Evidence map›Paper›PMID 26596421›Full record

ArticleBMC health services research2015

Toward cost-effective staffing mixes for Veterans Affairs substance use disorder treatment programs.

Jinwoo J Im, Ross D Shachter, John W Finney, Jodie A Trafton

Abstract read
In one paragraph

Article in BMC health services research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jinwoo J ImManagement of Innovation Program, Daegu Gyeongbuk Institute of Science and Technology, Daegu, 711-873, South Korea. jinwoo.im@dgist.ac.kr.
Ross D ShachterDepartment of Management Science and Engineering, Stanford University, Stanford, CA, 94305, USA. shachter@stanford.edu.
John W FinneyCenter for Health Care Evaluation, VA Palo Alto Healthcare System, Menlo Park, CA, 94025, USA. John.Finney@va.gov.
Jodie A TraftonCenter for Health Care Evaluation, VA Palo Alto Healthcare System, Menlo Park, CA, 94025, USA. Jodie.Trafton@va.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn fiscal year (FY) 2008, 133,658 patients were provided services within substance use disorders treatment programs (SUDTPs) in the U.S. Department of Veterans Affairs (VA) health care system. To improve the effectiveness and cost-effectiveness of SUDTPs, we analyze the impacts of staffing mix on the benefits and costs of specialty SUD services. This study demonstrates how cost-effective staffing mixes for each type of VA SUDTPs can be defined empirically.

methodsWe used a stepwise method to derive prediction functions for benefits and costs based on patients' treatment outcomes at VA SUDTPs nationally from 2001 to 2003, and used them to formulate optimization problems to determine recommended staffing mixes that maximize net benefits per patient for four types of SUDTPs by using the solver function with the Generalized Reduced Gradient algorithm in Microsoft Excel 2010 while conforming to limits of current practice. We conducted sensitivity analyses by varying the baseline severity of addiction problems between lower (2.5 %) and higher (97.5 %) values derived from bootstrapping. RESULTS AND

conclusionsCompared to the actual staffing mixes in FY01-FY03, the recommended staffing mixes would lower treatment costs while improving patients' outcomes, and improved net benefits are estimated from $1472 to $17,743 per patient.

Indexed as

Cost-Benefit AnalysisDelivery of Health CareFemaleHealth Care CostsHealth PersonnelHospitals, VeteransHumansLength of StayMaleSubstance-Related DisordersTreatment OutcomeUnited StatesUnited States Department of Veterans AffairsVeterans

Identifiers

PMID26596421
PMCPMC4656190

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.