Overview

About this study

In the developed world critical illness is routinely treated in an intensive care unit (ICU) by highly specialized physicians, nurses and support staff. This model of intensive care is spreading rapidly to low and middle income countries and as it spreads, challenges and limitations to this model arise. In resource-poor settings, inadequate human resources, training, and equipment all present barriers to safe and effective use of life-saving procedures. The advances in medical informatics and human factors engineering have provided tremendous opportunity for novel and user-friendly clinical decision support (CDS) tools that can be applied in a complex and busy hospital setting. Real-time data feeds and standardized patient care tasks in a simulated acute care environment have been proven to have a significant advantage of a novel interface (compared to a conventional) in reducing provider cognitive load and errors. Currently researchers within the investigator's research group have developed and are pilot testing a simple electronic decision support tool: CERTAIN (Checklist for Early Recognition and Treatment of Acute Illness). This tool has been successfully tested and validated in simulated settings and is being implemented as pilot study in 18 countries. Worldwide infant and early childhood mortality continues to be very high partly due to the inability to recognize and respond aggressively to critical illnesses. Investigators expect that adaptation of the algorithms from CERTAIN has potential to be a powerful tool to improve on the medical care of children in developing countries. Investigators aim in this project is 1) to develop a pediatric adaptation of CERTAIN (CERTAINp) and 2) to implement it into clinical practice in resource-poor settings and evaluate the impact of the tool on the processes and patient outcomes.

Participating Mayo Clinic locations

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