Memorial Hermann was named a 2018 HIMSS Davies Enterprise Award recipient for leveraging the value of health information and technology to improve outcomes. The three award-winning use cases cover improving early identification of sepsis, decreasing patient falls through clinical decision support tools in the electronic health record, and improving quality outcomes by addressing care gaps.
The ability to identify sepsis earlier plays a key role in improving and sustaining future outcomes. Memorial Hermann Health System implemented a technological footprint which encompassed an electronic version of the sepsis bundle so it could be included in the clinicians’ electronic workflow. This allowed for more seamless extraction of data needed for reporting and managing process measures around bundle compliance.
Clinical decision support (CDS) can improve safety, quality and cost-effectiveness of patient care – especially when implemented in computerized provider order entry (CPOE) applications. Medication-related decision support logic contributes to a large component of the CDS logic in the CPOE system. Memorial Hermann used CDS in the form of order sentences and alerts to limit the ordering of these medications for the elderly patient population. The EHR’s ability to add filters for age and conditions, as well as dose range checking alerts, improves the automation and reliability of the CDS alerts. This technology, combined with the HRO practice of conducting daily safety huddles and rounding, led to Memorial Hermann’s achievement one of the lowest fall injury rates in the nation.
Memorial Hermann Health System developed a robust population health data warehouse platform to support system efforts in utilizing multiple data sources, including claims and electronic medical records. This helped construct a comprehensive view of patients and facilitate subsequent closing of gaps in care. Additionally, the organization implemented tools to facilitate tracking and completion of registry gaps and HCCs, as well as the reporting, analyzing and visualization of data.