Bibliographic record
Abstract
Purpose This article is a primer which aims to examine the application of project management principles in organizational strategic planning. The intended audience is students in health administration and novice leaders in health care. Design/methodology/approach A six‐phase project management algorithm is presented to serve as a framework for implementing various aspects of an organization's strategic plan, with a particular emphasis on accountability processes. Findings Leaders in healthcare can increase the effectiveness of their organization's strategic planning processes and improve accountability by incorporating basic project management principles during the implementation phase of strategic planning. Research limitations/implications This is a review article drawing on a well‐established literature in project management and strategic planning. Practical implications The processes associated with generating an organizational strategic plan are well addressed in the management literature. This article succinctly outlines the application of basic project management principles to the implementation of strategic plans and organizational success, focusing on accountability processes. Social implications Cost effectiveness of health organizations can be improved by implementing project management practices in strategic planning. Originality/value The article succinctly applies basic project management principles to the implementation of strategic plans and organizational success.
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 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 | 0.026 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.024 | 0.013 |
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".