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Current Major Grants and Projects

Identifying and addressing missingness and bias to enhance discovery from multimodal health data 

NIH-NLM 1R01LM014239

Zhou L, Pengyu Hong (MPI) 4/1/2023-3/31/2027

This project will focus on developing methods for real-time risk prediction and patient monitoring in the critical care and ICU settings that address issues of health diversity, equity, and inclusion through the use of fair machine learning algorithms to appropriately handle missingness and bias in clinical data.

Leveraging Longitudinal Data and Informatics Technology to Understand the Role of Bilingualism in Cognitive Resilience, Aging and Dementia

NIH-NIA R01 AG080429

Zhou L, Xu H (MPI) 2/2023-1/2028

The goal of this study to use longitudinal EHR data and patient survey data to study the role of bilingualism in cognitive reserve/resilience, aging and dementia. By leveraging large-scale data across diverse populations and advanced informatics technology (including natural language processing, machine learning, and statistical models), we aim to test and refine potential theories of bilingual effects on cognitive reserve and resilience to Alzheimer’s Disease and Alzheimer’s Disease Related Dementias (AD/ADRD), and improve our understanding of the complex interactions between neural, sociocultural, and clinical factors and the progression of cognitive decline and AD/ADRD in older adult.

Clinical Decision Support System for Early Detection of Cognitive Decline Using Electronic Health Records and Deep Learning

NIH-NIA R44AG081006

Du J, Manion FJ, Zhou L (MPI) 2/1/2023-1/31/2025

The study aims to develop deep learning-based approaches to identify patients with cognitive decline and develop a user-centered decision support system to assist primary care physicians to manage identified patients.

Using Real-Time Automated Detection and Clinical Decision Support to Improve Lung-Protective Ventilation in Intensive Care

BWH Health & Technology Innovation Fund

Zhou Li (PI) 7/1/2022-6/30/2023

A significant number of patients in need of intensive care experience acute respiratory failure, yet fewer than two-thirds are recipients of lifesaving lung-protective ventilatory care. We will develop a computerized clinical decision support tool that leverages real-time ventilation data and electronic health records to provide the immediate, precise and safe bedside care necessary to protect against potentially fatal ventilation-associated lung injuries

Implementing and Piloting Mortality Prediction Models to Support Palliative Care in the Primary Care Setting

Brigham & Women’s Physician’s Organization

Lakin J, Zhou L 11/2021-3/2023

The goal of this project is to implement, pilot, and evaluate mortality prediction model and use mortality as a proxy to assist primary care clinicians with selecting patients who may benefit for early palliative care interventions.

Identification and Prevention of Potentially Inappropriate Inter-Hospital Transfers

AHRQ R01-HS2028621

Muller S (PI) 2022-2027

Identification and Prevention of Potentially Inappropriate Inter-Hospital Transfers

The goals of this study are to build off of the findings of our foundational work on inter-hospital transfers to rigorously evaluate the incidence of potentially inappropriate IHT among hospitalized medical patients, better understand the types of transfers that are potentially inappropriate, and to develop preliminary interventions to prevent potentially inappropriate transfers. To do this, we plan to collect data in collaboration with a national research collaborative (the Hospital Medicine Reengineering Network – HOMERuN) in combination with billing and administrative data available from benchmarking and purchasing organization (Vizient) .

Clinical Informatics to Advance Epidemiology and Pharmacogenetics of Serious Cutaneous Adverse Drug Reactions

NIH-NIAID — 1R01AI150295

Zhou L (PI) 09/16/2019–08/31/2023

The goal is to leverage advanced informatics and longitudinal EHR data to identify severe cutaneous adverse reactions (SCAR) cases to study genetic and epidemiological risk factors for SCAR related to commonly used drugs such as antibiotics.

eCQM: Rate of delayed or missed follow-up on abnormal cancer screening tests in primary care

Gordon and Betty Moore Foundation

Syrowatka, A (PI) 2022-2023

The diagnosis of cancer is a process. It begins with convenient, non-invasive, and low-cost screening tests, and when screening results are abnormal, require further diagnostic testing. When diagnostic testing is delayed, patients are at risk of the cancer progressing and being detected at a later stage requiring more aggressive treatments and associated with lower survival. We aim to improve diagnostic excellence in timely diagnosis of colorectal, breast and prostate cancers. The proposed electronic clinical quality measure (eCQM) will report the percentage of abnormal screening tests where diagnostic testing was delayed or missed according to established guidelines for follow up.

Developing Scalable Algorithms to Incorporate Unstructured Electronic Health Records for Causal Inference based on Real-world Data

NIH/NLM 1R01LM013204

Lin J (PI) 06/1/2020–03/31/2025

Risk Factors for Psychosis and Mania with Prescription Amphetamine Use

NIH/NIMH 1R01MH122427

Moran L (PI; McLean Hospital) 06/10/2020–04/30/2024

CONCERN: Implementation Toolkit: Advancing technology-enabled nursing expertise and equitable predictions

ANF CU-21-3594

PI: Rossetti, Sarah; Site-PI: Dykes, Patricia 04/2022 – 03/2025

Promoting follow-up of abnormal cancer screening tests using population-based systems to support stepped care multilevel intervention

NIH-NCI U01CA225451

Haas J (PI; Mass General Hospital) 2018–2023

Recent Completed Grants and Collaborations

Assessing the effectiveness of oral anticoagulants in patients with atrial fibrillation at high risk of underutilization due to dementia, recurrent falls, or poor anticoagulation quality

NIH-NIA R01AG063381

Lin J (PI) 05/01/2019–04/30/2023

Promoting follow-up of abnormal cancer screening tests using population-based systems to support stepped care multilevel intervention

Identifying Adverse Drug Events in Ambulatory Care Clinical Notes

IBM-BWH Collaborative Research Project

Zhou L (PI/Project Lead) 11/1/2020–10/31/2022

The goal is to investigate, characterize and annotate adverse drug events (ADEs) documented in ambulatory care clinical notes and to assess the ability of NLP and machine learning to identify ADEs.

Improving Allergy Documentation and Clinical Decision Support in the EHR

Agency for Healthcare Research and Quality (AHRQ) — R01HS025375

Zhou L (PI) 05/07/2018–04/30/2022

The goal of this study is to improve allergy documentation by developing a comprehensive and interactive value set for reaction mechanism and type, developing an innovative allergy reconciliation module within the EHR, and redesigning drug allergy alerting mechanisms using big data analytics and up-to-date evidence.

Evaluating and Improving the Accuracy of ICD-Coded Hospital Data Systems in Estimating the Incidence of Nonfatal Firearm Injuries by Intent Type

National Collaborative on Gun Violence Research (NCGVR)

Miller, M (Northeastern University); Goralnick, E 09/1/2020–08/31/2022

Communicating Narrative Concerns Entered by RNs (CONCERN): Clinical Decision Support Communication for Risky Patient States

NINR — 1R01NR016941

Collins S (PI; Columbia University) 04/06/2017–03/31/2022

Representation of Unstructured Data Across Common Data Models


Marsolo K (PI) 2021-2022

Personalizing AAV Management by Leveraging Big Data: Targeting Complication Clusters


Wallace Z (PI) 2021-2022

Investigating sex differences in subjective cognitive decline across patients captured in electronic health records

The Program for Interdisciplinary Neuroscience (PIN) and the Women’s Brain Initiative (WBI), BWH

Wang L (PI) 03/1/2020–02/28/2021

Finding Needles in the Haystack: Using Clinical Data and Machine Learning to Identify Patients for Early Palliative Care Interventions

Partners Healthcare Innovation

Zhou L (PI) 05/01/2019–04/30/2020

From Sepsis Prognosis Prediction to Tailored Clinical Practice: A Deep Learning Approach


Dykes P (PI) 07/01/2019–06/30/2021

Computerized Support for Malpractice Auditing and Coding


Zhou L (PI) 07/01/2018–12/30/2019

Similar-cAses Finder for Risk Reduction – the SAFRR system


Zhou L (PI) 07/01/2018–06/30/2020

Assessing Allergy Safety During Electronic Health Record Transitions


Kimberly Blumenthal (PI; Mass General Hospital)           07/01/2018–06/30/2020

NLP to Improve Accuracy and Quality of Dictated Medical Documents

Agency for Healthcare Research and Quality (AHRQ) — R01HS024264

Zhou L (PI) 09/30/2015–09/29/2019

Encoding and Processing Patient Allergy Information in EHRs

Agency for Healthcare Research and Quality (AHRQ) — R01HS022728

Zhou L (PI) 09/30/2013–9/30/2018

Novel electronic health record phenotyping of LGBTQ intersectional identities and associated health disparities using NLP and machine learning approaches

Harvard Catalyst Health Disparities Research Program and President and Fellows of Harvard College — 2016D010012

Zhou L (PI) 07/01/2017–06/30/2018

NLP to Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department

Agency for Healthcare Research and Quality (AHRQ) — 1R21HS024541

Goss FR (PI) 09/01/2016–8/31/2018

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