AI in Healthcare: A guide for Executives

Artificial Intelligence is getting better and better than humans in more and more dimensions. In healthcare as well, AI has immense potential. The role of AI in healthcare is becoming increasingly important. It is safe to assume that the future of AI in healthcare is bright. Also, the benefits of AI in healthcare are too many for executives to ignore. In different departments of healthcare, applications of AI are numerous.

It is transforming the way diagnosis and treatment of illnesses takes place. We have provided a concise guide for executives about the necessary things they need to know about healthcare. First, let’s have a look at the applications of AI in healthcare.

1. Consumer Wearables

AI has already transformed the relationship of people with healthcare. Phones, watches, and wrist bands all contain AI and Internet of Things (IoT) through healthcare apps which help people keep track of their health. This encourages healthy behavior in individuals and makes them more in control of their health and well-being. Moreover, daily patterns and needs of people are better understood by healthcare professionals. In this way, better feedback, guidance and support is provided to customers for staying healthy.

2. Detection in Earlier Stages

Diseases like cancer are being detected with more accuracy and in earlier stages already with the help of AI. A high percentage of mammograms yield false results, causing 50% of women being told they have cancer, according to American Cancer Society. The need for unessential biopsies is reduced with review and translation of mammograms getting 30% faster with 99% accuracy through the use of AI.

3. Decision Making

Appropriate and timely decisions need to be made alongside the availability of big data in healthcare if care is to be improved. Clinical decision-making, actions and prioritization of administrative tasks can be aided through the use of predictive analytics.

To identify patients at risk of developing a condition, pattern recognition can be used. Also, variables like lifestyle, environmental, and genomic factors can be monitored to see if they are causing a condition to worsen, with the help of AI.

5. End of Life Care

The average age of people around the world is increasing with improved healthcare. By helping people to remain independent for longer, reducing the need for hospitalization and care homes, robots have the potential to completely transform end of life care. Furthermore, AI is able to have conversations with old people which helps keep their aging minds sharp.

In addition to knowing the applications of AI in healthcare, executives also need to know the challenges of adopting AI in healthcare. Below listed are the most salient challenges:

1. Initial issues of Adoption

Healthcare companies need to be on board if successful case studies are to be documented and presented in order to attract investors for AI in healthcare. Because of concerns regarding its applicability and feasibility, there is an initial hesitation to adoption in market as it is with any new technology.

2. The problem of Black Box

The ability to give answer to “why” questions is missing from machine learning and deep learning currently. AI is able to reach medical conclusions but it is unable to give justifications and reasoning for those conclusions. The “why” is the important part of the treatment plan and therefore, the physician would have the final word in this matter.

3. Concerns of Data Privacy

With Internet of Things increasing with the consumer wearables, increasing amount of data is being made available to be made use of by AI. This patient data is often sensitive in nature and sophisticated systems need to be put in place to ensure the safety of this data.

4. Compliance to Regulations

Healthcare in US is a highly regulated business. Laws like HIPPA regulate the collection of patient data collection and organizations such as FPA are sought after for the approval of incorporation of AI in healthcare. In terms of HIPPA compliance, sharing of data across various data bases in order to be analyzed by AI algorithms poses serious challenge in terms of adoption of AI in healthcare.

Key Takeaway

Although AI already has numerous useful applications in healthcare and those applications are increasing by the day, there are still some hurdles to its complete adoption in healthcare which will be interesting to keep an eye upon in the future. Look at our Artificial Intelligence services to know how the we are helping clients take over the future.

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