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AI and automation in healthcare in 2020

We often read about how AI (artificial intelligence) and automation could transform the way we work. And in healthcare, these tools offer much more than commercial value. Here, there’s a potential to improve the cost, accessibility, and efficacy of patient care—and have a positive impact on people’s quality of life.

Of course, automation is not a new concept in the medical field. Robots have been laboring away in labs and operating theaters for quite some time now. However, the improved accessibility of AI and automation in healthcare in 2020 has brought these technologies into mainstream consciousness. Essentially, these systems are becoming more affordable and easier to work with.

When Accenture surveyed healthcare executives in 2019, 94% reported that the pace of innovation in their organizations had “accelerated over the past three years due to emerging technologies”.

The interplay between AI and automation

There’s plenty of potential for AI and automation in healthcare in 2020. This is especially true when these capabilities are combined. This approach, often called intelligent automation, creates an environment where AI and automation work together to amplify their value—and that of every resource within the organization, including data and human expertise.

Today, AI can extend automation beyond simple, repetitive tasks into more complex areas that have previously relied heavily on human input. The result? Healthcare professionals’ skills can be redirected to more valuable work; and they can access AI-driven insights and intelligent support to stretch their capabilities even further.

Intelligent automation ingredients

Key components of the intelligent automation environment include:

Use cases for AI and automation in healthcare in 2020

Beyond adding these technologies to your productivity toolkit, you could leverage AI and automation to better understand the patient experience and meet the needs of patients.

From data overload to opportunity

There’s a staggering volume of health data available today. Medical journals, patient notes, wearables, treatment case studies, and many other sources deliver data that could be used to meet multiple healthcare transformation goals.

But the task of translating this tidal wave of content into actionable information is one we humans can’t manage alone. And given that 80% of this data is unstructured, traditional technologies that can only “read” clean, formatted data are not much help.

Now, AI can be harnessed to make sense of this information. Through optical character recognition, natural language processing, machine learning, and deep learning, you can analyze and extract actionable insights from multiple data sources—regardless of the format.

Ultimately, you are now able to access intelligence that provides a better understanding of costs, risks, patient needs, the relevance of your approaches, and more.

AI-assisted screening and detection

AI can help medical practitioners detect diseases earlier or with more accuracy. For example, a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Massachusetts General Hospital (MGH) recently created a new deep-learning model, trained on mammograms and known outcomes from over 60,000 patients. This model can predict from a mammogram if a patient is likely to develop breast cancer; it accurately placed 31% of all cancer patients in its highest-risk category, compared to only 18% for existing approaches.

This type of approach makes risk-based (rather than age-based) screening possible. This could lead to much more effective individualized screening and prevention programs.

Smart process automation

When it comes to reducing the cost of care, process automation is an excellent focus area. Using software robotics, workflow automation, and low-code applications that connect data sources, you could streamline countless processes across the healthcare sector.

With this approach, you could automate routine record-keeping and admin tasks, from scheduling patient appointments to managing accounts payable. You could also digitize and optimize more complex processes, such as hospital caseload management and insurance claims processing.

AI could then be pulled in for unstructured data management, advanced analytics and even to power smart virtual assistants to retrieve information and files in the background, if required.

The human element

Rather than stealing healthcare jobs, AI and automation could be used to create new career opportunities for health workers. Doctors and nurses, for instance, are often laden with routine admin tasks that eat into the time they could be spending with patients. AI and automation tools could work together to take many tasks off these skilled professionals’ hands.

When people and intelligent automation technologies work together, so much more can be achieved. Research shows that machine learning can drive a 200% increase in relevant KPIs. But when processes are overhauled, and humans and machines collaborate, performance can be improved ten times more.

Think ahead

AI and automation are already making waves in healthcare, yet we’re only just beginning to imagine their potential to transform this sector.

With so many possibilities, it can be difficult to know where to start. We recommend looking at your processes first and identifying where automation and AI can make a tangible impact – on your operations and in your patients’ lives.

In other words: focus on the outcomes you want to achieve and build your technology foundation from there. Nintex K2 can help you to construct an agile, user-friendly and future-focused platform for process automation, which can integrate with AI tools and emerging capabilities as these become relevant to your organization.



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