Bibliographic record
Abstract
Purpose – The purpose of this paper is to provide an overview of the state of clinical governance practices globally as well as a more detailed examination of the clinical governance landscape in Canada. The paper explores the concept that established clinical governance practices are more important than ever as healthcare systems are increasingly under pressure to reduce costs while dealing with the challenges of ageing populations. Additionally, it suggests that healthcare could benefit by studying and adopting some of the successful governance policies that exist in other jurisdictions or sectors where quality and safety are an integral part of their governance mandate, such as the airline or nuclear energy sectors. Design/methodology/approach – This paper explores the status of clinical governance practices in Canada. This is achieved through a combination of author experience in addition to the review of existing literature and assessments on clinical governance practices and patient safety. Findings – While individual success stories can be found, standardized clinical governance practices across the range of healthcare providers remain largely absent. By focussing on standardized processes, and by placing an emphasis on improved clinical governance, healthcare providers can control and in some cases lower costs while improving efficiency and increasing patient safety. While progress has been slow for many years, the authors speculate that healthcare has reached a tipping point. As information systems develop and become more reliable and robust, and systems move to a patient-centric collaborative approach to care, there is a tremendous opportunity for healthcare and life sciences organizations to exploit and capitalize on both their growing information repositories, and the big data trends that have been embraced and leveraged by other sectors in recent years. Practical implications – Managing costs and delivering safe, efficient care to patients remain top considerations for healthcare boards and healthcare systems alike. As healthcare systems grapple with the increasing costs and risk associated with ageing populations and a more complex healthcare delivery model, effective clinical governance policies focussed on quality outcomes are essential. Originality/value – This paper highlights the responsibility of healthcare boards to learn lessons from other safety-critical industries and develop their own capacity to evaluate progress toward the goals identified above. It also provides insight into the role that leaders on both the corporate and clinical sides of the industry have to play, and the need for meaningful measures that will drive a quality agenda. The paper also emphases the link between established clinical governance practices and greater efficiency, reduced costs and improved patient safety.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.020 | 0.033 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 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".