We are excited about our current body of work and want to share project insights. For more information, questions about our work, or to share ideas, please contact us.
The Lab Projects
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Evaluation and Validation of a Mobile Application for Patient Functional Assessment in Spinal Surgery
By developing a composite score algorithm based on wearable collected data, this project assesses the functional status of patients with lumbar degenerative spine disease.
Project Lead: Camilo Molina
- Big Ideas
active
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Care Transition TRUST; Trust Through Understanding via Smart Use of Technology
The team is working to determine the feasibility and effectiveness of using an iPad within BJC hospitals to allow a video conversation among patients, their caregivers, their PCP, and the hospitalist involved in their inpatient care.
Project Lead: Mark Williams
- Big Ideas
active
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Expediting Radiotherapy Initiation via a Simulation Free Workflow
This project investigates the feasibility of a simulation-free workflow to enhance clinical decision-making with up-front planning on diagnostic images.
Project Lead: Tianyu Zhao
- Big Ideas
active
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Avoiding Pulmonary Complications after Major Abdominal Surgery Using Novel Digital Incentive Spirometry Technology
In an effort to reduce postoperative pulmonary complications, the team is working to determine the efficacy of perioperative incentive spirometry to improve forced expiratory volume (FEV1).
Project Lead: Chet W. Hammill and Chenyang Lu
- Big Ideas
completed
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Prediction of Persistent and Profound Intraoperative Hypoxemia in Pediatric Patients to Mitigate Life-Threatening Events and Improve Patient Safety
The team worked to detect intraoperative hypoxemia within the Epic electronic medical records and assess the clinical meaningfulness of the Deep Intraoperative Alert system.
Project Lead: Michael C. Montana and Thomas Kannampallil
- Big Ideas
completed
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Using Mobile Health Technology to Capture Physical, Functional, and Psychosocial Features that Predict Recovery after Lumbar Fusion
This project uses intensive psychometric and biometric data to define how different disease domains impact patient recovery from lumbar fusion surgery.
Project Lead: Wilson Z. Ray and Jacob Greenberg
- Big Ideas
completed
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User-Centered Design of a Digital Health Solution to Improve Symptom Management in Advanced Cancer Care
By conducting user evaluations of the current ENVISION prototype, the team is working to create a functional version of the ENVISION tool to assist caregivers in the assessment and management of advanced cancer patients.
Project Lead: Karla T. Washington
- Big Ideas
completed
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Clinical Translation of a Device and System for Preventing the Development of Pressure Ulcers
This project demonstrates the feasibility of a pressure sensor device to record skin pressure and prevent pressure injuries in ICU patients.
Project Lead: Amanda Westman and Justin M. Sacks
- Big Ideas
completed
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Development of Predictive Analytics Model for Need of Extracorporeal Support in COVID-19
By developing a machine learning, predictive-analytics model, this COVID-19 Big Ideas team identified variables associated with the need for ECMO in pediatric COVID-19 patients.
Project Lead: Ahmed Said
- Big Ideas
completed
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Integrating Real-Time Clinical Activity, Physiological Sensors, and Behavioral Responses for Predicting Physician Burnout (IGNITE)
In an effort to predict and reduce physician burnout, the team used advanced machine learning to measure physician workload and its association with burnout and medication errors.
Project Lead: Sunny Lou
- Big Ideas
completed
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Integration of Artificial Intelligence (AI) Based Cognitive Behavioral Therapy (CBT) with the Electronic Medical Record (EMR), and Effectiveness Comparison to In-Person CBT
Using AI-based Cognitive Behavioral Therapy, this project generated an effective point-of-contact electronic medical records notification to alert clinicians when a patient shows concerning anxiety or depression symptoms.
Project Lead: Abby Cheng
- Big Ideas
completed
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Impact of Glucose Variability on Dynamic Cognitive Function in Youth with T1D
Focusing on youth with Type 1 diabetes, the team optimized an existing smartphone app that will test dynamic cognition of these patients.
Project Lead: Tamara Hershey and Mary Katherine Ray
- Big Ideas
completed
