Role of HIT in Healthcare Planning

Role of HIT in Healthcare Planning

Healthcare information technology (HIT) is one of the greatest disruptive forces that will affect vision and planning over the next decade. However, regardless of the technology that is developed, it must be supported and executed by hospital leadership to be successful. Currently, research is underway for the use of artificial intelligence, supercomputing, and clinical support systems in the healthcare environment. This research will explore how these technologies are likely to change healthcare in the future, and the role of readership in making the integration of these technologies a success.


Currently, information technology is an integral part of the healthcare system. HIT refers to a variety of technologies that collect, transmit, store, and display patient data electronically (Hemmat, Ayatollahi, Maleki, and Safhafi, 2017). This makes it easy to send, review, and update patient information quickly and easily. The current list of technologies includes remote and mobile health technology, cloud-based services, medical devices, telemonitoring tools, sensor technologies, and electronic health records (EHR’s) (Hemmat, Ayatollahi, Maleki, and Safhafi, 2017). The use of technology in many different types of healthcare settings is already in daily practice. However, in the future, the use and types of technologies used in the healthcare setting are expected to expand exponentially. Countries continue to make extensive investment in the area of technology development for the healthcare industry (Hemmat, Ayatollahi, Maleki, and Safhafi, 2017). This suggests that there is considerable interest in the development of technology in the healthcare industry in the near and long-term future. Now, it is time to examine some of the different types of technology that can be expected to be seen in the future.

Artificial Intelligence

Artificial intelligence (AI) is technology that is designed to mimic human cognitive functions. One of the areas that it offers improvement in the healthcare setting is the ability to assist in analytics that can be applied to both structured and unstructured data (Jiang, Jiang, Zhi, Dong, Hao, & Ma, et al., 2017). In the future, it is expected to be able to help doctors make better clinical decisions, with many of the advances in this area in the field of radiology (Jiang, Jiang, Zhi, Dong, Hao, & Ma, et al., 2017). The fascinating feature of AI is that it can be trained through data to perform clinical activities including diagnosis and treatment assignment for patients (Jiang, Jiang, Zhi, Dong, Hao, & Ma, et al., 2017). Technology is being developed that can learn similar groups of subjects and the associations between features, such as race and demographic information, to increase the likelihood of the desired outcome.

One of the areas where AI is being developed to be used in future is in the field of cancer diagnosis. In a recent study, this technology was used to analyze abnormal genetic expression in non-coding RNA to diagnose gastric cancer in a sample population (Li, Liang, Yao, Sui, Shen, & Zhang, 2016). It also been applied to detect diabetic retinopathy through retinal fundus photographs with a sensitivity of over 90% (Gulsham, Peng, & Coram, 2016). These are only a few examples of the uses of this technology that are currently under study and development. However, an examination of the literature indicates that there is a significant amount of interest in the use of AI for diagnostic and treatment analysis. This technology is designed to assist physicians, and give them another tool, but it will not replace human intervention in the process. It is another set of eyes and gives the physician a level of information that they did not have access to in the past.


Supercomputing is another form of information technology that is set to revolutionize the ability to solve data intensive problems in the healthcare industry. This technology uses an array of computer systems working in parallel at their maximum performance to do data intensive calculations. In many cases, this type of data analysis would take months or years to complete by humans, and in some it may not even be possible without the use of these arrays of computers.

Cray supercomputer systems have teamed up with Microsoft using Microsoft Azure data centers (O’Dowd, 2017). This will allow users in the healthcare industry to run heavy workloads and support artificial intelligence in this environment. In addition, this technology can now be deployed in the cloud. This allows the ability to process real-time analytics and provide powerful solutions to the healthcare industry (O’Dowd, 2017).

Supercomputers have been around since 1964, but their power and ability to process big data has increased exponentially with the power of the computers hooked into the array (Engel, 2019). Now, computers can perform 1 trillion operations every second (Engel, 2019). One of the most prominent areas where super computers are being employed is in the area of genetics and DNA. Plans are under development to be able to use supercomputers to detect tiny genetic differences that can help adjust medications and save lives (Engel, 2019).

One of the challenges of developing super computers that can be used in a real-time clinical setting is cost. Supercomputer systems cost hundreds of millions of dollars. This is one of the key barriers to implementing them in the average healthcare setting. For this reason, they are typically only found in research setting at the present time (Engel, 2019). However, as computer technology continues to grow, these systems may become more accessible to healthcare providers in the future.

Many researchers are now beginning to develop the potential for combining artificial intelligence and supercomputing in a way that opens possibilities that were never achievable in the past. This is some of the technology that is behind the sequencing of the human genome and that will be at the forefront of genetic research in the future. Never before has humanity have the ability to analyze such large numbers of data quickly and efficiently. This opens up many new possibilities and probabilities that have not been considered in the past.

Clinical Support Systems

Perhaps one of the most exciting areas in the development of HIT for the healthcare community is research into clinical support systems that will assist in helping to make clinical decisions for patients. One of the key areas where this technology is being developed is to promote patient safety. It is expected that in the future clinical support systems will be the cornerstone of improved efficiency, effectiveness of healthcare, quality, and safety (, 2018). The clinical support system allows the information to be filtered and presented at an appropriate time in the clinical workflow (, 2018). Currently, a wide number of tools are being developed for use in many different clinical settings. There is a significant interest in the development of the systems at the present time.

The capabilities of clinical support systems include alerts and reminders to care providers and patients (, 2018). It includes clinical guidelines, and a condition-specific treatment sequence. It can provide instant patient data reports and summaries, documentation templates, and diagnostic support. Can also provide relevant reference information and a number of other tools (, 2018). The systems that are currently in use and being further developed have functions in place for reasoning and inferences. This allows them to combine both data collection and knowledge in a way that is relevant and useful to the current patient situation (, 2018).

Clinical support systems are currently a requirement for healthcare facilities that accept Medicare and Medicaid (Centers for Medicare & Medicaid Services, 2014). There are also quite a few systems of one the market from major manufacturers. This area is highly lucrative for both suppliers and healthcare providers. By now, most healthcare staff are familiar with using clinical support systems as a part of their daily routine. The purpose of the clinical support system is to provide not only information, but information that is relevant to the patient and provide interventions that will be most likely to be effective (Centers for Medicare & Medicaid Services, 2014). Their use in pharmacies, hospitals, and many individual practices. One of the advantages of the clinical support system is that records are portable and allow the electronic transmission of records that are compliant with HIPAA (Centers for Medicare & Medicaid Services, 2014). Currently, there are well-established guidelines that affect the operation of these systems. However, they are likely to become even more advanced and capable of doing more things in the future.

Role of Leadership

This research provided an overview of some of the exciting advances in technology that are currently under development, and currently in use in healthcare systems. These systems promise to provide the ability to analyze data faster and analyze larger quantities of data to achieve more precise and valid research results. Computers can now do things in terms of data analysis that humans are no longer capable of when it comes to time and ability. There is no doubt that HIT will provide promising outcomes in the future. However, this technology is only as good as the ability to apply it in a real-world settings. It is up to healthcare leaders to keep up-to-date with the latest advances in technology and to support their application in the clinical setting.

There is no doubt that having the latest technology in a healthcare setting gives it a decided competitive advantage. Having the latest technology is an excellent branding and advertising point. Leaders must understand the importance of having the latest technology to improve their operational costs, staff efficiency, and reduce their rates of errors. It is responsibility of leadership to keep up with the advances in HIT and to find ways to implement these new technologies and their healthcare setting as quickly as possible. Of course, funding is always an issue when it comes to new technology, but the advantages in the ability to process through a higher number of patients and provide them with better care justifies the cost of this new technology.

In the healthcare industry, staff members and lower managers look to the attitudes and support of upper leadership in terms of whether to support the adoption of the latest advances in technology. Sometimes these new technologies can be intimidating because they are unfamiliar. However, it is up to the leaders to make certain that staff is trained and becomes familiar with the operation of the new technology and that they have a supportive attitude towards it on adoption. Leadership plays a key role in the adoption and use of new advances in technology in the real world.

Keeping up with the newest technology is paramount to the commitment to provide quality healthcare to patients. It is a leader’s responsibility to make sure that their patients have access to the most advanced technology available in order to improve overall outcomes. Technology is the key to leading a healthcare organization to excellence and sustaining a competitive advantage. Leaders must keep this in the forefront of their decision-making guidelines. The bottom line is not about controlling costs, it is about providing excellent patient care and making sure that they have the best equipment and technology available in order to do so.








Centers for Medicare & Medicaid Services. (2014). Clinical decision support: more than just ‘alerts’ tipsheet. eHealthUniversity. Retrieved from

Engel, K. (2019), Supercomputers are shaping future of humanity. Retrieved from

Gulshan, V., Peng, L. & Coram, M. (2016). Development and Validation of a Deep Learning Algorithm for detection of Diabetic Retinopathy in retinal fundus photographs. JAMA, 316, 2402–10. Retrieved from:

Hemmat, M., Ayatollahi, H., Maleki, M., & Saghafi, F. (2017). Future research and health information technology: a review. Perspectives in Health Information Management, 14(1b), Retrieved from (2018). Clinical Decision Support. Retrieved from

Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Hao, L. & Ma, S. et al. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology, 2(4). Retrieved from:

Li, C., Liang, G., Yao, W., Sui, J., Shen, X., & Zhang, Y et al. (2016). Integrated analysis of long non-coding RNA competing interactions reveals the potential role in progression of human gastric Cancer. Int J Oncol 48, 1965–76. Retrieved from

O’Dowd, E. (2017). Cray Supercomputers, Microsoft Azure Aid Healthcare Analytics. HIT Infrastructure. Retrieved from


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