health care utilization and costs
• Does not rely on patient recall of health care services
• But precludes care paid for by a different payer or not
paid for by health plan
• Lacks good socio-demographic data (unlike surveys)
• Large patient populations but comparison groups may be
limited
• Access to data can be difficult
– Authorizations, data use agreements, competing demands
– APCDs not viable choice in some states

• Time consuming and more complicated to obtain,
prepare, and analyze
• Relationship with source agency essential

13
Administrative Data Used

14
Administrative Data Lessons
• Key outcomes of interest include enrollment, insurance
take-up, continuity in coverage, churning
• Large patient populations
• As with claims, not designed for research purposes per
se
– Data elements important to research may be limited

• As with claims, access may be difficult
• As with claims, time consuming and more complicated to
obtain, prepare, and analyze
• Relationship with source agency essential

15
Qualitative Data Lessons
• Ideal for assessing
– Political/social/historical context of the program/policy
– Perspectives related to processes, implementation, outcomes

• State staff/officials and other stakeholders motivated to
participate
• Constraints
– Both national and state health reform have state agencies
maxed out!
– Other typical competing demands: legislative sessions, recent
political developments, regular program schedules
– Turnover in state program personnel

16
Conclusions
•
•
•

•

•

Wealth of data available for health reform evaluation research
No one data source has it all
Shifts occurring among relevant data sources
– APCDs
– National health reform has triggered new data needs and
existing federal and state data sources are responding
– New potential data sources (e.g., marketplaces)
Relationship with state program important in state health reform
evaluation for a host of reasons, including data access
– Allocating funds for their role as well as data acquisition and
preparation
– Evaluation timelines need to accommodate
IRB reviews may require extra time and attention especially with
administrative/claims data sources
17
Contact Information
Donna Spencer, PhD
SHARE Deputy Director
dspencer@umn.edu

©2002-2009 Regents of the University of Minnesota. All rights reserved.
The University of Minnesota is an Equal Opportunity Employer

18

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Aea presentation final 18_oct2013

  • 1. Data and Methodologies Used in the Evaluation of Health Reform at the State Level Donna Spencer, PhD State Health Access Data Assistance Center University of Minnesota, Twin Cities AEA: Evaluation 2013 Washington, DC October 18, 2013 Supported by a grant from The Robert Wood Johnson Foundation
  • 2. Agenda • State Health Access Reform Evaluation (SHARE) Grant Program • Systematic review of grant methods and data • Data sources used in health reform research and evaluation – – – – – Federal surveys State surveys Administrative data Medical claims data Qualitative methods • Lessons learned from the SHARE program 2
  • 3. About SHARE • National Program of the Robert Wood Johnson Foundation (RWJF) since 2006 • Goals: – support the evaluation of health policy reform at the state level – develop an evidence-based resource to inform health reform efforts in the future • Focus: State-level reform and state implementation of national reform • Operated out of the State Health Access Data Assistance Center (SHADAC) in the Division of Health Policy and Management, School of Public Health, University of Minnesota. • Collaborators on this presentation: – Kelsey Avery (Graduate Research Assistant) – Carrie Au-Yueng, MPH (Research Fellow) – Lynn Blewett, PhD (SHADAC and SHARE Principal Investigator) 3
  • 4. About SHARE • 3 rounds of grant awards – 33 grants funded to date – 9 currently in the field • Over $7 million in research and evaluation funding to date • Projects have ranged from 3-30 months in duration • Grantee institutions: mostly universities but also private research organizations and state agencies • States studied: – Single-state (14 grants) – Multi-state (10 grants) – All states/national (9 grants) 4
  • 5. States Studied by SHARE Grants Studied by one or more single- or multi-state share grant(s) Map excludes all-state/national studies. 5
  • 6. Policies and Programs Studied Grants may be assigned to more than one policy and/or program. 6
  • 7. Topics and Outcomes Studied Grants may be assigned to more than one topic and/or outcome. 7
  • 8. Systematic Review of Grants: Approach • Excel-based abstraction tool • Data abstracted: – – – – – Type of study/evaluation Quantitative/qualitative methods Types of data used and data sources Facilitators/obstacles in research/evaluation Methodological lessons learned • Grant documents used in review: – Proposals – Grant progress reports – Grant deliverables (presentations, publications, substantive reports, briefs) 8
  • 9. Types of Data Used by Grantees* * Grants may be assigned to more than one data type. ** Administrative data includes eligibility data and enrollment data. 9
  • 10. Federal and State Surveys Used 10
  • 11. Survey Data Lessons Federal Surveys State Surveys • • • • • Existing data – Time and $ resource efficient Some have good state sample sizes Can facilitate state comparisons No one survey offers it all in terms of policy-relevant content and ample state data • • • • Larger state-specific sample sizes (in some cases) Targeted oversampling Questionnaire more easily modified and relevant for local policy environment Inconsistency/uncertainty in funding Own methodological limitations 11
  • 13. Claims Data Lessons • Ideal for measuring health care utilization and costs • Does not rely on patient recall of health care services • But precludes care paid for by a different payer or not paid for by health plan • Lacks good socio-demographic data (unlike surveys) • Large patient populations but comparison groups may be limited • Access to data can be difficult – Authorizations, data use agreements, competing demands – APCDs not viable choice in some states • Time consuming and more complicated to obtain, prepare, and analyze • Relationship with source agency essential 13
  • 15. Administrative Data Lessons • Key outcomes of interest include enrollment, insurance take-up, continuity in coverage, churning • Large patient populations • As with claims, not designed for research purposes per se – Data elements important to research may be limited • As with claims, access may be difficult • As with claims, time consuming and more complicated to obtain, prepare, and analyze • Relationship with source agency essential 15
  • 16. Qualitative Data Lessons • Ideal for assessing – Political/social/historical context of the program/policy – Perspectives related to processes, implementation, outcomes • State staff/officials and other stakeholders motivated to participate • Constraints – Both national and state health reform have state agencies maxed out! – Other typical competing demands: legislative sessions, recent political developments, regular program schedules – Turnover in state program personnel 16
  • 17. Conclusions • • • • • Wealth of data available for health reform evaluation research No one data source has it all Shifts occurring among relevant data sources – APCDs – National health reform has triggered new data needs and existing federal and state data sources are responding – New potential data sources (e.g., marketplaces) Relationship with state program important in state health reform evaluation for a host of reasons, including data access – Allocating funds for their role as well as data acquisition and preparation – Evaluation timelines need to accommodate IRB reviews may require extra time and attention especially with administrative/claims data sources 17
  • 18. Contact Information Donna Spencer, PhD SHARE Deputy Director dspencer@umn.edu ©2002-2009 Regents of the University of Minnesota. All rights reserved. The University of Minnesota is an Equal Opportunity Employer 18