Hospital Libraries Have a Positive Impact on Clinical Decision Making and Patient Care
Notice bibliographique
Résumé
A review of: Marshall, Joanne Gard. “The Impact of the Hospital Library on Clinical Decision Making: the Rochester Study.” Bulletin of the Medical Library Association 80.2 (1992): 169-78. Objective – To determine the impact of hospital library services on clinical decision making. Design – A descriptive survey. Setting – Fifteen hospitals in the Rochester area of New York, United States of America. Seven hospitals were in the city of Rochester, and eight were in surrounding rural communities. Subjects – Active physicians and residents affiliated with the Rochester hospitals. Methods – This study built upon the methodology used in an earlier study by D. N. King of the contribution of hospital libraries to clinical care in Chicago. Lists were compiled of all the active physicians and residents who were affiliated with the Rochester hospitals. In order to ensure that there was a reasonable number of participants from each hospital, and that librarians in hospitals with larger numbers of staff were not overburdened with requests, predetermined percentages were set for the sample: 10% of active physicians from hospitals with more than 25 medical staff members, 30% from hospitals with less staff, and 30% of residents and rural physicians. This resulted in a desirable sample size of 448. A systematic sample with a random start was then drawn from each hospital’s list, and physicians and residents were recruited until the sample size was achieved. Participants were asked to request information related to a clinical case from their hospital library, and to evaluate its impact on patient care, by responding to a two-page questionnaire. Main results – Based on usable questionnaires, there was an overall response rate of 46.4% (208 of 448). Eighty percent of the respondents stated that they probably (48%) or definitely (32.4%) handled a clinical situation differently due to the information received from the library. In terms of the specific aspects of care for which changes were made, 71.6% reported a change in advice given to the patient, 59.6% cited a change in treatment, 50.5% a change in diagnostic tests, 45.2% a change in drugs, and 38.5% a change in post-hospital care or treatment. Physicians credited the information provided by the library as contributing to their ability to avoid additional tests and procedures (49%), additional outpatient visits (26.4%), surgery (21.2%), patient mortality (19.2%), hospital admission (11.5%), and hospital-acquired infections (8.2%). In response to a question about the importance of several sources of information, the library received the highest rating amidst other sources including lab tests, diagnostic imaging, and discussions with colleagues. Conclusion – This study validates earlier research findings that physicians view the information provided by hospital libraries as having a significant impact on clinical decision making. Library supplied information influences changes to specific aspects of care as well as the avoidance of adverse events for patients. The significance of this influence is underscored by the finding that relative to other sources, information obtained from the hospital library was rated more highly.
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 | 0,013 | 0,066 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,005 | 0,005 |
| Communication savante | 0,015 | 0,004 |
| Science ouverte | 0,001 | 0,010 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,003 |
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 ».