OBJECTIVE: Develop an antibiotic clinical decision support (CDSS) system to improve treatment for critical care patients with severe infections. The system will provide recommendations to critical care providers in the intensive care unit (ICU) on antibiotic dosing based on multiple patient factors, including weight, infection source, infectious agent, cultures, susceptibilities, and prior treatments. The final system will include the ability to be configured to the unit"s specific antibiotic regiments, characteristics, and anti-biograms and will also integrate with hospital information technology (IT) infrastructure. DESCRIPTION: Many military casualties survive the first few days of burn and trauma resuscitation and surgeries only to fall victim to an infection and sepsis. Intensive care for these casualties is complex, requires treatment of systemic and often multiple organ systems at a time and is highly error-prone. Permanent morbidity or death results when the right care is not delivered or is delivered too late. Evidence-based best practices are published, but yet not implemented in step by step detail at the bedside due to complexity. Severe sepsis and septic shock have a mortality rate near 30% (1). Recent data has shown that computer based clinical decision support programs can greatly increase compliance with evidence based best practices, resulting in a 50% reduction in mortality for sepsis (2) and for initial empiric antibiotic therapy (3). Targeted antibiotic therapy is important for effective treatment of the organism and for avoiding highly toxic side effects of broad spectrum antibiotics and for avoiding increased pathogen resistance. However, choice of antibiotics often requires changing after susceptibility and cultures results are received. Burn casualties are particularly susceptible to multiple incidents of sepsis over a prolonged hospital stay. An antibiotic CDSS system is needed to quickly process a myriad of factors in determining the optimal antibiotic therapy for a patient at any given time throughout the hospital stay. This system should take into account not only empiric choice decisions but individualize dosages based on minimum inhibitory concentration (MIC) calculations. PHASE I: Develop an initial concept design and demonstrate elements of a CDSS software program providing specific antibiotic therapy guidance from initial diagnosis through discharge. Contractors should provide a basic software application that demonstrates a basic ability to process and make recommendations on potential antibiotic therapies. Contractors should explore novel approaches to implement antibiotic decision making as additional patient data is received. The clinical decision support system should include broad spectrum, narrow spectrum, and targeted antibiotic therapy. The CDSS system should provide new recommendations when susceptibility and culture results are received. The system should include MIC calculations. The contractor will conceptualize a graphical display showing the infection status and antibiotic therapy from initial infection diagnosis to discharge. PHASE II: The contractor will further develop and demonstrate the CDSS and will optimize bedside workflow. The contractor will demonstrate input clinical data IT integration with the hospital IT system for at least one variable. The contractor will develop and demonstrate a graphical representation of infection status and antibiotic therapy from initial infection diagnosis unto discharge. The successful clinical decision support program will allow physicians to adjust antibiotic therapy and will be easily adopted by the bedside caregivers. PHASE III: The contractor will produce a working CDSS system capable of updating antibiotic decisions by the medical director of a unit. The CDSS system should gather most of the input laboratory data through IT integration. The CDSS system should be configured so that multiple client computers, tablets, or smartphone device can access the system simultaneously. The final CDSS system must include evidence-based antibiotic therapy recommendations and an algorithm to optimize dosage for patients based on MIC calculations. Such a system could save lives by providing evidence-based, individualized, optimized antibiotic therapy for critical care patients throughout a hospital stay. Such a system should be of great commercial interest for all branches of the U.S. armed services as well as civilian critical care professionals in multiple critical care units.