Notice bibliographique
Résumé
Linked Comment: Aungst et al. Int J Clin Pract 2014; 68: 155–62. In this issue of the International Journal of Clinical Practice, Aungst et al. give us an overview of mobile medical applications, ‘apps’, intended to enhance medical decision-making and potentially improve therapeutic outcomes 1. One of the undersigned (LC) had the good fortune of virtually meeting Tim by being a peer reviewer of his manuscript on apps that he wrote for his fellow pharmacists 2, and he kindly agreed to work on a similar paper for the International Journal of Clinical Practice. Tim is Assistant Professor at MCPHS University (formerly Massachusetts College of Pharmacy and Health Sciences) and an Editor for iMedicalapps.com, an online publication for medical professionals, patients and analysts interested in mobile medical technology and healthcare apps. By way of full disclosure, among his co-authors, Iltifat Husain is Editor in Chief of iMedicalapps.com, Satish Misra is Managing Editor and Tom Lewis, an Editor; Kevin Clauson is Director, Center for Consumer Health Informatics Research (see cchir.org). Finding good medical apps can be like searching for a platypus. You know they are out there thriving, but how do you find them? This paper can get you started. Apps are hot. This past month, I have received many emails touting one app or another, including one ‘Physician iPhone/iPad App of the Week’ that promised ‘full-text reading for journal subscribers, including society member subsubscriptions, for over 500 [competitor's name deleted] published journals in the medical, nursing, dental, allied health and veterinary field.’ Apps have not escaped the notice of regulators. The US Food and Drug Administration (FDA) recently issued a guidance document regarding mobile medical applications 3, after initially issuing a draft in July 2011. Although the FDA does not intend to regulate apps that can inform consumers about healthcare options (or to allow patients to measure and track their own vital signs), the FDA does plan to regulate apps that are essentially medical devices and ‘whose functionality could pose a risk to a patient's safety if the mobile app were to not function as intended.’ This can include sensor-based ‘electronic stethoscopes.’ The guidance states that ‘When the intended use of a mobile app is for the diagnosis of disease or other conditions, or the cure, mitigation, treatment, or prevention of disease, or is intended to affect the structure or any function of the body of man, the mobile app is a device.’ The FDA does not intend to regulate or enforce regulations if the medical app poses a low risk to the public 4. Nor have apps escaped the notice of managed care executives, with the promise of reduced overall costs when quality of care is enhanced and processes made more efficient 5. Practitioners may be left in the dust if they do not adapt to these technological changes. Just as the electronic health record is becoming a standard of care for hospitals, other best practices continue to be rapidly shared, facilitated by the internet and social media. Some of these best practices will involve using medical apps. Handwriting-to-text apps can be addictive. Medical records can be stored and/or accessed securely in an iPad and practitioners can have instant access to their information wherever they are. Camera apps can be used to image paper reports before they get misplaced. Although everything is electronic, it is accessible, searchable and usable, and now, inexpensive. Consistent with its aim, Aungst's paper provides a framework to help physicians identify, evaluate and implement medical apps. It covers challenges in how to identify what is an actual medical app intended for use by a physician, and raises the issue of bias and quality of reviews of apps. Readers are reminded of the importance of patient privacy, data security, the need to backup data and to keep apps updated. Some of the points raised may seem obvious to an experienced user but, to the physician who is new to medical apps, this paper is a useful read before setting out to acquire medical apps. No disclosures relevant to the subject of this editorial other than a fascination with technology.
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 | 0,009 | 0,050 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,007 |
| 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 ».