Posted: 01 May 2018 5 min. read

Taking the robot out of the human: Meet the health care workforce of the future

By Sarah Thomas, Managing Director, Deloitte Center for Health Solutions, Deloitte Services LP

Based on some of the headlines I’ve come across recently, it seems we are all about to be replaced by robots and artificial intelligence (AI). From NBC News, “Will robots take your job? Humans ignore the coming AI revolution at their peril.”1 Or this one from The New York Times, “Will robots take our children’s jobs?”2

These stories paint a pretty dire picture of the future workforce. But the future for health care employees might be much more optimistic. Rather than replacing human workers, technology could help health care organizations create a more professionally satisfied workforce—by taking the robot out of the human.

Labor is a major part of health care costs. Among hospitals, labor is typically the largest line item in any hospital’s budget, and accounts for almost 60 percent of noncapital costs,3 on average, and costs are growing. Health plans and life sciences companies also employ many people, with a variety of jobs. Some of these are highly focused on complex and innovative work, but many of these have aspects that are routine and repetitive.

Health care jobs are evolving, and they are likely to change even more as technology removes some of these routine and repetitive tasks. We recently held a Dbriefs webcast to explore how emerging technologies could impact the workforce at hospitals, health plans, and life sciences companies.

The term “no-collar workforce” is used to describe a strategic combination of humans and machines that results in enhanced performance and drives greater efficiencies. Another way to think about this is how to take the robotic (routine, repetitive) functions out of the jobs now performed by humans.

What kinds of technologies are we talking about?

The rise of technology can transform what work is done and how it is accomplished:

  • Robotic process automation (RPA): The performance of repetitive, rules-based tasks facilitated by software that sitson the desktop.
  • Cognitive automation: The situation of human thought processes in the way of a computer or device appraoaches a problem.
  • Natural language processing: The application of cognitive technologies to analyze large volumes of unstructured text.
  • Machine learning: The ability of a computer or device to use experience to improve its abilitieswithout a human adding data or code.
  • Artificial intelligence: The ability of a computer or device to simulate human intelligent behaviour as it senses and interatcts with its environment to carry out a task.

The spectrum in the chart above starts with robotic process automation (RPA), which is the easiest cognitive technology to implement. It is effective for high-volume, repetitive, rules-based tasks. Users can see a relatively quick payback in the form of reduced costs, which is an important goal for many organizations.

Moving along this spectrum, there are increasing levels of intelligent cognitive automation, which can help handle less structured data and more complex activities. Natural language processing is where a machine learns to read and pull relevant information from documents. This technology could help streamline processes related to contracts with providers, employers, health plans, or suppliers. Software, for example, can extract information from very lengthy documents to develop insights.

Machine learning is used when there are large amounts of data, and the machine learns the best way to process it. This technology also begins to understand various data formats. It also can learn from humans about how to respond to different scenarios. Finally, artificial intelligence is the ability of machines to behave in a way that imitates intelligent human behavior.

Robots could make us less robotic

Here is an overview of how these technologies could impact the workforce of the future for health care and life sciences companies:

Health plans: These organizations are adopting technologies across the entire automation spectrum—typically starting in the shared-service areas. For RPA, adoption is happening in finance areas that have many high-volume repetitive activities, such as monthly journal entries to update the general ledger. Another area for automation is in human resources operations, which might include managing the leave-of-absence process for employees.

Often, health plans will use these technologies for back-office functions, such as enrollments, billing, and claims processing. The goal is to reap the benefits of core operational areas by automating those processes and freeing employees from mundane tasks such as data entry and reconciliation. Staff members should then have time to conduct insightful analyses. They also can focus on improving the customer experience by spending more time taking care of members. For many employees, this is what they really want to be doing.

We also are seeing some activity around machine learning. This technology can help health plan leaders understand how their employees and customers are interacting with the organization. Machine learning could, for example, anticipate a member’s needs and offer suggestions to customer service representatives as they are talking to members, or even to providers who are interacting with the health insurer. Machine learning could also allow brokers and sales agents to offer real-time quotes when interacting with potential customers.

Health systems: Some health care providers are beginning to take advantage of technology to transform their workforce in big and small ways. Like health plans, providers are using RPA for functions such as revenue cycle, but we also are starting to see it used in care delivery.

While about 90 percent of registered nurses say they are satisfied with their career choice, one out of three are unhappy with their current job, according to a survey of 3,400 nurses conducted by staffing firm AMN Health Care.

Clinicians typically spend about a quarter of their work day completing tasks that are not critical to patient care. That means they often can’t respond quickly to call buttons. Using artificial intelligence, Deloitte worked with clients to revolutionize the nurse call button. Patients can speak to the device and explain what they need (e.g., medication, help getting to the restroom). The patient receives an immediate response to the request, so they know that it has been heard. Critical details are smart-routed to the care team, including the priority and urgency of the requests.

This smart call button can change the way the clinicians’ work is processed, and it reduces or even eliminates some tasks. This can give clinicians more time to spend caring for patients, which should help improve patient experiences and outcomes.

Life sciences companies: Finance is certainly an area where we are seeing adoption, but life sciences companies are also building Centers of Excellence and are looking at use cases across the spectrum, including supply chain, research and development (R&D), and commercial. Examples in R&D include protocol development, the cognitive analytics to comb through all published and proprietary data to build a protocol for clinical trials, as discussed in Deloitte’s recent research. Life sciences companies can use natural language processing to build clinical study reports.

In the manufacturing supply chain area, we see use cases for emerging technologies in quality control and assurance. Some medical device companies, for example, are looking into how augmented reality could be used to train people to use their products.

On the commercial side of the business, applications of these technologies could be used to set reimbursements for 340B validation. Cognitive automation could help avoid ineligible payments.

Can technology improve job satisfaction?

I think all of these examples are exciting. While we are not seeing wholesale changes to jobs yet, removing routine and repetitive duties should help to make people happier in their professional lives. I predict that the use cases and adoption of these technologies will accelerate over time, and will eventually change not just what people do in their jobs, but also the types of careers people will have in life sciences and health care.

As Maureen Medlock, one of our speakers on the webcast, said, “I would challenge leaders to shift their mindset. Instead of focusing on questions like, ‘how can we hire and retain more employees to combat labor shortages?’ [they should] instead ask, ‘how can we automate and innovate so that high-performing people would not want to work anywhere else?’”

Despite recent articles, I don’t expect robots are going to push us all out of the workforce, but I do think emerging technology could help remove some of the more tedious elements of our jobs. I hope that the adoption of technology will lead to happier health care clinicians and administrators, happier and healthier patients, and less expensive and more efficient care.






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Sarah Thomas

Sarah Thomas

Managing Director | Center for Health Solutions

Sarah is the managing director of the Center for Health Solutions, part of Deloitte LLP’s Life Sciences & Health Care practice. As the leader of the Center, she drives the research agenda to inform stakeholders across the health care landscape about key trends and issues facing the industry. Sarah has more than 13 years of government experience and has deep experience in public policy, with a focus on Medicare payment policy.