Pros & Cons of Artificial Intelligence in Medicine

Photo of doctors utilizing artificial intelligence with a patient in a hospital bed using a tablet.

No matter the industry, artificial intelligence (AI) has become commonplace. When it comes to medicine, AI helps health practitioners to streamline tasks, improve operational efficiencies and simplify complex procedures. Large tech companies are investing more funding into AI healthcare innovations. For instance, Microsoft announced a five-year $40 million program in 2020 to address healthcare challenges. Although AI is doubtlessly changing the healthcare industry, this technology is still relatively new. As AI adoption expands throughout the healthcare sector, questions about the advantages and limitations of this technology become ever more pertinent.

How Does AI Help Healthcare?

1. Provides Real-Time Data

A critical component of diagnosing and addressing medical issues is acquiring accurate information in a timely manner. With AI, doctors and other medical professionals can leverage immediate and precise data to expedite and optimize critical clinical decision-making. Generating more rapid and realistic results can lead to improved preventative steps, cost-savings and patient wait times.

Real-time analytics can help improve physician-patient relationships. Making vital patient data available through mobile devices can engage patients in their treatments. Mobile alerts can inform doctors and nurses of urgent changes in patient statuses and emergencies.

Drexel University Information Science Professor Christopher C. Yang, PhD, says, “As AI technology is becoming more advanced, more data can be collected than traditional medical institutions could ever possibly accumulate.”

2. Streamlines Tasks

Artificial intelligence in medicine has already changed healthcare practices everywhere. Innovations include appointment-scheduling, translating clinical details and tracking patient histories. AI is enabling healthcare facilities to streamline more tedious and meticulous tasks. For example, intelligent radiology technology is able to identify significant visual markers, saving hours of intense analysis. Other automated systems exist to automate appointment scheduling, patient tracking and care recommendations.

One specific task that is streamlined with AI is reviewing insurance. AI is used to minimize costs resulting from insurance claim denials. With AI, health providers can identify and address mistaken claims before insurance companies deny payment for them. Not only does this streamline the claims process, AI saves hospital staff the time to work through the denial and resubmit the claim.

Enabling faster payments and greater claims accuracy, hospitals can be more confident about reimbursement time frames, making them more willing to accept a larger number of insurance plans. AI essentially allows hospitals to accept a wide array of plans, benefiting potential and existing patients.

3. Saves Time and Resources

As more vital processes are automated, medical professionals have more time to assess patients and diagnose illness and ailment. AI is accelerating operations to save medical establishments precious productivity hours. In any sector, time equals money, so AI has the potential to save hefty costs.

It’s estimated around $200 billion is wasted in the healthcare industry annually. A good portion of these unnecessary costs are attributed to administrative strains, such as filing, reviewing and resolving accounts. Another area for improvement is in medical necessity determination. Hours of reviewing patient history and information are traditionally needed to properly assess medical necessity. New natural language processing (NLP) and deep learning (DL) algorithms can assist physicians in reviewing hospital cases and avoiding denials.

By freeing vital productivity hours and resources, medical professionals are allotted more time to assist and interface with patients.

4. Assists Research

AI enables researchers to amass large swaths of data from various sources. The ability to draw upon a rich and growing information body allows for more effective analysis of deadly diseases. Related to real-time data, research can benefit from the wide body of information available, as long as it’s easily translated.

Medical research bodies like the Childhood Cancer Data Lab are developing useful software for medical practitioners to better navigate wide collections of data. AI has also been used to assess and detect symptoms earlier in an illness’s progression. Telehealth solutions are being implemented to track patient progress, recover vital diagnosis data and contribute population information to shared networks.

5. May Reduce Physician Stress

Some latest research reports over half of primary physicians feel stressed from deadline pressures and other workplace conditions. AI helps streamline procedures, automate functions, instantly share data and organize operations, all of which help relieve medical professionals of juggling too many tasks.

Yang explains, “The most significant contributor to physician burn out is patient load and the nature of the profession. However, as AI can assist with more time-intensive operations, explaining diagnoses for example, medical professionals may experience some stress alleviation.”

Limits of AI in Medicine

1. Needs Human Surveillance

Although AI has come a long way in the medical world, human surveillance is still essential. For example, surgery robots operate logically, as opposed to empathetically. Health practitioners may notice vital behavioral observations that can help diagnose or prevent medical complications.

“AI has been around for a few decades and continues to mature. As this area advances, there is more interaction between healthcare professionals and tech experts,” Yang explains. AI requires human input and review to be leveraged effectively.

As AI develops, the tech and medical fields are increasingly communicating to improve the technology. Yang adds, “Years of education are required for medical professionals to operate in their fields. Essential information gathered from Subject Matter Experts (SMEs) enriches the data available and improves explainable AI (XAI) to provide healthcare workers with trusted and valuable insights.”

2. May Overlook Social Variables

Patient needs often extend beyond immediate physical conditions. Social, economic and historical factors can play into appropriate recommendations for particular patients. For instance, an AI system may be able to allocate a patient to a particular care center based on a specific diagnosis. However, this system may not account for patient economic restrictions or other personalized preferences.

Privacy also becomes an issue when incorporating an AI system. Brands like Amazon have free reign when it comes to collecting and leveraging data. Hospitals, on the other hand, may face some set backs when attempting to channel data from Apple mobile devices, for instance. These regulatory and social restrictions may limit AI’s ability to facilitate medical practices.

3. May Lead to Unemployment

Although AI may help cut costs and reduce clinician pressure, it may also render some jobs redundant. This variable may result in displaced professionals who invested time and money in healthcare education, presenting equity challenges.

A 2018 World Economic Forum report projected AI would create a net sum of 58 million jobs by 2022. However, this same study finds 75 million jobs will be displaced or destroyed by AI by the same year. The major reason for this elimination of job opportunities is, as AI is more integrated across different sectors, roles that entail repetitive tasks will be redundant.

Though AI promises to improve several aspects of healthcare and medicine, it’s vital to consider the social ramifications of integrating this technology.

4. Inaccuracies Are Still Possible

Medical AI depends heavily on diagnosis data available from millions of catalogued cases. In cases where little data exists on particular illnesses, demographics, or environmental factors, a misdiagnosis is entirely possible. This factor becomes especially important when prescribing particular medicine.

Remarking on this data gap, Yang says, “No matter the system, there is always some portion of missing data. In the case with prescriptions, some information regarding certain populations and reactions to treatments may be absent. This occurrence can lead to issues with diagnosing and treating patients belonging to certain demographics.”

AI is constantly evolving and improving to account for data gaps. However, it’s important to note that specific populations may still be excluded from existing domain knowledge.

5. Susceptible to Security Risks

As AI is generally dependent on data networks, AI systems are susceptible to security risks. The onset of Offensive AI, improved cyber security will be required to ensure the technology is sustainable. According to Forrester Consulting, 88% of decision-makers in the security industry are convinced offensive AI is an emerging threat.

As AI uses data to make systems smarter and more accurate, cyberattacks will incorporate AI to become smarter with each success and failure, making them more difficult to predict and prevent. Once damaging threats out-maneuver security defenses, the attacks will be much more challenging to address.

Should Artificial Intelligence be Used in Healthcare?

AI has doubtless potential to improve healthcare systems. Automating tedious tasks can free up clinician schedules to allow for more patient interfacing. Improving data accessibility assists healthcare professionals in taking the right steps to prevent illness. Real-time data can better and more rapidly inform diagnoses. AI is being implemented to reduce administrative errors and save vital resources. SMEs are increasingly involved in AI development, making the technology more applicable and better-informed. AI is increasingly applied to healthcare, and limits and challenges continue to be confronted and overcome. AI still requires some human surveillance, may exclude social variables, experiences gaps in population information and is susceptible to increasingly-calculated cyberattacks. Despite some of the challenges and limits AI faces, this innovative technology promises extraordinary benefits to the medical sector. Whether a patient or physician, lives everywhere are improving thanks to AI.

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