Health Information Systems’ Support for Management and Changing Work: Survey Study Among Physicians
Notice bibliographique
Résumé
Background: The digitalization of health care has advanced significantly in recent years. Consequently, physicians have needed to increasingly adopt new digital health technologies such as electronic health record systems and other health information systems. Digitalization has changed physicians' clinical work, work environment, management work, and use of tools for leadership. Many physician leaders have been critical of the capabilities of health information systems (HISs) to support leadership, management, and knowledge management. Objective: We aimed to examine the association between leadership position and perceived changes in clinical work due to digitalization among a nationally representative sample of Finnish physicians and physician leaders. In addition, we examined physician leaders' perceptions of HISs as a support for management and whether their opinions differed based on their perceptions on changes in clinical work due to digitalization. Methods: Altogether 4630 Finnish physicians (2960/4586, 64% women) responded to a cross-sectional nation-wide web-based survey conducted in spring 2021. Perceptions of improved preventive work, facilitated access to patient information, progressed interprofessional collaboration, and accelerated clinical encounters were used as measures of changes due to digitalization. First, we examined with multivariable logistic regression analyses whether being in a leadership position was associated with perceived changes in work due to digitalization (improved preventive work, facilitated access to patient information, progressed interprofessional collaboration, and accelerated clinical encounters in separate analyses) in the total sample. Second, we examined with analyses of covariance whether the variables related to perceived changes in work due to digitalization were associated with perceived management support from HISs among those who had administrative or management responsibilities (n=817). All analyses were adjusted for gender, age, and sector. Results: Physician leaders had greater odds of agreeing that digitalization had improved preventive work (odds ratio [OR] 1.62, 95% CI 1.33-1.98), facilitated access to patient information (OR 1.28, 95% CI 1.09-1.51), progressed interprofessional collaboration (OR 1.81, 95% CI 1.53-2.14), and accelerated clinical encounters (OR 1.31, 95% CI 1.01-1.70) than those in nonleadership positions. Furthermore, leaders who perceived these changes in work due to digitalization positively also considered that health information systems supported their management work. Conclusions: Physician leaders appeared to view the changes in work due to digitalization more positively than other physicians. In addition, those leaders who perceived these changes positively also perceived that HISs supported their management work. Thus, leaders should thoroughly evaluate and address physicians' perceptions of their routine clinical work and its evolving nature. Doing so ensures access to up-to-date and accurate insights, enabling more effective planning of staffing, training programs, and future implementations. Furthermore, our results show that to guarantee positive views about digitalization among physician leaders, information systems should also support managerial work. This highlights the need to focus on the quality, utility, and usability of information systems.
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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 | 0,002 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».