How Can Artificial Intelligence Be Used in Hospitals?
We list 7 possible applications of artificial intelligence in hospitals: check
them out
Moreover, the use of artificial intelligence is usually associated with production-oriented segments. Industry, agribusiness, and logistics are common examples. It is also common to see the mix of big data, artificial intelligence, and machine learning carry the suffix “4.0”. That alludes to the industrial revolution. After all, industry was the first sector to benefit from the technology.
In fact, our blog has several articles on the subject:
Machine Learning in industry
The impact of the Internet of Things on agribusiness
However, artificial intelligence in hospitals brings many administrative benefits. The same holds for the healthcare sector in general. Above all, it brings benefits for patients. The consultancy Acumen Research already projected strong expansion for this market early in the decade. Since then, analysts have kept revising those estimates upward. Therefore, the growth trend matters more than any single figure.
So the big question is: how should artificial intelligence in hospitals be developed? Above all, the main purpose of this type of technology is to cut time in waiting rooms. In addition, it helps people receive the care they deserve.
Likewise, as we covered in this article about the pharmaceutical sector, big data delivers gains for pharma. Examples include precision medicine and the identification of seasonality and trends. Furthermore, it enables customized medication, lower drug development costs, and more effective control of clinical trials.
As a result, we will now give some examples of “hospitals 4.0” throughout this article.
The applications of artificial intelligence in hospitals
1) Support during appointments
When visiting a clinic or hospital, the patient expects the professional’s full attention. Today, many platforms follow the appointment and transcribe the conversation. Then, they summarize the visit and fill in the medical record automatically.
Meanwhile, these tools usually follow a protocol and create a standard document. As a result, both machines and people can access the information more easily.
2) Optimizing waiting times and patient flow
One of the great challenges for hospitals is managing patient flow and waiting times. There are different protocols, such as the Manchester triage system, which sorts cases by severity. In theory, it seems perfect. In practice, however, reality is quite different.
Automated platforms collect patient information, such as blood pressure and heart rate. In this way, they identify more serious cases. In addition, data from the institution’s own systems can manage patient admission at each point of care. Consequently, the team is less overloaded.
In short, emergency services track the number of patients treated and waiting. That information even helps them direct patients to more suitable locations. In this way, artificial intelligence in hospitals simplifies the management of spaces. It also simplifies staff scheduling and demand planning. Therefore, administration becomes more efficient and transparent.
3) Managing the patient’s history
After all, imagine the following situation. A patient arrives at the hospital in serious cardiac condition. Having more information from the start makes care far more assertive. Therefore, systems and data can keep an efficient record of patient history.
Furthermore, with the evolution of biometric scanners, the patient can be identified through biometrics. This allows nurses and other teams to retrieve data even if the person is unconscious or unaccompanied.
Consequently, this information can prevent certain medications from reaching patients with a history of allergies. Moreover, it helps identify which procedures they have already undergone.
4) Better diagnosis
In practice, several machine learning and artificial intelligence platforms in hospitals support patient diagnosis. The idea is not for technology to replace the healthcare professional. Instead, it serves as a point of support.
Therefore, specialized software identifies patterns and evaluates patient data. In addition, current models are multimodal. As a result, they combine images, record notes, and lab results in a single analysis.
Likewise, during the covid-19 pandemic, automated tools read patients’ lung X-rays. In this way, they sped up the triage of severe cases.
As a result, artificial intelligence software also supports diagnoses, including cancer. After all, it helps flag suspicious tissue even before the biopsy.
A 2016 study came early in clinical adoption. It showed that this support sharply reduced the chance of misdiagnosis. Moreover, the models have improved a great deal since then. Therefore, most hospitals now use that support in daily routine.
5) Wearable devices: more patient information and virtual monitoring
Meanwhile, a large share of people now own smartwatches or other wearable devices. These devices carry very important information about patients.
In short, devices exchange data via the Internet of Things. Therefore, it is possible to monitor a patient outside the hospital. This paves the way for remote care and monitoring.
After all, the FDA (the US equivalent of Anvisa) has already approved the use of “smart pills”. They can monitor certain information from a patient’s body and send alerts to their caregivers or nurses.
6) Tailored medication dosages
Furthermore, treating people means calculating the exact medication dosage. That calculation can be the difference between life and death. The variables depend on weight, severity, diagnosis, and various other factors.
For this reason, artificial intelligence makes this control far more effective and automated. As a result, it indicates the exact dosage for each case. The goal is to promote well-being and avoid serious repercussions.
7) Robot-assisted surgery
In practice, who is more precise: human or machine? The answer is not simple. However, well-programmed equipment sustains a level of precision that is hard to repeat by hand.
Therefore, one of the possibilities of artificial intelligence in hospitals is robot-assisted surgery. Surgeons no longer use only their hands to conduct a procedure. Instead, they combine their experience with technology, such as cameras, mechanical arms, and the right instruments. As a result, they perform more precise procedures.
Likewise, the result? Less invasive surgeries, higher success rates, smoother recovery, and happier patients!
As a result, the current landscape holds great possibilities for healthcare and for patients. However, gaining this kind of competitive advantage requires investment in technology. Healthcare institutions must also structure their systems and handle sensitive data under strict privacy rules.