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The Digital Scalpel: Business Informatics and the Future of Healthcare Operations
Ja’Zarrion K. Ellsworth
Department of Information, University of North Texas
INFO 4710: Information Technology Management
Stephen Lancaster, MBA
February 14, 2025
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Abstract
The field of healthcare business informatics, also referred to as health informatics or
healthcare IT, has transitioned from a simple data processing system to a sophisticated field
influencing patient care. “Health IT has been championed as a tool that can transform healthcare
delivery.” (Lee et al., 2016) A multitude of recent studies and even a few monumental reports
have paved the way for us to explore not only the historical development of healthcare business
informatics but also its current state and possible future trends. What the majority of these
studies and reports claim is that healthcare business informatics comprises some key
foundational technologies, which are in themselves far from perfect and indeed present a number
of both obvious and not-so-obvious challenges and opportunities.
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The Digital Scalpel: Business Informatics and the Future of Healthcare Operations
The industry of healthcare is complex and full of data. Whether it's from patient records,
clinical trials, or administrative and financial processes, there's a huge volume of information
generated that needs to be well managed. Healthcare business informatics is the field that attends
to this need, applying the principles and practices of information technology to the effective
delivery, management, and research of health information. It encompasses a wide range of
activities, including the development of electronic medical records, the development of platforms
for telehealth, the use of artificial intelligence in healthcare, and the use of decision-making
support systems for clinicians.
Historical Evolution
Healthcare business informatics can be linked to its roots in the mid-20th century with the
advent of computers. This is the point at which we transitioned to Healthcare 2.0, when
healthcare became technologically advanced. Initial attempts at computerizing hospitals were
made in the 1960s and 1970s, and these were mainly in the financial and administrative areas.
The beginning of systematic data collection could be attributed to the initial development of
hospital information systems (HIS). Data sharing in the 1980s and 1990s moved forward with
the advancements of the internet and networking.
The 2000s were a significant forward step toward the implementation of electronic
medical records (EMRs) through the government’s support in places such as the United States,
where acts like HITECH helped push the EMR movement along. This period also saw the
advancement of more sophisticated types of clinical information systems and data warehousing
and analysis. This is the point at which we transitioned into Healthcare 3.0.
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The last 10 to 15 years have seen a surge in growth regarding big data, cloud computing,
and mobile technologies in healthcare informatics. The attention was paid to interoperability,
data analytics, population health management, telehealth, and the integration of artificial
intelligence and machine learning. “The impressive signs of progress of Big Data in the medical
field... will lead to a reconsideration of the conventional views on the functioning of healthcare
systems and organizations.” (Au-Yong-Oliveira et al., 2021) The advantages of big data are
already apparent in health informatics, and their impact will only grow as technology advances.
The heavy hitter of the next era is Artificial Intelligence (AI), or Machine Learning (ML).
Current Landscape
Those historical advances brought us into the current age of healthcare, Healthcare 4.0.
The never-ending benefits of big data didn’t go overlooked, so from those different government
initiatives like the HITECH Act, EMRs were made standard. That widespread adoption enabled
even more significant clinical data to be collected. (Ross et al., 2014) EMRs have turned out to
be the heart of the current healthcare system, and they are the single source of patient’s medical
details. It has many advantages which include better patient care, avoidance of costly medical
errors, and easy access to information for research purposes. Still, there are problems regarding
the solution's effectiveness, comprehensibility, and high costs that affect its further development.
Healthcare systems and other related industries churn out huge amounts of data that are analyzed
to yield meaningful insights. This assists clinicians in the identification of crucial patterns,
trends, and tendencies; in forecasting, in the individualization of our treatment plans; and the
enhancement of our overall population health. Prediction modeling and statistical analysis are
widely applied to the assessment of risk and disease progression. Allowing a more hands-on
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preventative approach to healthcare. This has also greatly benefitted and essentially spearheaded
the Telehealth industry.
Telehealth services have greatly expanded, especially in the last few years. It gives
people a way to get medical services at home or anywhere else, which is useful for those living
in rural areas and for people who want to save time. For the teleconsultations, telemonitoring,
and telemanagement of various chronic illnesses, the EMR serves as the medium that make
virtual visits as seamless as office visits.
Coupled with the telehealth environment, Clinical Decision Support Systems (CDSS)
exist to assist medical providers make decisions. Clinicians use them to decipher an everincreasing hoard of clinical information to make well-informed decisions at the moment of care.
They can enhance the accuracy of diagnosis, decrease the likelihood of medication errors, and
increase the rates of complying with the standards.
The application and integration of AI and its related technology ML is changing the
practice of healthcare in nearly every aspect, including imaging, healthcare delivery, and
pharmaceuticals. AI algorithms can be applied to the analysis of medical images; to the
prediction of patients’ outcomes; and to the development of new treatments.
The sharing of information among different healthcare platforms is very essential for the
proper management of care. This concept is referred to as interoperability. Although progress has
been made in the development of interoperability standards, the issue of achieving
interoperability among all healthcare providers remains a problem. This poses the greatest
challenge for the current landscape of health informatics.
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Future Trends
The future of healthcare business informatics, Healthcare 5.0, is characterized by
continued innovation and integration of emerging technologies. In the short future, we will
probably be seeing robots perform minor surgical procedures with the advancements of ML.
Since the dawn of healthcare 3.0, where our focus has been the development of personalized
patient care big data has been the driving force for taking healthcare into the future. Now we set
out to make it even more personalized with robotics, advanced AI, and other immersive
technologies.
Genomics and data analytics are now making it possible to practice personalized
medicine, as treatments are being delivered based on the patient’s characteristics. Mattick stated
"Thus, genomic analysis will empower a huge shift from practising medicine according to the
mythical 'average' person, unaware of personal genetic factors, to tailored individual 'precision'
medicine—summarised as the 4 Ps: predictive, preventive, personalised and participative—in
what’s arguably the biggest advance in healthcare since sanitation." (2020) Sanitation was a
pretty big deal, but you can’t deny healthcare tailored specifically for you is bigger, because it
can potentially end disparities based on race and other factors.
Informatics is essential in the management and analysis of the genomic data and its
correlation with the clinical data. AI and ML will be more essential in predictive analytics to
help clinicians understand the patient’s needs and intervene early. Some of the applications that
will be expedited by the use of AI in healthcare include; disease prediction, risk assessment, and
treatment planning.
This machine learning also benefits the precursor of those “robots” mentioned previously,
they are officially called The Internet of Medical Things (IoMT). IoMT is the network of
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medical devices and sensors that are connected and share information with each other. The IoMT
devices can help in remote monitoring of patients, digital wellness management, and medication
adherence. The data collected from the IoMT will be very useful in individualized patient care
and public health. However, that data must be secured and the answer to this problem is
Blockchain.
Blockchain technology offers security, privacy, scalability, integrity, authorization, and
authentication and can help improve interoperability of the healthcare data. (Aggarwal et al.,
2021) It is also feasible to employ blockchain technology to document patients’ rights, track
drugs, and exchange data safely. Since security and interoperability remain a challenge,
developing Blockchain should remain a priority for the future of healthcare.
At present, virtual and augmented reality (VR/AR) are being adopted for training
purposes, surgery, and patient care. They can also be employed in the treatment of various
disorders including pain and physical and neurological rehabilitation. "VR seems to be a
promising tool for clinical assessment and rehabilitation because of its many advantages:
standardization, reproducibility, and stimuli control." (Morel, Bideau, Lardy, Kulpa, 2015) So
following the trends, we can expect to see VR/AR as a standard in healthcare within the next 510 years.
Future healthcare systems will be more patient-centered and patients will have more roles
to play in the management of their health. These emerging technologies will help medical
providers prevent, detect, and treat you sooner; additionally, the informatics tools listed in this
section will assist the patient in accessing health information, communicating with the provider,
and self-care. Ultimately fulfilling the problems of the current age of healthcare.
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Challenges and Opportunities
The future of healthcare business informatics holds great promise, but it confronts some
difficult problems. The most important of these is ensuring the protection of the patient's data.
Healthcare organizations must put sturdy security measures in place that accomplish two things:
they must prevent breaches of patient data, and they must ensure that the organization is in
compliance with relevant privacy laws, such as HIPAA. Another ongoing issue that healthcare
informatics must tackle is achieving "seamless interoperability" between different healthcare
systems. Further work is still required to further develop and apply interoperability standards.
Maybe the solution is one EMR for all hospital systems. It is possible that the implementation
and maintenance of sophisticated healthcare IT systems can be costly. Healthcare organizations
have to make sure that they have considered the costs and benefits of each technology.
Healthcare IT systems must be easy to use and navigate for both the clinicians and the patients.
User experience design and human factors are important factors and so the role of the UX/UI
researcher will become even more crucial. AI and machine learning applications in healthcare
carry some ethical concerns, including bias, transparency, and accountability. (Tilala et al., 2024)
The ethical considerations surrounding these technologies cannot be overlooked or the industry
will lose the trust of the people.
Despite all these challenges, there are several ways through which business informatics
can improve healthcare. Informatics can help in personalized medicine by improving care
management, and it can do this in several ways from wearable technology to genome
sequencing. It can reduce medical errors by assisting providers in their decision-making. This is
a fundamental part of what makes informatics useful to medicine when done well. Computing
tools can serve to check both the fundamental and the applied parts of care. It is possible to use
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informatics to improve the administration and management of healthcare delivery, in turn,
decrease costs, and enhance the performance of healthcare organizations. Healthcare systems
produce a lot of data, which if well exploited can be utilized in research and innovation to
develop new treatments and cures. Informatics can help patients by giving them access to their
health information and thereby allowing them to manage their health more effectively.
Conclusion
The area that was once primarily concerned with the management of administrative
processes has grown into a strategic field and is helping to change the very nature of clinical
practice and research. The future of healthcare business informatics is a bright and booming
field. Its continued development, along with its integration with emerging technologies such as
AI, IoMT, and blockchain, is exponentially expansive. There are plenty of opportunities to make
meaningful impacts. Still, we have some challenges to address: data security, interoperability,
cost, usability, and ethics, to name the most prominent ones. By innovating solutions for these
challenges, the full potential of health informatics can be realized to enhance patient care,
productivity, and the future of healthcare. Informaticians, clinicians, researchers, and
policymakers will have to work in sync to guarantee that the next advances are being utilized
ethically for the benefit of society.
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References
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