Outcomes of a Decision-Making Capacity Assessment Model at the Grey Nuns Community Hospital
Bibliographic record
Abstract
BACKGROUND: With an increasing elderly population, the number of persons with dementia is expected to increase and, consequently, the number of persons needing decision-making capacity assessments (DMCA) is too. However, many healthcare professionals do not feel ready to provide DMCAs. Since 2006, we implemented a DMCA Model that includes a care pathway, worksheets, education, and mentoring. The objective of this study was to assess the impact of the utilization of this patient-centered DMCA model on the need for Capacity Interviews. METHODS: This was a retrospective quality assurance chart review of patients referred for DMCA to the Geriatric Service at the Grey Nuns Community Hospital from 2006-2020. The Geriatric Service is run by Family Physicians with extra training in Care of the Elderly. We extracted patient demographics, elements of the DMCA process, and whether Capacity Interviews were performed. We used descriptive statistics to summarize the data. RESULTS: Eighty-eight patients were referred for DMCAs, with a mean age of 76 years (SD = 10.5). Dementia affected 43.2% (38/88) of patients. Valid reasons for conducting a DMCA were evident in 93% (80/86) of referrals, and DMCAs were performed in 72.6% (61/84). 85.3% (58/68) of referrals identified the need for DMCA in two to four domains, most commonly accommodation, healthcare, and finances. Two to three disciplines, frequently social workers and occupational therapists, were involved in conducting the DMCAs for 67.2% (39/58) of patients. The Capacity Assessment Process Worksheet was used 63.2% of the time. Capacity Interviews were conducted in only 20.7% of referrals. Following the DMCAs, 48.2% (41/85) of those assessed were deemed to lack capacity. CONCLUSION: This study suggests that the DMCA Model implemented has decreased the need for Capacity Interviews while simultaneously respecting patient autonomy. This is an important finding as DMCAs carried out following this process reduced the need for both a Capacity Interview and declarations of incapacity while simultaneously respecting patient autonomy and supporting patients in their decisions in accordance with the legislation.
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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 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".