How informatics is shaping the future of emergency medicine
An in-depth analysis-review article
Keywords:
Emergency Medicine Informatics, Electronic Health Records, Clinical Decision Support Systems, Telemedicine, Data Analytics, InteroperabilityAbstract
Background: Emergency Medicine Informatics (EMI) represents a transformative intersection of information technology and emergency medical services aimed at enhancing patient care and operational efficiency. This review article explores the evolution, current applications, and future directions of EMI. The background outlines how EMI integrates technologies such as Electronic Health Records (EHRs), Clinical Decision Support Systems (CDSS), telemedicine, data analytics, and interoperability to optimize emergency care. Aim: The aim of the article is to provide a comprehensive overview of how these informatics tools have advanced and their impact on emergency medicine. Methods: The methods involve a detailed review of recent literature and technological advancements in EMI. Results: Results indicate that EHRs improve patient information management, CDSS enhance decision-making with evidence-based recommendations, telemedicine expands access to remote care, and data analytics facilitate predictive and prescriptive insights. Challenges such as interoperability issues, data security, and implementation costs are also discussed. Conclusion: The conclusion emphasizes that while EMI has significantly improved patient outcomes and operational efficiency, ongoing advancements are needed to address current limitations and further enhance the field. Future directions include enhancing interoperability, advancing analytics capabilities, expanding telemedicine, focusing on user-centered design, and strengthening data security.
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References
Transient and sustained changes in operational performance, patient evaluation, and medication administration during electronic health record implementation in the emergency department. Ward MJ, Froehle CM, Hart KW, Collins SP, Lindsell CJ. Ann Emerg Med. 2014;63:320–328. DOI: https://doi.org/10.1016/j.annemergmed.2013.08.019
Incorporating technology in pharmacy education: students' preferences and learning outcomes. Alhur A, Hedesh R, Alshehri M, et al. Cureus. 2023;15:0.
Exploring Saudi Arabia individuals’ attitudes toward electronic personal health records. Alhur A. J Comput Sci Technol Stud. 2022;4:80–87. DOI: https://doi.org/10.32996/jcsts.2022.4.1.10
Implementing electronic health records in the emergency department. Handel DA, Hackman JL. J Emerg Med. 2010;38:257–263. DOI: https://doi.org/10.1016/j.jemermed.2008.01.020
Rates, levels, and determinants of electronic health record system adoption: a study of hospitals in Riyadh, Saudi Arabia. Aldosari B. Int J Med Inform. 2014;83:330–342. DOI: https://doi.org/10.1016/j.ijmedinf.2014.01.006
Risko N, Anderson D, Golden B, Wasil E, Barrueto F, Pimentel L, Hirshon JM. Healthc (Amst) Vol. 2. Elsevier; 2014. The impact of electronic health record implementation on emergency physician efficiency and patient throughput; pp. 201–204. DOI: https://doi.org/10.1016/j.hjdsi.2014.06.003
The use of computerized clinical decision support systems in emergency care: a substantive review of the literature. Bennett P, Hardiker NR. J Am Med Inform Assoc. 2017;24:655–668. DOI: https://doi.org/10.1093/jamia/ocw151
Clinical decision support systems for triage in the emergency department using intelligent systems: a review. Fernandes M, Vieira SM, Leite F, Palos C, Finkelstein S, Sousa JM. Artif Intell Med. 2020;102:101762. DOI: https://doi.org/10.1016/j.artmed.2019.101762
Systematic review of telemedicine applications in emergency rooms. Ward MM, Jaana M, Natafgi N. Int J Med Inform. 2015;84:601–616. DOI: https://doi.org/10.1016/j.ijmedinf.2015.05.009
The acceptance of digital health: what about telepsychology and telepsychiatry? Alhur A, Alhur AA. J Sist Inf. 2022;18:18–35. DOI: https://doi.org/10.21609/jsi.v18i2.1143
Prediction of in-hospital mortality in emergency department patients with sepsis: a local big data-driven, machine learning approach. Taylor RA, Pare JR, Venkatesh AK, Mowafi H, Melnick ER, Fleischman W, Hall MK. Acad Emerg Med. 2016;23:269–278. DOI: https://doi.org/10.1111/acem.12876
Exploring the potential of predictive analytics and big data in emergency care. Janke AT, Overbeek DL, Kocher KE, Levy PD. Ann Emerg Med. 2016;67:227–236. DOI: https://doi.org/10.1016/j.annemergmed.2015.06.024
Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services. Kang DY, Cho KJ, Kwon O, et al. Scand J Trauma Resusc Emerg Med. 2020;28:17. DOI: https://doi.org/10.1186/s13049-020-0713-4
The HL7 standards-based model of emergency care information. McClay J, Park P, Marr SD, Langford LH. https://europepmc.org/article/med/23920954. Stud Health Technol Inform. 2013;192:1180.
A national, semantic-driven, three-pillar strategy to enable health data secondary usage interoperability for research within the Swiss personalized health network: methodological study. Gaudet-Blavignac C, Raisaro JL, Touré V, Österle S, Crameri K, Lovis C. JMIR Med Inform. 2021;9:0. DOI: https://doi.org/10.2196/27591
Informatics and knowledge translation. Bullard MJ, Emond SD, Graham TA, Ho K, Holroyd BR. Acad Emerg Med. 2007;14:996–1002. DOI: https://doi.org/10.1111/j.1553-2712.2007.tb02379.x
Informatics solutions for emergency planning and response. Weiner EE, Trangenstein PA. https://pubmed.ncbi.nlm.nih.gov/17911898/ Stud Health Technol Inform. 2007;129:1164–1168.
Artificial intelligence for emergency medical care. Rajput S, Sharma PK, Malviya R. Health Care Sci. 2023:1–16.
Disparate systems, disparate data: integration, interfaces, and standards in emergency medicine information technology. Barthell EN, Coonan K, Finnell J, Pollock D, Cochrane D. Acad Emerg Med. 2004;11:1142–1148. DOI: https://doi.org/10.1111/j.1553-2712.2004.tb00697.x
Medical informatics standards applicable to emergency department information systems: making sense of the jumble. Coonan KM. Acad Emerg Med. 2004;11:1198–1205 DOI: https://doi.org/10.1111/j.1553-2712.2004.tb00705.x
Advancing emergency nurses’ leadership and practice through informatics: the unharnessed power of nurses’ data. Picard C, Kleib M. Can J Emerg Nurs. 2020;43:13–17.
An exploration of nurses’ perceptions of the usefulness and easiness of using EMRs. Alhur A. J Public Health Sci. 2023;2:20–31. DOI: https://doi.org/10.56741/jphs.v2i01.263
An investigation of nurses’ perceptions of the usefulness and easiness of using electronic medical records in Saudi Arabia: a technology acceptance model. Alhur A. Indones J Inf Syst. 2023;5:30–42 DOI: https://doi.org/10.24002/ijis.v5i2.6833
Health departments' engagement in emergency preparedness activities: the influence of health informatics capacity. Shah GH, Newell B, Whitworth RE. Int J Health Policy Manag. 2016;5:575–582. DOI: https://doi.org/10.15171/ijhpm.2016.48
Solving interoperability in translational health: perspectives of students from the International Partnership in Health Informatics Education (IPHIE) 2016 master class. Turner AM, Facelli JC, Jaspers M, et al. Appl Clin Inform. 2017;8:651–659. DOI: https://doi.org/10.4338/ACI-2017-01-CR-0012
Why digital medicine depends on interoperability. Lehne M, Sass J, Essenwanger A, Schepers J, Thun S. NPJ Digit Med. 2019;2:79. DOI: https://doi.org/10.1038/s41746-019-0158-1
Employment of telemedicine in emergency medicine: clinical requirement analysis, system development and first test results. Czaplik M, Bergrath S, Rossaint R, et al. Methods Inf Med. 2014;53:99–107. DOI: https://doi.org/10.3414/ME13-01-0022
Telemedicine in emergency medicine in the COVID-19 pandemic-experiences and prospects-a narrative review. Witkowska-Zimny M, Nieradko-Iwanicka B. Int J Environ Res Public Health. 2022;19 DOI: https://doi.org/10.3390/ijerph19138216
Telemedicine applications for the pediatric emergency medicine: a review of the current literature. Gattu R, Teshome G, Lichenstein R. Pediatr Emerg Care. 2016;32:123–130. DOI: https://doi.org/10.1097/PEC.0000000000000712
Demand forecast using data analytics for the preallocation of ambulances. Chen AY, Lu TY, Ma MH, Sun WZ. IEEE J Biomed Health Inform. 2016;20:1178–1187. DOI: https://doi.org/10.1109/JBHI.2015.2443799
Kumar Kumar, Vikas Vikas. Exploring clinical care processes using visual and data analytics: challenges and opportunities. Proceedings of the 20th ACM SIGKDD. 2014. https://poloclub.github.io/polochau/papers/14-kdd-ExploringClinicalCare-kumar.pdf
Big data analytics for preventive medicine. Razzak MI, Imran M, Xu G. Neural Comput Appl. 2020;32:4417–4451. DOI: https://doi.org/10.1007/s00521-019-04095-y
Big data in home healthcare: a new frontier in personalized medicine. Medical emergency services and prediction of hypertension risks. Antonio C, Zota RD, Tinica G. Int J Healthc Manag. 2018;12:241–249. DOI: https://doi.org/10.1080/20479700.2018.1548158
A systematic review of patient tracking systems for use in the pediatric emergency department. Dobson I, Doan Q, Hung G. J Emerg Med. 2013;44:242–248. DOI: https://doi.org/10.1016/j.jemermed.2012.02.017
Impact of patient monitoring on the diurnal pattern of medical emergency team activation. Galhotra S, DeVita MA, Simmons RL, Schmid A. Crit Care Med. 2006;34:1700–1706. DOI: https://doi.org/10.1097/01.CCM.0000218418.16472.8B
Artificial intelligence in emergency medicine. Liu N, Zhang Z, Ho AF, Ong ME. J Emerg Crit Care Med. 2018;2:82. DOI: https://doi.org/10.21037/jeccm.2018.10.08
Critical care in the emergency department: monitoring the critically ill patient. Andrews FJ, Nolan JP. Emerg Med J. 2006;23:561–564. DOI: https://doi.org/10.1136/emj.2005.029926
Information technology and emergency medical care during disasters. Chan TC, Killeen J, Griswold W, Lenert L. Acad Emerg Med. 2004;11:1229–1236. DOI: https://doi.org/10.1111/j.1553-2712.2004.tb00709.x
Promoting patient safety and preventing medical error in emergency departments. Schenkel S. https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/j.1553-2712.2000.tb00466.x. Acad Emerg Med. 2000;7:1204–1222. DOI: https://doi.org/10.1111/j.1553-2712.2000.tb00466.x
Using information technology to improve the quality and safety of emergency care. Handel DA, Wears RL, Nathanson LA, Pines JM. Acad Emerg Med. 2011;18:0–51. DOI: https://doi.org/10.1111/j.1553-2712.2011.01070.x
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