m-Health in the Surgical Context: Prospecting, Review and Analysis of Mobile Applications
Notice bibliographique
Résumé
Background m-Health initiatives can show an opportunity to improve the identification, prevention and management of certain diseases. Most health-care applications aims at chronic noncommunicable diseases care, and it is necessary to seek evidence from applications intended for surgical patient care, either before, during or after hospitalization. Objective: The Study Aims to identify and analyze, from the literature review and prospecting, applications for smartphones developed to assist the surgical patient. Methods: A descriptive-exploratory study developed in two sequential phases. The first one corresponded to an integrative review of the literature in the databases PubMed, Web of Knowledge, Europe PMC database and Cumulative Index to Nursing and Allied Health Literature database. The second phase corresponded to an exploration of applications in the European Patent Office, United States Patent and Trademark Office (USPTO), Free Patents Online, Canadian Intellectual Property Office and World Intellectual Property Organization. In both phases, we do not restrict the results by year of publication/registration or language. At each stage, the selected studies/patents were analyzed and pre-selected, according to the inclusion and exclusion criteria, by reading their titles and abstracts. Subsequently, we analyzed those with the potential of participation in the study, evaluating the answer to the research question, as well as the type of research, objectives, sample, method, outcomes, results and conclusion. Finally, the articles/patents record found were read in full. Results In the databases, 14 studies that presented some application for smartphone aimed at the surgical patient were selected. Most of them were in PubMed (64.3%), published in English (100%). Regarding origin, 28.6% of the texts are from the United States of America, 14.3 from Sweden and 14.3 from Canada. On the other hand, in patent databases, 10 registries were selected, 60% in the USPTO patent base, hosted in hybrid systems (iPhone and Android) and developed in the last 5 years (2014-1018) (80%). In general, there is a series of applications aimed at surgical patients, such as targets and/or users, mainly focused on the exchange of text and image messages but concentrated on assisting the physician/health team in the preparation of the patient during the procedure or post discharge. It is necessary to invest in the creation of technologies that aim to monitor these patients, especially in post discharge. Conclusion The characteristics of applications indicate a strong hospital centered tendency in relation to its purpose, having the surgeon as the main user and the surgical patient as the main target. The applications are still focused on optimizing diagnostics or functions, and no initiatives are identified to monitor the patient in a non-hospital environment.
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 | 0,005 | 0,028 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,030 | 0,023 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».