Interprofessional Collaboration in a Telehealth Context in Primary Care: A Research Protocol Exploring the Perspectives of Patients Living with Chronic Illness (Preprint)
Bibliographic record
Abstract
BACKGROUND The enhancement of Primary care and the prevalence of chronic diseases are key issues worldwide, especially in Canada. As the incidence of chronic illnesses rises, they have emerged as the foremost cause of mortality worldwide. This trend has led to a surge in demand for healthcare services, placing significant pressure on primary care systems. The evolving and multidimensional nature of the chronic disease situation creates challenges that can affect the quality of care offered to patients. The lack of communication directly affects relational continuity, i.e., the sharing of information from previous events and circumstances, to ensure that care is appropriate to the individual and his or her problem. Patients living with chronic disease may also perceive contradictory recommendations from different professionals, which undermines their potential for self-management. These challenges highlight the importance of establishing clear patient pathways within interprofessional teams, ensuring that information is shared efficiently, and that the continuity of care is coordinated effectively, especially in a telehealth context. In 2019, with the arrival of the pandemic, the demanded of telehealth emerged as a crucial resource for patients with chronic illnesses. This resource was implemented with no specific infrastructure, often without patient support, and left to the discretion of individual professionals. Interprofessional collaboration plays a critical role in the use of telehealth in managing chronic diseases. Despite its advantages, telehealth can have negative effects on interprofessional teamwork if used sub-optimally OBJECTIVE This study aims to understand the interprofessional collaboration (IPC) process as experienced by patients in a telehealth context within primary care, with a focus on patient engagement. More specifically, the study's objectives are: 1) to describe the IPC process in telehealth within primary care from the perspective of patients living with chronic conditions; 2) to identify, in collaboration with patients living with chronic disease, the barriers and facilitating factors of this process; 3) to understand the engagement of these patients in relation to the IPC process in a telehealth context. METHODS To describe the process of interprofessional collaboration in the telehealth context in primary care from the perspective of patients living with chronic disease, this qualitative research is based on a constructivist research methodology. The research team constructs knowledge derived from the interpretation of information that was obtained during the interviews with participants. To meet the study's objectives, a qualitative journey mapping data collection will be carried out, following the approach of Trebbel et al., (2010). Individual interviews will be analyzed iteratively. This method is useful for this research as it visually and collaboratively captures patients lived experiences. RESULTS Data collection was completed between May 2024 and November 2024. A total of 22 interviews were conducted. The project is currently in progress, with multiple papers being drafted for publication in peer reviewed journals. CONCLUSIONS The results of this study will support and improve the interprofessional collaboration process in the telehealth context by providing concrete insights into patients’ experiences, identifying gaps and strengths in current collaborative practices, and offering evidence-based recommendations. Journey mapping will help identify potential facilitating factors for improving primary care in the telehealth context according to the patient's journey. Results will be used to build a practical guide (in phase 2) supporting interprofessional collaboration in the primary care telehealth context.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".