A pre-post study of the impact of a multidisciplinary model of care on linkage to hepatitis C care following release from prison: The Beyond Prison Walls study
Bibliographic record
Abstract
BACKGROUND: Many people are released from prison with untreated hepatitis C virus (HCV) and fail to link to care due to competing priorities. We compared linkage to HCV care among individuals who engaged in a multidisciplinary model of care versus in standard of care, and examined factors associated with linkage to care. METHODS: We conducted a prospective, quasi-experimental pre-post study in Quebec's largest provincial prison. Participants in the intervention arm met with a nurse, social worker, and patient navigator and were offered appointment accompaniment post-release. Participants in the control arm received a pre-release discharge appointment. The primary outcome was linkage to HCV care, defined as a documented visit with an HCV care provider within 90 days of release. Bayesian logistic regression was used to determine the impact of the intervention on linkage and to analyze relationships between covariates of interest and linkage. Probability differences and 95 % credible intervals (95 % CrI) were calculated. RESULTS: Overall, 648 participants underwent HCV screening; 19 and 20 had current HCV infection in the control and intervention arms, respectively. Among these, 2 (11 %) and 14 (80 %) were linked to care post-release, respectively. Intervention participants had a + 70 % (45 %, 88 %) difference in linkage to care versus control participants. Among intervention participants, those who were successfully contacted post-release were more likely to be linked to care [+64 % (14 %, 90 %)] than those who were not. CONCLUSIONS: A multidisciplinary model of care increased linkage to HCV care among untreated individuals released from prison. Future interventions should support similar models, leveraging social support networks to maximize continuity of care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".