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Record W2943141698 · doi:10.1097/naq.0000000000000340

Engaging Stakeholders to Co-design an Academic Practice Strategic Plan in an Integrated Health System

2019· article· en· W2943141698 on OpenAlexaff
Lianne Jeffs, Jane Merkley, Maya Sinno, Nicole Thomson, Nathalie Peladeau, Sandra Richardson

Bibliographic record

VenueNursing Administration Quarterly · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoSinai Health SystemUniversity of WaterlooRegistered Nurses' Association of OntarioCentre for Addiction and Mental Health
Fundersnot available
KeywordsBlueprintStrategic planningTransformational leadershipOperationalizationStrategic leadershipProcess managementBusinessStrategic thinkingProcess (computing)Strategic sourcingKnowledge managementPublic relationsStrategic financial managementPolitical scienceMarketingEngineeringComputer science

Abstract

fetched live from OpenAlex

As key members of the executive team, nurse executives play an integral role in the planning process and operationalization of strategic imperatives to ensure the overall success of the organization. Nurse executives are leading organizations through transition periods that require transformational leadership. Leaders must design a shared vision and set strategic priorities; empower others to lead; ensure access to resources needed for safe care delivery; and inspire people to meet the demands of the future. Paramount to effective strategic planning and achievement of positive outcomes is a leadership team that engages key stakeholders in the strategic planning process. This article provides an overview of a recently integrated health system's strategic planning process that included the engagement of patients and caregivers. This can serve as a blueprint for others in their efforts to implement a systematic approach for enhancing collaborative academic practice in their organizations.

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)0.087
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.087
Threshold uncertainty score0.459

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0870.062
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0170.009
Scholarly communication0.0210.012
Open science0.0040.026
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0050.002

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 head0.420
GPT teacher head0.536
Teacher spread0.117 · 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 designNot applicable
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".

Quick stats

Citations12
Published2019
Admission routes1
Has abstractyes

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