Evidence map›Paper›PMID 39260804›Full record

ArticleJournal of substance use and addiction treatment2024

Evaluating and identifying changes in the rate of unplanned discharge among Department of Veterans Affairs (VA) facilities providing substance use disorder residential care.

Natalie B Riblet, Daniel J Gottlieb, Brian Shiner, Lisa Zubkoff, Korie Rice, Brett Rusch

Abstract read
In one paragraph

Article in Journal of substance use and addiction treatment, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Natalie B RibletVeterans Affairs Medical Center, 215 North Main Street, White River Junction, VT 05009, USA; Geisel School of Medicine at Dartmouth College, 1 Rope Ferry Road, Hanover, NH 03755, USA. Electronic address: Natalie.Riblet@dartmouth.edu.
Daniel J GottliebVeterans Affairs Medical Center, 215 North Main Street, White River Junction, VT 05009, USA.
Brian ShinerVeterans Affairs Medical Center, 215 North Main Street, White River Junction, VT 05009, USA; Geisel School of Medicine at Dartmouth College, 1 Rope Ferry Road, Hanover, NH 03755, USA.
Lisa ZubkoffUniversity of Alabama at Birmingham Marnix E. Heersink School of Medicine, 1670 University Blvd, Birmingham, AL 35233, USA; Birmingham/Atlanta Veteran's Affairs Geriatric Research, Education, and Clinical Center (GRECC), 700 19th St. S., Birmingham, AL 35233, USA.
Korie RiceVeterans Affairs Medical Center, 215 North Main Street, White River Junction, VT 05009, USA.
Brett RuschVeterans Affairs Medical Center, 215 North Main Street, White River Junction, VT 05009, USA; Geisel School of Medicine at Dartmouth College, 1 Rope Ferry Road, Hanover, NH 03755, USA.

Funding

Improving Analysis of Endogenous Multimodal Treatments for Use in Geriatrics Health Outcomes StudiesI01HX002237 · VA · VA BOSTON HEALTH CARE SYSTEM · PI GARRIDO, MELISSA M · 2018 to 2021
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Prevention of Suicide in Veterans Through Brief Intervention and Contact (VA-BIC)IK2CX001920 · VA · WHITE RIVER JUNCTION VA MEDICAL CENTER · PI RIBLET, NATALIE · 2021 to 2025
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CSRD VA IK2 CX001920HSRD VA SDR 02-237
6 · The paper itself

Abstract

introductionQuality improvement (QI) methods play a critical role in ensuring that patients receive high-quality and timely care. Healthcare systems should use valid and reliable measures to inform QI efforts. Mental health settings including substance use disorder (SUD) residential programs have been slow to develop and incorporate quality measurement into routine practice. Unplanned discharge is of particular concern because this event is associated with harm including suicide. Healthcare systems require criteria that they can use to operationalize unplanned discharge as a quality measure in SUD residential programs.

methodsThe study included all discharges from the Department of Veterans Affairs (VA) residential SUD programs between 2018 and 2022. The study calculated crude and adjusted rates of irregular discharge. The study used the first two years of observation (2018-2019) in a logistic regression model to determine the parameter estimates for three important covariates, age, risk for homelessness, and principal diagnosis. The study tested permutations of bin size (N) and days (D) per bin to identify a single set of parameters to enable small and large facilities to have sufficient power to detect out-of-control processes (i.e., significant worsening or improvement in rates). Aligned with standard nomenclature, the study calculated the control limits based on three standard deviations (SD). Values that fell above or below three SD were statistically significant.

resultsThe cohort included 56 facilities (26,361 discharges). Irregular discharge was associated with younger age (18-40 years) and a principal diagnosis of a drug use disorder. Testing parameter values of 100 discharges (N) over 120 days (D) would yield enough power to detect modest relative changes to the irregular discharge rate for small and large facilities while testing frequently enough to make the evaluations temporally relevant. Because secular trends such as staff changes over time will impact results, the quality control method should allow for real-time feedback to those most proximal to the event.

conclusionsThe study created a set of parameters and a methodology that residential SUD programs can use to operationalize unplanned discharge locally. These data could assist programs in conducting QI work to address unplanned discharge and related harms.

Indexed as

Patient DischargeResidential TreatmentSubstance-Related DisordersUnited States Department of Veterans AffairsAdultFemaleHumansIll-Housed PersonsMaleMiddle AgedQuality ImprovementUnited StatesVeteransQuality control methodsQuality improvementResidential treatmentSubstance use disorders

Identifiers

PMID39260804
PMCPMC11527561

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Registered trials

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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.