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Record W2947213028 · doi:10.2196/13896

Using a Triple Aim Approach to Implement “Less-is-More Together” and Smarter Medicine Strategies in an Interprofessional Outpatient Setting: Protocol for an Observational Study

2019· article· en· W2947213028 on OpenAlexvenueno aff
Monique Lehky Hagen, René Julen, Pierre-Alain Buchs, Anne-Laure Kaufmann, Jean‐Michel Gaspoz, Henk Verloo

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineObservational studyPharmacyFamily medicineHealth careProtocol (science)PopulationMedical prescriptionNursingMedical educationAlternative medicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Increased awareness of the world's problematic growing health care expenditure and health care shortages requires sustainable use of available resources. To promote cultural changes in medical mindsets, societies representing medical specialties have developed new Choosing Wisely strategies. The Valais Medical Society and the Valais Pharmacy Association have developed an interprofessional collaboration project entitled "Less-is-more Together-PPI" to analyze and optimize change management practices focusing on the prescription and deprescription of proton pump inhibitors (PPIs). OBJECTIVE: This study aims to enhance interprofessional collaboration between physicians, pharmacists, and patients to optimize PPI use, avoid unnecessary treatments and improve therapeutic adherence to indicated therapies, and to analyze hindrances and facilitators to implementing interprofessional Less-is-more strategies in the field. METHODS: Home-dwelling adults domiciled in Valais and prescribed PPIs in the last 6 months will be invited to participate in this observational study. The studied subpopulation will be constituted of consenting patients whose physicians and pharmacists also voluntarily agree to participate. The process of collecting, pooling, transmitting, evaluating, and protecting data has been validated by the Human Research Ethics Committee of the Canton Vaud. RESULTS: The Primary Triple Aim outcome measures will be (1) population health: patient's assessment of their own health, functional status, and disease burden using a monthly questionnaire for 6 months; Behavioral/physiological factors will be investigated using a final questionnaire at 6 months, (2) experience of care: assessment using a final questionnaire for participating patients, pharmacists and physicians, and an analysis of negative/positive experiences via 6 follow-up questionnaires, and (3) Per capita cost: participants' fluctuating or decreasing PPI intake (number of pills/dosage) and an analysis of participants' different categories following their medical prescription, in relation to possible bias effects on the overall drug intake of the population studied. Secondary outcomes will be participation rates; patient, physician, and pharmacist follow-up; and evaluations of participants' experiences and their perceived benefits, as well as whether the interprofessional process can be improved. CONCLUSIONS: This project seeks a deeper understanding of how Less-is-more and smarter-medicine strategies are perceived by patients and health care providers in their daily lives in a very specific context. It will reveal some of the hindrances to and facilitators for efficient cultural change toward a more sustainable health care system. The results will be useful to optimize and scale up further Choosing Wisely approaches. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13896.

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)0.045
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.045
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.028
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0030.002
Science and technology studies0.0050.003
Scholarly communication0.0030.003
Open science0.0030.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0250.006

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 head0.957
GPT teacher head0.777
Teacher spread0.180 · 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 designObservational
Domainnot available
GenreProtocol

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

Citations3
Published2019
Admission routes1
Has abstractyes

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