Integrated Care and Population Health Management: Does Your System have the Capacity to Succeed?
Bibliographic record
Abstract
Introduction: Integrated Care and Population Health Management are inter-related concepts that are gathering much attention in health systems around the world; however, in both cases, their implementation may require a fundamental shift in how health systems are structured. Purpose: This work aims to identify tangible enablers that must be established if a health system is to be successful in achieving its goals of Integrated Care and Population Health Management; and establish a framework by which a system can assess their capacity to be successful. Working with a team of health system experts (including patients, caregivers, health-care professionals, researchers, and administrators) five key enablers were identified from literature on Integrated Care and PHM; 1) a Collaborative Governance structure 2) a detailed registry of all members of the population 3) a detailed list of all service providers (including registered and non-registered health professionals, and both clinical and social service providers) 4) an integrated Shared Care Record and 5) an integrated data and analytics platform. Each enabler was mapped onto at least one of the 9 pillars of Integrated Care and/or the 6 steps in the Population Health Alliance’s Population Health Management Framework. Audience and Engagement: This workshop seeks to bring together policy makers, administrators, clinicians, providers, patients, clients, and caregivers working at implementing integrated care and/or population health management principles within a healthcare system. While these enablers may be taken for granted in systems further evolved in their Integrated Care journey, they remain challenges in many others. Our Audience will be asked to apply a “whole system” lens to consider the validity of these enablers as described and their system’s capacity relative to each (eg. Do we have a collaborative governance structure that incorporates all organizations and providers who support our population?). Workshop structure: The workshop will be 90 minutes in length and proceed as follows 1) 5 min introduction to the problem and reference materials; 2) 20-minute description of our internal validation process and results; 3) 20-minute Rapid-cycle world café style engagement to validate each of the 5 enablers with audience members; 4) 40-minute group discussion and report-back on their health system’s relative capacity in each of the 5 areas and success criteria to be considered; 5) 5-min wrap-up and summary. Takeaways: Through this collaborative workshop we hope that participants will benefit from a reflection on some of the key enablers necessary to support integrated care and PHM, and an understanding of where their system has strengths and opportunities for improvement. We also hope that attendees will develop relationships with one another that will facilitate shared learning around their relative strengths and ideas about tangible projects that can support their development. The facilitation team hopes to apply lessons learned from the session to development of a tool that can be shared with systems around the world considering how to build capacity for integrated care and PHM.
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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 | 0.062 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.027 | 0.029 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.014 | 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".