Change in the Population of Health Systems: From 1985 to 1998
Bibliographic record
Abstract
This article compares the predictions in Stephen Shortell's 1988 seminal article, The Evolution of Hospital Systems: Unfulfilled Promises and Self-Fulfilling Prophesies, with current data on health systems over a 14-year period from 1985 to 1998. Specifically, we review five of Shortell's predictions related to the horizontal growth of health systems and compare these predictions with empirical data on structural changes in the population of health systems. Our analyses suggest that Shortell's predictions corresponded to much of the actual behavior demonstrated in the population over the past one-and-a-half decades. Support was found for the following: (1) health systems form in two recurring stages; (2) previously unaffiliated hospitals are affiliating with existing systems rather than participating in the creation of new systems; and (3) health systems have evolved into five different strata, each of which represents different shares of the population; such population patterns have important implications for individual hospitals and health systems. By attending to patterns of change in the industry's social structure, hospitals and health systems can determine whether it is likely to continue along past trajectories or whether it shows signs of change that may pave way for the breakdown of existing organizational forms, entry of new organizational players, and the emergence of new governance structures.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".