Digitizing Integrated Care – Aligning technology to values
Bibliographic record
Abstract
Introduction: This workshop will build on an international integrated knowledge translation project that seeks to advance meaningful adoption of digital health services to enable delivery of high-quality and equitable person-centred integrated care. Problem: Digital health solutions and services are recognized as critical to achieve person-centred integrated health and social care. To date work in this area has focused on the development and adoption of these technologies in supporting the (functional) activities of integrated care delivery, but less known is how these technologies can advance, or upend, the (normative) values of the communities, teams, and organizations that underpin their vision for greater integration. With the global rapid uptake of digital health tools in the wake of the COVID-19 pandemic, systems are faced with the opportunity to quickly leverage innovative solutions, and the risk of doing so without a clear view the path this adoption sets us up to follow. Audience: To address the problem this workshop will share findings from the work of the Value Aligned Digital Health Consortium to develop a set of recommendations to inform implementation, evaluation, scale and spread of value-aligned technologies in person-centred integrated care. The Consortium includes researchers, providers, systems leaders, industry representatives as well as a central community partnership ensuring representation of diverse patient, caregiver and community stakeholders. As such, the audience for this workshop will include a similar range of representative groups, bringing in additional international perspectives to discuss how recommendations can be refined and adapted to meet local needs and contexts. Structure and engagement: The Consortium has been running a series of deliberative dialogues with diverse stakeholder groups to arrive at recommendations and guidelines. This workshop would run a modified dialogue session in which delegates will discuss and refine recommendations to account for contextual considerations across different regions. Delegates will work in small groups (5-6 per table), facilitated by our team members, to discuss three topics: values, implementation recommendations, and evaluation recommendations. Facilitators will use a live Google Jamboard to record ideas shared by the group. Workshop structure: 1) Introduction and background of the project (10 minute presentation from project co-leads Carolyn Steele Gray and Jay Shaw); 2) Understanding values of integrated care (10 minute presentation by Nick Zonneveld); 3) patient/community reflection from a patient consortium member (8 minutes) 4) Dialogue methods and activity set up (7 minute presentation by Marissa Bird to describe methods and set up the dialogue activity for delegates); 4) Facilitated small group work on 3 topics, values, implementation, evaluation (45 minutes; 15 minutes per topic); 5) Wrap-up (10 minutes – facilitators present the live Jamboards and elicit any additional feedback from delegates. Summarizing take home messages: This workshop will directly inform the final report to be published on this project. We will additionally be generating info-graphics and short videos to help disseminate learning generated by this workshop and the broader project. All delegates of the workshop will be invited to join the Consortium should they wish to have ongoing engagement.
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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 | 0.043 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.027 |
| Scholarly communication | 0.030 | 0.037 |
| Open science | 0.005 | 0.033 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.016 | 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".