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
FDA
Marsolo K (PI) 2021-2022
Personalizing AAV Management by Leveraging Big Data: Targeting Complication Clusters
NIH/NIAMS R03AR078938
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
CRICO/RMF
Dykes P (PI) 07/01/2019–06/30/2021
Computerized Support for Malpractice Auditing and Coding
CRICO/RMF
Zhou L (PI) 07/01/2018–12/30/2019
Similar-cAses Finder for Risk Reduction – the SAFRR system
CRICO/RMF
Zhou L (PI) 07/01/2018–06/30/2020
Assessing Allergy Safety During Electronic Health Record Transitions
CRICO/RMF
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