Comment: Artificial Intelligence: Focusing on care, not cost

Amit Shukla, assistant vice president and head of healthcare consulting at Infosys, discusses the role of AI and robotic process automation within the healthcare industry

Amit Shukla

In 2014, the market for AI in healthcare was worth over £440m, and this figure is expected to rise ten times by 2021.

Today, healthcare is widely believed to be one of the industries destined for AI-led transformation, which will be an antidote for the high costs as well as an enabler for better health outcomes and experiences.

The sector is traditionally slow to adopt new technologies owing to complexities arising out of multiple ecosystem players and intricate regulations

Digital and AI-led disruption, which could bring about significant cost and process efficiencies, have been relatively slow in this industry, however.

The sector is traditionally slow to adopt new technologies owing to complexities arising out of multiple ecosystem players and intricate regulations.

However, consumers are now demanding more from healthcare.

As digitisation sweeps across industries, consumer technologies have been growing in popularity, with increasing demand for better pricing transparency, connected experience across doctors, hospitals, pharmacies, and other supporting institutions, all of which play an integral role in the care continuum. And the healthcare industry is beginning to respond.

For some years now, a chatbot at Aetna named Ann has been providing round-the-clock assistance to new members in using its website, guiding them through the registration process, or helping them to recover user names and passwords.

Similarly, at Credit Agricole, chatbot Marc responds to product queries in the company’s health insurance space and makes relevant offers to customers after analysing their needs. The potential of robots in superseding humans at the front office is enormous.

Deploying Robotic Process Automation (RPA) and AI in health technology can help deliver a rich and seamless experience for all participants in the care continuum.

Such a model will pivot around the member, enabling them to navigate the healthcare ecosystem to derive the best-possible care.

In this article, we share our view on the impact of these technologies on business.

Enthusiasm over RPA and AI has caused a proliferation of solutions in the healthcare space.

While the perfect solution might be elusive; the best way forward is to choose a solution that is most effective for the organisation.

This, however, invariably leads to the bigger challenge – to secure support, technical and otherwise, for RPA and AI initiatives, especially at the grassroots level, and ensure robust governance around them.

It is important to identify the processes best suited for automation, conduct pilots to demonstrate quick wins, and then trigger a virtuous cycle where success breeds success.

Automating broken processes, however, can not only be inefficient but also dangerous. Processes must be rationalised, optimised and simplified before automation

Automating broken processes, however, can not only be inefficient but also dangerous. Processes must be rationalised, optimised and simplified before automation.

The good news is that unlike traditional IT projects, which run for several years; an RPA/Automation project lifecycle lasts for 6-10 weeks – from ideation to implementation.

In our view, RPA is the right place to commence an automation journey, laying the foundation for more-sophisticated AI deployment.

RPA and AI will have a far-reaching impact on healthcare, well beyond their potential to save costs or reduce labour, although these two benefits are currently paramount.

By eliminating duplicate processes and automating patient support processes, RPA will make it much simpler for patients to avail of healthcare services, even as it enables them to complete transactions faster, benefiting all stakeholders.

Another important benefit is improvement in quality of compliance, because with RPA, processes become fully documented, traceable, and transparent.

AI can ensure accuracy of provider data, which will help healthcare companies avoid steep regulatory penalties imposed in the absence of accurate provider data.

In addition, an intelligent system can turn its vast data resources into insights and use that to propose personalised offerings to prospects, or simply offer the most-relevant additional product to an existing patient.

Last, but not the least, AI would help hospitals, GPs and pharmacies to take better care of their patients.

In this business, it is not uncommon to encounter emotional or agitated callers. Companies can train their service staff to deal with them with empathy.

The savings for a healthcare provider such as the NHS is clearly enormous. Beyond this cost factor, there is an enticing opportunity to deliver a human-centred design for healthcare

There are AI software solutions which analyse the speech of company associates during calls and prompt them to soften their tone or slow down, whenever required.

The savings for a healthcare provider such as the NHS is clearly enormous. Beyond this cost factor, there is an enticing opportunity to deliver a human-centred design for healthcare; by redeploying freed-up staff on work of a higher order, such as patient intimacy and patient care.

Automating most routine tasks in service operations will make staff available to engage patients in pro-active, contextual and meaningful conversations, which are also AI-enabled, and help patients improve their health, or enjoy more healthy days.

An illustration might be useful here: If an AI system alerts an associate about a patient who has missed renewing a prescription for diabetes medication and provides a predictive insight in to the patient’s health disposition based on health history and related attributes, the healthcare associate can promptly arrange a review for the patient.

Like in several other industries, AI in healthcare can complement the workforce and amplify their capabilities.

Human capital in healthcare needs to be diverted to care at the intersection of caregivers and patients rather than be involved in low-value, back-office operations to support frontline caregivers. AI-led automation is ushering in this great opportunity today.

Challenges and concerns

Employees are anxious about losing their jobs to automation, and their employers about managing the change. These concerns can be addressed to a great extent by communicating plans for redeployment and retraining as early as possible.

In our view, RPA is the right place to commence an automation journey, laying the foundation for more-sophisticated AI deployment

An expanding technology landscape around robotics and intelligent operational systems (RIOS) gives rise to several challenges.

The proliferation of solutions and the need for government approval and funding complicates the decisions around AI adoption.

Maintenance of AI solutions, as they scale from a single process to several thousands, is another important concern, followed by their governance and ROI.

RIOS and AI in general will also precipitate new positions within companies and new business models in the market.

The Chief Robotics Officer (CRO) will emerge in the next few years, especially in industries such as healthcare where automation is beginning to be embraced rapidly.

The CRO will assume a comprehensive role with many responsibilities – from choosing the right technologies, managing change and effective staff communications to managing costs, governance and ensuring ROI. They will also eventually become what the CIO is today across businesses and may even earn a place in the boardroom.