By: Lyzanne Dsouza RIG Intern Researcher

 

Artificial Intelligence in Healthcare

Better health is the key to human happiness and well-being. It also contributes to the economic progress and growth of the country as healthy populations live longer, are more productive, and save more [1].  Many factors influence health status and a country’s ability to provide quality health services for its people [2]. As of today, Artificial Intelligence (AI) and Machine Learning (ML) services are set to transform global productivity, working patterns, and lifestyles and create enormous wealth. Healthcare is a field that is thought to be highly suitable for the applications of AI tools and techniques [3].

 

Electronic Medical Records (EMR) are being used today in healthcare systems for applying Big Data tools for next-generation data analytics. AI and ML tools are further destined to add value to this flow. One such application of AI is the use of infrared sensors and detectors to discern whether a person has sanitized their hands before entering hospital rooms; if not, an alert is further issued. Infrared and thermal sensors could also be used above an ICU (Intensive Care Unit) bed to help detect twitching or writhing beneath the sheets and alert clinical team members to impending health crises without going from room to room [4].

Figure 1: Artificial Intelligence in Healthcare

AI can also help the elderly by detecting unusual behavior patterns, checking their health conditions, detecting potential accidents, and alerting caregivers to make prompt interventions. Nowadays, AI is even being used to diagnose patient’s health conditions and to prescribe drugs for their treatment accordingly. Although one cannot rely entirely on the AI system for its effectiveness in prescribing such drugs; it is a useful platform that can help doctors and nurses.

 

Data Privacy Concerns in Healthcare Applications

AI and ML services can be used in various applications, such as those mentioned above, to add value to the Healthcare field. However, the most concerning issue in any healthcare application is its data privacy. Often patients are worried about how any application would use their healthcare information. Privacy, security, and governance of such information are especially important in the health sector.

 

Dynamic Trust in Healthcare

Can any product supply such privacy and security to help AI better set up Trust in healthcare systems? Well yes, RIG’s (Revolutionary Integration Group Inc.) Dynamic Trust (DT), is an innovative software solution that evaluates and controls the “trust level” between equipment “Agents” within a heterogeneous multi-agent network. The product is a blended solution of proprietary and COTS (Custom Off the Shelf) software, powered by AI. Consistent with administrative safety boundary set up explicitly by HIPAA (Health Insurance Portability and Accountability Act), DynamicTrust also supplies a safeguarded channel to allow essential data to cross between appropriate users.

Dynamic Trust can also be applied to various applications to help automate, optimize, make better decisions, prevent an incident from occurring, help teams reason a solution, rationalize agent’s actions, and most importantly, safeguard sharing of critical data among “Agents” (patients, doctors, medical device sensors etc.) in the Healthcare AI ecosystem.

 

Dynamic Trust applications in Healthcare

The ongoing pandemic is a critical example of how a global crisis could push medical resources, staff, and facilities beyond their ability. In such situations, help is called from external sources to cope, this way of help is referred to as a “Surge”. The challenge here is to engage and incorporate this Surge of healthcare workers and the sensitive healthcare information transferred among these Agents. Dynamic Trust can thus help set up robust protocols and security to ensure that dissimilar Agents may assimilate into a sophisticated hospital AI ecosystem securely without introducing harmful elements into the system. Dynamic Trust also allows aggregation of data from many sources and supports HIPAA safeguards, meeting equipment requirements, and essential data needs of the Surge.

Figure 2:  Dynamic Trust integrates healthcare workers at each new site providing access, and Safeguarding equipment and information consistent with HIPAA requirements.

Dynamic Trust can also be used to confirm and evaluate the performance metrics of doctors, nurses, and clinics. This evaluation may be done using patient’s reviews, treatment effectiveness, treatment timeliness etc. These performance metrics can be further used by medical insurance companies to improve the quality chain of medical providers they include in their networks and make payment policy changes accordingly. This also helps assure trust between doctors and patients and gives patients a much better and reliable network of doctorsfor their treatment.

 

Conclusion

We exist in an era where healthcare is a primary concern for the well-being of humans and growth of economies. Even a couple of seconds/minutes can save a person’s life and, in such times, Artificial Intelligence and Machine Learning can be very beneficial. Data is inexpensively available to drive these AI and ML services for various applications as mentioned above. However, there is a potential risk associated with its data privacy, security and governance. Dynamic Trust, can therefore play a significant role in enhancing the workflow of these applications in a highly trusted manner and can prove to be a great game-changer in the healthcare industry.

 

References:

[1] Biodrivers | An inside dive into the human body, https://biodrivers.com/.

[2] WHO | Health and development, http://origin.who.int/entity/hdp/en/.

[3] AI and machine learning for healthcare | by Tirthajyoti …, https://towardsdatascience.com/ai-and-machine-learning-for-healthcare-7a70fb3acb67.

[4 ] Ambient intelligence could transform hospitals and enhance …, https://www.hhmglobal.com/knowledge-bank/news/ambient-intelligence-could-transform-hospitals-and-enhance-patient-care.

[5] Figure 1 – Artificial Intelligence in Healthcare: https://www.mathematica.org/commentary/ethics-and-artificial-intelligence-in-health-care-the-pivot-point