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Record W4283218475 · doi:10.1186/s12916-022-02401-5

Length of initial prescription at hospital discharge and long-term medication adherence for elderly, post-myocardial infarction patients: a population-based interrupted time series study

2022· article· en· W4283218475 on OpenAlexafffundabout
Jon-David Schwalm, Noah Ivers, Zachary Bouck, Monica Taljaard, Madhu K. Natarajan, Francis Nguyen, Waseem Hijazi, Kednapa Thavorn, Lisa Dolovich, Tara McCready, Erin O’Brien, Jeremy Grimshaw

Bibliographic record

VenueBMC Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsOttawa HospitalUniversity of OttawaPublic Health OntarioUniversity of TorontoHamilton Health SciencesWomen's College HospitalMcMaster UniversityPopulation Health Research Institute
FundersCorHealth OntarioOntario Ministry of Health and Long-Term Care
KeywordsMedicineMedical prescriptionMyocardial infarctionPsychological interventionEmergency medicinePopulationInternal medicinePhysical therapyPediatrics

Abstract

fetched live from OpenAlex

BACKGROUND: Preliminary evidence suggests that providing longer duration prescriptions at discharge may improve long-term adherence to secondary preventative cardiac medications among post-myocardial infarction (MI) patients. We implemented and assessed the effects of two hospital-based interventions-(1) standardized prolonged discharge prescription forms (90-day supply with 3 repeats for recommended cardiac medications) plus education and (2) education only-on long-term cardiac medication adherence among elderly patients post-MI. METHODS: We conducted an interrupted time series study of all post-MI patients aged 65-104 years in Ontario, Canada, discharged from hospital between September 2015 and August 2018 with ≥ 1 dispensation(s) for a statin, beta blocker, angiotensin system inhibitor, and/or secondary antiplatelet within 7 days post-discharge. The standardized prolonged discharge prescription forms plus education and education-only interventions were implemented at 2 (1,414 patients) and 4 (926 patients) non-randomly selected hospitals in September 2017 for 12 months, with all other Ontario hospitals (n = 143; 18,556 patients) comprising an external control group. The primary outcome, long-term cardiac medication adherence, was defined at the patient-level as an average proportion of days covered (over 1-year post-discharge) ≥ 80% across cardiac medication classes dispensed at their index fill. Primary outcome data were aggregated within hospital groups (intervention 1, 2, or control) to monthly proportions and independently analyzed using segmented regression to evaluate intervention effects. A process evaluation was conducted to assess intervention fidelity. RESULTS: At 12 months post-implementation, there was no statistically significant effect on long-term cardiac medication adherence for either intervention-standardized prolonged discharge prescription forms plus education (5.4%; 95% CI - 6.4%, 17.2%) or education only (1.0%; 95% CI - 28.6%, 30.6%)-over and above the counterfactual trend; similarly, no change was observed in the control group (- 0.3%; 95% CI - 3.6%, 3.1%). During the intervention period, only 10.8% of patients in the intervention groups received ≥ 90 days, on average, for cardiac medications at their index fill. CONCLUSIONS: Recognizing intervention fidelity was low at the pharmacy level, and no statistically significant post-implementation differences in adherence were found, the trends in this study-coupled with other published retrospective analyses of administrative data-support further evaluation of this simple intervention to improve long-term adherence to cardiac medications. TRIAL REGISTRATION: ClinicalTrials.gov : NCT03257579 , registered June 16, 2017 Protocol available at: https://pubmed.ncbi.nlm.nih.gov/33146624/ .

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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

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 head0.028
GPT teacher head0.323
Teacher spread0.295 · 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 designObservational
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

Citations4
Published2022
Admission routes3
Has abstractyes

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