Reducing Healthcare-Associated Infections using an Infection Control Network

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Project Summary Healthcare-associated infections (HAI) are often caused by multidrug-resistant organisms (MDROs). MDROs are a growing epidemic associated with significant morbidity, mortality, and cost. An essential strategy for mitigating this epidemic is to prevent transmission of MDROs through infection control precautions. These measures can be implemented only if healthcare providers are aware - early on - that a patient is known to have a previous or new MDRO infection. Currently, recognition of MDROs occurs independently at each hospital: providers manually review patient records for a history of MDROs. Information is rarely shared between facilities, and recognition is limited to facility-level surveillance; regional population surveillance does not exist. There is no way to know if a presenting patient had an MDRO diagnosed at another institution. This leads to a delayed or unrecognized need for infection control precautions, perpetuating transmission of MDROs. Population surveillance is needed to improve recognition of patients with MDRO infections and to facilitate population-level studies; regional clinical decision support (CDS) is needed to more effectively prevent transmission of healthcare-associated MDROs. Biosurveillance using a health information exchange (HIE) can fill these gaps. Our goal is to reduce healthcare- associated MDROs by creating a regional electronic infection control network. The objective of this network is to provide surveillance and CDS for organizations in an HIE and establish a platform for population-level studies. The central hypothesis is that a regional infection control network will improve the ability of each institution to quickly identify MDRO infections and to implement interventions to prevent transmission. A previous project has proven the effectiveness of a MRSA-specific infection control network to reduce HAIs. We will build upon this success to develop software to process microbiology reports coming into our HIE in order to 1) identify patients with seven different MDRO infections, and 2) implement CDS. We will evaluate the accuracy and effect of the network in reducing healthcare-associated MDROs, and its ability to facilitate population-level studies of MDRO infections. We believe that this project is innovative because it leverages an HIE to provide automated surveillance of healthcare-associated MDRO infections and deliver CDS across multiple institutions. The project is significant because it improves recognition and control of HAIs by automating identification of healthcare-associated MDROs and by providing CDS alerts to ensure timely ordering of infection control interventions.