Provincial legislative and regulatory standards for pain assessment and management in long-term care homes: a scoping review and in-depth case analysis
Bibliographic record
Abstract
Abstract Background Among Canadian residents living in long-term care (LTC) facilities, and especially among those with limited ability to communicate due to dementia, pain remains underassessed and undermanaged. Although evidence-based clinical guidelines for the assessment and management of pain exist, these clinical guidelines are not widely implemented in LTC facilities. A relatively unexplored avenue for change is the influence that statutes and regulations could exert on pain practices within LTC. This review is therefore aimed at identifying the current landscape of policy levers used across Canada to assess and manage pain among LTC residents and to evaluate the extent to which they are concordant with evidence-based clinical guidelines proposed by an international consensus group consisting of both geriatric pain and public policy experts. Methods Using scoping review methodology, a search for peer-reviewed journal articles and government documents pertaining to pain in Canadian LTC facilities was carried out. This scoping review was complemented by an in-depth case analysis of Alberta, Saskatchewan, and Ontario statutes and regulations. Results Across provinces, pain was highly prevalent and was associated with adverse consequences among LTC residents. The considerable benefits of using a standardized pain assessment protocol, along with the barriers in implementing such a protocol, were identified. For most provinces, pain assessment and management in LTC residents was not specifically addressed in their statutes or regulations. In Alberta, Saskatchewan, and Ontario, regulations mandate the use of the interRAI suite of assessment tools for the assessment and reporting of pain. Conclusion The prevalence of pain and the benefits of implementing standardized pain assessment protocols has been reported in the research literature. Despite occasional references to pain, however, existing regulations do not recommend assessments of pain at the frequency specified by experts. Insufficient direction on the use of specialized pain assessment tools (especially in the case of those with limited ability to communicate) that minimize reliance on subjective judgements was also identified in current regulations. Existing policies therefore fail to adequately address the underassessment and undermanagement of pain in older adults residing in LTC facilities in ways that are aligned with expert consensus.
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 | 0.126 | 0.260 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.031 | 0.051 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".