124 The Effect of Picture Archiving and Communications Systems on the Diagnostic Performance of Pediatric Emergency Physicians
Notice bibliographique
Résumé
Digital radiography, with hospital-wide accessibility is being implemented in many centres. No previous study has evaluated the impact of a Picture Archiving and Communications Systems (PACS) on the diagnostic ability of Pediatric Emergency Physicians (PEPs). To compare the accuracy of diagnostic interpretation of radiographs by PEPs before and after the introduction of a PACS. A before-and-after study was conducted. The before time period (Group PRE) was defined as Sept 2001, during which time only conventional radiographs were available. The after time period (Group POST) was defined as September 2002, when only digital radiographic studies were available. The consecutive medical records of all patients (0–18 years) who underwent radiological studies while they presented to an Emergency Department (ED) of a pediatric university-affiliated centre during both study periods were reviewed. Ultrasonographic, CAT, MRI and bone scan studies were excluded. The radiographic interpretation of the PEP, documented at the time of the ED visit, was compared to the pediatric radiologist's report, documented within 72 hours of the ED visit. Data were obtained via the ED Hospital Information System, the Radiological Information System and the medical records. The criterion validity (sensitivity, specificity, NPV, PPV, accuracy) (95% CI) of the PEPs' radiographic interpretations were measured. Data were available from 1644 out of the 1651 sets of conventional radiographs ordered by PEPs for the Group PRE and from 1430 out of the 1431 sets of digital radiographic studies for the Group POST. A similar distribution of types of studies was found among both groups. Both groups were similar for age, times of presentation, triage levels and admission rates. The prevalence of positive radiological studies as per the radiologists was 32.2% for Group PRE and 28.7% for Group POST. Overall the PEP's accuracy was 98.1% (94.6–100%) vs. 98.5% (87.5–100%), sensitivity 96.4% (94.5–97.8%) vs. 98.1% (96.2–99.2%), specificity 98.9% (98.1–99.4%) vs. 98.6% (97.7–99.3%), NPV 98.3% (97.4–99.0%) vs. 99.2% (98.5–99.7%) and PPV 97.7% (96.0–98.8%) vs. 96.6% (94.4–98.2%) for Group PRE vs. Group POST respectively. The proportion of false negatives (FN) was 1.2% (19/1644) vs. 0.6% (8/1430). Only 1 FN patient for each group required immediate follow-up for a missed diagnosis. Radiographs interpretations by PEPs of digital studies remain extremely accurate compared to conventional studies. Infrequently, a severe diagnosis (1/1430) was missed by the PEPs with the use of digital radiographs.
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 | 0,024 | 0,231 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».