The role of electronic medical records (EMRs) and health informatic technician in enhancing interdisciplinary collaboration
Keywords:
EMRs, interdisciplinary collaboration, emergency medicine informatics, clinical decision support systems, telemedicineAbstract
Background: Electronic Medical Records (EMRs) play a pivotal role in enhancing interdisciplinary collaboration in Emergency Medicine Informatics (EMI). Utilizing advanced technologies such as EHRs, CDSS, telemedicine, data analytics, interoperability, and patient monitoring systems, EMI aims to improve clinical outcomes and streamline workflows in emergency departments. Methods: This study explores the impact of EMRs on interdisciplinary collaboration by analyzing the implementation of EHRs, CDSS, telemedicine, data analytics, interoperability, and patient monitoring systems in emergency medicine settings. Through a review of existing literature and case studies, the effectiveness of these technologies in enhancing patient care and clinical decision-making is evaluated. Results: The integration of EMRs has significantly transformed emergency care by improving the accuracy of patient records, reducing medication errors, and enhancing the quality of diagnoses and treatments. CDSS aids in minimizing diagnostic errors and improving adherence to clinical guidelines, while telemedicine enables rapid access to specialist care, particularly in remote areas. Data analytics and predictive modeling enhance resource allocation and operational efficiency in emergency departments. Interoperability ensures seamless data exchange, leading to more informed clinical decisions and coordinated patient care.
Downloads
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
4.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. [ Jun; 2024 ]. 2014.
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
Published
How to Cite
Issue
Section
Copyright (c) 2024 International journal of health sciences
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Articles published in the International Journal of Health Sciences (IJHS) are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant IJHS right of first publication under CC BY-NC-ND 4.0. Users have the right to read, download, copy, distribute, print, search, or link to the full texts of articles in this journal, and to use them for any other lawful purpose.
Articles published in IJHS can be copied, communicated and shared in their published form for non-commercial purposes provided full attribution is given to the author and the journal. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
This copyright notice applies to articles published in IJHS volumes 4 onwards. Please read about the copyright notices for previous volumes under Journal History.
