"Technology is the enabler Enhancing “one team, one record, one number, one fund” and connecting Home Care utilization to outcomes for patients and providers”.
Bibliographic record
Abstract
Since 2012, St. Joseph’s Health System has been testing and evaluating Integrated Models of Care while maintaining a focused commitment to spreading and scaling sustainable integrated service delivery and integrated funding models. Our collective learnings and expanding partnerships are being celebrated through the creation of the SJHS Centre for Integrated Care. The Centre for Integrated Care, or “CIC”, is an innovation incubator and accelerator powered by the St. Joseph’s Health System (SJHS), the Research Institute of St. Joe's Hamilton, and the partners we work with. We believe getting timely and adequate care should be less complicated: fewer steps, less confusion, less wasted effort, more sharing, and more time to spend with people. Integrated care means integrating people who provide care and the systems they use. We prefer practical and simple innovations that fit within existing resources. Our mission is to integrate systems and remove barriers to advance people-centred care. Our hub includes patients, families/caregivers, care providers, health care leaders, researchers, educators, and technology experts who are united in one goal: to improve the delivery of health and social services for better outcomes. During the presentation we will describe our Integrated Comprehensive Care (ICC) Program for COPD and CHF patients and highlight how the work and in particular the technology, has enabled integration at the micro, meso, and macro levels with a specific focus on equity, access, and provider experience. We will touch on learnings from the pandemic and provide a visual representation linking actual volume and type of home care utilization to outcomes both the year prior to the pandemic and two years during the pandemic; Understanding service delivery trends is important to understanding how resources are contributing to an outcome, such as community staffing decisions impacting hospital lengths of stay. Discussion begins with best practice care standards and pathways. Funding constraints are secondary. The ongoing dialogue between and within acute and home and community care serves to educate and adjust practice as the evidence directs. This approach comes from establishing a shared vision, transparency, trust, and hard work upfront when developing programs. As opposed to command and control, it’s a collective goal to provide the best care within the existing resources and be open to shuffling resources, and looking at other ways of delivering care, including the use of technology, to provide services. Time permitting, we will engage participants in discussions around how we can collectively advance integrated care and suggest opportunities for moving forward. At the end of the day, technology is not the driver in health care. Rather, care is enabled by technology – to support remote access, consistent practice, easily accessible synchronous documentation, ongoing refinement of best practice, and much more. It is essential to the future of health care, meeting client expectations and supporting practitioners to give their best.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.022 | 0.009 |
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".