A Toolkit to facilitate the implementation of an Integrated Care Network for People living with Parkinson: A Codesign Approach
Bibliographic record
Abstract
Background: In response to the critical health care situation faced by People living with Parkinson’s (PwP), a group of experts decided to develop and implement a care model (iCARE-PD project) for addressing the complex care needs in Parkinson’s disease (PD). As part of this multidisciplinary and international project, a codesign approach was implemented to identify the central pillars of the care model, namely: home-based care delivery; integrated care; self-management support and technology-enabled care. For the success of this patient-centered model in a varied social, cultural and economic landscape, we need to develop a tool that facilitates the implementation of an integrated care network across different social contexts. Purpose & Method: The codesign approach, implemented in this study, consisted of four linked steps that were coordinated among 5 countries: (1) Preparation (2) Capture patients’ experiences by using narrative interviews and understand the patients’ trajectory; (3) Design scenarios for an integrated care delivery network with patients, care partners (CP), and health care providers (HCP) and (4) Co-produce solutions by identifying key requirements for designing a roadmap and toolkit to facilitate the implementation of an integrated care network in various social contexts. As part of the iCARE-PD project, this communication presents the findings of the final phase of the codesign approach which brought together researchers, clinicians, nurses and patient advisors in May 2022 for a workshop aimed at collectively co-defining the key elements to be included in an integrated care toolkit. Scenarios identifying key components for designing an integrated care network for PD were created by PwP, CP and HCP during previous workshops. Based on these scenarios designed previously, a workshop was conducted and recorded in order to produce a roadmap and toolkit that takes into consideration the unique challenges faced by PwP in each country, and the need for an integrated care delivery network that can be personalized and malleable to evolving and changing needs over time. Results: We will present the results of the thematic analysis of the transcript of the workshop. In order to improve person centeredness, tailor and personalize care and propose a holistic approach of PD in integrated care, a roadmap including three features needs to be integrated into a toolkit: (a) Identify ‘boundary spanners’ such as key individuals people or tools to support patient-centered care, (b) select mediators to connect various actors in the networks and create informational and technological infrastructure to facilitate access to tailored information and resources and, (c) create and share tools, data and resources to improve communication processes and coordination of care. Each of the design features involves various practical solutions shared and co-created during the workshop that could be useful to develop an integrated care toolkit.
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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 | 0.052 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.005 | 0.024 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".