Increasing resuscitation status-related goals of care discussions for older adults with severe mental illness in a Canadian mental health setting: a retrospective study
Bibliographic record
Abstract
BACKGROUND: Older adults with severe mental illness, including advanced dementia (AD), within geriatric admission units (GAU) often prioritise comfort care, avoiding life-prolonging procedures including cardiopulmonary resuscitation (CPR). Pre-2019, hospital policy lacked a resuscitation status order (RSO) incorporating distinct do-not-resuscitate levels. Providers entered 'NO CPR' orders in the electronic health record (EHR), necessitating transfers for non-CPR medical issues, contradicting patient preferences. METHODS: The study aimed for a 75% increase in resuscitation status-related (RSR) goals of care discussion (GOCD) completion rates within 1 week of GAU admission or transfer by December 2022. We implemented an EHR RSO, updated hospital policy and provided staff education. A 4-year GAU retrospective chart review assessed RSR GOCD frequency, completion time, documentation quality and discrepancies. Additionally, an environmental scan identified contributing factors to RSR GOCD. RESULTS: Among 431 reviewed charts, the mean RSR GOCD completion rate was 13.9%; taking 39.5 days, with extreme outliers removed, the mean of time to completion was 15 days. Subgroup analysis highlighted a significant difference in RSR GOCD completion rates for AD (41.6%) compared with non-AD patients (16.3%). Discrepancy rates in charts with RSR GOCD were substantial: documentation without a corresponding RSO (66.7%), RSO without documentation (26.1%) and discordant resuscitation status between documentation and RSO (7.2%). Documentation quality varied: 32.9% lacked context, 20.7% had limited context, while 46.3% provided comprehensive context. Barriers to RSR GOCD included the absence of an EHR documentation tool and clear triggers. CONCLUSION: RSR GOCD completion rates were lower and took longer than anticipated, highlighting improvement opportunities. AD subgroup analysis indicated provider awareness of RSR GOCD importance in this population. Discrepancies and documentation quality issues pose risks to patient-centred care. Collaborative stakeholder efforts are imperative for developing system-based informatics solutions, ensuring timely, comprehensive and patient-centred RSR GOCD.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".