Healthcare teams depend on electronic health records (EHRs) to compile important medical data from innumerable lab tests and medical devices, observations, treatments, and diagnostic codes. They rely on it so much they we consider the EHR to be a team member.
But in fast-paced critical care units, where even small errors can have big consequences, this digital team member can overload physicians with information. The sheer volume of data in EHRs creates a staggering challenge in complex environments such as intensive care units (ICUs) and emergency medicine departments. Individual clinicians may have to sift through more than 50,000 data points to find key information. This proliferation of data (both meaningful and meaningless) and the workload created by EHR systems have been key drivers of clinician burnout and, paradoxically, introduced new threats to patient safety. What is more, relying only on EHR data greatly limits the insights derived from artificial intelligence algorithms or big data analytics.
Mayo Clinic, the nation’s second-largest critical-care provider in the United States, with nearly 350 beds in 15 intensive care units (ICUs) across its campuses in Minnesota, Arizona, and Florida, decided to combat the data deluge with ambient intelligence: A set of decision-making tools powered by data on, and insights into clinicians’ goals, work environments, strengths, and performance constraints. When layered on top of existing information infrastructure, ambient-intelligence applications can cut through the clutter and deliver the right information in a digestible form that clinicians can use, quickly and effectively, at the patient’s bedside.
A multidisciplinary team of clinicians, researchers, and experts in clinical informatics to design and test information-technology tools that can help, rather than hinder, clinical care was created. The ambient-intelligence approach adopted prioritized a deep understanding of clinicians, the way they work, and the environmental factors they face. A NASA Task Load Index identified clinicians with a very high mental, or cognitive, workload who continuously have to filter important information out of the cluttered environment.
Subsequently, over a two-year period, 1,500 interviews were conducted with clinicians from Mayo Clinic ICUs nationwide. These insights identified that, out of tens of thousands of pieces of data pouring through EHR, roughly only 60 pieces are crucial patient information that clinicians needed to access quickly and easily for effective care. This information included both expected data points, such as blood pressure and medications, as well as less-obvious but critical information such as cough strength or previous difficulty with endotracheal intubation.
A better way to deliver the crucial information to clinicians at the point of care was needed. An EHR interface for clinicians in the ICU called Ambient Warning and Response Evaluation (AWARE) was built, which was introduced in ICUs in Rochester, MN, in 2012, and in campuses in Phoenix/Scottsdale and Jacksonville, FL, in 2014. A rules-based, ambient-intelligence application, AWARE filters out meaningless data and delivers context-specific, high-value information to clinicians in real time. It contains more than 1,000 rules that run continuously through data, and enriches it with insights from clinicians and patients. Data is organized around familiar clinical concepts needed for timely and accurate decision-making.