Comparing the Costs of Surveillance of Early-Stage Breast Cancer by Digital or Traditional Follow-Up Methods: Randomized Crossover Study
Notice bibliographique
Résumé
Background: An increasing number of early-stage breast cancer (EBC) survivors and limited health care resources have raised interest in developing digital methods for communication between patients and health care personnel. In 2015, Helsinki University Hospital (HUS) Comprehensive Cancer Center (CCC) launched a digital solution called Noona (Helsinki University Hospital; Noona Healthcare) for patients with cancer, which allows patients to report their symptoms or side effects and ask questions with a computer or smart mobile device. Objective: In this study, we compare the cost and contacts of surveillance of EBC by 2 follow-up methods: digital solution and phone calls during their first year of follow-up outside preplanned visits. Methods: This was a prospective, open-label, randomized crossover study. After postoperative radiotherapy, patients with EBC were randomized to surveillance with either a digital solution or phone calls in addition to routine follow-up visits. After 6 months, the patient switched to the alternative follow-up method. All patients were thus exposed to both follow-up methods, and the order was determined by randomization. Hospital contacts and the costs of specialized health care were extracted from the Ecomed database of the Helsinki and Uusimaa Hospital District. The Ecomed database records all hospital costs. The costs of follow-up visits and diagnostics at the HUS CCC were analyzed in a repeated measurements general linear model analysis. Results: The study extended from July 2015 to January 2017. Of 765 patients, 734 were included in the final analyses. For the digital solution group, the mean number of contacts per patient was 1.06 (SD 1.57) during the first 6-month period and 1.22 (SD 1.04) in the second period, with associated costs of €269 (US $313.21) and €311 (US $362.11). Similarly, in the phone call group, the mean number of contacts increased from 0.95 (SD 1.39) to 1.24 (SD 1.14) with the costs of €236 (US $274.78) and €344 (US $400.53), respectively. There were no statistically significant differences in the number of outpatient contacts (P=.46 and P=.35) or total costs (P=.80 and P=.12) between the 2 follow-up methods or randomization groups. Conclusions: We did not find any statistically significant differences in the total cost of follow-up of EBC by digital solution or phone calls. The number of visits and costs were higher during the latter follow-up period, probably due to the scheduled routine 1-year visit. There were more visits and higher costs in the digital solution group during the first 6 months, but these were higher in the phone call group during the latter 6-month period. This shows that the digital solution may enable faster access to outpatient services than conventional follow-up.
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 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 | 0,009 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,005 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».