The impact of managed competition on diversity, innovation and creativity in the delivery of home-care services
Bibliographic record
Abstract
Reforming publicly funded healthcare systems by introducing elements of competition, often by allowing for-profit providers to compete with not-for-profit providers, is a strategy that has become commonplace in Western democracies. It is widely thought that the competitive forces of the marketplace will lead to greater efficiency, diversity and even innovation in the delivery of services. Between 1997 and 2000, a model of 'managed competition' was introduced as a major reform to the delivery of home-care services in Ontario, Canada. It was expected that by allowing greater competition within the home-care sector, this model would constrain costs and encourage provider agencies to become more innovative and creative in meeting service delivery needs. The purpose of this case study is to explore the impact of the managed competition reform on the for-profit and the not-for-profit organisations that provided rehabilitation home-care services, and, more specifically, to assess the extent to which the goal of greater diversity, innovation and creativity was achieved following implementation of the reform. A purposive sample of 49 key informants were selected for in-depth interviews, and a survey of the 36 organisations that provided rehabilitation home-care services and the 43 community care access centres that purchased services from these provider agencies was conducted. Data were collected between November 2002 and May 2003. Findings demonstrate that a combination of coercive, mimetic and normative isomorphic pressures have constrained diversity, innovation and creativity within the home-care sector. The implication is that the features that have traditionally distinguished for-profit and not-for-profit provider agencies from each other are rapidly disappearing, and a new hybrid organisational structure is evolving.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".