Continuous Quality Improvement in Orthopaedic Surgery: Improving Patient Experience, Safety and Outcomes
Bibliographic record
Abstract
As the demand for accountability and transparency surrounding the supply of increasingly expensive medical services grows, health- care providers have put continuous quality improvement (CQI) programs in place to optimize care and improve efficiencies. CQI pro- grams that rigorously evaluate healthcare services can lead to informed decisions about the direction of planned improvements through evolving knowledge translation. Successful end products may include better patient satisfaction, improved patient-reported outcomes, highly-efficient care pathways, and overall cost-savings. There are numerous steps involved in implementing CQI programs that require collaboration and cooperation from physicians, allied health care workers, support staff and hospital management in order to achieve desirable goals. The Division of Orthopaedic Surgery at The Ottawa Hospital (TOH) has initiated a CQI program which is designed as a classic Donabedian Construct with a triple aim framework of: 1. improving care, 2. improving patient experience, and 3. lowering cost. The development of our electronic CQI database will be a key component in the 5-year (2015-2020) Strategic Plan for the Division, and is in keeping with the goal of TOH becoming a top 10% performer in quality and safety of patient care in North America. The aim of this paper is to outline our compliance with the ongoing activities required to meet clearly delineated quality metrics, and the development of the many facets of our CQI program. RÉSUMÉ En réponse à la demande croissante de transparence et de responsabilité concernant les services de santé dispendieux, les fournis- seurs de soins de santé ont mis sur pied des programmes d’amélioration continue de la qualité (ACQ) pour optimiser les soins et l’efficience. Les programmes d’ACQ qui évaluent rigoureusement les services de santé permettent des décisions plus éclairées quant aux améliorations à apporter, grâce au transfert de connaissances. Parmi les résultats positifs de ces programmes, on peut compter une plus grande satisfaction et une amélioration des résultats rapportés par les patients, des plans d’intervention particulièrement efficients, et une réduction des coûts. De nombreuses étapes dans la mise en place des programmes d’ACQ nécessitent une collabora- tion entre les médecins, le personnel de soutien, les gestionnaires de l’hôpital et les autres professionnels de la santé afin d’atteindre les objectifs désirés. La Division de chirurgie orthopédique de l’Hôpital d’Ottawa a lancé un programme d’ACQ conçu selon le modèle classique Donabedian, qui poursuit un triple objectif : 1. améliorer les soins, 2. améliorer l’expérience des patients, et 3. minimiser les coûts. La création d’une base de données électronique pour l’ACQ sera une composante clé du plan stratégique de 5 ans (2015-2020) de la Division, et se conforme à l’objectif de l’Hôpital d’Ottawa de devenir l’un des plus performants en Amérique du Nord, sur le plan de la qualité et de la sécurité des soins aux patients. Le but de cet article est de décrire brièvement le développement de nombreuses facettes de notre programme d’ACQ, et notre conformité aux normes de la qualité.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".