The development of these tools was inspired by the realization that traditional methods of caring for wounded service members in conflicts in Iraq and Afghanistan were not working as well as they could—despite advances in technology such as body armor, tourniquets, and rapid clotting. After examining the processes (joint casualty management) and the rates of wound failure in service members, we were motivated to develop an enhanced decision-making tool that would help the critically wounded.

SC2i Clinical Decision Support Tools




Invasive fungal infections (IFI) are devastating and threaten both life and limb. Typically, rare in immunocompetent individuals, IFI have developed with remarkable frequency in severely combat-injured patients, particularly those sustaining multi-system blast trauma with associated abdomino-pelvic injuries, multiple amputations, and/or requiring massive early life saving transfusions.  Despite the high survival rate of our wounded warriors from the current conflicts, some such patients have succumbed to these aggressive infections after reaching military medical centers. Surviving patients have complex, morbid clinical courses frequently requiring multiple additional procedures and proximal migration of amputations, with high associated complication rates. Using a large database of combat-injured personnel, we have developed Clinical Decision Support Tools to allow early IFI risk stratification at either the in-theater or medical center echelons of care; these tools were subsequently externally validated utilizing a separate, similar database. These tools can facilitate the early diagnosis and aggressive prophylactic local and systemic treatment of patients at high risk for IFI, which we believe is critical to mitigate IFI-associated morbidity and mortality.


The decision to activate a massive transfusion protocol is both complex and time sensitive. It requires not only an urgent assessment of a critically injured patient's physiology but also must take into account issues of resource availability and utilization. Oftentimes, little empiric data is available rapidly enough to assist the bedside clinician and therefore this key decision is often left to the instincts of the treating team. Several published tools use manual calculations that are either too complex, making them of little use in real-time, or too simple, making them not accurate enough to be truly useful. Fortunately, technology allows us to bring sophisticated computers in the form of smart phones to the bedside to assist in these complex decisions. A mobile application designed to take simple physiologic data available to the clinician within minutes of patient arrival and create an extremely accurate prediction of the need for urgent massive transfusion has been designed using data from over 10 years of patient care in a busy urban trauma center. This application is currently being studied prospectively to understand if it will be a useful Clinical Decision Support tool.

Artificial Intelligence Sepsis Expert

*Live in civilian sector and in process for the military health system


Damage Control Laparotomy - Open Abdomen

The management of complex, contaminated abdominal wounds remains largely dependent upon the experience and judgment of the surgeon. This may result in either the premature closure of abdominal wounds destined for clinical failure or performing additional procedures on wounds well beyond the window necessary for successful closure. There is therefore a need for a standardized process to determine the best method for achieving expedient and successful definitive closure of abdominal fascia. We are designing a Clinical Decision Support tool that will provide the necessary objective criteria for predicting successful abdominal closure after damage control laparotomy. This could potentially help us achieve delayed fascial closure during the same hospital admission when it can be accomplished safely, while avoiding the complications of multiple unsuccessful attempts to do the same. This might also optimize the chance of a successful planned staged ventral hernia. The ultimate goal is to improve outcomes while reducing costs for hospitals and victims of traumatic abdominal injury.


Blast injuries and other combat-associated wounds present unique challenges to healthcare enterprises. We found that a comprehensive biological assessment, coupled with advanced mathematical techniques, can be used to generate a predictive model that may help surgeons improve outcomes by minimizing wound-related complications. This translates to shorter hospital stays, quicker rehabilitation, and lower costs. We then distilled the prognostic information into a Clinical Decision Support tool called WOUNDx™, which uses common inflammatory markers coupled with clinical observations to estimate the likelihood of wound failure in complex wounds. This highly predictive algorithm can help surgeons identify when to close or otherwise cover wounds in high risk military and civilian populations.