3cisd

3C Institute

The Impact Integrated Data System for Quality and Outcomes Tracking of Prevention Programs

NATIONAL INSTITUTE OF MENTAL HEALTH
ID: 1R43MH111299-01
PI: MELISSA DEROSIER, JANEY MCMILLEN
TERM: 09/16 – 03/17

In recent years, tremendous progress has been made in developing prevention programs with proven efficacy for preventing risky behaviors and promoting positive outcomes for youth.Unfortunately, actual use of these evidence-based prevention programs (EBPPs) in real world settings continues to lag far behind. Research in the field of implementation science has underscored how research evidence alone is not sufficient for broad scale adoption and sustained use of EBPPs.In order to move research to practice, we must develop effective methods to address systemic barriers to implementing EBPPs in everyday practice in community- and school-based service settings. Only by lowering these barriers can EBPPs achieve broad public impact in which youth, and society at large, are able to realize the benefits of these effective prevention programs.

This SBIR Phase I project addressed a key implementation barrier to broad scale adoption and sustained use of EBPPs—the need for ongoing tracking and documentation of how and to what extent an EBPP results in intended youth outcomes under real-world conditions. Through this SBIR, we developed Impact, an easy to use, cost- and time-efficient technology platform to gather relevant process and outcome data and produce meaningful real-time reports at provider, service setting, and state-wide levels. The existing collaborations among 3C Institute, co-I Dr. Brian Bumbarger, and intervention developers Dr. Brad Stein and Dr. Lisa Jaycox provided a solid foundation upon which to build Impact and test it with EBPP stakeholders across the U.S.

As the healthcare market steadily moves toward outcome-based reimbursement models, process and outcomes data is critically important for helping payors and policymakers justify expenditures needed to adopt and implement EBPPs with fidelity (e.g., staff training, supervision). Ready access to these data is also an essential ingredient in continuous quality improvement (CQI) enabling providers to make data-driven decisions to ensure youth are making progress toward target outcomes. Concrete, real-time feedback by which providers can see how their service provision translates into benefits for youth fosters sustained quality implementation of EBPPs over time.

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DEB CHILDRESS, PHD

Chief of Research and Learning Content

BIOGRAPHY

Dr. Childress obtained her PhD in psychology at the University of North Carolina at Chapel Hill. Prior to coming to 3C Institute, she served as a research associate and a postdoctoral fellow in the Carolina Institute for Developmental Disabilities at the University of North Carolina at Chapel Hill working on a longitudinal imaging study aimed at identifying the early markers of autism through behavioral and imaging methodologies. She has 19 years of autism research experience, during which she has examined the behavioral, personality, and cognitive characteristics of individuals with autism and their family members. Dr. Childress also has experience developing behavioral and parent report measurement tools, coordinating multi-site research studies, and collecting data from children and families. She has taught courses and seminars in general child development, autism, and cognitive development at the University of North Carolina at Chapel Hill.

Expertise

  • autism
  • early development
  • behavioral measurement
  • integrating behavioral and biological measurement

Education

  • Postdoctoral fellowship, Carolina Institute for Developmental Disabilities (Institutional NRSA-NICHD), University of North Carolina at Chapel Hill
  • PhD, developmental psychology, University of North Carolina at Chapel Hill
  • BS, psychology (minor in sociology), University of Iowa

Selected Publications

  • Elison, J. T., Wolff, J. J., Heimer, D. C., Paterson, S. J., Gu, H., Hazlett, H. C., Styner, M, Gerig, G., & Piven, J. (in press). Frontolimbic neural circuitry at 6 months predicts individual differences in joint attention at 9 months. Developmental Science.
  • Wassink, T. H., Vieland, V. J., Sheffield, V. C., Bartlett, C. W., Goedken, R., Childress, D. & Piven, J. (2008). Posterior probability of linkage analysis of autism dataset identifies linkage to chromosome 16. Psychiatric Genetics,18(2),85-91.
  • Losh, M., Childress, D., Lam K. & Piven, J. (2008). Defining key features of the broad autism phenotype: A comparison across parents of multiple- and single-incidence autism families. American Journal of Medical Genetics (Neuropsychiatric Genetics), 147B(4):424-33.
  • Wassink, T. H., Piven, J., Vieland, V. J., Jenkins, L., Frantz R., Bartlett, C. W., Goedken, R., … Sheffield, V.C. (2005). Evaluation of the chromosome 2q37.3 gene CENTG2 as an autism susceptibility gene. American Journal of Medical Genetics (Neuropsychiatric Genetics), 136, 36-44.
  • Barrett, S., Beck, J., Bernier, R., Bisson, E., Braun, T., Casavant, T., Childress, D., … Vieland, V. (1999). An autosomal genomic screen for autism. American Journal of Medical Genetics (Neuropsychiatric Genetics), 88, 609-615. doi: 10.1002/(SICI)1096-8628(19991215)88:63.0.CO;2-L
  • Piven, J., Palmer, P., Landa, R., Santangelo, S., Jacobi, D. & Childress, D. (1997). Personality and language characteristics in parents from multiple-incidence autism families. American Journal of Medical Genetics (Neuropsychiatric Genetics), 74, 398-411.
  • Piven, J., Palmer, P., Jacobi, D., Childress, D. & Arndt, S. (1997). Broader autism phenotype: Evidence from a family history study of multiple-incidence autism families. American Journal of Psychiatry, 154, 185-190.