Rationale / Objectives
Caring for cricially ill patients in hospital intensive care units is demanding. Integrating information and data from multiple sources including continuous patient monitoring equipment, electronic health records, verbal commands and other sources is challenging for providers especially at critical moments of decision-making. Many existing EHR systems do not incorporate specific solutions for Critical Care Units due to problems with interoperability. This can lead to a lack of relevant information during critical episodes of care. NTT Data and everis have initiated a joint project with the Andalusian Health Service and Virgen del Rocio University Hospital in Seville, Spain to develop a new medical analytics solution technology, ehCOS SmartICU, designed to improve processes of care in intensive care units (ICUs), with the objective of reducing patient morbidity, mortality and adverse events.
Project/Program Description & Major Achievements
Predictive technology with real-time alerts was developed and piloted tested in 2016 for the care of 147 critical patients from three intensive care units at the Virgen del Rocio University Hospital in Seville, Spain. More than a 10% reduction in time spent managing clinical information has been achieved to date. In addition, over 95 providers in three ICUs are using the technology and 70% of users report that the system is easy to use.
The team identified data management and reporting as a major obstacle to workflow. Change management was crucial to ensure that all data is captured electronically going forward by healthcare professionals. While the technology is a key enabler, collaboration between the clinicians, the hospital’s innovation group and IT staff, and NTT DATA’s data scientists and IT team is critical to success.
People / Organizations Involved
The Virgen del Rocio University Hospital in Seville is one of the largest health centers in Spain and the largest hospital complex in the Andalusian public healthcare system. With over 8,000 staff, the hospital serves a population of greater than 500,000 in the province of Seville. A technology solution has been jointly developed over a one-year period based on algorithms that provide healthcare staff with a tool for predicting outcomes and generating alerts to make real-time personalized clinical decisions to support ICU patients. The team identified data management and reporting as a fundamental obstacle at the outset of the journey to developing the technology. Incorporating information captured manually (e.g., nurse-captured hourly vital signs) in addition to electronically was critical. The teams thus spent a significant amount of time on data discovery, integration, reporting dashboard designing and customizing. At this stage of the ehCOS SmartICU pilot test, the data and biosignals from 156 different devices, including monitors, ventilators and infusion pumps from various manufacturers have been integrated into a single interface to increase accuracy in capturing data from monitored patients. Relationships among vital signs and treatment protocols are being studied to design and predict future scenarios in the care of patients in Intensive Care, Critical Care and Resuscitation units. Expansion to other hospitals in Spain and Latin America is anticipated in the near future.
More than a 10% reduction in time spent managing clinical information has been achieved to date. In addition, over 95 providers are using the technology and 70% of users report that the system is easy to use. Validation of the predictive algorithms with hospital collected data will be conducted in the near future. A mobile alert system will also be developed to let clinicians know if a patient is in danger of a serious complication.
- A new big data predictive analytics solution for the healthcare industry
- everis and NTT DATA announce a joint project with Andalusian Health Service and Virgen del Rocio University Hospital to develop a Predictive Analytics Solution to improve the Care Process for Acute Patients in ICU
- Real-Time Data Analysis at the Point of Care in the ICU