Improving comparative effectiveness research through electronic health records continuity cohorts
National Institutes of Health (NIH)/National Library of Medicine R01 LM012594
Principal investigator: Joshua Lin
This grant proposed to develop generalizable algorithms to identify high-validity continuity cohorts in a given electronic health record (EHR) system that will allow researchers to leverage the rich clinical data while minimizing information bias from data incompleteness due to care provided outside of the study EHR system.
2019 - 2023
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/National Institute on Aging (NIA) RF1 AG063381
Principal investigator: Joshua Lin
This grant aims to investigate how treatment effects of warfarin and direct oral anticoagulants (DOAC) are affected by presence of dementia, high risk of falls, and predictors for anticoagulation quality in patients with atrial fibrillation.
2021 - 2023
Developing dynamic prognostic and risk-stratification models for informing prescribing decisions in older adults with Coronavirus Disease 2019
NIH/ NIA RF1 AG063381
Principal investigator: Joshua Lin
This grant aims to develop and prospectively validated a prognostic tool incorporating dynamic changes of patient characteristics, biomarkers, and drug therapies, which can inform prescribing decisions and resource allocation.
Current
2019 - 2024
Prospective monitoring of newly approved cardiovascular drugs in older adults with frailty
NIH/NIA R01 AG062713
Principal investigator: Dae Kim
The proposed research aims to establish a prospective monitoring program in routine healthcare databases for older adults with frailty and identify predictors of benefit from newly marketed drugs for cardiovascular disease.
2020 - 2025
Developing scalable algorithms to incorporate unstructured electronic health records for causal inference based on real-world data
NIH/National Library of Medicine R01 LM013204
Principal investigator: Joshua Lin
This grant aims to develop a highly flexible and effective analytical method for reducing confounding bias in studies that utilize routine-care data to compare effects of medical or surgical treatments. This method will enable researchers to leverage a large amount of patient information recorded in the clinical notes and reports that are contained within electronic health records to adjust for differences in background risks of different comparison groups.
2023 to 2026
Transportability of Machine Learning-Enabled Confounding Control Methods Across EHR Databases
PCORI ME-2022C1-25646
Principal investigator: Richard Wyss
Funded by PCORI, this project seeks to extend methods for high-dimensional confounding control in healthcare database studies by developing and testing a framework for evaluating the transportability of automated machine learning-enabled methods for confounding control in causal effectiveness studies across multiple EHR systems.
2022 - 2023
Identifying patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) in insurance claims data
Takeda Development Center Americas, Inc.
Principal investigator: Joshua Lin
This study is to investigate the performance of insurance claims data coding algorithms to identify patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) based on diagnosis, procedure, and prescription drug information.
2022 - 2026
Effectiveness and Safety of Transcatheter Left Atrial Appendage Occlusion vs. Anticoagulation in Older Adults with Atrial Fibrillation and Alzheimer's Disease and Related dementias
NIH/ NIA R01 AG075335
Principal investigator: Joshua Lin
This grant aims to determine the treatment effects, utilization patterns, and potential barriers of transcatheter left atrial appendage occlusion devices and specific oral anticoagulants in persons living with dementia (PLWDs) and atrial fibrillation (AF), and how the net clinical benefits vary by dementia severity, frailty, fall risks, and advanced kidney disease. It will also produce a novel and generalizable prospective monitoring program for newly marketed medical devices and pharmacotherapies with detailed treatment effect heterogeneity evaluation needed for personalized prescribing decisions.
2023-2027
A targeted analytical framework to optimize posthospitalization delirium pharmacotherapy in patients with Alzheimers disease and related dementias
NIH/ NIA R01 AG081412-01
Principal investigator: Joshua Lin
The study aims to establish an integrated healthcare database and a novel analytical framework for causal analyses comparing continuation vs. different discontinuation strategies of antipsychotic medications (APMs) used to manage delirium due to hospitalization in persons living with dementia (PLWDs). The proposal will produce data reflecting routine-care delivery to optimize delirium pharmacotherapy management in PLWDs and a generalizable framework that facilitates evidence generation guiding deprescribing of potentially inappropriate medications in older adults.
2023-2027
Deprescribing antipsychotics in patients with Alzheimer’s disease and related dementias and behavioral disturbance in skilled nursing facilities
NIH/ NIA (R01 AG081268-01)
Principal investigator: Joshua Lin
The proposed research aims to determine the health outcomes of different deprescribing strategies of antipsychotics used for behavioral and psychological symptoms of dementia in a skilled nursing facility. It will generate direct evidence that facilitates timely deprescribing of potentially inappropriate medications in people living with dementia. It will also yield a novel analytical framework specializing in comparative safety and effectiveness analyses of discontinuing psychotropic treatments with detailed subgroup analyses informative for individualized deprescribing decisions.