Notice bibliographique
Résumé
CONSIDER THIS IRONY OF MODERN LIFE: IN A MEDICAL CRISIS, EMERGENCY physicians would have an easier time accessing a patient’s bank account using his or her automatic teller machine card than they would finding critical medical history using his or her medical insurance card. Medical records, including crucial electrocardiograms, drug allergies, or medical conditions, are typically stored on paper and are often inaccessible in emergencies. The ability to access medical charts electronically, in emergency situations or in routine medical settings, has not paralleled the growth of financial networks or indeed of the Internet. Although several commercial sites are now selling space for individuals to put their medical records online and numerous institutions have local electronic medical records (EMRs) in place, most clinical records are still kept in paper charts that are stored at a single location. The challenge of building an integrated EMR system has proved to be more than technological; 25 years of attempts to formalize the terms and concepts of medical practice has exposed some fascinating philosophical conundrums. What belongs in a medical record, and how should medical conditions or ideas be encoded? Which tasks are best performed by physicians, and which by the computer? Is it possible to encapsulate the medical encounter in digital form? A number of centers have had local EMRs available for decades, providing evidence that thoughtfully implemented EMRs improve medical care through adjunct technology like error checking and allow easier study of trends in a clinic population. New links are being forged between individual patient data and the information in digital libraries or the tools of computerized decision support. While the potential for ease of access and error reduction seems obvious, new technologies should be held to the same standards of evidence as new treatments are. Research in this field has started to look not only at efficiency and institutional satisfaction but also at health outcomes and impact on the patient-physician relationship. As researchers measure the gains made by using EMRs, they should also consider potential losses. Will physicians rely too heavily on the safety nets of automatic warning systems, losing the ability to think through the problem—just as many who rely on calculators cannot compute answers on their own? With full histories available at the touch of a button, will tired interns and residents cut corners, neglecting to ask their own questions? EMRs must be a tool for improving patient care rather than a crutch or a hindrance to the primary work of caring for patients. This month, MSJAMA examines the legal, ethical, and technical challenges of EMRs. With a new generation of physicians accustomed to working with computer technology, we may see some of the promise of the past 3 decades of research in this field come to fruition in the coming years.
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 | 0,010 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,004 | 0,008 |
| Communication savante | 0,015 | 0,043 |
| Science ouverte | 0,003 | 0,009 |
| Intégrité de la recherche | 0,007 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,048 | 0,033 |
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 ».