Intelligent automation in healthcare and the role of responsible cognitive computing


The concept of automation, as depicted by fiction writers and futurologists for over a century, is no longer a piece of fiction. The notion that quickly caught the collective imagination of humans in the 1920s, when the word ‘robot’ was first used, is today’s reality.

Today, automation is being widely applied across organisations to augment human thinking and potential, reduce costs, increase scalability, improve accuracy, generate greater value from resources and deliver seamless operations. 

Automation is being applied to computerise repeatable tasks, identify new opportunities for automation by extracting and understanding concepts and relationships from data patterns and prior experience, and deliver hyper personalisation in services, solutions and customer engagements.

Taking a leap from RPA to CPA

While robotic process automation (RPA) enables macro-level task automation, standardizing tasks that have a fixed workflow and finite rules, cognitive process automation (CPA) is based on machine learning, natural language processing and speech recognition. 

The latter can automate tasks which are non-standard and involve understanding meaningful information by drawing inferences from reams of data.

As organisations move along the automation maturity curve, they are looking towards the exciting potential of CPA. RPA has proved to be instrumental in addressing key parts of processes without undergoing a complete overhaul, achieving quick and short-term wins. With CPA, machines can emulate the human mind, understand context, interact with humans, make decisions and adapt to resolve new problems. 

Therefore, CPA is the next logical step for businesses as it can help execute more complex, multiple task-level processes, to achieve more strategic and permanent cost and customer experience benefits through insights-driven end-to-end automation, with no human assistance required.

Cognitive automation may just be the cure to address healthcare sector challenges

With cognitive automation, healthcare organisations can address the challenges of efficiency, patient-centricity and growth.

From digitization of health records, to maintaining inventory, dealing with unstructured data and addressing regulatory and reporting challenges, there have been great opportunities for implementation of CPA across the healthcare industry.

Cognitive technologies are being applied by health plans to automate prior authorization, an otherwise manually intensive, time-consuming and costly exercise. 

With regard to population health, CPA can help discover patterns in data through automatic analytical techniques, which in turn can be used to make informed predictions. In this manner, health plans can better understand, predict and influence the health of patient populations.

Over the next few years, health plans are likely to adopt CPA to define product strategies, develop and maintain provider networks, and in pricing and risk management, marketing and sales, and patient engagement.

Talking about claims processing, the health insurance sector has already witnessed extensive automation, in areas of fraud, waste and abuse, policy checking and renewal, calculating premiums, data retrieval, research, and delivering positive customer experiences.

In healthcare delivery, cognitive capabilities are positioned to revolutionize in-patient healthcare operations. The pain points for healthcare facilities across the globe include high operational cost, a lack of integration and data sharing, paper-based information, scarcity of clinical staff, etc.

CPA can help relieve the burden of administrative tasks which consume a great deal of time that can alternatively be devoted to patient care. CPA can also take over more clinical tasks such as collecting and interpreting diagnostic results, drug dispensary automation, suggest thoroughly researched treatment options in a short time frame, etc. 

For example, through intelligent automation, hospitals can receive results of an analysis of billions of phenotypic and genetic images stored in their database, and accordingly make informed, data-backed decisions.

Future implications of CPA in healthcare delivery will be in the form of virtual caregivers or cognitive counselors, discharge management robots, and healthcare companions that can answer health and wellness questions on the basis of voice and facial recognition technologies and can also securely manage storing, dispensing and refilling medications.

The importance of creating a responsible cognitive automation strategy

“With great power comes great responsibility." This holds true for cognitive automation because the role of AI across industries is growing exponentially while regulation has not kept pace. This is especially true for the healthcare industry. 

Also, it needs to be ensured that there is no power concentration that can threaten humanity, and that robotics and cognitive automation are embraced proactively but in a socially responsible manner.

Effective governance of CPA requires increased collaboration between those governing and those building these systems. There has been an increasing call for transparency in automated and robotic systems, which stems from concerns over trust, fault identification, and validation. One of the main concerns with complex CPA systems is the difficulty in determining accountability for failures. Narrowing this responsibility gap is an essential legal-ethical issue that needs to be addressed.

As for the predicted massive job displacements as a result of cognitive automation, the point that is largely missed is that the same technology will also create different jobs than what exist today and the future canvas of work may be starkly different from what we have currently.

Apart from safety, transparency, complexity and regulatory factors, at the business level there are some operational factors that must be considered as part of a responsible cognitive automation strategy. These include:

  • Big bets: Selecting the right process or activity that fulfils the business case for automation, which will include the most complicated business processes.
  • Change management: Engaging stakeholders from the outset to adopt to newer ways of working, to ensure effective buy-in, collaboration and adoption of changes.
  • Reengineer before: Adopting design thinking for future, making the selected process as efficient as possible before implementing automation.
  • Outcome focused: Finalizing the approach for measuring and tracking benefits delivered or impact made to customers’ lives, prior to implementation.
  • Technology: Ensuring the availability of required infrastructure, technology and partnerships.
  • Risk and compliance: Ensuring that compliance requirements are met is one of the most important considerations when implementing CPA.

In conclusion, as task-level automation with RPA is being mastered across healthcare organisations, it is important to keep an eye on the horizon. RPA benefits in healthcare will soon arrive at a plateau, because most decisions in the healthcare domain need to be made based on context and with an extra level of intuitiveness and sophistication. 

CPA is positioned to bring this disruption to healthcare, where intelligent data retrieval and redaction will become a matter of milliseconds, workflows will be streamlined and the workforce/specialists will be able to focus on more value-adding work.


The above article appeared in Businessworld.in, the online edition of Businessworld.