Faculty Opinions recommendation of Sustained improvement? Findings from an independent case study of the Jönköping quality program.
Bibliographic record
Abstract
Quality methods of many types have been widely used in hospitals. Although a number of specific projects have shown evidence of improvement, there is no strong evidence of the effectiveness of organization-wide or system programs over a period of time. There is no evidence of which approaches might be more suitable for different settings, or of value for money compared, for example, to employing more doctors and nurses. Jönköping is widely known in Sweden and internationally as one long-running example of a successful systemwide improvement program. As with other programs, critics and researchers have asked for evidence of improved outcomes for patients and of the costs of the program. There are methodological challenges to providing strong evidence of these outcomes, even in small projects where it is easier to attribute outcomes to interventions, at least over the short term. However, there are ways to gather data that are more objective than participants' and consultants' reports and that are useful for assessing the value of the program and to enable others to learn from the experience of Jönköping. This article presents such data from a case study of the program carried out in 2006. It presents evidence of how the program was implemented, of some results, and of the unusual conditions that appear to have shaped or allowed the program to be carried out in the way described. There is some evidence of process improvements in a number of departments and of outcomes improvement in one department. The program is widely perceived to be of benefit and some of the explanations for this are presented. PMID: 17235253
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 | 0.032 | 0.183 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".