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Record W4401190110 · doi:10.1080/21548331.2024.2386924

Opportunities to improve inpatient services and reduce rates of patient-direct discharge among people who use substances

2024· review· en· W4401190110 on OpenAlexafffund
Hannah Peters, Alex Liaukovich, N Grace, Christine Ausman, Niki Kiepek

Bibliographic record

VenueHospital Practice · 2024
Typereview
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsDalhousie University
FundersDalhousie University
KeywordsMedicineMEDLINEHospital dischargePsychiatryIntensive care medicine

Abstract

fetched live from OpenAlex

PURPOSE: Patients who use substances (PWUS) report experiencing stigmatizing encounters and undertreatment of pain and withdrawal symptoms that increase the likelihood of patient-directed discharge (PDD). This scoping review examines North American literature to gain insights about how institutional factors intersect with patient experiences and contribute to PDD. METHODS: A scoping review was conducted using MEDLINE, CINAHL, Scopus, and EMBASE databases. Screening was completed by two reviewers. A data extraction tool developed by the research team was used to collect demographic information and explore patients' experiences and reasons for PDD. RESULTS: We present four themes related to PDD: i) effective management of pain and withdrawal symptoms, ii) therapeutic alliance with healthcare providers, iii) hospital policies, protocols, and procedures, and iv) recommendations. Notably, all patients in all qualitative studies reported predominant experiences of uncaring, stigmatizing interactions with healthcare providers. DISCUSSION: Findings suggest that transformations are required at individual and institutional levels. At an individual level, to provide equitable care to all patients, healthcare providers in all practice settings should be competent to effectively and compassionately care for PWUS. At an institutional level, policies need to be re-envisioned to support the implementation of effective practices. CONCLUSION: Hospitals are faced with the challenges to ensure respectful care environments guided by harm reduction policies that will improve engagement of PWUS in services.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.334
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

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