Who’s Using PDAs? Estimates of PDA Use by Health Care Providers: A Systematic Review of Surveys
Notice bibliographique
Résumé
BACKGROUND: Personal digital assistants (PDAs) find many uses in health care. Knowing rates of collective PDA use among health care providers is an important guiding step to further understanding those health care contexts that are most suited to PDA use and whether PDAs provide improved health outcomes. OBJECTIVES: The objectives of this study were to estimate current and future PDA use among health care providers and to discuss possible implications of that use on choice of technology in clinical practice and research. METHODS: This study was a systematic review of PDA usage surveys. Surveys were identified as part of an ongoing systematic review on the use of handheld devices. Reports from eight databases covering both biomedical sciences and engineering (1993-2006) were screened against distinct eligibility criteria. Data from included surveys were extracted and verified in a standardized way and were assessed descriptively. RESULTS: We identified 23 relevant surveys, 15 of which were derived from peer-reviewed journals. This cohort of surveys was published between 2000 and 2005. Overall, since 1999, there is clear evidence of an increasing trend in PDA use. The current overall adoption rate for individual professional use ranges between 45% and 85%, indicating high but somewhat variable adoption, primarily among physicians. CONCLUSIONS: Younger physicians and residents and those working in large and hospital-based practices are more likely to use a PDA. The adoption rate is now at its highest rate of increase according to a commonly accepted diffusion of innovations model. A common problem with the evaluation of information technology is that use frequently precedes research. This is the case here, in which PDA adoption rates are already high and projections are for rapid growth in the short term. In general, it appears that professional PDA use in health care settings involves more administrative and organizational tasks than those related to patient care, perhaps signaling where the growth in adoption is most likely to occur. We conclude that physicians are likely accustomed to using a PDA, and, therefore, technology expertise will probably not be a barrier to implementing PDA applications. However, there is an urgent need to evaluate the effectiveness and efficiency of specific tasks using handheld technology to inform those developing and those using PDA applications.
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 | 0,061 | 0,227 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,007 | 0,010 |
| Bibliométrie | 0,019 | 0,021 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».