MétaCan
Menu
Back to cohort

P17 Implementation success of a digital cardiac rehabilitation pathway: a time and motion study

2025· article· W4417122765 on OpenAlex
Aaqil A Favas, Mihir A Kelshiker, Patrik Bächtiger, Saloni Nakhare, Eleanor Murphy, Neil Lockyer, Neil Chapman, Nicholas S. Peters

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePoster · 2025
Typearticle
Language
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsKensington Health
Fundersnot available
KeywordsUsabilityWorkforceStaffingRehabilitationObservational studyBaseline (sea)Task (project management)Cohort

Abstract

fetched live from OpenAlex

<h3>Background</h3> Cardiac rehabilitation (CR) is a structured, multidisciplinary programme that improves clinical and economic outcomes in cardiovascular disease. In the UK, these benefits are limited by poor access, uptake, and completion. Traditional in-person CR is workforce-intensive and difficult to scale amid staffing and funding constraints. Digital cardiac rehabilitation (DCR), using remote delivery through online platforms, offers a scalable alternative. While DCR may enhance access and adherence, its impact on workforce burden – a key factor in implementation success – remains unclear. <h3>Aim</h3> To evaluate DCR’s impact on workforce burden. <h3>Methods</h3> A prospective, mixed-methods, observational cohort study was conducted over nine weeks in an NHS CR department. Staff were observed at five prespecified time points before and after DCR implementation. The primary outcome was total mean task time (TMTT) per patient. Secondary outcomes included staff sentiment (questionnaire) and system usability (System Usability Scale, SUS). <h3>Results</h3> A total of 264 observations were recorded (figure 1). TMTT rose from 260.0 minutes at baseline to 318.5 minutes two weeks post-implementation, then declined to 218.0 minutes by study end – a 16.0% reduction (p &lt; 0.0001). A significant downward trend followed implementation (β = –35.6 mins/period, R² = 0.90, p = 0.0494), with reductions across roles and tasks. Pre-implementation sentiment showed dissatisfaction with documentation. SUS scores dropped initially but returned to near baseline by study end. <h3>TMTT</h3> Total Mean Task Time<b>; SD</b>: Standard Deviation; <b>DCR</b>: Digital Cardiac Rehabilitation. <h3>Conclusion</h3> The TMTT reduction reflects a decrease in workforce burden following DCR implementation. While a temporary increase occurred post-implementation, this reversed with staff adaptation. Usability score recovery suggests familiarity improved perceptions, underscoring the importance of sustained training during digital transitions. This study provides the first quantitative evidence that DCR can reduce staff task time per patient after initial adjustment. These findings support DCR’s potential to ease workforce burden and improve CR scalability. Future work should assess long-term outcomes and economic impact.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.356
Teacher spread0.346 · 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