“I wish I had known from start but somehow had to learn hard way”: reflections on their integrated care journey 
Bibliographic record
Abstract
Introduction: System-wide integrated care cases across the world have often been recognised as “groundbreaking”, “disruptive” or “pioneer”. We all have heard narratives of success, usually by inspirational leaders and told at the initial take-off phases of programmes. But we now little about the challenges faced by these innovators as time passes, leaders perhaps move on, new policy agendas come to compete with integrated care and expectations on the outcomes decline. The programme then rests on decisions makers who have to muddle through the challenges and eventually crises, aiming to advanced integrated health and care in their territories. Aim: Workshop will discuss the experience of decision makers from well-known international cases of system-wide integrated care that have been in place for a few years and have endured various challenges over their journey. Purpose will be to discuss informally the challenges of putting in place and implementing integrated care systems, and the efforts to muddle them through over the years. Four international cases will be discussed by decision-makers. At present, it can be confirmed the inclusion of Catalonia (Spain) and the Basque Country (Spain) and other two experiences are suggested now as a placeholder (one of the Well-being counties in Finland; one of the cases of the Body Corporate model in Scotland; examples from Australia; New Zealand; Canada; etc.) until they can be confirmed. Participants will engage with the following questions: oWhat would we have done differently? oHow much structure did we deploy over the years? oHow far have we moved towards changing relationships, power, involving people, etc? oWhich new governance arrangements and distribution of power has been redesigned? oHow much has the journey changed “whole system”? oHow much the journey has changed me as leader? Do we need a new updated “system leadership” orientation? oWhich main outcomes and measures are being used to monitor progress, from the patient/citizen, workforce and system perspective? oWhich digital transformation are you developing related to Integrated Care agenda? Who is it for? Representatives from other international organisations that have been on the integrated care journey. Representatives from organisations and policymakers from different countries and regions who have recently started or are about to start their own journey. What are you going to do? oIntroduction oRoundtable with different experiences (60 min): Short presentation of each panellist (12 min) Q&A (15 min) oOpen discussion with the audience (20 min) oConclusions (10 min) How are you going to engage with the audience? Special focus on policy and action to develop Integrated Care strategy both within health (vertical integration) and also between health and social care sector (horizontal integration) How are you going to summarize the take home messages? Special focus on practical lessons which could be feasible and scalated in other countries and regions related to Integrated and key core elements of new model of care, governance, outcome framework, finance and commissioning arrangements and integrated information systems to facilitate Integrated care in practice.
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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 | 0.024 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.036 | 0.026 |
| Scholarly communication | 0.021 | 0.016 |
| Open science | 0.005 | 0.023 |
| Research integrity | 0.013 | 0.043 |
| Insufficient payload (model declined to judge) | 0.010 | 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".