Richard Lester

Associate Professor

Research Classification

Infectious diseases

Research Interests

Digital health
Mobile health (mHealth)
Precision Public Health
Patient-centered care
Global Health
Infectious diseases

Relevant Thesis-Based Degree Programs

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Affiliations to Research Centres, Institutes & Clusters

Action on Sepsis
Data Science and Health (DASH)

Research Options

I am available and interested in collaborations (e.g. clusters, grants).
I am interested in and conduct interdisciplinary research.
I am interested in working with undergraduate students on research projects.
 
 

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Research Methodology

Randomized Controlled Trials
Pragmatic trials
Implementation science
data science
Natural Language Processing

Recruitment

Master's students
Doctoral students
Postdoctoral Fellows
Any time / year round

Global digital health for patient engagement in care and virtual care. Work in Canada, Africa and globally. Quantitative and qualitative studies, implementation research, data science, and digital health policy and ethics. Especially among scaling interventions to benefit vulnerable populations and health equity.

Passionate, self-motivated, high achieving. Interest in vigorous scientific method and digital health innovation and research.

I support public scholarship, e.g. through the Public Scholars Initiative, and am available to supervise students and Postdocs interested in collaborating with external partners as part of their research.
I support experiential learning experiences, such as internships and work placements, for my graduate students and Postdocs.
I am open to hosting Visiting International Research Students (non-degree, up to 12 months).
I am interested in hiring Co-op students for research placements.

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ADVICE AND INSIGHTS FROM UBC FACULTY ON REACHING OUT TO SUPERVISORS

These videos contain some general advice from faculty across UBC on finding and reaching out to a potential thesis supervisor.

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Supervision Enquiry

If you have reviewed some of this faculty member's publications, understand their research interests and have reviewed the admission requirements, you may submit a contact request to this supervisor.

Great Supervisor Week Mentions

Each year graduate students are encouraged to give kudos to their supervisors through social media and our website as part of #GreatSupervisorWeek. Below are students who mentioned this supervisor since the initiative was started in 2017.

 

Thank you, Dr. Lester, for your friendly supervision and your dedication during the last years!

Nelson Gorrin (2019)

 

In our research group, Dr. Lester sparks innovative conversations between students from a wide range of backgrounds. From computer science students contributing to the development of a mobile health technology to public health researchers studying the implementation of this tech globally, he has a knack for translating information that serves a spectrum of interests. It really helps to bring together students who might otherwise work in silos. I've really appreciated his can-do attitude and the positive perspective he has when tackling complex problems in low-resource settings. He always makes his students feel capable and confident in their abilities and reminds us of the importance our research has in a broader context. As a student from a remote and isolated community, I value that Dr. Lester, his family, and the research group offer a sense of community I need to thrive. Thank you, Dr. Lester, for making anyone and everyone feel welcome in your lab. And I am so grateful for the accommodation of my dog as well; this helped me acclimatize to the city and make transitioning back into post-secondary an easier choice. Thank you! 

Alissa MacMullin (2019)

 

Graduate Student Supervision

Doctoral Student Supervision

Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.

A master protocol of an adaptive platform trial to assess effectiveness of multi-component interventions for linear growth of sub-Saharan African children during complementary feeding period (2021)

Randomized clinical trials (RCT) are an important tool that has led to important reduction of global childhood mortality. Low and middle-income countries (LMICs) still face important challenge in stunting (low height-for-age) that can produce detrimental effects on child’s long-term development. Facing important challenges in stunting Rwanda has adopted stunting prevention with a particular focus on complementary feeding period ([CFP]: 6-24 months) as their national strategic plan. Rapid Pro, a community health workers program that provides routine health and monitoring services from pregnancy to five years of age using SMS, is a unique health system in Rwanda that can be used to improve linear growth for their children. A single overarching master protocol for an adaptive platform trial (APT) that could be embedded into Rapid Pro to determine comparative effectiveness of multi-component interventions on linear growth during CFP was developed. APTs are a new RCT design that allows for evaluation of multiple interventions against a common control using interim evaluation and flexibilities of allowing new interventions to be added during the trial. To inform the trial design, a landscape analysis of master protocols and APTs was done through a systematic literature review (SLR). This showed 83 master protocols, 16 of which were platform trials, that have been mostly conducted in the US (n=44/83) for pharmaceutical development (n=82/83). This was followed by an SLR with network meta-analysis (NMA) of LMIC-based RCTs studying interventions under the domains of micronutrients and food supplements, deworming, maternal education, and water, sanitation, and hygiene aimed to improve linear growth for children during CFP. An NMA of 79 RCTs involving 81,786 children showed largely equivocal results highlighting the need for more investigation with interventions being combined and tested as packages. The results of these findings were then presented to the governmental stakeholders to determine intervention packages to be tested and to inform the APT design. Simulations were performed to design Bayesian early stopping rules that could reduce the expected sample size while keeping type I error rates under 2.5%. The findings support the use of APTs for child health and other key areas in global health research.

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Mediation adherence in asthma: a systematic review and concurrent mixed methods studies exploring the impact of text messages on self-reported medication adherence (2019)

Background: Despite the availability of effective therapy, health outcomes are poor and costs associated with asthma are high. Consistent reports of sub-optimal medication adherence among adults with asthma highlight the importance of assessing the effect of interventions on medication adherence and exploring possible mechanisms to better understand how medication adherence can be promoted and supported.Objectives: My objectives are to review the effects of interventions to improve asthma outcomes on medication adherence and to explore the impacts of text message supported interventions on self-reported medication adherence using a mixed methods approach. Methods: For the systematic review, I conducted a search of databases to identify randomized controlled trials of interventions to improve asthma outcomes using medication. A structured framework was applied to classify interventions based on the emphasis placed on medication adherence. Furthermore, I conducted two convergent mixed methods studies integrating qualitative findings with medication adherence results nested within two studies to improve asthma outcomes. Results: 61 RCTs testing interventions to improve asthma outcomes using medication were identified with variable degree of emphasis placed on medication adherence. The systematic review showed that medication adherence can be effectively promoted if it is seen as objective by researchers. However, improvements observed in medication adherence could not be translated into better health outcomes. These contradictory findings could reveal limitations of RCTs to show some effects in clinical epidemiology. Self-reported medication adherence changes observed in the two nested mixed methods studies could be elucidated by differences in their settings as showed by the integration with a patient-centered model that emerged from the interviews with participants.To my knowledge, this is the first investigation that integrates a patient-centered model with self-reported medication adherence to expand our understanding of medication taking behaviours and generate recommendations for future interventions to improve medication adherence in asthma. Conclusion: This thesis shows how inconclusive results of RCTs to test interventions to improve asthma outcomes are not sufficient to provide answers for all questions. The integration of patients’ perspectives into the equation could bring some clarity into the problem and generate possible solutions for the complex phenomenon of medication non-adherence in asthma.

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The value of weekly short message service interventions targeting medication adherence: A multi-national economic evaluation in HIV and tuberculosis infection (2017)

Introduction: The World Health Organization has ambitious goals to eliminate AIDS and TB globally. However, the plan is expensive and financial commitment to achieve this goal is uncertain. Mobile phone-based short message service (SMS) interventions have demonstrated the ability to improve HIV drug therapy adherence. My objective was to evaluate the cost-effectiveness of SMS-based adherence interventions in three settings, which have unique epidemics and health systems, yet struggle with similar adherence barriers. In this thesis, I also consider the value of conducting a cost-effectiveness evaluation before, during and after a randomized trial.Method: This thesis has three parts. First, I evaluated the cost-effectiveness of SMS-based HIV drug adherence interventions in Kenya, where the interventions were first developed. Second, I evaluated the burden of non-adherence and cost sensitivity of SMS-based adherence interventions for latent tuberculosis infection (LTBI) drug therapy in British Columbia, where a trial of an SMS-based adherence intervention is underway. Finally, I evaluated 5,836 combinations of 15 HIV interventions, to understand the role of SMS interventions as part of a combination HIV intervention in India where a trial was being planned. Value was expressed in terms of incremental cost-effectiveness ratios (ICERs), which were a function of incremental costs and quality-adjusted life years (QALYs).Results: In Kenya, the SMS interventions were highly cost-effective in the base case (ICER=$1,389/QALY), and remained cost-effective across most sensitivity analyses. In British Columbia, hypothetical interventions that brought the population to full adherence to LTBI drug therapy could cost up to $450 per person per year and remain cost-effective. SMS interventions were least sensitive to cost and would likely be cost-effective if their efficacy were confirmed. Finally, in India, the SMS interventions were cost saving and were part of 4 of the 5 most efficient combination interventions out of 5,836 possible combinations.Conclusion: The SMS interventions are cost-effective or cost saving when compared to the standard of care in multiple settings. Findings support the implementation of SMS interventions as part of HIV and TB care and suggest they could play an essential role in global containment of these diseases.

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Master's Student Supervision

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

A study of Rwanda's two-way text messaging support for isolated COVID-19 patients during the pandemic: patient use and AI-enhanced conversation analysis (2024)

Background: In Rwanda, a two-way-SMS-based mHealth intervention, WelTel, was deployed to support isolated COVID-19 patients throughout the pandemic. Patients received daily open-ended check-in-messages throughout their isolation period. To inform further health system digitalization, we sought to quantify WelTel enrollment, assess patients’ usage patterns, and explore how patient characteristics influence such behaviours. We further sought to investigate patient isolation experiences by AI-enhanced-analysis (Natural Language Processing (NLP)) of patient-clinician conversations, to improve similar programs.Methods: WelTel registration and messaging records were extracted, supplemented with Rwanda Ministry of Health data, and quantified. Patient use (≥1 conversation) was computed and compared across sociodemographic groups (sex, age, province, COVID-19-status, pandemic-wave) using logistic regression. Conversation counts and characteristics (language, messages/conversation) were quantified alongside patient communication behaviours (conversations/user, response-times) which were also compared across sociodemographic groups using non-parametric tests. To understand isolation experiences, conversations were sampled (n=2,791/12,119), English-translated (as necessary), topic-labelled, language-restored, and used to train single-topic classifiers (Traditional-ML/Transformer architectures). Best-performing models meeting a F1≥0.7 cutoff were applied to unlabeled conversations. Topic prevalence and sociodemographic differences were assessed in human-labelled, and human-and-machine- labelled corpora using logistic regression.Results: Rwanda registered 33,081 individuals in WelTel (March 2020-March 2022). Of those, 18% (n=6,021) used WelTel, with variation by sex, COVID-19-status, province, and pandemic-wave (p
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Examining patient's mobile phone access and planning a virtual care intervention using mHealth and conversation analytics (2021)

Introduction: Unplanned hospital readmissions create stress for patients and their families while placing individuals at risk for negative outcomes and increasing healthcare system costs. Development of effective interventions to reduce readmissions involves timely discharge planning, transitional care, and stakeholder uptake. Mobile health (mHealth) and machine learning technology may help improve coordination of care, identify the underlying reasons for complications, and potentially reduce readmissions.Methods: To determine whether mHealth can help streamline and improve transitional care after discharge from the hospital, we will utilize a two-way text messaging virtual care platform to be piloted at the medical wards in the Vancouver General Hospital (VGH) Clinical Teaching Unit (CTU). Prior to launching the program, we conducted a survey of patients admitted to the CTU to determine mobile phone access, usage, and preferences to better understand the population we wish to serve. Using this information, we designed an mHealth intervention protocol that is patient-centered and collaborative.Results: We found that a two-way text messaging mHealth platform would likely be well-placed to facilitate better transitional care and to understand the underlying reasons for readmissions. Our survey results indicated that 86% of participants had access to a mobile phone, 63% of whom owned their own device and 23% of whom had access via a proxy (e.g., family or caregiver). These findings indicate that most patients can participate in mHealth interventions that rely on mobile phones and that engaging a proxy may further expand inclusivity. Lastly, we conducted training sessions and consulted with hospital staff to ensure the study protocol meets end-user needs and preferences. Using these findings, we developed a framework that utilizes natural language processing (NLP) and machine learning to analyze patient text message conversations with their health care provider (HCP).Conclusion: Our findings suggest that mHealth virtual care platforms are feasible and accessible in a hospital setting, which may help in reducing the burden of hospital readmission on patients, their families, and the health care system.

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News Releases

This list shows a selection of news releases by UBC Media Relations over the last 5 years.

Publications

 
Richard Lester's Profile
Scopus Profile
Other link
Supervision Enquiry

Membership Status

Member of G+PS
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Location

Vancouver General Hospital

Program Affiliations

Experimental Medicine

Academic Unit(s)

Division of Infectious Diseases
 

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