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Accelerating research to advance care for adults with congenital heart disease through development of validated scalable computational phenotypes

Award Number: R01HL151604
ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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Accelerating research to advance care for adults with congenital heart disease through development of validated scalable computational phenotypes - PROJECT SUMMARY The advent of surgery to treat congenital heart disease (CHD) in the second half of the 20th century shifted the care paradigm from palliation of disease fatal in infancy to management of lifelong chronic disease through adulthood. There are now more than 1.5 million adults with CHD living in the United States. These patients have a substantial burden of cardiovascular and other medical comorbidities, as well as markedly increased risk for adverse outcomes such as arrhythmia, heart failure, cerebrovascular accident, and premature death. The emergence of this population requires new clinical care models as well as the development of novel research tools and infrastructures to address these patients' unique characteristics and healthcare needs. Adult CHD is characterized by substantial complexity, era-dependent heterogeneity in treatment strategies, and time-varying implications of lifelong disease. This burgeoning population is understudied, and the pathophysiology of the component diseases remains incompletely understood. Billing and other administrative codes available in the electronic medical record are neither sensitive nor specific for CHD diagnosis and do not adequately describe many other salient clinical features. As a result, structured data in large administrative databases are not well suited to studying adults with CHD, even when the goal is simply to identify a cohort of patients with a given diagnosis. This constitutes a major impediment to research efforts and is the primary barrier underlying the limited population-based research performed to date. Adult CHD investigation would benefit immensely from methods to establish harmonized, large-scale, multi-center datasets. While billing codes are inadequate, the information needed to accurately classify adults with CHD is already available in the electronic medical record in the form of clinical notes, comprised mainly of unstructured (“free”) text. Manual data extraction is laborious, resource intensive, and, therefore, not scalable. We propose to apply cutting-edge natural language processing approaches to unstructured text in the electronic medical record to develop computable classifiers for variables fundamental to the study of adults with CHD. We will use two unique institutional data resources at Boston Children's Hospital and Brigham and Women's Hospital that are already populated with expert-adjudicated labels to train classifiers for key phenotypes that are poorly defined by administrative codes. These classifiers will be validated in an independent patient cohort at Vanderbilt University Medical Center and tested in new disease-specific risk prediction models. This work promises to accelerate CHD research by massively increasing the scale of the patient cohorts that can be studied and by establishing a foundation for improved evidence-based decision support for this underserved population.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = $0 )
2025	2023	CHILDRENS HOSPITAL MEDICAL CENTER	3333 BURNET AVE	CINCINNATI	OH	45229	HAMILTON	USA	Cardiovascular Diseases Research	002	4	4/15/2025	NON-COMPETING CONTINUATION	$0
2025	2023	CHILDRENS HOSPITAL MEDICAL CENTER	3333 BURNET AVE	CINCINNATI	OH	45229	HAMILTON	USA	Cardiovascular Diseases Research	000	4	1/21/2025	NON-COMPETING CONTINUATION	$0
2025	2023	CHILDRENS HOSPITAL MEDICAL CENTER	3333 BURNET AVE	CINCINNATI	OH	45229	HAMILTON	USA	Cardiovascular Diseases Research	001	4	3/28/2025	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2023 ( Subtotal = $493,772 )
2023	2023	CHILDRENS HOSPITAL MEDICAL CENTER	3333 BURNET AVE	CINCINNATI	OH	45229	HAMILTON	USA	Cardiovascular Diseases Research	000	4	4/26/2023	NON-COMPETING CONTINUATION	$493,772
														Subtotal = $493,772

Issue Date FY: 2022 ( Subtotal = $678,400 )
2022	2022	CHILDREN'S HOSPITAL MEDICAL CENTER	3333 BURNET AVE	CINCINNATI	OH	45229	HAMILTON	USA	Cardiovascular Diseases Research	000	3	4/27/2022	NON-COMPETING CONTINUATION	$678,400
														Subtotal = $678,400

Issue Date FY: 2021 ( Subtotal = $738,379 )
2021	2021	CHILDREN'S HOSPITAL MEDICAL CENTER	3333 BURNET AVE	CINCINNATI	OH	45229	HAMILTON	USA	Cardiovascular Diseases Research	000	2	5/12/2021	NON-COMPETING CONTINUATION	$738,379
														Subtotal = $738,379

Issue Date FY: 2020 ( Subtotal = $784,220 )
2020	2020	CHILDREN'S HOSPITAL MEDICAL CENTER	3333 BURNET AVE	CINCINNATI	OH	45229	HAMILTON	USA	Cardiovascular Diseases Research	000	1	7/10/2020	NEW	$784,220
														Subtotal = $784,220

Grand Total All Awards = $2,694,771

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Accelerating research to advance care for adults with congenital heart disease through development of validated scalable computational phenotypes

Award Number: R01HL151604

ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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