Omnia Health is part of the Informa Markets Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

IT automation and healthcare: a golden union

Article-IT automation and healthcare: a golden union

How AI and robots can act as problem-solvers for the sector without disrupting human touch.

The global pandemic has brought to light one of the most important intersects – the one between healthcare and technology. Technological innovations such as artificial intelligence (AI) and robots can solve many of the challenges that exist within the healthcare sector today. However, it is important for healthcare IT automation to be embraced at both a societal and governmental level while ensuring mindful implementation that safeguards human touch.

Breaking down healthcare’s five main challenges

AI and robotics automation are most impactful when optimised to solve specific problems. Here are the five main challenges facing the healthcare sector, for which automation may be a good solution:

  1. Human rights/access: While many consider healthcare to be a human right, millions around the world either don’t have access to good healthcare or have compromised access (see next point).
  2. Financial: Healthcare can be expensive – both at an individual and governmental level. Since healthcare expenditures rise at a faster rate than gross domestic product (GDP) growth, some national governments risk bankruptcy when trying to provide adequate healthcare to entire populations using taxpayer funds.
  3. Patient safety: According to a John Hopkins Medicine research article, prior to COVID-19, the third-highest cause of death in the U.S. was due to medical errors. Most of these resulted from systemic problems, including poorly coordinated care.
  4. Worker retention: Retaining healthcare professionals is increasingly challenging for hospitals and other clinical facilities. One study states 43 per cent of nurses are considering leaving their profession to work elsewhere in the healthcare sector.
  5. Workflow consistency: Healthcare workers have less automated workflows when compared to front-line workers in other sectors. In fact, nurses have said they spend less than half their time with patients due to heavy administrative tasks, which delays relaying critical patient information to other care team members.

AI use at a clinical and operational level

While all these challenges seem daunting, the good news is the strategic implementation of technology can address many of them simultaneously. For example, on a clinical level, AI can be leveraged for drug discovery to accelerate processes and the testing validation of certain pharmaceutical products. Radiologists can use AI to detect patterns in X-Ray and magnetic resonance imaging (MRI) images the human eye may not see to study large data sets more rapidly. It can also be utilised for clinical diagnosis. One of the most serious patient health threats inside a hospital is an infection of the blood known as sepsis. AI can help anticipate the occurrence of sepsis to give nurses an eight or nine-hour head start on treatment, which can help save lives.

From an operational standpoint, AI can help healthcare providers better manage resources to improve care capacity. Even before COVID-19, one of the main issues hospitals faced was having too many patients and not enough beds. Hospitals must remain efficient if they want to treat as many patients as possible. Based on data sets, AI can predict how long surgeries will take and then, five to 10 minutes before the surgery is over, send automated machine-to-machine notifications to alert support staff to prepare for room turnover.

AI integrations can also help improve operational connections between the many different Internet of Things (IoT) devices used in clinical environments. For example, the average hospital room has four or five smart medical devices monitoring patients in real time, all of which need to be constantly monitored to ensure optimal performance. Wouldn’t it be nice if hospital staff could receive a reminder notification on their mobile devices to routinely check equipment, just as they would to ensure proper medical supplies stocking for each room?

There is also an opportunity to extend the robotics automation solutions traditionally used in supply chain environments all the way to last-mile healthcare facilities. Hospitals are immense buildings with equipment and supplies stocked all over the place. Rather than removing staff from patient rounds to retrieve inventory, robots can be mobilised to provide nurses and doctors with the right products at the right time and location. If patient A needs medication Y, a robot can go down to the pharmacy to collect it and deliver it to the patient so the staff can focus on more imperative tasks.

What does the future hold?

The healthcare community is starting to make headway with AI-based automation integrations. But how will it evolve in the next five to 10 years?

Staff scheduling is one area where further development is expected. Currently, AI applications are well equipped to offer automated nurse scheduling solutions that achieve the right workload balance (i.e., when hospitals should schedule extra nurses and when a decreased staffing level is sufficient). In the future, this solution will be used across the whole care continuum (not only for nurses) to establish a more mobile and flexible clinical team model, with scheduling based on real-time and forecasted demand.

Efforts will also be made to boost communication between robots and front-line workers. Equipping these machines with enhanced intelligence, so they can monitor product availability, provide adequate substitutes, and foresee fulfilment challenges, will transform robots from a mere courier service to the nurse’s second brain.

There is also an opportunity to merge the capabilities of AI and robots. As mentioned before, one of the key challenges for the healthcare sector is an abundance of information and data. If we combine their respective strengths of analysis and mobility, AI can give robots the correct data and instruct them on the best next action to take – similar to how AI is used to guide front-line workers’ actions today. Embracing robots capable of independent decision-making in the course of care gives nurses the freedom to provide more personalised, attentive care to each patient. This, in turn, helps ensure one of healthcare’s founding values remains: the value of human touch.

Chris Sullivan.jpg

Chris Sullivan

This article appears in the latest issue of Omnia Health Magazine. Read the full issue online today.

Hide comments


  • Allowed HTML tags: <em> <strong> <blockquote> <br> <p>

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.