Abstract 46: An Innovative Approach to the Bedside Nursing Swallow Screening Tool: Can Be Used as a Trigger for an Inpatient Cognitive Evaluation to Improve Timeliness of Post-Discharge Cognitive Therapy Referrals
Bibliographic record
Abstract
Background: According to the American Heart Association, a formal assessment of cognitive dysfunction caused by stroke is a level I recommendation. However, cognitive evaluation is often missed or overlooked in the inpatient setting. When and who performs the assessment is not well-defined. Stroke nurses can corroborate with clinicians in completing the Montreal Cognitive Assessment (MoCA) 8.1, a validated tool for assessing cognitive function in stroke patients. Purpose: The purpose of this study was to evaluate the process of using the bedside nursing swallow screen (NSS) as a trigger for an inpatient cognitive evaluation by the Speech Therapist (ST). This study was also used to determine if post-discharge cognitive therapy referrals were placed based on the MoCA scores. Methods: All STs completed the required MoCA certification. The new process was implemented in October 2019. Data were analyzed from October 2019 through March 2020. NSS was performed on newly admitted stroke patients. If failed, an ST consult was ordered for a dysphagia evaluation. However, if passed, a cognitive evaluation consult was triggered by the RN. MoCA was completed within 24 hours. The total possible score is 30; a score of 26 or above is considered normal. A MoCA score of 25 or less, prompted a post-discharge cognitive therapy referral. Results: 229 patients were assessed, all of whom had an NSS completed. 120 (52.4%) passed the NSS, of which 85 (71%) completed a MoCA evaluation. 42 (49.4%) scored 25 or less, of which 35 (83.3%) were referred for a post-discharge cognitive therapy. 7 (17%) had no referral, of which 4 (57%) were discharged home to self-care; 2 (29%) discharged to other healthcare facility; and 1 (14%) left against medical advice. Conclusions: Repurposing the NSS as a standardized tool to trigger an inpatient MoCA evaluation was innovative, practical and efficient. Timely post-discharge cognitive therapy referrals were also evident on MoCA scores of 25 or less.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".