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A Meta Analysis of the Impact of SBI on Healthcare Utilization

A Meta Analysis of the Impact of SBI on Healthcare Utilization. Presented by Jesse M. Hinde RTI International. Presented at INEBRIA, Gateshead, UK October 9, 2009. This research was conducted under NIAAA grant no. R01 AA013925. Acknowledgements. Co-Authors Jeremy Bray, PhD

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A Meta Analysis of the Impact of SBI on Healthcare Utilization

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  1. A Meta Analysis of the Impact of SBI on Healthcare Utilization Presented by Jesse M. Hinde RTI International Presented at INEBRIA, Gateshead, UK October 9, 2009 This research was conducted under NIAAA grant no. R01 AA013925

  2. Acknowledgements • Co-Authors • Jeremy Bray, PhD • Alexander Cowell, PhD • Funding • National Institute on Alcohol Abuse and Alcoholism of the National Institutes of Health • Grant R01 AA013925 (PI: Jeremy Bray)

  3. Motivation: Broad Policy Support • Ensuring Solutions.org: • “Every dollar spent on SBI saves nearly four dollars in subsequent health care costs.” • United States Preventative Services Task Force: • “B” recommendation for SBI (some evidence that is reduce health care costs) • U.S. Substance Abuse and Mental Health Services Administration (SAMHSA): • SBI is associated with fewer hospital days and fewer ED visits • SBI cost-benefit and cost-effectiveness demonstrates cost-savings • Pending Joint Commission on Accreditation of Healthcare Organizations (JCAHO) accreditation: • All U.S. Hospitals would have to implement SBI • SBI saves hospitals money

  4. Support from the Literature • D’Onofrio et al., 2002: • Strongly recommends SBI to reduce ED/outpatient visits and hospitalizations after 32 article review • Gentilello et al., 2005: • SBI can potentially save $1.82 billion in health care costs annually • Solberg et al., 2008: • “Screening and brief counseling in primary care was cost-saving from the societal perspective and highly cost-effective from the health-system perspective.”

  5. Weaknesses in the Literature • Systematic reviews and meta-analyses often focus on drinking outcomes, not health care utilization • Whitlock et al. 2004: Only 1 of the 5 RCT studies that included health care measures showed reduced health care utilization • Policy statements are only based on a few source projects (TrEAT) or articles (Gentilello 2004)

  6. Systematic Review Methods • Search strategy: • Targeted electronic journals using online databases • EBSCOhost-PsycArticles; • EBSCSO-host-Psychology & Behavioral Sciences Collection; • Springer Online Journals System; • PubMed Central; • JSTOR Arts and Sciences Collections I and II • Supplemented with GoogleScholar queries • Reviewed references from identified articles, focusing on previous SBI systematic reviews and meta-analyses

  7. Systematic Review Methods cont… • Key words • Screening and brief intervention; alcohol brief intervention; SBI • Health care utilization; health care; cost; effectiveness; cost-effectiveness • Basic inclusion criteria • Used SBI, brief interventions, or motivational interviewing • Randomized controlled trial • Presence of health care utilization outcomes

  8. Article Selection Process

  9. Included Primary Care Studies

  10. Included Emergency Department Studies

  11. Studies Included from Other Settings

  12. Preliminary Meta Analysis • For each intervention and control condition, collected a post-baseline measure of the mean effect, standard deviation and sample N • For each study, there are potentially multiple • Follow-up points • Utilization measures • Intervention arms • Stratified data by setting • ED and primary care • Stata v.10 with random effects

  13. Meta Analysis Specifications • Calculated for both outpatient and inpatient measures • Observations stratified by primary care and emergency department settings • Only included observations for 12-month follow-ups. • Excluded “other” settings. • Excluded incomplete records (e.g. without sample N, mean effect, or standard deviation) • 5 total articles (5 Outpatient, 4 Inpatient)

  14. Outpatient Measures

  15. Limitations • Small sample size and clustering of articles • Excludes several articles both for and against health care utilization reductions (N=11) • 2 articles had no health care data • 2 articles were excluded on setting (inpatient only setting) • 3 articles did not have sufficient data to perform analyses • 4 articles did not have a 12-month follow-up • Project TrEAT was excluded due to incomplete data from the source articles

  16. Preliminary Conclusions • Strong evidence of heterogeneity • Large variation that is not random • Outpatient: • Significant negative effect for primary care setting • Rejected null hypothesis for heterogeneity

  17. Preliminary Conclusions (cont’d) • Inpatient: • No significant effect of the standardized mean differences for both settings • Significant evidence of heterogeneity • Across all settings: • No significant effect of the standardized mean differences • Significant evidence of heterogeneity

  18. Next Steps • Review • Complete review of literature that we have • Search on other databases • Seek out complete data from authors • Score articles • Score articles by qualitative analysis of studies, based on design (e.g. Vasilaki 2006)

  19. Next Steps (cont’d) • Heterogeneity • Investigate role of • intervention implementation • setting • Meta Analysis Methodology • Methodology to handle clustering • Meta-regression methods

  20. Outpatient Measures – Model 1

  21. Outpatient Measures – Model 2

  22. Inpatient Measures – Model 1

  23. Inpatient Measures – Model 2

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