In addition to transforming other businesses around the world, artificial intelligence (AI) and machine learning (ML) have the potential to fundamentally transform the healthcare industry. 

One can understand how these technologies could revolutionise patient care and diagnosis by being able to analyze data on patient visits to the clinic, medications prescribed, lab tests, and procedures performed. On a macro level, the data outside the health system — such as social media, census records, and Internet search activity—are used to track and spot changes and trends in the health of the population. 

A number of health-tech start-ups are using AI and ML to service a large number of patients. The same technology can also help employers track the health metrics of their employees across organisations. 

Employers today can leverage this to get an understanding of their employees’ health quotient and take timely action to address issues, plan and allocate resources. Apart from increasing the overall productivity quotient of the employees, it is also a great tool for employee engagement.

How healthcare digitisation impacted employee engagement 

COVID-19 ushered in digitisation worth several years' worth of work in almost no time. Today, millions of people are availing online consultations, telemedicine services, and doorstep care instead of the pre-pandemic practice of visiting a hospital or a clinic for every minor or major need and even routine check-ups. This opens up a new avenue of employee engagement for employers.

Employers have witnessed a tremendous increase in the number of creative employee health and wellness initiatives aimed at a range of objectives, from increasing employee fitness and treating chronic diseases to supporting value-based care models that meticulously track employee health results. 

Further, employers could enable AI and Machine Learning (ML) to be at the core of delivering these models to enable quality care at the workplace. 

How AI can help in delivering customised care

The current healthcare landscape is rapidly evolving, with some changes being incremental and evolutionary and others being radically transformative.  These modifications have altered patients' and their families' experiences as well as the clinical procedures and routines of healthcare practitioners. Health-tech has become increasingly personalized and the future is being defined by wearable and easily portable medical devices as well as virtual care platforms that will ensure seamless, standardized, and anytime, anywhere delivery of medical assistance through hybrid/virtual and in-person facilities as per the use case. 

Finding the health and wellness initiatives that work best for employees considering the remote and hybrid work cultures of today needs analysis of large volumes of data. With an increased number of variables, it is humanly impossible to arrive at the best solution. 

By leveraging AI algorithms, one can analyse data, draw insights and find appropriate solutions to ensure employees get quality and customized care. These technologies help in giving an understanding of the individual, which is necessary to tailor wellness communications and initiatives to that person. Additionally, conversational AI could be used to both drive conversation, engagement, and collect data from employees.

With surveys and usage patterns about how people prefer to manage their health, we can understand problems they encounter and push reminders for necessary health actions. From employees’ responses and actions, insights regarding health literacy, self-efficacy are gained. 

For example, AI and ML can connect employees with a specialist based on the symptoms and recommend tailored therapies using available clinical data, expertise, and research. This can help in preparing the finest and most bespoke patient care plans suitable for a particular individual. 

How AI can help increase employee engagement 

Technology will be our most crucial enabler as we all adjust to this era of remote relationships, for employers, employees, benefit providers, and health care providers. From business meetings to health check-ups, virtual relationships will become the norm. Therefore, it is critical to figure out how to engage individuals on these virtual touchpoints. 

Moreover, effective engagement requires personalization and relevant communication. AI and ML can help employers accomplish this by sending  matching solutions to specific challenges. It will help overcome the difficulties of managing health in a remote work setting. It can also help connect them to resources that benefit them personally. 

Role of Machine Learning in preventive care

Machine learning can help proactively identifying and classifying the type of medical issues of employees. ML algorithms can provide crucial medical insights based on emerging pattern. It has the ability to "cluster" similar medical cases together to identify conditions and guide future research. This helps to predict how future events will play out using current data and well-known trends. 

Using machine learning in healthcare, you can identify patterns that are an exception and decide whether they call for any action. For example, if an employer notices that 40% of his employees are facing back issues, they can relook at the seating in the office. Another example is diabetes. It is a health condition that is both common and also contributes to the development of numerous other severe ailments. With machine learning, diabetes could be detected relatively for a given cohort; in this case it could be a employee cohort with common indicators. 

The current healthcare landscape

Unfortunately, the quality and accessibility of healthcare in India are highly fragmented depending on geographic, economic, and social factors. While these technologies have their benefits, it is crucial to understand the challenges, like data privacy issues, for which various guidelines have been laid down by the concerned authorities. 

Data security must be prioritized as a result to prevent data theft. Sensitive information should be kept private, and as the world moves faster and faster into the digital sphere, it is essential to have the right safeguards in place to adhere to data privacy laws to protect confidential employee data. 

As of 2022, India does not have fully developed laws on AI and ML. However, it broadly follows a set of recommendations made by the 'NITI Aayog’ government think tank in 2018. This document made the promotion of AI and its applications a top priority of the government. It emphasizes a good IP (intellectual property) environment for AI innovations in India. However, implementing AI in the Indian healthcare system comes with a number of technical and social problems.

All predictive AI algorithms function by analyzing large datasets and predicting new results based on their interpretation. In highly diverse populations like India, this can lead to misdiagnosis if a patient presents with a subtly different health condition that the algorithm doesn’t recognize. Medical consultations are also invasive in nature and involve a lot of private data. However, how exactly an AI handles this sensitive data and makes its diagnosis can be impossible to determine, even by the algorithm’s own creator. 

The way forward

Naturally, both the government and tech-health organizations are constantly working together to solve these problems. The BIS (Bureau of Indian Standardization) and the ISO (International Organization for Standardization) have been working together since 2020 to make AI technology uniform and accessible across sectors, and one of the three main goals of the NITI Aayog is to scale Indian-made AI solutions for the rest of the developing world. 

Given the scale and need for healthcare solutions, AI and ML have a critical role to play in providing healthcare across India. At the same time, we need to be conscious of the fact that technology is a mere enabler; human touch and engagement are absolutely critical to ensure the effectiveness of healthcare.