Healthy Aging in Algoma: Tests of Change Program
Bibliographic record
Abstract
Introduction: In Algoma District, Ontario, Canada, approximately 25% of the population is 65 years of age and older. The Ontario Provincial Geriatrics Leadership Office (2020) predicts that by 2040 this number will increase to 32% and that 29% of older adults will be living with frailty. In February of 2022, Tests of Change (ToC) Program work commenced to bring an integrated care approach to healthy aging in Algoma. Healthcare member organizations of the Algoma Ontario Health Team (AOHT) and community patient, family, and caregiver advisors identified older adults living with frailty as the target population. A driver diagram of change ideas was conceptualized to support improving care for the identified population. To enact the recommended changes, three priority projects - Outpatient Geriatric Rehabilitation Capacity, Coordinated Access to Geriatric Services and Early Frailty Identification - complement each other with the common purpose of improving early frailty intervention and increasing access to the most appropriate care. Aims: The ToC Program entails: Embedding a frailty screening tool into electronic medical records for use in primary care; Initiating coordinated access to geriatric services leveraging eReferral and a common platform for electronic referral management; and Designing an outpatient geriatric rehabilitation program. This Program aims to advance the following elements: Design upstream engagement strategies (e.g., screening, prevention, disease self-management) for the target population; Increase patient access to the appropriate level of care; and Transform care coordination, transitions and recovery at home. Highlights: The AOHT has engaged partners from across the continuum of care who provide services for frail older adults. Partners include: community support services, home and community care support services, primary care, acute care, specialized geriatric services, and patient advisors. These critical partners assume leadership roles in program design, implementation and evaluation. Conclusions: Early frailty identification can improve quality of life, increase intervention success, and delay the need for specialist care. This program is predicated on the establishment of foundational processes enabled by digital tools to identify frailty early, streamline referrals for access to the most appropriate geriatric services, and provide patients with the opportunity to fully participate in interventions such as outpatient geriatric rehabilitation to increase their ability to live independently in the community. By taking an integrated collaborative approach to program planning and execution, overall patient outcomes will be improved. Transferability: The WHO Guidelines on Integrated Care for Older People (ICOPE) recommend advancing integrated care through community collaboration, a patient centered approach and supportive leadership. In 2019, the Ontario Health Team (OHT) model was introduced provincially as a way for healthcare providers to partner to deliver coordinated, integrated care. Of significance, several of the 54 approved OHTs have identified older adults living with frailty as a target population. Globally, as older adults are living longer lives, it is anticipated that there will be proportionally more older adults living with frailty. Through collaboration and sharing of the ToC program results, program scalability can be achieved at the OHT level and support the global knowledge base on efforts to strengthen integrated care for older adults.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".