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Record W7055180751

Cambridge-North Dumfries Ontario Health Team: An Exploratory Evaluation of Service Integration Planning

2021· article· en· W7055180751 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2021
Typearticle
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsExploratory researchFocus groupHealth careThematic analysisGeneral partnershipIntegrated careTransformational leadershipQualitative research
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Approaches to health care have shifted from individual treatment delivered by one health care provider, to an integrated care approach across health and social sectors involving multiple health care providers who are collaborating across sectors. A main focus of this research was to investigate the planning and development of the Cambridge-North Dumfries Ontario Health Team (CND-OHT). The CND-OHT is currently one of 42 Ontario Health Teams that are being implemented in the province according to integrated care (IC) principles.\nThe exploratory evaluation addressed a gap related to exploring initial planning and development of the CND-OHT IC team. In addition, contextual factors and mechanisms for successful integrated care efforts were explored within the evaluation. The exploratory evaluation answered three research questions. Specifically, how are members engaging in planning and decision making within the CND-OHT? How is the CND-OHT establishing a shared vision between members? And, what are the key components of successful planning and development of the CND-OHT? The exploratory evaluation drew upon realist methods, which provided a lens to understanding facilitators and barriers to IC planning.\nMethods/Research Design: Research methods involved an exploratory evaluation of CND-OHT planning processes and an evaluability assessment (EA), which is a form of exploratory evaluation. A purposive sample of N=18 was recruited from CND-OHT members, where members participated in focus groups and interviews. Thematic analysis was used to determine overarching themes across the dataset.\nResults: Five foundational partnership characteristics that foster transformational planning and integration were identified. Specifically, accountability, appreciation and value of members, optimism and hope, commitment to integration, and a “no ego” mindset. As well as, three components that support the CND-OHT common vision, and three components that hinder the CND-OHT common vision. Components that support the CND-OHT common vision include collaboration, support, and trust. Components that hinder the CND-OHT common vision include, fear and uncertainty to integration, lasting impacts of silos, and a disconnect between the provincial government and the CND-OHT. Finally, four additional components were suggested to support planning and service integration. The additional components that support planning and service integration include goals, incentives, opportunities for member engagement, and shared power.\nDiscussion and Conclusions: The exploratory evaluation provides useful information for the CND-OHT, and other integrated health care teams regarding planning and decision-making processes, and addresses an important gap in the literature in this area. A richer understanding of service integration and planning may encourage IC teams to dedicate time and resources to initial stages of integration that are necessary for success. The study also provides a rationale and context for why IC teams should consider prioritizing the importance of trusting relationships, commitment and a shared common vision.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.077
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.453

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0770.070
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0070.005
Scholarly communication0.0040.002
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.044
GPT teacher head0.245
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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