Data Products that Make a Difference.

Whatever it is, the way you tell your story online can make all the difference.

It all begins with an idea. Maybe you want to launch a business. Maybe you want to turn a hobby into something more. Or maybe you have a creative project to share with the world. Whatever it is, the way you tell your story online can make all the difference.

Process Control Analysis

I’ve developed interactive R Shiny applications to monitor and improve trauma care processes using the qcc package for statistical process control (SPC). The tools visualize key metrics in real-time, enabling quality improvement in clinical settings.

Example scenarios include:

  • Pain Scores Post-Surgery: Tracking pain score trends to detect deviations and optimize postoperative care.

  • TQIP Benchmarking: Monitoring mortality rates or complications against Trauma Quality Improvement Program (TQIP) benchmarks.

  • Length of Stay (LOS): Identifying outliers in hospital LOS for trauma patients to improve resource allocation.

  • Infection Rates: Detecting spikes in post-surgical infections to trigger interventions.

    Explore the Demo App (#) | Learn More (/trauma-analysis/process-control)

Prehospital Modeling

The prehospital modeling project delivers a machine learning-based model to predict blood transfusion needs in trauma patients, optimizing resource allocation in military and civilian settings. Using vital signs, injury characteristics, and DoDTR data, our model achieves high sensitivity for timely interventions.

Applications include:

  • Prehospital triage for combat casualties.

  • Blood inventory management in trauma centers.

  • Integration with real-time decision support tools.

    View PHBLOOD Case Study (#) | Learn More (/trauma-analysis/phblood)

Real-Time Dashboards

I’ve created dynamic, OMOP-compliant trauma registry dashboards using R Shiny and cloud platforms (e.g., AWS) to provide real-time insights for clinicians and commanders. These dashboards visualize key metrics like injury severity, transfusion rates, and outcomes, supporting:

  • Situational awareness for Combatant Commanders (e.g., DHA, JOMIS).

  • Quality improvement in civilian trauma centers (e.g., TQIP reporting).

  • Research-ready datasets for epidemiological studies.

    See Dashboard Example (#) | Learn More (/trauma-analysis/dashboards)

AI-Driven Triage Tools

Building on our APPRAISE-HRI algorithm (published in Shock, 2023), we develop AI models to prioritize trauma patients based on vital signs and injury data. These tools enhance triage accuracy in high-pressure settings, offering:

  • Automated risk stratification for hemorrhage or mortality.

  • Decision support for medics in austere environments.

  • Integration with electronic health records (EHRs) for seamless deployment.

    View AI Triage Case Study (#) | Learn More (/trauma-analysis/ai-triage)

Clinical Trial Reporting

Building on our APPRAISE-HRI algorithm (published in Shock, 2023), we develop AI models to prioritize trauma patients based on vital signs and injury data. These tools enhance triage accuracy in high-pressure settings, offering:

  • Automated risk stratification for hemorrhage or mortality.

  • Decision support for medics in austere environments.

  • Integration with electronic health records (EHRs) for seamless deployment.

    View AI Triage Case Study (#) | Learn More (/trauma-analysis/ai-triage)