ArticleBMC medical informatics and decision making2024
Decision support systems for antibiotic prescription in hospitals: a survey with hospital managers on factors for implementation.
Article in BMC medical informatics and decision making, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence adoption in healthcare: a systematic review of implementation challenges and health services implications.BMC health services research · 2026Pooled it
- Development Process of a Clinical Decision Support System for Empiric Antibiotic Therapies in Patients With Sepsis: Case Study.JMIR medical informatics · 2026Article
- Quality of antibiotics prescription in hospitals in Burkina Faso: a multispecialty clinical audit.Antimicrobial resistance and infection control · 2026Article
- Enhancing quality of antimicrobial prescribing through 'Ask Eolas' (language model): a user-testing and simulation evaluation.npj antimicrobials and resistance · 2026Article
- The impact of artificial intelligence on the prescribing, selection, resistance, and stewardship of antimicrobials: a scoping review.BMC infectious diseases · 2025Article
- Diagnostic Innovations to Combat Antibiotic Resistance in Critical Care: Tools for Targeted Therapy and Stewardship.Diagnostics (Basel, Switzerland) · 2025Review
- Improving AI-Based Clinical Decision Support Systems and Their Integration Into Care From the Perspective of Experts: Interview Study Among Different Stakeholders.JMIR medical informatics · 2025Article
- The role of artificial intelligence and machine learning in predicting and combating antimicrobial resistance.Computational and structural biotechnology journal · 2025Review
- Implications of Artificial Intelligence in Addressing Antimicrobial Resistance: Innovations, Global Challenges, and Healthcare's Future.Antibiotics (Basel, Switzerland) · 2024Article
- Artificial intelligence, medications, pharmacogenomics, and ethics.Pharmacogenomics · 2024Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundInappropriate antimicrobial use, such as antibiotic intake in viral infections, incorrect dosing and incorrect dosing cycles, has been shown to be an important determinant of the emergence of antimicrobial resistance. Artificial intelligence-based decision support systems represent a potential solution for improving antimicrobial prescribing and containing antimicrobial resistance by supporting clinical decision-making thus optimizing antibiotic use and improving patient outcomes.
objectiveThe aim of this research was to examine implementation factors of artificial intelligence-based decision support systems for antibiotic prescription in hospitals from the perspective of the hospital managers, who have decision-making authority for the organization.
methodsAn online survey was conducted between December 2022 and May 2023 with managers of German hospitals on factors for decision support system implementation. Survey responses were analyzed from 118 respondents through descriptive statistics.
resultsSurvey participants reported openness towards the use of artificial intelligence-based decision support systems for antibiotic prescription in hospitals but little self-perceived knowledge in this field. Artificial intelligence-based decision support systems appear to be a promising opportunity to improve quality of care and increase treatment safety. Along with the Human-Organization-Technology-fit model attitudes were presented. In particular, user-friendliness of the system and compatibility with existing technical structures are considered to be important for implementation. The uptake of decision support systems also depends on the ability of an organization to create a facilitating environment that helps to address the lack of user knowledge as well as trust in and skepticism towards these systems. This includes the training of user groups and support of the management level. Besides, it has been assessed to be important that potential users are open towards change and perceive an added value of the use of artificial intelligence-based decision support systems.
conclusionThe survey has revealed the perspective of hospital managers on different factors that may help to address implementation challenges for artificial intelligence-based decision support systems in antibiotic prescribing. By combining factors of user perceptions about the systems´ perceived benefits with external factors of system design requirements and contextual conditions, the findings highlight the need for a holistic implementation framework of artificial intelligence-based decision support systems.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.