Process for Decision Making Regarding Technology.

Process for Decision Making Regarding Technology.

Nursing is one of the fields that requires the highest level of proficiency and competent, skilled employees, who should have additional knowledge and skills in addition to those acquired during professional training (Darvish et al., 2017). Critical thinking and the use of the evidence-based practice in decision-making are just a few of the concepts that must be understood and applied in all areas of medicine. The decision-making process for technology deployment necessitates a rigorous process that examines the usability, benefits, negative impacts, support systems, contract length, and how easy it will be to integrate the technology within the healthcare system, among other factors. Perhaps the decision-making process plays a critical role in the nursing and medical fields because it facilitates the easy arrival at agreeable working and operating terms that promote the welfare of nurses, improve the quality of nursing care and medical services provided to patients, and boost the effectiveness and efficiency of service delivery, particularly in those services that require collaborative decision-making processes.

Regarding the question of identifying the processes that entail technology decision-making, there are numerous steps and factors that must be considered before implementing new technologies in the healthcare system. With so many technology options available, it can be difficult to make an informed decision about which technology an organization like healthcare should use to facilitate its functions. What technology needs to be updated, retired, replaced, or introduced in the organization’s system is a delicate balance that must be effectively managed (Darvish et al., 2017). The technology decision-making process entails assessing the effectiveness of the technology in question in light of rising security and cybercrime concerns. Security has become a major concern in the world of technology. The technology must be able to perform its functions while posing no significant risks from external threats.

Aside from that, technology adoption decisions must consider the long-term cost of the technology to be chosen rather than the current cost (Darvish et al. 2017). These will include discussions and decisions about how much money should be spent to proactively mitigate security issues and other risks, as well as what the potential consequences of deploying technology without configuring adequate security features to prevent data breaches might be. To be sound and effective, the decision-making process may have to account for all of the costs of maintaining the system throughout its life cycle. Aside from that, there should be a discussion about the organization’s ability to comply with technology requirements and ensure that all stakeholders understand all technology compliance requirements, as well as the penalties and fines for negligence or failure to comply (Milovic, 2019).

Furthermore, there is important for an organization to identify and determine its vulnerability limitations and the gaps that need to be filled with the new technology when making technology decisions (Darvish et al., 2017). From the standpoint of best security practices, it is highly recommended that healthcare organizations, as well as other business organizations, perform quarterly vulnerability scanning and annual penetration testing to identify any vulnerable areas of technology in order to employ best practices to mitigate any further risk associated with cybercrime activities. Furthermore, when making technology decisions, it is prudent to consider technological glitches and the consequences they may have on an organization (Carmody, 2020). As a result, when making a decision, it is critical to consider how quickly the vendors of the technology under consideration could restore healthcare data in the event of a data breach or outage, as well as proof of regular updates and successful data backups (Milovic, 2019). Finally, when making technology-related decisions, it is critical to consider the educational needs of the technology as well as the length of time it may take for all nurses and other employees to receive proper training and gain a better understanding of the entire system on how the technology works and how to handle the technology when it develops technical issues (Carmody, 2020).

Data mining and visualization are two technologies that are widely used in medical and healthcare settings to help with decision-making. Data mining technology entails the process of sorting through large data sets and extracting specific data, which is then analyzed to aid in making predictions and future healthcare decisions (Carmody, 2020). The effects of data mining technologies such as XLSTAT, Wolfram Mathematica, SyncSpider, Octoparse, Statgraphics Centurion, and Neural Designer, among others, have been widely applied in the healthcare sector to improve the quality of decisions made in response to various emerging healthcare challenges around the world.

The application of data mining technology in the healthcare sector has improved services, particularly in the generation of large amounts of complex data on patients, hospital resources, electronic patient records, disease diagnosis, and medical services. In the healthcare system, it has been simple to diagnose and make accurate predictions about various illnesses. Data mining technology has increased the accuracy in determining the most effective treatment options for a variety of emerging diseases. This has been made possible because the technology has assisted nurses in effectively evaluating causes, symptoms, indications, and treatment costs (Milovic, 2019). Nurses can examine the effects of medications on various clients who have the same illness but were given different medications. Along these lines, nurses can determine the most appropriate and compelling treatment option that will meet the patient’s needs.

Furthermore, data mining technology and its applications can be used to identify and track chronic illness states and high-risk patients in order to design the most effective interventions to address the situation (Milovic, 2019).

The process of selecting and implementing an application or technology necessitates holding vendors accountable for the implementation plan, including the extent to which the vendor will support implementation. During the selection and implementation stages, it is recommended to document all application requirements, including the day-to-day needs of users, leaders, and consumers of data generated by the plan, including the application and must-have features (Milovic, 2019). Nurses will play critical roles in the selection and implementation of new technologies because they will define the application scope and capabilities of the anticipated program, allowing healthcare organizations to focus on the most critical needs. Identifying teams for successful implementation is another step or process in application selection. Nurses are crucial in determining the needs of the healthcare system by estimating the number of units and departments, as well as the total number of active users.

References

Carmody, B. (2020, May 29). 6 Common Medical Diagnostic Devices. Retrieved from https://www.verywellhealth.com/common-types-of-diagnostic-medical-equipment- 2318211

Darvish, A., Bahramnezhad, F., Keyhanian, S., & Navidhamidi, M. (2017). The Role of Nursing Informatics on Promoting Quality of Health Care and the Need for Appropriate Education. Global Journal of Health Science, 6(6). doi:10.5539/gets.v6n6p11

Dealy, G. (2018, August 13). Data-Driven Decisions as a Driver for Change in Healthcare. Retrieved from https://www.dimins.com/blog/2018/08/13/data-driven-decisions-as-a- driver-for-change-in-healthcare/

Milovic, B. (201). Prediction and decision making in Health Care using Data Mining. International Journal of Public Health Science (IJPHS), 1(2). doi:10.11591/is.v1i2.1380

Poulin, P., Austin, L., Poulin, M., Gall, N., Seidel, J., Lafreniere, R., & Scott, C. (2018). Introduction of new technologies and decision-making processes: a framework to adapt a Local Health Technology Decision Support Program for other local settings. Medical Devices: Evidence and Research, 185. doi:10.2147/mder.s51384

Williams, A. (2019, October 30). 8 Ways to Make Tech Decisions for Your Organization | Warren Averett. Retrieved from https://warrenaverett.com/insights/eight-ways-to-make- sound-technology-decisions-for-your-organization/

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