Michael Cheung

ORCID: 0000-0003-2913-7265
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About
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Research Areas
  • Patient-Provider Communication in Healthcare
  • Patient Satisfaction in Healthcare
  • Medication Adherence and Compliance
  • Healthcare professionals’ stress and burnout
  • Health Systems, Economic Evaluations, Quality of Life
  • Diversity and Career in Medicine
  • Health Literacy and Information Accessibility
  • Fire effects on ecosystems
  • Climate Change and Health Impacts
  • Adolescent and Pediatric Healthcare
  • Healthcare Systems and Technology
  • COVID-19 and Mental Health
  • Chronic Disease Management Strategies
  • Geriatric Care and Nursing Homes
  • Child Nutrition and Water Access
  • Innovations in Medical Education
  • Food Security and Health in Diverse Populations

University of California, San Diego
2022-2025

Scripps Institution of Oceanography
2024-2025

Human Longevity (United States)
2024

Physicians of all specialties experienced unprecedented stressors during the COVID-19 pandemic, exacerbating preexisting burnout. We examine burnout's association with perceived and actionable electronic health record (EHR) workload factors personal, professional, organizational characteristics goal identifying levers that can be targeted to address

10.1093/jamia/ocad136 article EN cc-by Journal of the American Medical Informatics Association 2023-07-08

Physician burnout is an ongoing epidemic; electronic health record (EHR) use has been associated with burnout, and the burden of EHR inbasket messages grown in context COVID-19 pandemic. Understanding how are physician may uncover new insights for intervention strategies.To evaluate associations between message characteristics burnout.Cross-sectional study a single academic medical center involving physicians from multiple specialties. Data collection took place April to September 2020, data...

10.1001/jamanetworkopen.2022.44363 article EN cc-by-nc-nd JAMA Network Open 2022-11-30

A primary concern of public health researchers involves identifying and quantifying heterogeneous exposure effects across population subgroups. Understanding the magnitude direction these on a given scale provides ability to recommend policy prescriptions assess external validity findings. Traditional methods for effect measure modification analyses require manual model specification that is often impractical or not feasible conduct in high-dimensional settings. Recent developments machine...

10.1016/j.ssmph.2025.101764 article EN cc-by SSM - Population Health 2025-02-14

To examine sociodemographic factors associated with having unmet needs in medications, mental health, and food security among older adults during the COVID-19 pandemic.Primary data secondary from electronic health records (EHR) an age-friendly academic system 2020 were used.Observational study examining food, health.Data a computer-assisted telephone interview EHR on community-dwelling patients analyzed.Among 3400 eligible patients, 1921 (53.3%) (average age 76, SD 11) responded, 857 (45%)...

10.1111/1475-6773.14084 article EN cc-by-nc-nd Health Services Research 2022-10-10

A primary concern of public health researchers involves identifying and quantifying heterogeneous exposure effects across population subgroups. Understanding the magnitude direction these on a given scale provides ability to recommend policy prescriptions assess external validity findings. Furthermore, increasing popularity in fields such as precision medicine that rely accurate estimation high-dimensional interaction has highlighted importance understanding effect modification. Traditional...

10.48550/arxiv.2401.15257 preprint EN arXiv (Cornell University) 2024-01-26

Background Effective primary care necessitates follow-up actions by the patient beyond visit. Prior research suggests room for improvement in adherence. Objective This study sought to understand patients’ views on their visits, plans generated therein, and self-reported adherence after 3 months. Methods As part of a large multisite cluster randomized pragmatic trial health organizations, patients completed 2 surveys—the first within 7 days index visit another months later. For this analysis...

10.2196/50242 article EN cc-by Journal of Participatory Medicine 2024-03-14

<h3>Context:</h3> Despite various attempts to improve patient-clinician communication, there has been limited head-to-head comparison of these efforts. <h3>Objective:</h3> enhance building on a previous pilot that created promising prototypes interventions. Population <h3>Studied:</h3> 4,852 patients and 114 primary care clinicians in 21 clinics 3 health systems 2 states the U.S. <h3>Intervention:</h3> A cluster randomized controlled trial with arms: in-person communication coaching...

10.1370/afm.22.s1.6095 article EN 2024-11-20

Importance Despite various attempts to improve patient-clinician communication, there has been limited head-to-head comparison of these efforts. Objective To assess whether clinician coaching (mobile application or in-person) is more effective than reminder posters in examination rooms and mobile app use noninferior in-person coaching. Design, Setting, Participants A cluster randomized clinical trial with 3 arms. total 21 primary care clinics participated health systems the US; participants...

10.1001/jamahealthforum.2024.4436 article EN cc-by-nc-nd JAMA Health Forum 2024-12-13

<sec> <title>BACKGROUND</title> Effective primary care necessitates follow-up actions by the patient beyond visit. Prior research suggests room for improvement in adherence. </sec> <title>OBJECTIVE</title> This study sought to understand patients’ views on their visits, plans generated therein, and self-reported adherence after 3 months. <title>METHODS</title> As part of a large multisite cluster randomized pragmatic trial health organizations, patients completed 2 surveys—the first within 7...

10.2196/preprints.50242 preprint EN 2023-08-15

Identifying heterogeneity of treatment or exposure effects among subgroups a study population is important in public health to identify target with priority. Previous approaches have relied on the estimation conditional average effect, which requires effect modifiers be specified priori and for limited number potential modifiers. More recently, machine learning (ML) algorithms been proposed observational studies, allow greater flexibility accuracy identification heterogeneous...

10.1289/isee.2022.p-0010 article EN ISEE Conference Abstracts 2022-09-18
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