MétaCan
Menu
Back to cohort
Record W2176091573 · doi:10.5339/qfarc.2014.hbpp0575

An E-health Based Integrated Management Program Advancing Community Treatment Of Atrial Fibrillation (IMPACT-AF)

2014· article· en· W2176091573 on OpenAlexaffabout
Syed Sibte Raza Abidi, Jafna L. Cox, Samina Abidi, Ashraf Abusharekh, Joanna Nemis‐White

Bibliographic record

VenueQatar Foundation Annual Research Conference Proceedings Volume 2014 Issue 1 · 2014
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsDalhousie University
Fundersnot available
KeywordsOperationalizationPsychological interventionMedicineHealth careEvidence-based practiceClinical decision support systemAtrial fibrillationNursingAlternative medicinePolitical scienceInternal medicine

Abstract

fetched live from OpenAlex

Atrial fibrillation (AF) is the most common abnormality of cardiac rhythm. There is growing evidence advocating an integrated multi-disciplinary approach to delivery of AF care facilitates which has led to improved care and outcomes and reductions in hospitalizations. In this research program, we have implemented a patient-centered and community-focused AF management program—termed as IMPACT-AF—to provide specialized AF care at the primary care level. Our approach is to exploit state-of-the-art e-Health technologies to: (a) computerize Canadian clinical practice guidelines as a web-based clinical decision support accessible to primary care providers to deliver evidence-informed AF diagnostic and therapeutic interventions at the primary care level; (b) monitor the patient in a home-based setting and proactively generate alerts and reminders to family physicians in response to adverse trends in the patient condition; and (c) engage patients through m-Health (mobile health) tools to self-manage their condition and undergo behaviour modification. Two research themes have been pursued in the development of the IMPACT-AF program: (1) Translation of AF Clinical Guidelines to Achieve Evidence-Informed AF Management: This theme involved three main tasks: (i) Computerization of the AF guidelines using ontology based knowledge models; (ii) Localization of the computerized AF guidelines to implement the local clinical pathways; and (iii) Operationalization of the computerized AF guidelines into practice through a computerized decision support system to provide evidence-informed patient care at the point-of-care. (2) Patient Engagement to Achieve Home-Based AF Management: This theme focused on the implementation of innovative AF self-management and behaviour modification interventions delivered to patients using mobile devices. We computerized theoretical behaviour modification model—i.e. Social Cognition Theory (SCT)—to generate personalized and mobile patient care plans. Using an AF (mobile) patient diary patients record their vitals and other AF related symptoms, and in turn receive educational messages, alerts, reminders and behaviour modification plans. The primary outcome of the IMPACT-AF project is reduction in AF related CV hospitalization. The secondary outcome is at two levels: (i) Process of Care: Reduction in specialist consultation, echo, catheter ablations; and, (ii) Economic: Reduction in health care costs and utilization for AF services. The clinical decision support systems developed by the IMPACT-AF project is deployed across the province of Nova Sctioa, engaging 200 primary care providers to deliver evidence informed AF management at the primary care level. We are gearing for a cluster randomized study involving 4000 patients across the province--the study will permit measurement and comparison of the clinical decision support system pre- and post-intervention, and across cases. The overall result will be cost-efficient improvement of care and outcomes for AF patients. In summary, the IMPACT-AF solution offers an innovative strategy to address two critical knowledge gaps —i.e. primary care physicians are often ill-equipped to provide evidence-based care for chronic conditions, and likewise patients are underprepared to apply the 'right' self-management and behaviour modification strategies to achieve meaningful outcomes in response to a longitudinal care plan. IMPACT-AF exploits state-of-the-art e-health technologies to develop an integrated and mobile clinical decision support systems to provide evidence-based AF 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.092
GPT teacher head0.457
Teacher spread0.364 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations1
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueQatar Foundation Annual Research Conference Proceedings Volume 2014 Issue 1Same topicMedication Adherence and ComplianceFrench-language works237,207