# Complexity, Incidence, and Costs Related to Delayed Diagnosis of Venous Thromboembolism in Urban and Rural Primary and Urgent Care Settings

> **NIH AHRQ R01** · BRIGHAM AND WOMEN'S HOSPITAL · 2024 · $500,000

## Abstract

ABSTRACT
Venous thromboembolism (VTE), consisting of pulmonary embolism and deep vein thrombosis, is a common
and consequential public health problem affecting up to 600,000 adults in the United States annually. VTE
requires timely detection and treatment, but the VTE diagnosis workflow in ambulatory care is fraught with
challenges, including delays, inaccuracies, and misdirection, influenced by multiple factors including
nonspecific symptoms and a lack of systematic measurement and quality improvement tools. VTE is
associated with health disparities (highest in black and African American populations) and missed or delayed
VTE diagnosis can have serious consequences for patient and healthcare cost outcomes, resulting in
increased risk of morbidity, mortality, and prolonged hospital stays. These issues may be further compounded
by variation in the types of ambulatory care practices (primary care versus urgent care) and the geographical
locations and socio-economic status where patients seek care.
Our team developed an electronic clinical quality measure (eCQM) that uses structured and unstructured EHR
data to measure Diagnostic Delay of Venous Thromboembolism (DOVE) in primary care settings that was
recently endorsed by the Partnership for Quality Measurement. Using this eCQM, the rate of delayed VTE
diagnosis in urban, metro, and rural primary care practices across three large healthcare systems using
different EHR systems was found to be consistently over 70%, suggesting that this is an important type of
diagnostic error (DE) with likely negative impacts on patient outcomes.
Building on our preliminary work, we propose to leverage EHR data and stakeholder expertise to gain an
understanding of VTE DE risk factors, disparities and outcomes. We will develop artificial intelligence (AI) and
statistical learning tools to identify, factorize, and address vulnerabilities in a range of VTE DE workflows
including delayed and missed VTE diagnosis in both ambulatory and urgent care settings. This study brings
together a strong interdisciplinary team of experts in primary care, VTE diagnosis, informatics, data science
(natural language processing and machine learning). The advanced data-driven eCQM will be refined using
high-dimensional EHR data (structured and unstructured) to quantfy timely, delayed and missed VTE
diagnoses. To increase generalizability of the results, we will use multiple data sources from 220 primary
care/urgent care practices and clinics associated with 13 hospitals from urban, metro and rural clinics in the
Northeastern and Southern United States (2 different EHR vendors). If successful, this approach will
substantially improve our understanding of DEs and related risk factors, VTE DE related costs and build a
foundation for improving VTE diagnostic accuracy and precision and diminish disparities in healthcare
outcomes.

## Key facts

- **NIH application ID:** 11020773
- **Project number:** 1R01HS030221-01
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** Jin Chen
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** AHRQ
- **Fiscal year:** 2024
- **Award amount:** $500,000
- **Award type:** 1
- **Project period:** 2024-09-01 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11020773

## Citation

> US National Institutes of Health, RePORTER application 11020773, Complexity, Incidence, and Costs Related to Delayed Diagnosis of Venous Thromboembolism in Urban and Rural Primary and Urgent Care Settings (1R01HS030221-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/11020773. Licensed CC0.

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