Evidence Based Strategic Decision Making in Ontario Public Hospitals
Bibliographic record
Abstract
Context: A relatively recent focus on evidence based management has been influenced strongly by evidence based medicine. Healthcare administrators are encouraged to utilize similar principles to optimize their decision making. There are no known studies that address whether or not and how evidence is used by healthcare administrators in decision making practice and process. \nObjectives: This study explores how evidence is conceptualized by public hospital executives and whether or not, and how, evidence is brought to bear on strategic decision making. \nDesign: The study undertook a qualitative design, using a grounded theory approach. The focus was to uncover how evidence is conceptualized by decision makers, whether or not and how evidence as defined is brought to bear, and under what conditions and why evidence is brought to bear. The study included four public hospitals in the Greater Toronto Area, two academic health sciences centres and two community teaching hospitals. Hospital CEOs were asked to identify three strategic decisions (one clinical expansion, one partnership, and one decision on prioritizing quality improvement). Interviews were conducted with 19 healthcare leaders and decision makers, and content analysis was undertaken for 64 supporting documents.\nResults: Strategic decision makers in this study bring an amalgam of evidence to bear on strategic decisions. Evidence comes from sources internal and external to the organization, and includes a series of types of evidence ranging from published research to local business evidence. The reasons for bringing evidence to bear are highly intertwined. Evidence was sought, developed, and brought to bear on decisions in a formalized manner, and was used in concert with conditions internal and externalto the organization, and informed by the decision maker characteristics. \nConclusion: Evidence plays a prominent role in strategic decision making. Strategic decisions were supported by processes requiring evidence to be brought to bear.
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 | 0.023 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".