Healthcare Information Technology Trends
Artificial intelligence is a healthcare information technology trend that helps nurses to analyze medical data. The technology helps in analyzing huge volumes of data faster and efficiently (Jiang et al., 2017). They help in the early diagnosis of a disease. Artificial intelligence technology has been rated 95 accurate in detecting cancer. One of the risks of using an artificial intelligence system is that they may contain biased data sets or algorithms thus the data output may be biased (Fan, Liu, Zhu & Pardalos, 2018). For example, a data set may discriminate against ethnic minorities. One of the benefits of using an artificial intelligence system is that they help in the early diagnosis of a disease. Therefore, patients can begin treatment early and diseases can be tackled early before they develop to full-blown stages such as cancer. One of the risks related to data safety is that data privacy is not assured since the systems are not designed to block hacking attempts.
One of the most promising healthcare technology is telehealth or mHealth. It is a new concept involving attending to patients from a remote location. The technology is promising since it will enhance better access to health service and treatment of emergencies such as heart attacks from a remote location (Kao et al., 2016). It will allow patients to get immediate care for urgent and small issues. The technology will help in improving efficiency and better patient outcomes since urgent issues will be attended to easily. It will increase access to medical health (Kao et al., 2016). It will also enhance relationships between patients and nurses leading to higher patient satisfaction. For example, a patient in America will easily access his or her best healthcare provider in Write my essay for me – CA Essay writer Canada from the comfort of their homes.
References
Fan, W., Liu, J., Zhu, S., & Pardalos, P. M. (2018). Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS). Annals of Operations Research, 1-26.
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., … & Wang, Y. (2017). Artificial intelligence in healthcare: past, present, and future. Stroke and vascular neurology, 2(4), 230-243.
Kao, D. P., Lindenfeld, J., Macaulay, D., Birnbaum, H. G., Jarvis, J. L., Desai, U. S., & Page, R. L. (2016). Impact of a telehealth and care management program on all-cause mortality and healthcare utilization in patients with heart failure. Telemedicine and e-Health, 22(1), 2-11.
