COVID-19 may have made clinician burnout even more of problem. AI could help by streamlining workflows.
A recent New England Journal of Medicine opinion piece called the dual challenge of fighting COVID-19 while preventing harm to the well-being of clinicians a “parallel pandemic.” The authors noted that an alarmingly high number of health professionals – 45% to 55% – were suffering from burnout prior to the pandemic, and now COVID-19 is putting increased strain on the healthcare workforce.
While pharmaceutical companies worldwide are working around the clock to develop a COVID-19 vaccine, I find myself wondering what it would be like if we could create a vaccine to cure clinician burnout. If we could, our physicians and nurses would have greater satisfaction and lower rates of anxiety, depression, substance abuse and suicidality. Patient satisfaction and safety would also improve.
However, in the absence of a burnout vaccine, it’s more important now than ever for hospital and health system leaders to take tangible steps to reduce clinician stress.
While healthcare leaders are powerless to control many of the factors fueling clinician stress during this time, they can take steps to address one of the biggest ongoing stressors facing clinicians: EHR usability. In a recent article published in Mayo Clinic Proceedings, researchers found a direct correlation between the usability of EHRs and burnout rates — and unfortunately, the usability of current EHR systems received a grade of F by physician users when evaluated.
As leaders look for solutions to improve EHR usability, an increasingly popular approach is to leverage the power of artificial intelligence (AI)-based technologies. However, when considering AI alternatives, it’s critical to look for solutions that relieve EHR pain points — and don’t add to clinician burden. In particular, clinicians need tools that streamline clinical workflows, provide patient- and problem-specific information at the point of care, enhance clinical decision-making and improve interoperability.
Clinicians often complain of inefficient EHR workflows that force users to click through multiple screens to find the right information. A physician ordering a lab test, for example, might first want to make sure the patient didn’t recently have the same test. This may require searching through multiple previous encounter notes and reports from other providers to confirm the patient’s history. If the doctor can’t easily find the right information, she might give up the search and simply order a new test. That additional test can be inconvenient or even unsafe for the patient, while also driving up healthcare costs.
Clinicians need relief from cumbersome workflows that are often exacerbated by an over-abundance of data that is difficult to access and interpret, especially at the point of care. While some AI solutions are designed to dump even more data into EHRs, what physicians really need are AI tools that streamline workflows by providing easy access to actionable information that enhances clinical decision-making at the point of care.
Rather than scrolling through a patient’s chart to find specific information, clinicians need AI tools that quickly provide access to the data they need, when they need it. For example, when a physician is examining a patient with diabetes, he needs a snapshot “diabetic view” of the patient that includes all of the diabetes-specific history. By minimizing the amount of time required to find information, clinicians are more productive and empowered to assess a patient’s condition.
To produce this patient-and problem-specific snapshot view, the technology must be able to quickly identify and interpret all the disorganized and complex arrays of information from multiple sources, such as previous encounters, lab reports and inpatient records. With AI-powered natural language processing (NLP) tools and AI clinical engines, unstructured clinical data can be converted to a structured format, giving users access to important information embedded within the free text fields. By leveraging the power of AI tools within existing workflows, clinicians have ready access to clinically relevant and high-value information that improves decision-making and patient care.
What clinicians don’t need is a bunch of algorithms to help them diagnose and treat every patient based on the information entered into the computer. Instead, they need solutions that support – rather than replace – clinical decision making.
An experienced physician can quickly diagnose a patient’s condition and recommend an appropriate therapy in less time than it takes to enter all the patient’s symptoms in the computer. With AI tools that enable the delivery of clean, actionable information, a physician is empowered to use the best computer in the exam room: her own brain.
With advancements in interoperability, clinicians are sharing more clinical data than ever before. Too often, though, the data is disorganized and difficult to interpret, especially at the point of care. To ensure clinicians aren’t drowning in data, we need AI-based filtering solutions to transform data into clean, usable information that can be quickly accessed at the time of need.
Amid this current COVID-19 health crisis, clinicians, as well as researchers and regulatory agencies , have a heightened need to share information about test results, pre-existing conditions, symptoms and therapies. Many hospitals across the country are experiencing surging patient loads, and overburdened clinicians can’t afford to spend hours a day manually searching through various databases to find critical details about underlying health conditions or medication histories.
By adding AI tools to existing clinical systems, healthcare leaders can improve EHR usability, allowing clinicians to remain focused on the delivery of safe and efficient patient care. These solutions can also make it easier for organizations to address regulatory requirements, such as their COVID-related hospitalization and mortality rates.
As the country and the world continues to fight COVID-19, healthcare leaders need to act now to preserve the well-being of health professionals. One way to provide relief is by incorporating AI-based solutions that improve the efficiencies of EHRs and reduce some of the stress and frustrations that fuel clinician burnout.
Jay Anders, M.D., is the chief medical officer of Medicomp Systems.