Responses by hospital complaints managers to recommendations for systemic reforms by health complaints commissions
Bibliographic record
Abstract
Objective This paper explores how hospital complaints managers react to recommendations for systemic quality reforms by health complaints commissions in response to complaints by patients in Queensland and New South Wales. Methods Semi-structured qualitative interviews were conducted with complaints managers in 17 hospitals. Interview transcripts were then thematically analysed and data on responses to health complaint commissions was organised in relation to Valerie Braithwaite's typology of motivational postures. Results Respondents supported involvement by an independent authority where patients had serious complaints about the services they received in hospital, but wanted more negotiation with commissions on service improvement recommendations. Conclusions Hospital complaints managers mostly responded as virtuous or rational actors to the symbolic power of complaints commissions. This may be context dependent because Australian health commissions operate within a pro-reform context as a result of recent publicity around health system failures. What is known about the topic? Little is known about regulatory relationships between complaints commissions and hospitals. There has been no Australian research considering how complaints managers respond to commission recommendations for quality improvements and reforms to hospital services. What does the paper add? The paper uses a novel theoretical framework based on regulatory theory to understand and describe the reactions of complaints managers to commission recommendations. What are the implications for practitioners? Commissions should seek commentary from complaints managers through open dialogue before making final recommendations. This will ease the progress of reforms and make recommendations more acceptable and 'genuine' in the specific context of the hospital.
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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 | 0.086 | 0.267 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".