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Record W4377023000 · doi:10.1186/s40814-023-01315-0

Team approach to polypharmacy evaluation and reduction: feasibility randomized trial of a structured clinical pathway to reduce polypharmacy

2023· article· en· W4377023000 on OpenAlexafffund
Dee Mangin, Larkin Lamarche, Gina Agarwal, Abbas Ali, Alan Cassels, Kiska Colwill, Lisa Dolovich, Naomi Dore Brown, Barbara Farrell, Karla Freeman, Kristina Frizzle, Scott Garrison, James Gillett, Anne Holbrook, Jane Jurcic-Vrataric, James McCormack, Jenna Parascandalo, Julie Richardson, Cathy Risdon, Diana Sherifali, Henry Siu, Sayem Borhan, J.A. Templeton, Lehana Thabane, Johanna Trimble

Bibliographic record

VenuePilot and Feasibility Studies · 2023
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsUniversity of AlbertaBruyèreUniversity of VictoriaUniversity of TorontoMcMaster UniversityHealth Sciences CentreUniversity of British ColumbiaMcMaster University Medical Centre
FundersMcMaster University
KeywordsPolypharmacyRandomized controlled trialReduction (mathematics)MedicineIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Polypharmacy is associated with poorer health outcomes in older adults. Other than the associated multimorbidity, factors contributing to this association could include medication adverse effects and interactions, difficulties in managing complicated medication regimes, and reduced medication adherence. It is unknown how reversible these negative associations may be if polypharmacy is reduced. The purpose of this study was to determine the feasibility of implementing an operationalized clinical pathway aimed to reduce polypharmacy in primary care and to pilot measurement tools suitable for assessing change in health outcomes in a larger randomized controlled trial (RCT). METHODS: We randomized consenting patients ≥ 70 years old on ≥ 5 long-term medications into intervention or control groups. We collected baseline demographic information and research outcome measures at baseline and 6 months. We assessed four categories of feasibility outcomes: process, resource, management, and scientific. The intervention group received TAPER (team approach to polypharmacy evaluation and reduction), a clinical pathway for reducing polypharmacy using "pause and monitor" drug holiday approach. TAPER integrates patients' goals, priorities, and preferences with an evidence-based "machine screen" to identify potentially problematic medications and support a tapering and monitoring process, all supported by a web-based system, TaperMD. Patients met with a clinical pharmacist and then with their family physician to finalize a plan for optimization of medications using TaperMD. The control group received usual care and were offered TAPER after follow-up at 6 months. RESULTS: All 9 criteria for feasibility were met across the 4 feasibility outcome domains. Of 85 patients screened for eligibility, 39 eligible patients were recruited and randomized; two were excluded post hoc for not meeting the age requirement. Withdrawals (2) and losses to follow-up (3) were small and evenly distributed between arms. Areas for intervention and research process improvement were identified. In general, outcome measures performed well and appeared suitable for assessing change in a larger RCT. CONCLUSIONS: Results from this feasibility study indicate that TAPER as a clinical pathway is feasible to implement in a primary care team setting and in an RCT research framework. Outcome trends suggest effectiveness. A large-scale RCT will be conducted to investigate the effectiveness of TAPER on reducing polypharmacy and improving health outcomes. TRIAL REGISTRATION: clinicaltrials.gov NCT02562352 , Registered September 29, 2015.

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)0.009
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.611
GPT teacher head0.570
Teacher spread0.041 · 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 designRandomized trial
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

Citations16
Published2023
Admission routes2
Has abstractyes

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