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Record W2969803373 · doi:10.1089/sur.2019.148

Engaging Patients in Co-Design of Mobile Health Tools for Surgical Site Infection Surveillance: Implications for Research and Implementation

2019· review· en· W2969803373 on OpenAlex
Danielle C. Lavallee, Jenney R. Lee, John L. Semple, William B. Lober, Heather L. Evans

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

VenueSurgical Infections · 2019
Typereview
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsWomen's College HospitalUniversity of Toronto
FundersCenters for Disease Control and Prevention
KeywordsMedicineStakeholderPsychological interventionmHealthHealth careLeverage (statistics)Patient experiencePatient satisfactionQualitative researchNursingMedical emergencyPublic relations

Abstract

fetched live from OpenAlex

Abstract Background: As the use of patient-owned devices, including smartphones and tablets, to manage day-to-day activities grows, so does healthcare industry's interest to better leverage technology to engage patients. For surgical care, a unique opportunity exists to capture patient-generated health data (PGHD) including photographs. As part of a broader initiative to evaluate PGHD for surgical site infection (SSI) surveillance, we sought evidence regarding patient involvement and experience with PGHD for SSI monitoring and surveillance. Methods: Through a scoping review of the literature and semi-structured stakeholder interviews we gathered evidence on what is currently known about patient perspectives of and experiences with mobile health (mHealth) interventions for post-operative recovery. We presented findings to and discussed with the ASSIST PGHD Stakeholder Advisory Group (PSAG) to generate priorities for further examination. Results: Our scoping review yielded 34 studies that addressed post-discharge use of PGHD for monitoring and surveillance of SSI. Of these, 16 studies addressed at least one outcome regarding patient experience; the most commonly measured outcome was patient satisfaction. Only three studies reported on patient involvement in the development of PGHD tools and interventions. We conducted interviews (n = 24) representing a range of stakeholder perspectives. Interviewees stressed the importance of patient involvement in tool and program design, noting patient involvement ensures the “work” that patients do in their daily lives to manage their health and healthcare is recognized. Discussion of evidence with the ASSIST PSAG resulted in formal recommendations for direct involvement of patients and caregivers for future work. Conclusions: While mHealth initiatives to advance post-operative management offer the ability to improve patient engagement, work is needed to ensure the patient voice is reflected. Active engagement with patients and caregivers in the development of new technology, the design of new workflows, and the conduct of research and evaluation ensures that the patient experiences and values are incorporated.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.383
GPT teacher head0.626
Teacher spread0.243 · 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