Remote Symptom Monitoring With Electronic Patient-Reported Outcomes in Clinical Cancer Populations
Notice bibliographique
Résumé
Importance: Value-based health care increasingly requires electronic patient-reported outcome-based remote symptom monitoring (RSM) to improve health care utilization in patients with cancer. However, data on the impact of RSM in clinical practice are lacking. Objective: To evaluate the association of RSM with 3- and 6-month health care utilization among patients receiving systemic cancer treatment. Design, Setting, and Participants: This nonrandomized controlled trial used a hybrid, type 2 implementation-effectiveness design. Participants were patients with cancer at 2 Alabama-based academic institutions receiving chemotherapy, targeted therapy, or immunotherapy; the exposure group received standard-of-care delivered RSM from 2021 to 2024, and historical controls were patients who received cancer treatment prior to RSM implementation from 2017 to 2021. Data were analyzed from May to October 2024. Exposure: RSM using electronic patient-reported outcomes. Main Outcomes and Measures: Health care utilization at 3 and 6 months after RSM enrollment (intensive care unit [ICU] admissions, hospitalizations, emergency department [ED] visits). Adjusted modified Poisson models estimated the relative risk (RR) and 95% CI of health care utilization overall. Penalized logistic regression was used for stratified analyses by patient race, residence, neighborhood deprivation, insurance type, and comorbid conditions. Results: A total of 5949 patients were assessed. From May 2021 to May 2024, 1392 patients (median [IQR] age at index date, 61 [51-69] years; 933 [67%] female) were enrolled in RSM, including 378 Black patients (27%) and 922 White patients (66%), with 262 patients (19%) living in rural areas and 372 patients (27%) living in areas with high neighborhood disadvantage; RSM patients were compared with 4557 controls (median [IQR] age at index date, 62 [53-69] years; 2654 [58%] female), including 1177 Black patients (26%) and 3151 White patients (69%), with 1012 patients (22%) living in rural areas, and 1281 patients (28%) living in areas with high neighborhood disadvantage. Compared with historical controls, hospitalizations among patients receiving RSM were 19% lower at 3 months (RR, 0.81; 95% CI, 0.73-0.91) and 13% lower at 6 months (RR, 0.87; 95% CI, 0.80-0.96). ICU admissions were not significantly different among the RSM populations compared with controls (3 months: RR, 0.82; 95% CI, 0.59-1.13; 6 months: RR, 0.83; 95% CI, 0.65-1.06). ED visits were similar for both groups (3 months: RR, 1.02; 95% CI, 0.89-1.16; 6 months: RR, 1.03; 95% CI, 0.92-1.15). Subset analyses showed similar patterns in 3- and 6-month RR for hospitalizations, ED visits, and ICU admissions. Conclusions and Relevance: In this nonrandomized controlled trial, RSM implementation was associated with reduced risk of hospitalizations for patients with cancer, supporting the need to expand implementation nationally.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».