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Record W2886573020 · doi:10.2196/10128

Use of a Digital Medication Management System for Effective Assessment and Enhancement of Patient Adherence to Therapy (ReX): Feasibility Study

2018· article· en· W2886573020 on OpenAlexvenueno aff
Ronit Shtrichman, S. Conrad, Kai Schimo, Ran Shachar, Ehud Machluf, Enrique Mindal, Howard Epstein, Shirli Epstein, Alan Paz

Bibliographic record

VenueJMIR Human Factors · 2018
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMedication adherenceMedical physicsIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Medication nonadherence is a major problem in health care, imposing poor clinical outcomes and a heavy financial burden on all stakeholders. Current methods of medication adherence assessment are severely limited: they are applied only periodically, do not relate to actual pill intake, and suffer from patient bias due to errors, misunderstanding, or intentional nonadherence. ReX is an innovative medication management system designed to address poor patient adherence and enhance patient engagement with their therapy. ReX controls and tracks pills from the point of packaging right through to the patient's mouth. ReX generates robust, real-time adherence data. The system enables patients to report outcomes, complete surveys, and receive messages and instructions. ReX includes a reusable drug dispensing unit, disposable cassette containing pills, and a cloud-based data portal. OBJECTIVE: We aimed to evaluate ReX feasibility by human factor studies including evaluation of ReX safety; ReX acceptance and usability; and ReX efficacy of providing pills according to a preprogrammed dose regimen, managing reminders and adherence data, and enhancing the adherence rate compared with the standard of care. METHODS: The ReX system was evaluated in 2 human factor, nonclinical feasibility studies. Human subjects used ReX for the administration of pill-shaped Tic Tac sweets. The initial study evaluated ReX use and pill intake administration; second was a self-controlled, 4-day home-use study. All subjects took pills at home, according to a preprogrammed dose regimen, for 4 days each via the device (ReX test) or from standard packaging (control test). The adherence rate (percent of pills taken) was measured by the study subject's report, remaining pills count, and ReX records (in the ReX test). ReX safety and usability were evaluated by a questionnaire filled out by the subject. RESULTS: The initial feasibility study evaluated usability and acceptance of the ReX novel approach to pill dispensing. All subjects successfully managed 2 pill intakes. The ReX device was rated as easy to use by 81% (48/59) of subjects. The 4-day home-use study evaluated the safety, efficacy, and usability of the ReX system. No adverse event occurred; no pill overdose or pill malformation was reported. The overall adherence rate in the ReX test was 97.6% compared with 76.3% in the control test (P<.001). Real-time, personalized reminders provided in the event of a delay in pill intake contributed to 18.0% of doses taken during the ReX test. The ReX system was found easy to use by 87% (35/40) of subjects; 90% (36/40) felt comfortable using it for their medication. CONCLUSIONS: ReX's novel "tracking to the mouth" technology was found usable and accepted by subjects. The assessment of adherence rates was reliable; adherence of subjects to the dose regimen was significantly enhanced when using ReX compared with the standard of care.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.110
GPT teacher head0.413
Teacher spread0.303 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations15
Published2018
Admission routes1
Has abstractyes

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