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Record W7029273153

THE IMPACT OF A MEDICATION PROFILE RELEASE PROGRAM ON OUTPATIENT DRUG USE: AN EVALUATION OF SASKATCHEWAN'S PATIENT PROFILE RELEASE PROGRAM

2023· dissertation· en· W7029273153 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsPolypharmacyDrugCohortPopulationIntervention (counseling)PharmacyMedical prescriptionAsthmaPharmacotherapy
DOInot available

Abstract

fetched live from OpenAlex

The Patient Profile Release Program was designed to promote optimal drug use in Saskatchewan by identifying individuals who are at risk for drug-related problems and communicating these drug use concerns to the physicians and pharmacists responsible for their care. During 1992, the PPRP had three components — the Extreme User, Polypharmacy and Polyprescriber Programs — which monitored for the use of high dosages of mood- modifying drugs and asthma medications, the use of multiple different drugs and the use of multiple prescribers, respectively. Similar programs have been implemented elsewhere; however, there is little objective evidence that these programs effectively influence physician prescribing practices and improve patient drug use. 
\nThe objectives of the present investigation were to describe the individuals who were identified by the PPRP in 1992, evaluate the impact of the PPRP on drug use by these patients and describe the use of mood-modifying drugs and asthma medications in the province of Saskatchewan. An historical cohort study with a 3.5 month follow-up period was used to evaluate the impact of the PPRP. The study population included all individuals who had a profile released under the Program during 1992. Profiles for the intervention group subjects were released at the time that they were identified whereas profile release for the comparison group subjects was delayed for at least two months after the index identification. Re-identification by the PPRP was the primary outcome of interest.
\nDuring 1992, 3124 individuals were identified by the PPRP, of which 2542 (81%) were eligible for inclusion in this study. 58.7%, 25.1% and 15.3% of the subjects were identified under the ExU, PPh and PPr Programs, respectively. The ExU and PPh subjects tended to be female and elderly. Women were also more likely than men to be identified under the PPr Program.
\nFor all three Program components, the intervention group subjects were significantly less likely than comparison group subjects to be re-identified by the PPRP. This reduction in the likelihood of re-identification persisted even after controlling for differences between the study groups with respect to age, sex, residence, coverage type, the numbers of pharmacies and prescribers during the pre-identification period, hospitalization during the follow-up period, the level of extreme use and the number of different drugs. A long-term descriptive analysis of the intervention group subjects demonstrated that re-identification continued during the 9 month post-intervention period. This finding highlights the need for ongoing feedback.
\nThe findings of the present investigation indicate that the release of patient medication profiles under Saskatchewan's PPRP was associated with a reduction in the risk of re-identification during a short-term follow-up period. Since re-identification is a marker of changes in drug utilization, the findings indicate that profile release was associated with a decreases in the level of drug use, the number of different drugs and the number of different prescribers for individuals identified under the ExU, PPh and PPr Programs, respectively. Given the high threshold criteria for identification under the PPRP, the observed decreases in drug utilization reflect an improvement in the quality of patient drug use.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.322
Teacher spread0.277 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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