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Top Benefits and Use Cases of AI in Healthcare

Top Benefits and Use Cases of AI in Healthcare

Year after year, artificial intelligence has been affecting more industries and areas of our private lives. Healthcare is no exception! With its growing popularity, you may be wondering: is the hype around AI for medicine justified?

In this blog, we will start by explaining what exactly is AI in healthcare. Next, we will discuss the benefits of AI in healthcare and the main use cases for AI in healthcare. Before we continue, let’s start by answering the basic question:

What Exactly is AI in Healthcare?

Machine learning has the potential to provide data-driven clinical decision support (CDS) to clinicians and hospital staff, paving the way for increased revenue potential. Algorithms and data are used in deep learning, a subset of artificial intelligence made to find patterns, to provide healthcare providers with automated insights.

AI in Healthcare Market Overview: Striking Stats You Should Know

Check out these latest stats to know more in-depth about how AI is transforming the healthcare industry.

  • The global artificial intelligence in healthcare market reached US$ 13248.65 million in 2022 and is projected to witness lucrative growth by reaching up to US$ 187704.75 million by 2031. The market is growing at a CAGR of 41.1% during the forecast period (2024-2031). Artificial intelligence in healthcare is a rapidly growing sector that is transforming the way healthcare services are delivered.
  • Plans for AI are in place for more than 80% of health executives.
  • In 2026, it is anticipated that AI applications will be able to reduce annual US healthcare costs by $150 billion.
  • As per the reports, the market for artificial intelligence (AI) in healthcare is expected to grow from USD 14.6 billion in 2023 to 102.7 billion in 2028.
  • In 2022, the global market for artificial intelligence in healthcare was worth $15.4 billion. From 2023 to 2030, the market is expected to grow at a CAGR of 37.5 percent.
AI In Healthcare

Now, let’s proceed to learn how AI helps healthcare.  How Does AI Help the Healthcare Industry?

Benefits of AI In Healthcare

Here, in this section, we are going to explain the top benefits of using AI in healthcare. Let’s take a quick look:

Benefits of AI In Healthcare

01- Data Security

When it comes to healthcare, protecting sensitive patient data is of the utmost importance. Rapidly advancing AI algorithms help encrypt personal information, clinical reports, diagnostic findings, and more, preventing them from being hacked and storing them securely in the cloud for patients and professionals to access anywhere.

02- Save Time And Resources

As more vital processes become automated, medical professionals have more time to assess patients and diagnose illnesses and conditions. AI is speeding up operations to save valuable productivity hours for medical facilities. In any industry, time is money, so AI has the potential to save considerable costs.

The healthcare sector wastes approximately $200 billion annually, according to estimates. A good portion of these unnecessary costs is attributed to administrative efforts, such as filing, reviewing, and resolving accounts. Another area for improvement is the determination of medical necessity. Traditionally, it takes hours to review patient history and information to assess medical necessity properly.

As per the AI healthcare solutions provider, new natural language processing (NLP) and deep learning (DL) algorithms can help doctors review hospital cases and avoid denials. By freeing up vital productivity hours and resources, medical professionals have more time to help and interact with patients.

03- Robot-Assisted Surgery

Complex and critical surgeries demand extreme care, precision, and experience. The number of successful surgeries performed with AI-enabled robots is skyrocketing.

The surgical instruments, mechanical arms, and cameras on the robots are all included. They can be customized to reach every part of the human body and provide a clear, magnified view of the surgical site that is far better than human vision can offer. These surgeries reduce pain, take much less time, and help patients recover faster.

04- Speed Up Tasks

The application of artificial intelligence to medicine has already impacted healthcare procedures worldwide. Innovations include appointment scheduling, clinical detail translation, and patient record tracking. AI is enabling healthcare facilities to streamline more tedious and painstaking tasks. For example, smart radiology technology can identify significant visual markers, saving hours of intensive analysis. Appointment scheduling, patient tracking, and care recommendations are all automated by other systems.

One specific task that is streamlined with AI is insurance review. Insurance claim denials can be avoided by utilizing artificial intelligence (AI). With AI, healthcare providers can identify and address erroneous claims before insurance companies deny payment for them. This not only streamlines the claims process but AI also saves hospital staff time to work through the denial and resubmit the claim.

By enabling faster payouts and more accurate claims, hospitals can be more confident in reimbursement timelines, making them more willing to accept a larger number of insurance plans. Basically, AI allows hospitals to accept a wide range of plans, which benefits potential and existing patients.

05- Smart Health Insurance

Insurance companies can leverage connected devices to capture health data for their health and risk underwriting and claims operations. It gives transparency among insurers and clients and eliminates fake cases.

06- Location Tracking and Alerts

Smart medical devices enable real-time monitoring, tracking, and alerts, enabling practical treatments, greater precision, rapid intervention by clinicians, and improving overall patient care outcomes. Wheelchairs, scales, nebulizers, pumps, or monitoring equipment can be tracked with sensors, making it easy for staff to track.

07- Reduction of Prescription Errors

Prescription errors are a serious problem in the healthcare industry. In fact, according to a study, about 1.5% of prescriptions are incorrect. It might not appear to be a high percentage. Still, when you consider that more than 4 billion prescriptions are filled each year in the United States alone, it quickly becomes apparent that prescribing errors can significantly affect patient safety.

One of the main advantages of using artificial intelligence in medicine is that it has the potential to reduce prescription errors. AI-powered systems can help verify that prescriptions are filled correctly and the correct dose is dispensed. Also, AI can flag potential bugs so they can be fixed before they do any damage.

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08- Patient Impact

The many benefits of AI in healthcare are not limited to clinicians, but can also apply to patient impact.

Many patients are lost due to enrollment difficulties, so AI can help by recommending trials that match the patient’s conditions or symptoms. By using intelligent algorithms to extract data from a patient’s medical records, appropriate study recommendations can be made, saving the patient hours of painstakingly searching for a trial.

These examples of artificial intelligence in healthcare are not a case of using AI technology to replace healthcare professionals, but rather an example where the use of new technology can provide better diagnosis and care, faster and with less human intervention.

Now, you understand the benefits of AI in the healthcare industry, it’s the right time to hire AI developers for your project. 

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Top Use-Cases of AI in Healthcare

Let’s examine the most interesting AI applications in healthcare:

#1- Diagnosing Infectious Diseases

Machine learning and big data can help change the way we diagnose infectious diseases forever. That’s the case with technology implemented by Aperiomics, this firm developed an AI-based method for analyzing organic samples for the disease at incredible speed.

Using deep shotgun metagenomics, it can take any genomically sequenced organic sample and identify all 37,000 known and sequenced pathogens. Using proprietary databases and ML algorithms, they can relatively quickly run standard genetic samples through their system and create a complete profile of everything in the sample, identifying what should and shouldn’t be there and in what amounts they were found. 

This work, which would be impossible without the power of AI, means that patients who have difficulty diagnosing infectious diseases can finally get diagnosed and treated.

This technology has been used by people with chronic urinary tract infections to detect life-threatening cases of blood sepsis, severe gastrointestinal infections, and much more.

#2- Avoiding Unnecessary Surgery

It is not uncommon for patients to undergo surgeries that may later prove unnecessary. These unnecessary procedures force people to face entirely avoidable risks and burdensome surgical expenses.

Health plans often include programs that help patients and their local healthcare teams make better-informed decisions by informing them of the latest treatment options available. However, it is difficult to achieve adequate participation in these programs, especially when patients are already in a crisis situation.

Artificial intelligence and predictive analytics identify patients considering surgery and assesses whether these operations are really necessary or whether there are other much lower-risk alternatives that would better help them in the long run. Early identification of people on the path to surgery doubles the average program participation rate and reduces unnecessary surgeries.

#3- Improving Medical Image Analysis

Even the best doctor can miss a tiny detail on a CT scan or echocardiogram. Especially if a doctor focuses on looking for information in a medical imaging report related to a specific condition, it’s completely normal to miss signs of other, unrelated diseases.

Some companies are leveraging the power of AI for comprehensive algorithm-based analysis of medical imaging reports that can improve diagnostic accuracy by up to 90%.

The traditionally low quality of ultrasound images is improved so that this much cheaper diagnostic method can be used in patients without exposing them to unnecessary radiation.

#4- Virtual Nursing Assistants

Healthcare facilities dealing with a high volume of patients face many challenges in keeping costs of care low and improving outcomes. Nurses, in particular, often have to care for too many patients at once, so any technology that can help them reduce their workload is Artificial Intelligence.

Virtual nursing assistants are intelligent assistants that can perform many tasks, such as monitoring patients’ vital signs remotely at any time of the day, alerting providers and physicians when a patient’s symptoms are alarmingly reduced, checking compliance with the plan of care, or extending care outside the clinic. 

Virtual nurses are a futuristic fusion of all the latest technologies, including ML, to compare vast databases of patient information, computer vision, natural language processing, and even advanced robotics.

#5- Intelligent Robot-Assisted Surgery

Robotic surgeons have already been proven for years as being able to prevent many of the human errors associated with exhaustion and fatigue. Surgical procedures require, in fact, the utmost patience and precision, and the skill of mechanical surgeons does not falter even when they operate non-stop for hours on end.

AI combined with computer vision software can be used to achieve a new level of precision for even the smallest movements, allowing robot surgeons to perform procedures independently.

Human surgeons can also benefit from Artificial Intelligence, as algorithm-assisted instrumentation can be used to perform procedures on a scale too small to perform by hand.

#6- AI-powered Insights at Scale

Data-driven insights are essential resources for healthcare organizations and governments to establish new health policies that can benefit the general population. There is already a platform that has been developed to aggregate data from admission, discharge and transfer, claims, and EHR systems to provide information to stay ahead of chronic diseases such as chronic obstructive pulmonary disease (COPD), chronic heart failure, and diabetes.

This platform can be used to find new ways to reduce the risk of T2 diabetes through the use of wearable devices and lifestyle tips, and identify runaway drug costs and drug variance. Together with Microsoft, it is helping national governments to identify which COPD patients are getting worse and who need a higher dose of medication.

It has also been used to identify runaway drug costs and drug variance, revealing that the right data can tell you that giving oral acetaminophen is more effective and less expensive than giving it intravenously.

AI-powered Insights at Scale

#7- Reducing the Burden of Uncompensated Care

AI is being used to streamline and automate healthcare revenue cycle processes, particularly self-checkout. Some of the accounts are more likely to pay if given the chance, while others do not qualify for full financial assistance.

Coupled with robotic process automation, AI’s advanced micro-segmentation capabilities can now drill into each patient’s ability to manage and pay their bills. A smart score will help identify the categories most at risk of incurring debt they will never be able to pay.

#8- Supports Health Equity

The AI and ML industry has a responsibility to design healthcare systems and tools that ensure fairness and equality, both in data science and clinical studies, to deliver the best possible health outcomes. With the increased use of ML algorithms in various areas of medicine, the risk of health inequities may occur.

Those responsible for applying AI in healthcare need to ensure that AI algorithms are not only accurate, but also objective and fair. Since many clinical trial guidelines and diagnostic tests take into account the race and ethnicity of the patient, a debate has arisen:

Is the selection of these factors based on evidence? Is data on race and ethnicity more likely to solve or increase universal health inequities? It is established that ML comprises a set of methods that allow computers to learn from the data they process. That means that, at least in principle, ML can provide unbiased predictions based only on an unbiased analysis of the underlying data.

AI and ML algorithms can be educated to decrease or eliminate bias by promoting transparency and diversity of data to reduce health inequities. Healthcare research in AI and ML has the potential to eliminate differences in health outcomes based on race, ethnicity, or gender.

Future of Artificial Intelligence in Healthcare 

The increasing availability of annotated healthcare data sets and medical imaging serves as a springboard from which new use cases for artificial intelligence and computer vision emerge.

Most of the emerging technologies have yet to be tested in broader clinical settings. However, AI in healthcare has a bright future ahead of it!

Artificial intelligence, deep learning, and machine learning have proven useful in helping both healthcare providers and patients. Other than current (and future) applications include

  • Revenue Cycle Management
  • Drug development processes
  • Claims Processing
  • Robotic process automation
  • Diagnosis of treatment applications
  • Clinical documentation management

You can also analyze data about patient visits to the clinic, medications prescribed, laboratory tests, and procedures performed in the past. The theoretical results and early pilots instill great confidence in IT professionals and clinicians, who are joining forces to transform patient care and improve healthcare organizations around the world. However, for AI in healthcare to go mainstream, broader transformations of the healthcare sector are also required. 

Hospitals will have to invest in new technological systems and staff training. They will need to undertake substantial integration projects and focus their efforts on adopting these technologies into their daily clinical practice.

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Time to Sum Up 

As per a top artificial intelligence development company, the rapidly growing volume of patient data, both inside and outside the hospital walls, shows no signs of slowing down. Strained by ongoing financial challenges, operational inefficiencies, a global shortage of healthcare workers, and rising costs, healthcare organizations need technology solutions that drive process improvement and better care delivery while achieving crucial clinical and operational metrics.

The potential of AI in healthcare could improve the quality and efficiency of the delivery system by analyzing and extracting intelligent insights from the vast amounts of healthcare data, which is limitless and well documented. If you are interested in implementing AI solutions in your healthcare business, then get in touch with us. Being a leading AI solutions provider, our professionals will assist you with the best of their knowledge.

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