Systems Modeling & Optimization
Malone researchers model and evaluate processes and systems related to health care. Working with clinicians, they aim to understand complex interactions between patients and caregivers, streamline hospital operations, enhance patient safety, and inform organizational strategies and policy-making.
Ayse P. Gurses
PI: Scott Levin, Jeremiah Hinson
Funded by a $2.45 million grant from the Agency for Healthcare Research and Quality (AHRQ), the Connected Emergency Care (CEC) Patient Safety Learning Lab at Johns Hopkins will use systems engineering methods to reduce health and financial harm for ED patients, with an initial focus on patients with lower respiratory tract infections.
Patient safety is of particular concern in a fast-paced, high-volume emergency department setting. According to the project proposal, the research team plans to harness electronic health record (EHR) data to give clinical care teams real-time and predictive insights for patient care. The lab’s main objective is to mitigate problems caused by suboptimal diagnosis, treatment, and disposition (admission vs. discharge) decisions using advanced data science methods and EHR-integrated clinical decision support (CDS).
With these tools, the team will establish a connected (closed-loop) emergency care system that aims to make patient care safer, higher quality, and more affordable.
PI: Kimia Ghobadi
The goal of this project is to design radiation treatment plans that deliver a high enough radiation dose to the tumors that eradicate cancer cells, but still spares healthy tissue as much as possible.
PI: Anton Dahbura
Older patients are highly susceptible to the extreme physiological stresses of major surgery and the harmful effects of post-surgical bed rest. Preliminary studies show that physical conditioning prior to surgery, often called prehabilitation, can provide significant benefit to patients including reduced complications, shorter recoveries, and lower costs. However, results have been mixed, largely due to poor measurement and compliance.
Our team has developed a platform to collect data from wearable activity monitors in combination with displaying feedback to patients on existing smartphone technology. In this study, we will focus on elderly patients undergoing major abdominal colorectal surgeries to
- determine if activity feedback impacts overall pre-surgical activity levels
- determine the association between frequency, duration, and timing of pre-surgical activity and clinical outcomes
News | Systems modeling and optimization
The Connected Emergency Care (CEC) Patient Safety Learning Lab at Johns Hopkins will use systems engineering methods to reduce health and financial harm for ED patients, with an initial focus on patients with lower respiratory tract infections.
Algorithm helps medical offices to schedule reminders and fill vacant appointment slots with patients who urgently need to be seen.
Prof. Siddqui’s funds will be used to create mathematical models to help predict learning, decision-making, and gaming for a variety of societal systems.