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Effective MCH Epidemiology Translation and Use?. HRSA/CDC MCH Epidemiology Course Dr. William Sappenfield September 11, 2012 Webinar. Classic Definition of Epidemiology.
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Effective MCHEpidemiology Translation and Use? HRSA/CDC MCH Epidemiology Course Dr. William Sappenfield September 11, 2012 Webinar
Classic Definition of Epidemiology “Epidemiology is the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems.” J. M. Last
Definition of MCH Epidemiology “The systematic collection, analysis and interpretation of population-based and program-specific health and related data in order to assess the distribution and determinants of the health status and needs of the maternal child population for the purpose of planning, implementing, and assessing effective, science-based strategies and promoting policy development.” Coalition for Excellence in MCH Epidemiology, 2010
Definition of MCH Epidemiology “The systematic collection, analysis and interpretation of population-based and program-specific health and related data in order to assess the distribution and determinants of the health status and needs of the maternal child population for the purpose of planning, implementing, and assessing effective, science-based strategies and promoting policy development.” Coalition for Excellence in MCH Epidemiology, 2010
TRANSLATION Community Data Use“Triangle” Data & Analysis Planning & Programs Politics & Policy
According to a past survey of evaluators, what is the major problem related to program evaluation?
Using the results! According to a past survey of evaluators, what is the major problem related to program evaluation?
Common Reasons for Not Using Evaluation Results • Stakeholders are not engaged • Answering the wrong questions • Evaluator losing creditability • Not reading/understanding the results • Not liking the results • Not wanting change
Epidemiology Training Functions • Distribution Descriptive • Determinants Analytic Focus • New knowledge • Confirmation
Relevant! Policies & Programs Consequential Epidemiology
Relevant! Policies & Programs Intervention Epidemiology
Data Connections to Planning Cycle Awareness
“For we break, we’re going to let the statistics speak for themselves.”
"We must become the change we wish to see in the world." Mahatma Gandhi
Conceptual Framework MCH Epidemiology Efforts Health Agency Structure MACRO CONTEXT The capacity to do work: the work environment MCH-Epi Effort Structure Population Context Practice Activities: The work that is done MCH-Epi Effort Process Health Status Public HealthContext Practice Results: The results of that work Many processes and outputs become structural features Intermediate Outcome Output
Conceptual Framework MCH Epidemiology Efforts • Includes sufficient funding for continuing education and staff development • Includes database and web servers, statistical analysis software, GIS software, etc. Health Agency Structure MACRO CONTEXT • Includes a lead MCH epidemiologist • Includes sufficient staff for data collection, analysis, dissemination, etc. • Participates in the leadership of the agency MCH-Epi Effort Structure Population Context MCH-Epi Effort Process • Provides analytic direction • Provides expertise for data system development • Conducts high-level data analysis Health Status Public HealthContext Feedback Loop • Data linkage / integration • Grant submission and subsequent funding Many processes and outputs become structural features Intermediate Outcome Output • Disseminates reports • Generates policy briefs • Program and policy change, with or without legislation
Final Recommendations to States • Establish a named unit for MCH Epidemiology. • Ensure its leadership has organizational recognition & authority. • Acknowledge its broad scope and collaborative approach. • Hire increasing numbers with doctoral degrees. • Invest in a critical mass of MCH epidemiologists. • Pursue assignees, fellows, & interns.
Final Recommendations to States (2) • Provide staff with time and funding for training. • Ensure direct access to a wide variety of datasets. • Routinely link data beyond birth-death data • Disseminate the work using multiple approaches/venues. • Jointly translate findings into information for action. • Support external partners turning data into information.
Relevant! Policies & Programs Consequential Epidemiology
Infant Mortality RatesFlorida and U.S., 1975 to 2005 2000 1975 1985 2005 1990 1995 1980
Support during pregnancy for women at increased risk of low birthweight babies “Pregnant women need the support of caring family members, friends, and health professionals. While programs which offer additional support during pregnancy are unlikely to prevent the pregnancy from resulting in a low birthweight or preterm baby, they may be helpful in reducing the likelihood of caesarean birth.” Hodnett, Cochrane 2003
Draft Report Findings:Economic & Outcome Evaluation of the Florida Healthy Start Stephanie Staras, Ph.D. John Kairalla, Ph.D. Elizabeth Shenkman, Ph.D. Institute for Child Health Policy Department of Epidemiology and Healthy Policy Research College of Medicine, University of Florida Summarized by William M. Sappenfield, MD, MPH
Study Questions • How do Healthy Start prenatal clients in high benchmark coalitions compare to Healthy Start clients low benchmark coalitions? • Preterm, post-term, LBW, and SGA • Timely prenatal care and receiving postpartum care • Medicaid expenditures • How do Healthy Start prenatal clients compare to non-clients in high and low benchmark coalitions? • Same outcomes and expenditures
Methods Data:Merged files for 1998-2006 including Live birth certificates Healthy Start prenatal screens Healthy Start prenatal services Medicaid eligibility and claims Design:Retrospective Observational Cohort Study Population:All Florida resident women with a live birth
Methods—Services Women receiving Healthy Start prenatal services were collapsed into the following service categories: • Initial Contact • Initial Assessment • Care Coordination • Supplemental Services
Methods—Healthy Start Study Categories All Study Women:Women With singleton live births Covered by Medicaid (not medically needy) Healthy Start screen of four or more Healthy Start Care Coordination:Women who Received a care coordination service No Healthy Start Service:Women who Received no Healthy Start services
Methods—Healthy Start High and Low Benchmark Coalitions Eight Highest & Lowest Benchmark Coalitions: Prenatal screening rate Percent of women served prenatally Mean number of Healthy Start services Of eight selection methods explored Same 8 low benchmark coalitions selected Same 6 high benchmark coalitions selected
Methods—Comparisons HS in High Benchmark Coalitions HS in Low Benchmark Coalitions High Benchmark Coalitions—HS High Benchmark Coalitions—No HS Low Benchmark Coalitions—HS Low Benchmark Coalitions—No HS 41
Methods—Statistical Methods Observational Retrospective Cohort Analysis SAS Expenditures—Mixed model Birth Outcomes and Care—Generalized estimating equations (GEE) Manage repetitive events Provide multilevel adjustment 43
Differences in the Percentages or Expenditures for Three Healthy Start Comparisons If Healthy Start were effective…
Differences in the Percent Preterm Births for Three Healthy Start Comparisons
Differences in the Percent Low Birthweight Births for Three Healthy Start Comparisons
Differences in the Percent Small for Gestational Age Births for Three Healthy Start Comparisons
Differences in the Percent Receiving Timely Prenatal Care for 3 Healthy Start Comparisons
Differences in the Percent Receiving Postpartum Care for 3 Healthy Start Comparisons
Differences in Adjusted Expenditures for the Prenatal Period for 3 Healthy Start Comparisons