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个人简介
Dr. Tuan is a bioinformatics and health services research expert in using electronic health records (EHR), multi-organizational health data exchange frameworks, and big data analytics to improve quality and efficiency of care in our healthcare delivery system. His research has focused on the design, implementation, and evaluation of evidence-based strategies and policy for supporting patient-centered care continuum and teamwork, value-driven decision making processes, and health information technology and telehealth adoption in ambulatory care settings.
In particular, Dr. Tuan develops and uses information processing theories to understand the cognitive and behavioral responses of both clinicians and patients to the adoption of modern virtual health technology (e.g., EHR platforms, mHealth apps, and patient portals) and unintended consequences. His work involves using the access log record of the electronic health record system to estimate the amount of EHR time spent by clinicians to gain insight into associations between EHR use and clinician burnout. He also analyzes time spent by patients on online portals using machine learning techniques to encapsulate the complex, emerging features of the patient portal to a more concise and interpretable representation. His research provides empirical-based guidance for the healthcare industry on how to improve the usability and practicality of the virtual care platforms to help patients become better informed, engaged, and involved in their care.
Dr. Tuan has participated a number of federally-funded clinical trials and comparative effectiveness studies. In those studies, he leverages EHRs and predictive modeling to assess the impacts of system changes (e.g., new treatments or care guidelines) on access to and quality of medical care for patients who have multiple chronic conditions, receive long-term opioid therapy, and live in rural communities. His research efforts in developing the primary care panel workload scale and the morphine-equivalent daily dose algorithm have contributed substantially for improving population health management and pain care for individuals with opioid-treated pain. Essentially, Dr. Tuan’s research aims to quantify the effects of differentiated clinical, socioeconomic, and technological interventions on care outcomes among subpopulations, identify barriers to health equality, and develop innovative approaches for better and safer care.
Besides clinical and health services studies, Dr. Tuan plans to continue his epidemiological research in infant mortality, firearm fatality, and minority health to help public health officials and policymakers formulate more effective preventive strategies at the state and federal levels. He has also collaborated with computer engineers to evaluate novel use case scenarios designed to enhance analytic reproducibility and transparency for research using the Common Data Model (CDM) format. Dr. Tuan is an avid developer for IoT-based connected health applications using Raspberry Pi and other open-source tools to make essential care services more accessible, affordable and sustainable outside of typical clinical settings.
研究兴趣
论文共 45 篇作者统计合作学者相似作者
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W. Michael Hooten, Miroslav Backonja,Kayode A. Williams,John A. Sturgeon,Jacob B. Gross, Sergey Borodianski, Victor Wang,Wen-Jan Tuan,Aleksandra E. Zgierska,Tobias Moeller-Bertram, Michael L. Kriegel
Bhavna Bali,Wen Jan Tuan, Alyssa Scott, Pooja Bollampally,Destin Groff,Shou Ling Leong, Van L. King,Curtis Bone
Journal of opioid managementno. 5 (2023): 413-422
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