OD31 Value-Based Healthcare And Health Technology Assessment: Opportunities For Implementing A Colorectal Cancer Patient-Centered Care System
Bibliographic record
Abstract
Introduction The value-based healthcare (VBHC) concept links dollars spent to outcomes that matter to patients, rather than to the volume of services. A health technology assessment (HTA) was carried out to determine if the VBHC model could be effective to improve care delivery in colorectal cancer at the CHU de Québec-Université Laval. Methods A systematic review on VBHC models implemented in oncology was conducted in indexed databases and grey literature between January 2000 and January 2022. Semistructured interviews were conducted from various key informants in our hospital (n=19), including three patients, to characterize the colorectal cancer care organization. HTA was conducted with an interdisciplinary group including surgeons, nurses, hospital managers, and patients. Results Key factors to consider in the implementation of VBHC include organizing care around the same medical condition, measuring outcomes and costs for every patient, and tracking data through information technology platforms. Results from case studies suggest that VBHC may have promising effects on clinical, patient-reported, and process outcomes measures. Several issues regarding the degree of agreement with the VBHC principles have been identified in our facility, including a non-uniform care trajectory, a lack of an integrated interdisciplinary team, and the absence of efficient information technologies. Conclusions It was recommended that the CHU de Québec-Université Laval initiates an organizational transformation in colorectal cancer care to implement a VBHC model. An effective care transformation will require a significant culture change with impacts on organization and practices but also with positive spin-offs by creating value and patient-centered care.
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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 | 0.048 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".