ArticleJournal of pharmaceutical policy and practice2020
Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacy.
Article in Journal of pharmaceutical policy and practice, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Big Data for Drug Discovery: Some Historical Landscape, Considerations, and Applications for a Medicinal Chemist.ACS omega · 2026Review
- Artificial intelligence in pharmacy practice: pharmacists' perceptions and concerns toward implementation.Frontiers in digital health · 2026Article
- Closing the loop: human-augmented, mechanistically enhanced AI for proactive management of drug-drug interactions.Frontiers in pharmacology · 2026Article
- Utilization of Artificial Intelligence in Reducing the Incidence of Medication Error: A Bibliometric Analysis.Health science reports · 2025Article
- Article
- Paediatric medication incident reporting: a multicentre comparison study of medication errors identified at audit, detected by staff and reported to an incident system.BMJ quality & safety · 2024Observational
- Artificial intelligence in the field of pharmacy practice: A literature review.Exploratory research in clinical and social pharmacy · 2023Review
- Application of Artificial Intelligence or machine learning in risk sharing agreements for pharmacotherapy risk management.Journal of integrative bioinformatics · 2023Article
- Article
- Clinical Characteristics and Management of Patients with Secondary Hyperparathyroidism Undergoing Hemodialysis: A Feasibility Analysis of Electronic Health Records Using Natural Language Processing.Kidney diseases (Basel, Switzerland) · 2023Article
- Symptoms timeline and outcomes in amyotrophic lateral sclerosis using artificial intelligence.Scientific reports · 2023Article
- Using natural language processing to explore characteristics and management of patients with axial spondyloarthritis and psoriatic arthritis treated under real-world conditions in Spain: SpAINET study.Therapeutic advances in musculoskeletal disease · 2023Article
- How can artificial intelligence optimize value-based contracting?Journal of pharmaceutical policy and practice · 2022Article
- Major Adverse Cardiovascular Events in Coronary Type 2 Diabetic Patients: Identification of Associated Factors Using Electronic Health Records and Natural Language Processing.Journal of clinical medicine · 2022Article
- Evaluation of Natural Language Processing for the Identification of Crohn Disease-Related Variables in Spanish Electronic Health Records: A Validation Study for the PREMONITION-CD Project.JMIR medical informatics · 2022Article
- Article
- Assessing the Performance of Clinical Natural Language Processing Systems: Development of an Evaluation Methodology.JMIR medical informatics · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The digitalization of health and medicine and the growing availability of electronic health records (EHRs) has encouraged healthcare professionals and clinical researchers to adopt cutting-edge methodologies in the realms of artificial intelligence (AI) and big data analytics to exploit existing large medical databases. In Hospital and Health System pharmacies, the application of natural language processing (NLP) and machine learning to access and analyze the unstructured, free-text information captured in millions of EHRs (e.g., medication safety, patients' medication history, adverse drug reactions, interactions, medication errors, therapeutic outcomes, and pharmacokinetic consultations) may become an essential tool to improve patient care and perform real-time evaluations of the efficacy, safety, and comparative effectiveness of available drugs. This approach has an enormous potential to support share-risk agreements and guide decision-making in pharmacy and therapeutics (P&T) Committees.
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Registered trials
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.