Preliminary Findings on ABC Adoption in Canadian Hospitals: Reasons for Low Rates of Adoption
Bibliographic record
Abstract
Activity based costing (ABC) can be traced to the years before the Second World War, but its popularity in recent years has been widespread following the Johnson and Kaplan (1987) article. Both teaching and practice have been impacted by the extensive research and literature in this area. However, it is evident that there has not yet been widespread successful implementation of ABC. Adoption rates have been lower than expected given the potential advantages of using ABC suggested by leading academics and professional organisations around the world. We found through initial surveys that there are low rates of adoption of ABC in hospitals in Ontario. Since hospitals are under severe budgetary pressures, have a high variety and complexity of cases and a high level of shared resources, we would expect more adoption of ABC. We use the approach suggested by Scapens (1990) to ascertain the determinants of this low level of adoption. Our studies focus on four hospitals in Ontario, Canada, using surveys and interviews. Our preliminary findings are that the application of social theory, as suggested by Scapens (1990), provides useful explanations for the low ABC adoption rates in hospital care in Canada.
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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 | 0.008 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".