Governance in times of turbulence: how has management by pathway facilitated the adaptation of the health and social services system in the context of Covid-19?
Bibliographic record
Abstract
In Quebec, the notion of pathway integrates social and health dimensions, user-centered and is conceived as an intertwining of several episodes of care and services over long periods with an intersectoral perspective. A reform in Quebec's health system 2015 put the implementation of such pathways at the agenda. We conducted a developmental evaluation to study the implementation of integrated care pathways in 3 healthcare organizations and their network in Quebec (2017-2019). And we currently conduct another one to follow up with these 3 organizations (+ 2) in the turbulent context of COVID-19. In parallel, we gathered observational notes during meetings of various crisis cells set up to address the COVID-19 pandemic in its very early days in one of the territories of the study (April-May 2020). We seek to understand how change in governance occurred during the development of the integrated care pathways and its impact of leadership and decision taking inside and outside through healthcare organizations. Ultimately, we try to understand whether these governance practices have effectively facilitated the response to the pandemic crisis. The analysis used a conceptual framework based on the Complex Adaptive Systems (CAS) approach of multi-level governance and the model for robust governance strategies in a turbulent context developed by Ansell, Sorensen and Torfing (2020). Qualitative empirical data were collected through documentation (N=12) and observation (N=80h). Our results show that implementation of health and social pathways is based on a double innovation in terms of governance: based on a strategic community approach and introducing a matrix structure in the organization. Although pathway-based management has not been fully implemented in the healthcare organizations studied, our observations show that the change of vision has taken place and certain reflexes have been adopted. For example, the pandemic crisis cells were based on the perspectives put forward by the field (operational level), and the decision, action and feedback loops were very short. The COVID-19 pandemic showed that the health system is capable of great agility, particularly when it relies on a matrix dynamic for decision- making. Management by care and services pathways provides a systemic vision of the issues faced by the organization, in addition to being a cross-functional management tool between the various departments and between the operational, tactical and strategic levels of governance.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".