Gita Mody
University of North Carolina at Chapel Hill, NC·Medicine & Clinical Research·Early-career
Serious complications after chest (thoracic) surgery are common and lead to more hospital readmissions and deaths. Early warning signs often go unnoticed between scheduled follow-up visits until they become severe.
- Fields
Medicine & Clinical Research
Public Health & Epidemiology
- Topics
thoracic surgery
electronic patient-reported outcomes
ePRO
- Grants
- 1 known grant, through Dec 2026
What they work on
- Identify the optimal survey and alert features and clinic workflow for an electronic patient-reported outcome (ePRO) system that monitors symptoms after thoracic surgery.
- Identify barriers to routine use of postoperative ePROs in thoracic surgery clinics, using qualitative and mixed-methods implementation science approaches.
- Measure implementation and clinical effectiveness outcomes of postoperative ePROs in a prospective study of thoracic surgery clinics.
- Generate preliminary data to design a large randomized controlled trial of an ePRO system in cardiothoracic surgery patients.
More about the research
One possible solution is electronic patient-reported outcomes (ePROs). These are automated systems that send symptom surveys to patients at home and alert care teams when an answer is concerning. In cancer care, ePROs have improved quality of life and survival, and small trials show they are feasible after thoracic and colorectal surgery. Yet no ePRO system is in routine use in surgical care.
Why it matters
Patients recovering from thoracic surgery for chronic lung conditions face serious complications that might be prevented if warning symptoms were caught earlier. A well-designed home symptom-reporting system that alerts surgical teams could reduce complications and readmissions. Lessons from this work could extend to other medically complex patients having high-risk surgery.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Nicole Henderson
University of Alabama at Birmingham, AL·Medicine & Clinical Research·Early-career
Identify patient engagement profiles for remote symptom monitoring in the national OncoPRO dataset using latent class analysis, and map their geographic and contextual distribution with geospatial methods.
Julia Berian
University of Wisconsin-Madison, WI·Medicine & Clinical Research·Early-career
Map the preoperative comprehensive geriatric assessment (pCGA) process for older adults having major abdominal surgery, and identify system-level barriers and facilitators to its use with systems-engineering methods.
Ravi Parikh
Emory University, GA·Medicine & Clinical Research
Test in a randomized trial whether A-PACT, machine learning risk prediction paired with lay health worker phone outreach, reduces hospitalizations and intensive end-of-life care for patients with cancer.
The school
University of North Carolina at Chapel Hill: 72 labs on PI Pages, $1.6B a year on research, 523 research doctorates a year.
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