ICD-11 in Canada: Leveraging crosswalks to evaluate adoption, impact and transition strategies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: (ICD-11) is a modern classification system that provides enhanced granularity and flexibility for capturing clinical and health system data. For Canada, transitioning from ICD-10-CA, the Canadian modification, to ICD-11 poses opportunities and challenges. To explore these opportunities and challenges more thoroughly, a backward crosswalk was developed to evaluate statistical continuity. This approach helped identify the benefits of ICD-11, while also highlighting potential implications for health systems, case mix, and national health indicator reporting. OBJECTIVE: To examine how bidirectional crosswalks between ICD-10-CA and ICD-11 can support Canada's transition to ICD-11; and demonstrate how these crosswalks can be utilised in a Canadian-specific use case. METHOD: 14,652 ICD-11 Mortality and Morbidity Statistics (2022 release) codes were mapped to version 2022 ICD-10-CA codes. Each mapping was reviewed to determine the relationship between the ICD-11 and ICD-10-CA codes, categorising them as equivalent to, broader than or narrower than the source ICD-11 codes. The bidirectional crosswalks were applied to a Canadian use case to demonstrate level of specificity between ICD-10-CA and ICD-11 codes. RESULTS: 26% of the ICD-10-CA target codes were equivalent to a single ICD-11 code, 65% were broader, 9% were narrower and 0.03% had no applicable ICD-11 map. Findings from the Canadian use case showed that 55% of the ICD-11 target codes were equivalent to or narrower than their ICD-10-CA source codes in the forward crosswalk, and 57% of ICD-11 congenital anomaly concepts had greater specificity in the backward crosswalk. CONCLUSION: The backward crosswalk assessment highlights the benefits of ICD-11's increased specificity, which has the potential to enhance healthcare data in Canada. However, these findings must be considered alongside the forward crosswalk analysis, which noted a loss in specificity.Implications for health information management practice:As demonstrated in a Canadian use case example, bidirectional crosswalks can be leveraged to better understand the impact of ICD-11 adoption.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it