Technology in Healthcare: Electronic Health Records and Clinical Decision Support
Today, health information technologies are serving a critical role in promoting optimal clinical outcomes and advancing healthcare in a rapidly changing world (van Velzen et al., 2023). Indeed, these technologies are instrumental in facilitating seamless transdisciplinary communication among healthcare providers, streamlining patient data management, and fostering data-driven decision-making. The purpose of this paper is to provide a brief description of the process used for selecting an information system solution and why is it important for nurses to be a part of the process. In addition, an evaluation concerning the types of health information technology that are currently used in my current organization and a discussion about the respective pros and cons of the software are followed by a summary of the research and key findings in the conclusion.
Review and Discussion
Process used for selecting an information system solution
Although the process used by my organization to select health information technologies was coordinated by the information resources management services, it is essential for nurses to be actively involved in selecting these systems for multiple reasons. For instance, nurses play a central role coordinating patient care across specialties and communicating both with patients and within the care team. Likewise, as frontline providers, nurses have valuable insights into current workflow needs and challenges that new systems might exacerbate or help alleviate. They understand intimately how clinical and administrative processes interact. Therefore, nurses should have a seat at the table early on when evaluating potential health IT investments and new technologies.
As the healthcare professionals that will actually be interacting with programs such as electronic patient records, e-prescription, and point of care systems daily, nurses can assess the actual intuitiveness and user-friendliness of these technologies (van Velzen et al., 2023). Their experience identifying existing inefficiencies or potential technology gaps makes them essential contributors weighing in on system design and implementation issues such as legacy system migrations, security compliance, and mobile capabilities, issues that have assumed new importance and relevance in recent years as patient autonomy and privacy are central issues of concern.
In addition, taking nursing knowledge, concerns and priorities into account during the selection process also promotes staff buy-in and trust in the adoption of the systems that are ultimately selected for use. Likewise, soliciting feedback from nurse system end users also serves to ensure that any solutions under review match and serve their real-world priorities by positively impacting healthcare delivery and relationships. In essence, ensuring that nurses have a voice in the healthcare IT decision making process leverages their valuable insights to select the optimal technologies that are best positioned to complement and improve nursing practice and patient care.
Evaluation of my organizations health information technologies
At present, my organization uses integrated electronic health records (EHR) software and supplemental clinical decision...
…measures.Notwithstanding these significant benefits, however, similar to the parable about the boy who cried wolf, nurses also face alert burnout due to lack of context-filtering. Likewise, based on empirical observations and personal use, it is reasonable to suggest that a majority of the communications generated by CDS and EHR tools remain primarily physician-centric as well. Therefore, it is important for healthcare organizations considering the adoption or refinement of these technologies to provide timely, ongoing, substantive training and demand-driven refinement to optimize their usability by nurses at the point of care (Harmon et al., 2023).
Conclusion
The research showed that by leveraging the power of health information technologies, the healthcare industry can adapt more effectively to the dynamic demands of the modern world, ultimately promoting optimal clinical outcomes and ensuring a higher standard of patient well-being. While promising health IT advances, current EHR and CDS tools still struggle integrating smooth, holistic nursing processes. Ideal systems would emphasize interoperability, nurse-focused design, and role-based customization. Still, the healthcare systems governance partnership and IT feedback mechanisms provide the valuable framework that is needed to develop these eventualities in the foreseeable future. In sum, while electronic health records, clinical decision support systems, and other emerging innovations in healthcare information technologies promise improved patient outcomes through enhanced data accessibility and evidence-based care protocols, substantial optimization remains necessary in order to maximize the usability of these technologies for nurses at the point…
References
Electronic health records. (2023). Office of the National Coordinator for Health Information Technology. Retrieved from https://www.healthit.gov/faq/what-electronic-health-record-ehr.
Harmon, C. S., Adams, S. A., Davis, J. E., Gephart, S. M., & Donevant, S. B. (2023). Unintended consequences of the electronic health record and cognitive load in emergency department nurses. Applied Nursing Research, 73, 151724.
Jimenez-Zambrano, A., Ritger, C., Rebull, M., Wiens, M. O., Kabajaasi, O., Jaramillo-Bustamante, J. C., Argent, A. C., Kissoon, N., Schlapbach, L. J., Sorce, L. R., Watson, R. S., Dorsey Holliman, B., Sanchez-Pinto, L. N., & Bennett, T. D. (2023). Clinical decision support tools for pediatric sepsis in resource-poor settings: an international qualitative study. BMJ Open, 13(10), e074458.
Khan, A. R., Rosenthal, C. D., Ternes, K., Sing, R. F., & Sachdev, G. (2022). Time Spent by Intensive Care Unit Nurses on the Electronic Health Record. Critical Care Nurse, 42(5), 44–50.
Stephen, R. J., Lucey, K., Carroll, M. S., Hoge, J., Maciorowski, K., Jones, R. C., O’Connell, M., Schwab, C., Rojas, J., & Sanchez Pinto, L. N. (2023). Sepsis Prediction in Hospitalized Children: Clinical Decision Support Design and Deployment. Hospital Pediatrics, 13(9), 751–759.
Susanto, A. P., Lyell, D., Widyantoro, B., Berkovsky, S., & Magrabi, F. (2023). Effects of machine learning-based clinical decision support systems on decision-making, care delivery, and patient outcomes: a scoping review. Journal of the American Medical Informatics Association, 30(12), 2050–2063.
van Velzen, M., de Graaf-Waar, H. I., Ubert, T., van der Willigen, R. F., Muilwijk, L., Schmitt, M. A., Scheper, M. C., & van Meeteren, N. L. U. (2023). 21st century (clinical) decision support in nursing and allied healthcare. Developing a learning health system: a reasoned design of a theoretical framework. BMC Medical Informatics & Decision Making, 23(1), 1–11.
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