Strategic Management System in a Healthcare Setting - Moving from Strategy to Results
Bibliographic record
Abstract
One of the historical challenges in the healthcare system has been the identification and collection of meaningful data to measure an organization's progress towards the achievement of its strategic goals and the concurrent alignment of internal operating practices with this strategy. Over the last 18 months the Toronto East General Hospital (TEGH) has adopted a strategic management system and organizing framework that has led to a metric-based strategic plan. It has allowed for formal and measurable linkages across a full range of internal business processes, from the annual operating plan to resource allocation decisions, to the balanced scorecard and individual performance evaluations. The Strategic Management System (SMS) aligns organizational planning and performance measurement, facilitates an appropriate balance between organizational priorities and resolving "local" problems, and encourages behaviours that are consistent with the values upon which the organization is built. The TEGH Accountability Framework serves as the foundation for the entire system. A key tool of the system is the rolling three-year strategic plan for the organization that sets out specific annual improvement targets on a number of key strategic measures. Individual program/department plans with corresponding measures ensure that the entire organization is moving forward strategically. Each year, all plans are reviewed, with course adjustments made to reflect changes in the hospital's environment and with re-calibration of performance targets for the next three years to ensure continued improvement and organizational progress. This system has been used through one annual business cycle. Results from the past year show measurable success. The hospital has improved on 12 of the 15 strategic plan metrics, including achieving the targeted 1% operating surplus while operating in an environment of tremendous change and uncertainty. This article describes the strategic management system used at TEGH and demonstrates the formal integration of the plan into its operating and decision making processes. It also provides examples of the metrics, their use in decision-making and the variance reporting and improvement mechanisms. The article also demonstrates that a measurement-oriented approach to the planning and delivery of community hospital service is both achievable and valuable in terms of accountability and organizational responsiveness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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.
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 teacher head, 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".