The Road Towards Evidence-based, Person-centered, Provider-friendly Integrated care Management of Chronic Conditions.
Bibliographic record
Abstract
Background: Clinical pathways and integrated care systems are closely related concepts, both aiming to streamline and improve patient care. Clinical pathways are structured multidisciplinary care plans which detail essential steps in the care of patients with a specific clinical problem. They promote organized and efficient patient care based on evidence-based practice. Integrated care systems, conversely, are a more holistic approach that coordinates services across the entire spectrum of patient care, including primary, secondary, and tertiary services, as well as social care. The relationship between the two lies in their shared goal of providing seamless, high-quality care that is tailored to the individual needs of patients, reducing fragmentation and improving outcomes. Approach: In 209, the Ministry of Health and Long-term Care in Ontario, Canada, unveiled Ontario Health Teams (OHTs) as a groundbreaking integrated care model designed to provide integrated, person-centered care to Ontarians throughout their life span. Presently, there are 58 OHTs in operation. The Burlington OHT was one of the initial OHTs to receive approval. In late 2023, the Burlington Ontario Health Team (BOHT) was identified as one of 2 OHTs who would be supported with additional resources to accelerate their journey to become a designated OHT. A designated OHT will be fiscally and clinically responsible for their attributed population. A new set of deliverables and tasks were assigned to the accelerated OHTs. The first of these tasks was to design and implement two clinical pathways for individuals living with Chronic Obstructive Pulmonary Disease (COPD) and Heart Failure (HF). The BOHT's approach to co-designing interventions with a population health perspective necessitated a redefinition of clinical pathways to better fit within an integrated care system. The goal was to create an integrated care pathway that covers the entire disease trajectory, from prevention and early detection to palliation, and facilitates care across various health and social care settings. Results: To co-design our integrated care pathways we followed the -step methodology described by O'Cathain A, et al in 209 when co-designing complex health interventions. We added some additional steps. The modified methodology included planning the co-design process, involving all stakeholders (including those who will implement, deliver, use and benefit from the intervention), bring together a team and establish decision-making processes, needs assessment via multiple engagement tools (interviews/focus groups and virtual and in-person engagement sessions), review published research evidence and local data, draw on existing international exemplars, identify relevant change ideas, articulate program theory, undertake primary data collection, understand the local context, pay attention to future implementation of the intervention in the real world, design and refine the intervention and finally implement and evaluate. Three change ideas were identified based on the co-design process: ) One Digital Platform: This platform aims to centralize care pathways for various chronic diseases, incorporating evidence-based standards, and providing tools like standardized forms and navigation maps to streamline health and social services, 2) Navigation Hub: The establishment of a hub to offer advanced navigation services is crucial for both providers and patients, ensuring efficient and directed care, 3)Expand Self-Management Programs: Leveraging the success of existing community-based programs to empower patients in managing their conditions is a key strategy. Implications: At the conference, we will unveil the intricately crafted co-design and implementation blueprints of the BOHT's integrated care pathways, setting the stage for other integrated care systems to follow suit in deploying comparable health interventions.
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 | 0.044 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".