# The Intersection of Personalized Medicine and Implementation Science to Improve Healthcare Utilization in Cirrhosis

> **NIH NIH K23** · INDIANA UNIVERSITY INDIANAPOLIS · 2021 · $180,179

## Abstract

ABSTRACT
Management of cirrhosis is resource-intensive and disproportionately contributes a growing burden on
healthcare. Inpatient care is a sizeable portion of this burden where nearly 30% of admissions result in a
readmission within 30 days. Unfortunately, health system-based interventions successful in reducing
readmission rates face important barriers to dissemination. In order for successful health delivery redesign to
occur, it is important to target the right patient and deliver a tailored intervention. Precisely segmenting patient
populations to identify high utilizers is an important first step. Current readmission prediction models based on
traditional medical records data have weak performance in cirrhosis. Instead, our novel preliminary data correlate
patient reported outcome measures (PROMs) to future healthcare utilization (HCU). Further, the PI’s mentor has
shown that when healthcare systems combine real-time PRO tracking with evidence-based management
algorithms and patient-facing health tools, HCU burden can be reduced. Based on these data, this proposal will
first test the overarching hypothesis that a combination of EHR-based and non-EHR, patient-centered measures
will better identify high utilizers in cirrhosis. Taken a step further, this proposal will also test the hypothesis that
successful, scalable models of care can be translated to high-risk cirrhotics through adaptation of a health
technology tool. We will test these hypotheses via three aims and a robust training plan. Specific Aim #1 will
assess HCU prediction by existing risk models and then utilize a state-wide data source to further refine risk
prediction with liver disease-specific and population health data. Specific Aim #2 will further calibrate prediction
of future HCU using PROMs in a prospective cohort of hospitalized cirrhotics. With the ability to identify a
vulnerable group of cirrhotics from SA#s 1-2, Specific Aim #3 will build on the co-mentor’s (Dr. Boustani)
success in improving HCU in dementia populations by adapting Brain Care Notes, a mobile phone health
application designed to support real-time symptom tracking, care-giver support and engagement to reduce HCU
in those with cirrhosis. Further, while completing these aims, the PI will accomplish 3 interdisciplinary training
goals: 1) develop advanced biostatistical and big data management and analysis skills; 2) acquire experience
in methodologies needed for the study of PROMs; 3) gain expertise in healthcare implementation science
research all under the guidance of a robust mentorship team led by national experts in the proposed fields.
Successful completion of these aims will support the design of a future R01-level intervention that provides
innovative, scalable solutions for the chronic disease management in cirrhosis.

## Key facts

- **NIH application ID:** 10217128
- **Project number:** 5K23DK123408-02
- **Recipient organization:** INDIANA UNIVERSITY INDIANAPOLIS
- **Principal Investigator:** Archita P. Desai
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $180,179
- **Award type:** 5
- **Project period:** 2020-07-15 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10217128

## Citation

> US National Institutes of Health, RePORTER application 10217128, The Intersection of Personalized Medicine and Implementation Science to Improve Healthcare Utilization in Cirrhosis (5K23DK123408-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10217128. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*