Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacy
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 lar...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-12-01
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| Series: | Journal of Pharmaceutical Policy and Practice |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1186/s40545-020-00276-6 |
| _version_ | 1797401271126196224 |
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| author | Carlos Del Rio-Bermudez Ignacio H. Medrano Laura Yebes Jose Luis Poveda |
| author_facet | Carlos Del Rio-Bermudez Ignacio H. Medrano Laura Yebes Jose Luis Poveda |
| author_sort | Carlos Del Rio-Bermudez |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T02:07:32Z |
| format | Article |
| id | doaj.art-49b8cfc34b354c3091b4e255d6347535 |
| institution | Directory Open Access Journal |
| issn | 2052-3211 |
| language | English |
| last_indexed | 2024-03-09T02:07:32Z |
| publishDate | 2020-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Pharmaceutical Policy and Practice |
| spelling | doaj.art-49b8cfc34b354c3091b4e255d63475352023-12-07T15:28:03ZengTaylor & Francis GroupJournal of Pharmaceutical Policy and Practice2052-32112020-12-0113110.1186/s40545-020-00276-612315199Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacyCarlos Del Rio-Bermudez0Ignacio H. Medrano1Laura Yebes2Jose Luis Poveda3Savana Medica,Savana Medica,Savana Medica,Pharmacy Department, Drug Clinical Area,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.http://dx.doi.org/10.1186/s40545-020-00276-6natural language processingelectronic health recordsmachine learningpharmacovigilance |
| spellingShingle | Carlos Del Rio-Bermudez Ignacio H. Medrano Laura Yebes Jose Luis Poveda Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacy Journal of Pharmaceutical Policy and Practice natural language processing electronic health records machine learning pharmacovigilance |
| title | Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacy |
| title_full | Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacy |
| title_fullStr | Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacy |
| title_full_unstemmed | Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacy |
| title_short | Towards a symbiotic relationship between big data, artificial intelligence, and hospital pharmacy |
| title_sort | towards a symbiotic relationship between big data artificial intelligence and hospital pharmacy |
| topic | natural language processing electronic health records machine learning pharmacovigilance |
| url | http://dx.doi.org/10.1186/s40545-020-00276-6 |
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