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Record W4413358452 · doi:10.5334/ijic.nacic24048

Connected Care: A co-designed community-led pathway for early detection and intervention for chronic obstructive pulmonary disease

2025· article· en· W4413358452 on OpenAlexaboutno aff
Cécile Raymond, Christopher T. Chan, Kyle Maccallum, Paulina Bleah, Joe Pedulla, Lori Seeton, Melissa Chang, Alina Blazer, Andrew Kouri, Ana MacPherson, Erin Stankevicius, Tania Carlyle, Jill Quance

Bibliographic record

VenueInternational Journal of Integrated Care · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsnot available
Fundersnot available
KeywordsPulmonary diseaseMedicineIntervention (counseling)COPDIntensive care medicineNursingInternal medicine

Abstract

fetched live from OpenAlex

Background: We developed a community pathway for chronic obstructive pulmonary disease (COPD), one of the most prevalent chronic respiratory conditions in Canada. We had the unique opportunity to co-develop a pathway that truly reflects health status and care continuum perspectives and strengths in COPD. Approach:COPD is one of the most common reasons for hospital admission in Canada, and in Ontario accounts for up to one-third of all health care utilization. COPD is also one of the most common comorbidities in the community.During this presentation, the audience will learn how Connected Care in partnership with the University of Toronto Division of Respirology and Toronto Paramedic Services Community Paramedicine developed a comprehensive COPD pathway for residents of the Greater Toronto Area (GTA). We will also demonstrate how these groups worked together to co-design a pathway, and will share interesting findings from this complex patient population.Planning involved bringing key partners and stakeholders together in the engagement phase to better understand the target patient population we proposed to screen for COPD. Leveraging existing resources was key given the abundance of information about the COPD journey and the testing required for this patient population. The clinical team, including nurse practitioners, respiratory therapists and Respirologists were instrumental in the design of the pathway, providing input and clinical guidance. Throughout the pathway pilot phase, we will continue to revise the process based on both clinical and patient feedback.This pathway will provide earlier access to treatment for community residents with diagnosed and un-diagnosed COPD that are often missed, preventing unnecessary 9 calls, Emergency Department visits, and hospital admissions. Results:The COPD Pathway aims to keep residents in their community and manage symptoms to prevent unnecessary 9 calls, visits to the Emergency Department, and hospitalization. The pathway has multiple services and streams of follow-up based on the patients needs: ) Proactive outreach and screening in high priority settings such as Naturally Occurring Retirement Communities (NORCs) with an emphasis on prevention and health promotion in addition to intervention;a. NORCs present an opportunity to keep people healthy; this was an opportunity to not re-invent the wheel but bring together evidence-based models that are working to be even greater than the sum of its parts2) Leveraging the experience and scope of various roles to create an effective pathway3) Patients are treated based on the pathway that suits their needsa. We have an escalation of care option where a nurse practitioner is able to refer patients living with moderate to severe COPD to a Respirologist4) Patients receive ongoing monitoring and care5) Patients are reintegrated into community and able to self-manage their condition.The pilot was initiated in April 2024 and residents were identified through Paramedic Led Wellness Clinics. So far, we have conducted four Wellness Clinics, where 95 residents have been screened, and 0 referrals to the pathway have been generated. We will provide initial results and impacts at the conference. Implications: Through this pathway, our highly engaged team is: Detecting residents who may be living with undiagnosed COPD earlier than otherwise possible Monitoring existing COPD patients to reduce exacerbation/unnecessary 9 calls/Emergency Department visits Providing seamless care from community to hospital In addition, we have discovered that we are screening not only patients who may screen positive for COPD through spirometry testing, but also patients who fall outside this pathway but equally require a more comprehensive assessment for another respiratory condition, and we therefore are providing our findings back to their primary care provider for further investigations and treatment.

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)0.006
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0040.002
Open science0.0020.011
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.013
GPT teacher head0.317
Teacher spread0.304 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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