Evaluation of the implementation of an electronic occurrence reporting system at Eastern Health, Newfoundland and Labrador (Phase One)
Notice bibliographique
Résumé
In June 2008, Eastern Health completed the implementation of an electronic occurrence reporting system (Phase One). Phase One included a pre-go-live site (an integrated services site in a rural setting) and three go-live sites (acute care, long term care and community health in an urban setting). The evaluation study had a dual purpose: (a) to assess and report on the impact of the implementation of the electronic occurrence reporting system on achieving its stated objectives, particularly those that could be measured within the timelines of the project and (b) to analyze findings to identify contributions to the literature in the recently developing field of implementations of electronic occurrence reporting systems in health care. -- The evaluation was guided by the framework outlined in the report, "Towards an Evaluation Framework for Electronic Health Records Initiatives" (Neville et al., 2004), which emphasizes stakeholder involvement in evaluation studies, pre/post comparative study design, and triangulation of data where possible. Data were collected from several sources such as project documentation, administrative occurrence reporting records, surveys, focus groups and key informant interviews. -- The findings of this study provide evidence that frontline staff and managers support the implementation of the electronic occurrence reporting system, that there is little difference in results between the various sectors of the continuum of health services and the new system had both positive and negative impacts on the role of frontline managers. There were limitations related to some of the findings due to the small sample size, particularly the long term care sector. -- Many benefits were realized such as: (a) an increase in the number of occurrences reported, (b) increase in the number of occurrences reported within 48 hours, (c) increase in the number of occurrences reported by staff other than registered nurses, (d) increase in the number of close calls reported, (e) positive changes in the patient safety culture, (f) improved timelines for notification of high alert occurrences to managers, and (g) satisfaction with the electronic tool related to ease of use, accessibility, and consistency. -- The implementation process also encountered challenges, such as issues related to customizing the software and development of the classification system for coding occurrences. These issues impacted on the ability of the managers to obtain timely customized reports and to close out files. These challenges are currently being addressed by the Project Implementation Team. Participants noted that resolving these issues will enhance the many positive impacts of the system already realized. Lessons learned during the Phase One implementation process (including the identification of facilitators and barriers) resulted in recommendations that can assist with future implementations.
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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 | 0,044 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».