Remote symptom monitoring alerts for nurses: Removing the noise.
Notice bibliographique
Résumé
379 Background: Within remote symptom monitoring (RSM) programs, nurses may respond to many symptom alerts in a given day. The shift to standard-of-care delivery necessitates adding this responsibility to an already strained nursing workforce. Thus, selecting the right symptoms to alert is critical and requires care to minimize non-actionable alerts. Little is known about strategies to reduce alert burden on nursing. Methods: In this quality improvement initiative, we aimed to improve the nurse’s perception of alert utility and minimize “noise” or alerts that were not actionable. A continuous quality improvement approach, with multiple Plan Do Study Act (PDSA) cycles, was conducted based on nursing feedback. Modifications were captured, described, and categorized. Alert details prior to and after changes are described. Descriptive statistics were calculated using frequencies and percentages for categorical variables. Results: In PDSA cycle 1, we allowed nurses to set an expected level for specific symptoms to “snooze” alerts for up to 1 month in June 2021. Snoozed alerts did not trigger to nurses. Overall, 5.8% (405/7029) of symptom alerts were snoozed from late June 2021-May 2023 (Alert Redundancy Change). In PDSA cycle 2, an option “I don’t want a call back” was added for patients in late January 2022; 42.8% (2394/5595) of subsequent symptom alert surveys requested no call back from the nurse (Survey Response Threshold Change). In PDSA cycle 3, nurses reported that “insomnia” was not actionable weekly. This was encountered in 7.2% (170/2368) of surveys prior to removal at the end of June 2022. “Insomnia” was replaced with “rash”, which generated alerts in 6.5% (295/4549) of surveys (Survey Content Change). In PDSA cycle 4, nurses identified that hospitalized patients generated alerts that were not appropriate for outpatient action. The system was modified to add a banner bar highlighting to the nurse that the patient was hospitalized and alert could be closed with a response of “patient hospitalized” late February 2023. Following implementation, a total of 9.1% (35/384) enrolled patients either self-selected or a navigator marked them as hospitalized and therefore their surveys were paused and/or the nurse was able to close the alert selecting “patient hospitalized”. (Survey Location Change). With these changes, there were 9.9% (97/975) surveys in May 2023 with at least one actionable alert. Conclusions: Modifications to alert systems can reduce the number of non-actionable alerts that nursing must address in real-world settings, thus minimizing burden on staff.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,040 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».