The Importance of Computer Science in the Healthcare Industry
by Angelica Sharma

Advanced technologies and algorithms developed by computer scientists are widely used in the healthcare industry to enhance global medical care.

Health Informatics

Computer science and healthcare are two strikingly different fields: while computer science is about computers and their complex computational systems, healthcare is about the distribution of medical care to a community. A relatively new field called health informatics integrates the two by studying the use of computer science in the healthcare industry[10].

Health informatics first rose in prominence at the start of World War II, when doctors began researching how computer logic could help diagnose and treat medical disease. It wasn’t until the 1950s, when computer technology advanced substantially, that health informatics gradually became a reality[14]. Today, countries across the globe are implementing policies that promote the use of health informatics.

Ultimately, health informatics saves time, money, and lives. Indeed, combining a doctor’s expertise with a computer’s algorithmic results can reduce errors in the diagnosis and treatments of patients[4]. Furthermore, health informatics facilitates communication between patients and doctors and makes remote medical care possible. Finally, computer technology comes with better coordination and management – utilities like electronic health records and digital apps make it easier for patients to monitor their health and receive accurate, reliable medical advice.

Because health informatics is a broad field, it is often divided into five subcategories: consumer health informatics, public health informatics, clinical informatics, clinical research informatics, and translational informatics[17].

Consumer Health Informatics

Consumer health informatics focuses on health informatics from the perspective of the patient. In this subfield, computer technologies are used to enhance the patient’s experience with their healthcare.

Web-portals used by hospitals to help patients find medical providers, schedule appointments, and organize treatment plans are developed by computer scientists who study and program these interfaces. For instance, during the recent COVID-19 pandemic, hospitals like the Houston Methodist relied on online platforms to allow patients to schedule coronavirus vaccine appointments online. Once patients received their doses, these hospitals also utilized digital surveys to check in with patients remotely to ensure that no severe side effects were taking place. Today, roughly 4 in 10 individuals have filled out paperwork or made medical appointments online, increasing the need for computer scientists to design these virtual web-portals[5].

Mobile apps and wearable devices have also been programmed and designed by computer scientists to help users monitor their health. For instance, the Apple Watch that was introduced in 2014 by Apple inc. incorporated a feature that allowed users to track their heartbeat while resting and exercising. This gave users the flexibility to track their heart rates at their own convenience without the need for a Holter monitor. Furthermore, in later years, newer versions of the same watch also detected irregular heart rates and notified users when this inconsistency occurred. These warnings made it easier for users to get medical help before health conditions significantly worsened[9].

With the help of computer science, medical records can also be digitized into EMRs, or electronic medical records, which convert physical, complex medical records into a digital format, reducing paperwork for patients. EMRs also ensure that accurate data about patients is being recorded and stored on a timely basis, which helps doctors correctly diagnose and treat patients. Given the benefits of EMRs, countries like India are working to incorporate the technology in their hospitals to improve upon their healthcare systems[6]. Today, the U.S has even adopted federal policies to motivate physicians to use EMRs.

Finally, computer scientists are developing platforms like Zoom and Google Meet to meet recent demands for telemedicine. During the COVID-19 pandemic, hospitals quickly reached their maximum capacities which resulted in more patients requiring remote care during 2020. As computers and phones become more widespread, telemedicine is becoming a more convenient and necessary option for patients.

Public Health Informatics

Public health informatics focuses on applying findings from population data to public healthcare. Computers are used to collect, analyze, and respond to large data sets obtained from populations.

Primarily, computers are used to monitor worldwide disease outbreaks in order to help users analyze current global health conditions. One example of this technology is Johns Hopkins University’s COVID-19 map that was developed in 2020 during the pandemic to show users
where in the world coronavirus cases were arising. By integrating data from different countries about coronavirus outbreaks with geographic data from satellites, Johns Hopkins successfully created a live visual that allowed users to stay up-to-date on information regarding the pandemic. This helped users avoid certain areas of the world where cases were rising and educated the public on the global health status.

It is also important to have computer scientists build programs that will efficiently, securely, and accurately collect data. As an example, PCR, polymerase chain reaction, testing results used during the COVID-19 pandemic were enhanced by the addition of algorithms that output results in minutes.

Finally, computer technologies are used to analyze population data and make decisions for the general public. For instance, algorithms designed to analyze global weather patterns can notify weather reporters when a hurricane may be forming. When computer programs give this signal, authorities are better able to handle and respond to these adverse situations and protect communities around the world. Without computer science, this task cannot be done as quickly, and the consequential delay could cost thousands of lives.

Clinical Informatics

Clinical informatics studies how computer science can help deliver healthcare services. Modern technologies like artificial intelligence play a significant role in this sector of health informatics.

By designing software and programs that analyze specific data, computer scientists make it easier for doctors to diagnose their patients with the correct treatments. For example, MIT researchers used machine learning to help radiologists detect different forms of cancer. After the
computer was given pictures of chest X-rays as well as other data, it predicted which cancer disease was affecting the patient. The researchers found that pairing the results outputted by the computer with doctor expertise resulted in 8% more accuracy, implying that computer science can make a positive difference in medical decision-making[1].

Furthermore, artificial intelligence can enhance algorithmic processes entailed by doctors by juggling multiple variables at a time[2]. As a Harvard researcher once stated, “[Artificial Intelligence] can rescue us from data overload” – although humans can only handle four to five
variables at a time, computers can handle many more, making it possible for them to make better decisions than humans when faced with complex situations[12].

Additionally, medical equipment used by doctors is often programmed by computer scientists. For instance, the da Vinci Surgical System, an FDA approved robot that assists surgeons during surgery, requires extensive programming[3]. However, once coded, the robot can perform many surgical procedures and make the process accurate and efficient. Medical imaging machines like MRI, or magnetic resonance imaging, and X-ray require coding as well[3]. They provide extraordinary insights that doctors cannot obtain themselves, which helps direct patients to accurate and more reliable treatment options.

Clinical Research Informatics

Clinical research informatics uses new data and findings to improve healthcare. Computer technologies are used to perform studies, analyze the results, and apply outcomes to the healthcare industry.

Primarily, computers are used to perform clinical studies that give researchers new data to work with. For example, results from large studies like the one performed by Neurochem Inc. to test a new drug called Alzhemed, which was designed to help patients fight Alzheimer’s disease, are often collected, organized, and interpreted by computer programs[11]. This allows researchers to ensure that the drug tested works and can be reliably distributed to the rest of the population.

Computer science also makes translational research easier to perform. Today, computer science plays a key role in oncology, one of the largest fields undergoing translational study, by detecting mutations in DNA that can lead to insight on the cause of cancer[8]. For example, a researcher named Dr. von Mehren created a drug that fights against gastrointestinal stromal tumors by targeting specific genetic mutations that are only found in gastrointestinal cancerous patients[13]. In this example, computer programs were used to detect mutations in the DNA and provide researchers like Dr. von Mehren with patient-specific genetic information to develop these revolutionary solutions.

Translational Bioinformatics

Finally, translational bioinformatics uses computers to store and analyze biomedical and genomic data. With simulations, algorithms, and modeling, researchers can easily interpret complex data sets.

Computer algorithms, as mentioned previously, allow researchers to find patterns and analyze data. For instance, researchers often use Genbank, an NIH genetic sequence database, to interpret human DNA. Computer programs are needed to find slight differences in genetic questions and identify these diseases because the human genome contains over 3 billion pairs of nucleotides, which is too large of a dataset for humans to handle[7].

Computer modeling is another technique used in translational bioinformatics. By modeling certain organs, sequences, or situations, researchers can obtain information they can’t easily see. A group of researchers at King’s College in London modelled a patient’s heart in order to infer certain properties like stiffness, which can potentially cause heart failures. The models created were incredibly beneficial – the researchers successfully analyzed the heart’s stiffness and also gained new understandings of different mechanisms of the heart[16].

Other technologies

Aside from the five basic subfields of health informatics, there are also other fields of study currently advancing as new technologies are being innovated. Nanomedicine, for instance, is being implemented by select hospitals around the world – when doctors use nanomedicine, they use nanoparticles to distribute drugs in humans or research the insides of a body. 3D printing is also being developed to bioprint human organs. This reduces the shortage of organs and allows surgeons to perform more transplants.[15]

Both technologies rely heavily on computer science – computer programs must be written to track nanoparticles, and computer modelling must be done to 3D print human organs. Computer science and the healthcare industry will only continue to become more reliant and relevant to each other as new innovations are introduced to the medical industry.

In the end, health informatics reduces errors, saves money, improves communication between patients and doctors, and makes it easier for patients to receive accurate medical treatments.

Works Cited

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news.mit.edu/2020/machine-learning-health-care-system-understands-when-to-step-in-0731.

2. “Combining Computer Science and Medicine.” USAnews, 23 Mar. 2021, www.usnews.com/education/blogs/medical-school-admissions-doctor/articles/ways-premeds-combine-computer-science-and-medicine.

3. Cybernet. “4 Medical Devices That Absolutely Need Integrated Medical Computers.” Cybernet Blog, 12 Nov. 2020, www.cybernetman.com/blog/4-medical-devices-that-absolutely-need-integrated-medical-computers.

4. “How Health Care Changes When Algorithms Start Making Diagnoses.” Harvard Business Review, 3 Nov. 2020,hbr.org/2018/05/how-health-care-changes-when-algorithms-start-making-diagnoses.

5. “Individuals Use of Technology to Track Health Care Charges and Costs.” Health IT Dashboard, 2017, dashboard.healthit.gov/quickstats/pages/consumers-health-care-charges-costs-online.php.

6. Mabiyan, Rashmi and ET HealthWorld. “India Bullish on AI in Healthcare without Electronic Health Records.” ETHealthworld.Com, 6 Jan. 2020, health.economictimes.indiatimes.com/news/health-it/india-bullish-on-ai-in-healthcare-without-ehr/73118990.

7. “Mapping and Sequencing the Human Genome.” NCBI, 2021, www.ncbi.nlm.nih.gov/books/NBK218247/#:%7E:text=The%20human%20genome%20is%20thus,nucleotide%20on%20the%20other%20strand.

8. Mattick, John. “The Impact of Genomics on the Future of Medicine and Health.” The Medical Journal of Australia, 7 July 2014,
www.mja.com.au/journal/2014/201/1/impact-genomics-future-medicine-and-health.

9. Miller, Korin. “Here’s What Cardiologists Say About the Apple Watch’s New Heart Monitoring Features.” SELF, 15 Sept. 2018,
www.self.com/story/cardiologists-apple-watch-heart-monitoring-features.

10. Penny. “Is There a Role in the Healthcare Industry for Computer Programmers?” Computer Science Degree Hub, 11 May 2015,
www.computersciencedegreehub.com/faq/role-healthcare-industry-computer-programmers.

11. Petersen, Andrea. “A New Approach To Fighting Alzheimer’s.” WSJ, 29 June 2004, www.wsj.com/articles/SB108845338235649420.

12. Powell, Alvin. “Risks and Benefits of an AI Revolution in Medicine.” Harvard Gazette, 11 Nov. 2020, news.harvard.edu/gazette/story/2020/11/risks-and-benefits-of-an-ai-revolution-in-medicine.

13. “The Role of Translational Research in Fighting Cancer.” Fox Chase Cancer Center- Philadelphia, PA, 11 June 2019, www.foxchase.org/blog/role-translational-research-fighting-cancer.

14. University of Illinois at Chicago. “A Brief History of Health Informatics.” UIC Online Health Informatics, 7 July 2020,
healthinformatics.uic.edu/blog/a-brief-history-of-health-informatics.

15. University of Illinois at Chicago. “5 Emerging Technologies and Their Impact on Health Informatics.” UIC Online Health Informatics, 20 July 2020, healthinformatics.uic.edu/blog/5-emerging-technologies-and-their-impact-on-health-informatics.

16. Vennin, Samuel. “How Computational Modelling Is Transforming Medicine –.” Physics World, 17 Sept. 2020, physicsworld.com/a/how-computational-modelling-istransforming-medicine.

17. “When Healthcare and Computer Science Collide.” UIC
Online Health Informatics, 7 July 2020, healthinformatics.uic.edu/blog/whenhealthcare-and-computer-science-collide.