Collaborating to Innovate and Improve Patient-Centred Care at Hamilton Health Sciences
Bibliographic record
Abstract
Although working in teams is common for most healthcare practitioners today, the Romanow Report (2002) directed our collective attention towards the need for effective interprofessional collaboration in primary healthcare settings. Subsequently, federal policy and funding agencies like CANARIE Inc. and the Office of Learning Technologies have focused efforts on promoting interprofessional practice using new technologies. Ideally, effective interprofessional collaboration leads to improvements in patient care ‐ yet how do organizations assess where they are and need to go with respect to optimizing teamwork and collaborative practice to improve patient care? This was exactly the design challenge taken up by Hamilton Health Sciences (HHS) in a recent collaborative pilot project with the Institute of Knowledge Innovation and Technology (IKIT) at the Ontario Institute for Studies in Education of the University of Toronto. An interprofessional Task Force was struck to develop a new philosophy of patient care for HHS (Cunningham et al., in press; Russell et al. 2004). The main challenge was to shift teamwork from exclusive reliance on face-to-face meetings and use of one-way communications technologies (e.g., voice mail and e-mail) towards asynchronous collaboration in a communal database technology called Knowledge Forum®. Over the past 18 months, results of the project reveal that participation in Knowledge Forum® successfully supported interprofessional teamwork and collaboration; democratized the knowledge-creation process; reduced turnaround times for interprofessional teamwork; and provided an ideal environment for sharing multiple sources of evidence, including patient survey data to support the knowledge-creation process. New technologies that support interprofessional teams to produce public knowledge of value to the local and extended community (such as the new philosophy of patient-centred care that emerged in this project) are powerful mediums for hospital based teamwork.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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.
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".