Embracing the electronic era: the role of digital prescribing solutions in paediatrics
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| Publicado no: | Archives of Disease in Childhood vol. 109, no. 12 (Dec 2024), p. 965 |
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| Autor principal: | |
| Publicado em: |
BMJ Publishing Group LTD
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| Assuntos: | |
| Acesso em linha: | Citation/Abstract Full Text Full Text - PDF |
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MARC
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| 100 | 1 | |a Hassan, Hadeel |u Paediatric Haematology and Oncology, The Hospital for Sick Children, Toronto, Ontario, Canada; Program in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, Ontario, Canada | |
| 245 | 1 | |a Embracing the electronic era: the role of digital prescribing solutions in paediatrics | |
| 260 | |b BMJ Publishing Group LTD |c Dec 2024 | ||
| 513 | |a Editorial | ||
| 520 | 3 | |a The research presented in the ‘Smartphone Use for Paediatric Calculations in Emergencies’ (SPaCE) study by Dr Jordan Evans and colleagues sheds light on this issue, suggesting that embracing digital solutions could significantly improve healthcare prescribing safety and efficiency.1 The SPaCE study evaluated emergency calculation methods, including smartphone apps, reference charts and traditional calculations. Furthermore, the integration of generative artificial intelligence and machine learning models into healthcare proposes an exciting frontier for medication error reduction and clinical decision support.6 While studies investigating the use of machine learning have been undertaken, evaluation and validation are required before its widespread implementation as a prediction or clinical decision support tool in EHRs. Scepticism about the initial costs and learning curves associated with digital solutions often overlooks the long-term benefits, such as time and resource savings and the potential to save lives by reducing prescribing errors. | |
| 651 | 4 | |a United Kingdom--UK | |
| 653 | |a Artificial intelligence | ||
| 653 | |a Interoperability | ||
| 653 | |a Collaboration | ||
| 653 | |a Smartphones | ||
| 653 | |a Health care | ||
| 653 | |a Medical personnel | ||
| 653 | |a Machine learning | ||
| 653 | |a Automation | ||
| 653 | |a Computerized physician order entry | ||
| 653 | |a Pediatrics | ||
| 653 | |a Learning algorithms | ||
| 653 | |a Efficiency | ||
| 653 | |a Drug dosages | ||
| 653 | |a Electronic health records | ||
| 653 | |a Patient safety | ||
| 653 | |a Clinical decision making | ||
| 653 | |a Human error | ||
| 653 | |a Social | ||
| 653 | |a Calculators | ||
| 653 | |a Patients | ||
| 653 | |a Predominantly White Institutions | ||
| 653 | |a Influence of Technology | ||
| 653 | |a Records (Forms) | ||
| 653 | |a Technology Integration | ||
| 653 | |a Reference Materials | ||
| 653 | |a Computer Oriented Programs | ||
| 653 | |a Computer Software | ||
| 773 | 0 | |t Archives of Disease in Childhood |g vol. 109, no. 12 (Dec 2024), p. 965 | |
| 786 | 0 | |d ProQuest |t Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3147062023/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3147062023/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3147062023/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |