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Transforming Kidney Care in the Emergency Department using Artificial Intelligence Driven Clinical Decision Support

Award Number: R01HS027793
ORGANIZATION: AGENCY FOR HEALTH CARE RESEARCH AND QUALITY
OPDIV: AHRQ
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/30/2020
PERIOD OF PERFORMANCE END DATE: 07/31/2026

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Transforming Kidney Care in the Emergency Department using Artificial Intelligence Driven Clinical Decision Support - PROJECT SUMMARY/ABSTRACT The objective of this proposal is to determine best-practice methods for incorporating artificial intelligence (AI)- derived insights into emergency care. This investigation will use the iterative development and evaluation of an AI-driven clinical decision support (CDS) system to prevent or mitigate acute kidney injury (AKI) as a reference use-case. We are responding to the AHRQ Special Emphasis Notice: Health Services Research Priorities for Achieving a High Value Healthcare System (NOT-HS-18-015), calling for research on prevention of disease through incorporation of AI into healthcare and on interventions to prevent kidney disease progression. Emergency departments (EDs) deliver high-volume patient care in hazardous decision-making environments fraught with excessive cognitive loading and time-pressure. AI has potential to support ED clinician decisions by exploiting large-scale electronic health record (EHR) data to aid prognosis, extract signal from noise, and reduce untoward variability in practice. Despite AI’s fervent promotion, translation to practice is rare and means to incorporate AI that is trustworthy, transparent, and explainable in the ED are unknown. AKI is an important target for AI-driven predictive modeling. It is prevalent and strongly associated with adverse outcomes including dialysis and death, yet is under-recognized and therefore under-treated. In addition, many ED treatments inadvertently promote the progression of AKI and kidney disease. AKI prevention is achievable with evidence-based CDS at the point of care. We will use our AI-driven model, with proven capacity for early and reliable AKI risk estimation, to achieve the following Specific Aims: Aim 1: Develop an AI-driven algorithm for promotion of AKI-focused clinical decision-making in the ED. We will leverage previously developed AKI surveillance and prediction tools to generate a unified EHR-based algorithm that empowers ED clinician prevention of kidney disease progression. Aim 2: Translate the AI algorithm to an AKI-CDS system to enable in-depth study of Clinician-AI interactions in the ED. We will establish end-user requirements while creating data collection instruments to examine AI in the ED. Both efforts will support the development of the AKI-CDS system to pilot and investigate ED clinician perceptions of AI trustworthiness and explainability in preparation for multi-site implementation. Aim 3: Perform a multi-site effectiveness-implementation evaluation of the AKI-CDS system in the ED. We will implement the AI-driven CDS system across three ED study sites using a pragmatic investigational framework to perform effectiveness and implementation evaluations in parallel. The research proposed will generate new knowledge and tools to advance the study of AI in the ED, and will result in a scalable CDS product with the capacity to improve the quality of kidney care delivered to more than 1 million patients affected by AKI in the US each year.


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	2024	THE JOHNS HOPKINS UNIVERSITY	3400 N CHARLES ST	BALTIMORE	MD	21218	BALTIMORE CITY	USA	Research on Healthcare Costs, Quality and Outcomes	000	5	5/2/2025	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2024 ( Subtotal = $390,412 )
2024	2024	THE JOHNS HOPKINS UNIVERSITY	3400 N CHARLES ST	BALTIMORE	MD	21218	BALTIMORE CITY	USA	Research on Healthcare Costs, Quality and Outcomes	001	5	7/24/2024	NON-COMPETING CONTINUATION	$390,412
2024	2023	THE JOHNS HOPKINS UNIVERSITY	3400 N CHARLES ST	BALTIMORE	MD	21218	BALTIMORE CITY	USA	Research on Healthcare Costs, Quality and Outcomes	000	4	4/25/2024	NON-COMPETING CONTINUATION	$0
														Subtotal = $390,412

Issue Date FY: 2023 ( Subtotal = $393,654 )
2023	2023	JOHNS HOPKINS UNIVERSITY, THE	3400 N CHARLES ST	BALTIMORE	MD	21218	BALTIMORE CITY	USA	Research on Healthcare Costs, Quality and Outcomes	001	4	8/1/2023	NON-COMPETING CONTINUATION	$393,654
2023	2022	JOHNS HOPKINS UNIVERSITY, THE	3400 N CHARLES ST	BALTIMORE	MD	21218	BALTIMORE CITY	USA	Research on Healthcare Costs, Quality and Outcomes	000	3	4/13/2023	NON-COMPETING CONTINUATION	$0
														Subtotal = $393,654

Issue Date FY: 2022 ( Subtotal = $393,415 )
2022	2022	JOHNS HOPKINS UNIVERSITY, THE	3400 N CHARLES ST	BALTIMORE	MD	21218	BALTIMORE CITY	USA	Research on Healthcare Costs, Quality and Outcomes	002	3	7/21/2022	NON-COMPETING CONTINUATION	$393,415
2022	2021	JOHNS HOPKINS UNIVERSITY, THE	3400 N CHARLES ST	BALTIMORE	MD	21218	BALTIMORE CITY	USA	Research on Healthcare Costs, Quality and Outcomes	001	2	12/6/2021	NON-COMPETING CONTINUATION	$0
2022	2020	JOHNS HOPKINS UNIVERSITY, THE	3400 N CHARLES ST	BALTIMORE	MD	21218	BALTIMORE CITY	USA	Research on Healthcare Costs, Quality and Outcomes	000	1	12/6/2021	NEW	$0
														Subtotal = $393,415

Issue Date FY: 2021 ( Subtotal = $400,000 )
2021	2021	JOHNS HOPKINS UNIVERSITY, THE	3400 N CHARLES ST	BALTIMORE	MD	21218	BALTIMORE CITY	USA	Research on Healthcare Costs, Quality and Outcomes	000	2	7/22/2021	NON-COMPETING CONTINUATION	$400,000
														Subtotal = $400,000

Issue Date FY: 2020 ( Subtotal = $386,137 )
2020	2020	JOHNS HOPKINS UNIVERSITY, THE	3400 N CHARLES ST	BALTIMORE	MD	21218	BALTIMORE CITY	USA	Research on Healthcare Costs, Quality and Outcomes	000	1	9/10/2020	NEW	$386,137
														Subtotal = $386,137

Grand Total All Awards = $1,963,618

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Transforming Kidney Care in the Emergency Department using Artificial Intelligence Driven Clinical Decision Support

Award Number: R01HS027793

ORGANIZATION: AGENCY FOR HEALTH CARE RESEARCH AND QUALITY

OPDIV: AHRQ

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 09/30/2020

PERIOD OF PERFORMANCE END DATE: 07/31/2026

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