Implementing the interRAI Check-Up Comprehensive Assessment: Facilitating Care Planning and Care Coordination during the Pandemic
Bibliographic record
Abstract
Background: Long-stay home care patients are a large population of older adults with multi-morbidity and frailty. The COVID-19 pandemic posed challenges to executing care coordination and completing in-home assessments due to provincial mandates restricting in-person care. We evaluated the implementation of the interRAI Check-Up Self-Report instrument administered by phone and video. Methods: We report on a mixed-methods study, which involved the collection and analysis of survey and focus group data. Care coordinators from two regions in Ontario who had implemented the Check-Up at least once between March 2020 to September 2021 were recruited via convenience sampling. Results: A total of 48 survey respondents and 7 focus group participants consented to the study. Advantages of completing the Check-Up over the telephone or video call included: reduced travel time, reduced risk of disease transmission, familiarity with the assessment questions, and reduced time spent administering the assessment. Limitations most frequently reported were: the inability to see the living environment, hearing impairments, inability to observe non-verbal responses or cues, language barriers, difficulty building rapport, and difficulty understanding the patient. Conclusions: The Check-Up was advantageous in providing sufficient information to create a care plan when administered over the phone and by video. Implementation of the Check-Up assessment was facilitated by familiarity and alignment with other interRAI assessments. Our results indicate that population characteristics need to be taken into consideration for administration of self-report style of assessments.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".