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Record W3001248810 · doi:10.2196/15691

Exploring an Innovative Care Model and Telemonitoring for the Management of Patients With Complex Chronic Needs: Qualitative Description Study

2020· article· en· W3001248810 on OpenAlexaffvenueabout
Kayleigh Gordon, Carolyn Steele Gray, Katie N. Dainty, Jane DeLacy, Patrick Ware, Emily Seto

Bibliographic record

VenueJMIR Nursing · 2020
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsWilliam Osler Health SystemNorth York General HospitalSinai Health SystemLunenfeld-Tanenbaum Research InstituteUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsChronic careThematic analysisNonprobability samplingHealth careQualitative researchNursingIntegrated careAmbulatory careMedicinePopulationProcess managementPsychologyChronic diseaseFamily medicineBusinessSociology

Abstract

fetched live from OpenAlex

BACKGROUND: The growing number of patients with complex chronic conditions presents an urgent challenge across the Canadian health care system. Current care delivery models are overburdened, struggling to monitor and stabilize the complex needs of this growing patient population. OBJECTIVE: This qualitative study aimed to explore the needs and perspectives of patients and members of the care team to inform the development of an innovative integrated model of care and the needs of telemonitoring (TM) for patients with complex chronic conditions. Furthermore, we explored how these needs could be successfully embedded to support this novel model of complex chronic care. METHODS: A qualitative description design was utilized to conduct and analyze 29 semistructured interviews with patients (n=16) and care team members (CTM) (n=13) involved in developing the model of care in an ambulatory care facility in Southern Ontario. Participants were identified through purposive sampling. Two researchers performed an iterative thematic analysis using NVivo 12 (QSR International; Melbourne, Australia) to gain insights from examining multiple perspectives of different participants on complex chronic care needs. RESULTS: The analysis revealed 3 themes and 13 subthemes, including the following: (1) adequate health care delivery remains challenging for patients with complex care needs, (2) insights into how to structure an integrated care model, and (3) opportunities for TM in an integrated model of care. Participants not only identified continued challenges in accessing and navigating care in a fragmented and disconnected delivery system but also identified the need for more self-management support. Patients and CTM described the structure of an integrated model of care, including the need for a clear referral and triage processes and composing a tight-knit circle of collaborating interdisciplinary providers led by a nurse practitioner (NP). Finally, opportunities for TM in an integrated model of care were identified, including increasing access and communication, the ability to monitor specific signs and symptoms, and building a clinical workflow around TM-enabled care. CONCLUSIONS: Despite entrenched health care service delivery models, a new model of care is acutely needed to care for patients with complex chronic needs (CCN). NPs are in a unique position to lead TM-enabled integrated models of care. TM can facilitate frequent and necessary monitoring of patients with CCN with more than one condition in integrated models 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 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)0.023
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0100.010
Scholarly communication0.0050.005
Open science0.0020.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.307
GPT teacher head0.416
Teacher spread0.109 · 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 designQualitative
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".

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Citations17
Published2020
Admission routes3
Has abstractyes

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