# Understanding the Quality of Tuberculosis Care in Uganda

> **NIH NIH F31** · YALE UNIVERSITY · 2020 · $30,411

## Abstract

Project Summary/Abstract
Achieving high-quality care for tuberculosis (TB) remains one of the most important obstacles to ending the
global epidemic of TB, the world's leading infectious cause of death. Care cascades have been used to show
how well each stage of care is implemented from screening to diagnosis and treatment, and to provide a useful
framework for assessing multiple dimensions of quality, including efficiency, effectiveness, and timeliness.
However, a major barrier to improving TB case finding, treatment initiation, and cure is a lack of capacity for
health systems to collect and utilize routine data to identify determinants of high- and low-quality care and
targets for improvement interventions. This training proposal addresses these challenges and identifies
methodological gaps for me to address through three scientific aims and three training aims. First, we will
measure the accuracy of routine TB surveillance data in Uganda as compared to a reference standard and
determine if aggregated routine data or high-fidelity sampling of routine individual-patient data can provide the
best operational measure of the quality of TB care in Uganda. Next, we will use the best approach to evaluate
the impact of Xpert MTB/RIF, a novel rapid, ultra-sensitive diagnostic test, on case finding and treatment
initiation. Finally, we will develop a mathematical model of the potential impact of different quality improvement
interventions on the TB care cascade in Uganda. Three training aims are well-matched to these scientific aims
and will provide coursework and mentored research experiences to allow me to refine and develop mastery in
advanced biostatistics, mathematical modeling, and in how to collaborate with policymakers to solve real-world
analytical problems. Our findings will help program decision makers use surveillance data not only to monitor
TB, but also to address key gaps in quality care. The resulting inferences will yield insights about the accuracy
of surveillance data, measuring and improving the quality of care, and operationalizing these elements for
quality improvement – that go beyond Uganda and have relevance in a wide range of high TB burden, low-
income settings.
This project will draw upon established research collaborations at the Uganda Tuberculosis Implementation
Research Consortium (U-TIRC) between investigators at Yale University, Makerere University, and the
Uganda National Tuberculosis and Leprosy Programme (NTLP) who have provided access to the existing data
that will be used in this proposal. The proposed research and the collaborative, interdisciplinary training
environment at Yale and U-TIRC will allow the applicant to develop expertise in quantitative methods for
infectious disease epidemiology. After completing the fellowship, the applicant will be well-positioned to seek
career opportunities as an independent researcher working collaboratively between academic, government,
and other public health partners.

## Key facts

- **NIH application ID:** 10067057
- **Project number:** 1F31HL156805-01
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Elizabeth B White
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $30,411
- **Award type:** 1
- **Project period:** 2020-09-15 → 2022-09-14

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10067057

## Citation

> US National Institutes of Health, RePORTER application 10067057, Understanding the Quality of Tuberculosis Care in Uganda (1F31HL156805-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10067057. Licensed CC0.

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