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“Swimming against the Tide” Restricting Prescribing Practices in a Prison: A Personal Journey

2015· article· en· W3017094589 on OpenAlexaffvenueabout
David Francis Craig

Bibliographic record

VenueThe Canadian Journal of Addiction · 2015
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPrisonMedical prescriptionPillMedicinePsychiatryPsychotropic drugHealth careDrugPsychologyNursingCriminology

Abstract

fetched live from OpenAlex

Objectives: I sought to reduce the unnecessary prescribing of psychotropic medications with abuse potential, chiefly benzodiazepines (Valium-like drugs), HS sedatives (“sleeping pills”) and psychostimulants (e.g. methylphenidate [Ritalin]) in prison settings. Method: After each patient/inmate was assessed, benzodiazepines and HS sedatives were tapered and stopped. Patients/inmates were restricted to no more than one antidepressant and no more than one antipsychotic agent; prescriptions for psychostimulants were also restricted. Results: Other health care staff consistently reported that the overall mental health of inmates improved soon after these changes were implemented. Prison staff reported that incidents of “strong-arming” of inmates for medications decreased as did levels of prison violence. Prescription drug costs dropped substantially and psychiatrist visits dropped by approximately 75%. Drug-seeking behaviors included complaints to the media, which was sympathetic, and to the College of Physicians and Surgeons of Newfoundland and Labrador, and eventually to a widely publicized peer review which, fortunately, endorsed my practices. Conclusions: Reducing unnecessary prescribing rates of psychotropic drugs with abuse potential to prison inmates has beneficial effects on both health care costs and inmate well-being. However, dealing with public criticism for doing so is difficult. Objectifs: J'ai cherché à réduire la prescription inutile de médicaments psychotropes avec un potentiel d'abus, principalement les benzodiazépines (médicaments comme le Valium), les sédatifs HS (“sleeping pills”), et les psychostimulants (ex.: méthylphénidate [Ritalin]) en milieu carcéral. Méthodologie: Suivant l’évaluation de chaque patient/détenu, les doses de benzodiazépines et sédatifs HS étaient progressivement diminuées jusqu’à l'arrêt. Les patients/détenus étaient limités à un antidépresseur et une substance antipsychotique; les prescriptions de psychostimulants étaient aussi limitées. Résultats: Le personnel médical signalait régulièrement que la santé mentale globale des détenus s'améliorait peu après que les changements soient mis en place. Le personnel carcéral a signalé une diminution des incidents impliquant la force avec d'autres détenus pour obtenir des médicaments et de la violence en prison. Les coûts liés à la prescription de médicaments ont diminué substantiellement et les visites en psychiatrie ont diminué d'environ 75%. Les comportements toxicomaniaques incluaient des plaintes aux médias, qui étaient favorables, et au Collège des médecins et chirurgiens de Terre-Neuve et Labrador, puis à un examen par les pairs largement publicisé, qui ont approuvé ma pratique. Conclusions: La diminution de prescription inutile de médicaments psychotropes avec un potentiel d'abus parmi les détenus a des effets positifs à la fois sur les coûts de soins de santé et le bien-être des détenus. Toutefois, faire face à la critique du public pour avoir agi ainsi est difficile.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0220.015
Scholarly communication0.0120.010
Open science0.0030.011
Research integrity0.0120.020
Insufficient payload (model declined to judge)0.0060.002

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 head0.264
GPT teacher head0.389
Teacher spread0.125 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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
Published2015
Admission routes3
Has abstractyes

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