We hear all the time about the ways data and artificial intelligence (AI) are helping improve our lives – everything from finding the best route through traffic to helping us make investment decisions tailored to our goals and situation. These little improvements in our day-to-day are certainly convenient, but the impact of data-driven technologies in healthcare is transformational. AI and machine learning (ML) are already changing care delivery in acute care and senior care settings, with even more astonishing developments on the horizon for those giving and receiving care.
Data-driven healthcare in hospitals
In some cases, hospitals are moving to place data at the centre of patient care and safety, particularly through the use of location technology – commonly called real-time location systems (RTLS). These systems allow for more efficient inventory management by using barcodes to associate items used in a procedure with a patient and a place. Ultimately, the goal is to increase safety, reduce costs, and free up clinician time for patient care.
Many healthcare providers are now building on that foundation to automate aspects of this process and proactively place information into the hands of carers. Take, for example, the critical task of locating mobile medical equipment for a patient procedure. By leveraging active location technology, carers are enabled to quickly find a piece of equipment and see whether it’s clean and ready for use.
Active tags are placed on key equipment, with location and status updated in real-time even as the item moves about the hospital. No human intervention needed. This visibility is especially important during a crisis like COVID-19 when every piece of equipment – ventilators, infusion pumps, telemetry packs, etc. – is desperately needed.
This technology is also being used by healthcare providers for other applications, such as automated environment monitoring of refrigerators and freezers storing pharmaceuticals, vaccines, blood products, and more. Active tags provide 24/7 monitoring and alerting of changes in conditions that could lead to loss or damage of the stored materials. Over the past year, healthcare workers have been increasingly stretched, facing burnout as they’ve dealt with a much greater number of patients. Data provided by RTLS solutions can reduce the time carers spend on manual checks and increase time spent on patient care.
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But this is just the beginning. Real-time data and alerts provided by devices such as active tags are incredibly useful for rapid response to events and in-the-moment decision making, but the deeper value is in understanding long-term trends. What’s the optimum number of infusion pumps for each ward so that clean devices are always available… but also in use as much of the time as possible? Answer that, and you both maximise efficiency of your capital fleet and drive patient safety. Analysing trends of this kind allows hospitals to move beyond rapid response and build resilience in their processes that make emergencies less likely.
In truth, healthcare providers may have had this data at their disposal for some time, but limited means of leveraging it beyond immediate alerting. However, with advances in AI, we finally have the tools to move to true predictive analytics. We’re seeing products enter the market that can actually generate alerts based on observed patterns before something bad happens, allowing carers to take action to prevent an emergency.
Data-driven healthcare in residential settings
While the value of such preventative systems in hospitals is clear, for residents in care homes, this added protection can also help increase the quality of care given. Predictive technology such as the Foresite solution can indicate to carers where their attention is needed the most and which residents are at greater risk. This kind of technology monitors subtle changes in a senior’s health and can accurately predict events like falls, which allows intervention prior to an event occurring. Technology like Foresite can also flag heightened risk for heart conditions, urinary tract infections (UTIs), and other infections, allowing earlier assessment and intervention that might well prevent a trip to the hospital.
For carers, this technology could help eliminate the anxiety of guesswork and free up time to spend where needed the most. In a time when we have an aging population and a shortage of carers, data-driven insights of this kind will be invaluable in the effort to provide care for all who need it and improve working conditions for those employed in the sector. Their value has never been more apparent than in this past year. Now it’s time for healthcare leaders to invest in data-driven technologies to help those who serve as the backbone of the industry: carers.