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Desi Small-Rodriguez
Desi Small-Rodriguez, PhD, is an Assistant Professor of Sociology and American Indian Studies at the University of California, Los Angeles. As a social demographer, she applies critical quantitative and mixed methods to research at the intersection of race, indigeneity, data, and inequality. An indigenous woman (Northern Cheyenne and Chicana), Small-Rodriguez specializes in survey research in partnership with Indigenous communities and other marginalized populations. She grounds her research in Indigenous studies, sociology of race and ethnicity, political sociology, sociology of knowledge, critical demography, health policy research, and science and technology studies. She directs the Data Warriors Lab, which is an Indigenous social science laboratory that connects researchers, students and Indigenous communities to build data that support "strong self-determined Indigenous futures."

 

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Desi Small-Rodriguez, PhD Assistant Professor, Sociology and American Indian Studies, UCLA
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Cover of the journal Social Indicators Research
This study investigates the strength and significance of the associations of health workforce with multiple health outcomes and COVID-19 excess deaths across countries, using the latest WHO dataset.

Multiple log-linear regression analyses, counterfactual scenarios analyses, and Pearson correlation analyses were performed. The average density of health workforce and the average levels of health outcomes were strongly associated with country income level. A higher density of the health workforce, especially the aggregate density of skilled health workers and density of nursing and midwifery personnel, was significantly associated with better levels of several health outcomes, including maternal mortality ratio, under-five mortality rate, infant mortality rate, and neonatal mortality rate, and was significantly correlated with a lower level of COVID-19 excess deaths per 100K people, though not robust to weighting by population.

The low density of the health workforce, especially in relatively low-income countries, can be a major barrier to improving these health outcomes and achieving health-related Sustainable Development Goals (SDGs); however, improving the density of the health workforce alone is far from enough to achieve these goals. Our study suggests that investment in health workforce should be an integral part of strategies to achieve health-related SDGs, and that achieving non-health SDGs related to poverty alleviation and expansion of female education are complementary to achieving both sets of goals, especially for those low- and middle-income countries. In light of the strains on the health workforce during the current COVID-19 pandemic, more attention should be paid to health workforce to strengthen health system resilience and long-term improvement in health outcomes.

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Social Indicators Research
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Karen Eggleston
Jinlin Liu
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We conducted a cluster-randomized trial to measure the effect of community-level mask distribution and promotion on symptomatic SARS-CoV-2 infections in rural Bangladesh from November 2020 to April 2021 (N = 600 villages, N = 342,183 adults). We cross-randomized mask type (cloth vs. surgical) and promotion strategies at the village and household level. Proper mask-wearing increased from 13.3% in the control group to 42.3% in the intervention arm (adjusted percentage point difference = 0.29 [0.26, 0.31]). The intervention reduced symptomatic seroprevalence (adjusted prevalence ratio (aPR) = 0.91 [0.82, 1.00]), especially among adults 60+ years in villages where surgical masks were distributed (aPR = 0.65 [0.45, 0.85]). Mask distribution and promotion was a scalable and effective method to reduce symptomatic SARS-CoV-2 infections.

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A randomized trial of community-level mask promotion in rural Bangladesh during COVID-19 shows that the intervention increased mask-use and reduced symptomatic SARS-CoV-2 infections.

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Innovations for Poverty Action
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Stephen P. Luby
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Noa Ronkin
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As the COVID-19 pandemic remains a crucial global public health threat, pandemic control measures such as lockdowns and mobility restrictions continue to disrupt the provision of health services, leading to reduced healthcare use. Indeed, evidence shows the pandemic has emerged as a particular challenge for people with chronic conditions such as diabetes and hypertension. Yet there is limited data comparing the pandemic’s impact on access to care and the severity of chronic disease symptoms at the population level across Asia.

Now a new collaborative study, published by the Asia Pacific Journal of Public Health, addresses this limitation. The study co-authors, including APARC’s Asia Health Policy Program Director and FSI Senior Fellow Karen Eggleston, offer the first report comparing the impacts of the COVID-19 pandemic and its associated mobility restrictions on people with chronic conditions at different stages of socio-demographic and economic transitions in five Asian regions — India, China, Hong Kong, Korea, and Vietnam.

The findings show that the pandemic has disproportionately disrupted healthcare access and worsened diabetes symptoms among marginalized and rural populations in Asia. Moreover, the pandemic’s broad social and economic impact has adversely affected population health well beyond those directly suffering from COVID-19, with the resulting delayed and foregone care leading to uncertain longer-term effects.


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Unintended Adverse Consequences

Routine screening, risk factor control, and continuity of care for non-communicable diseases are a global challenge. The COVID-19 pandemic has exacerbated the challenge even further. Existing reports show the pandemic has particularly adverse impacts on essential prevention and treatment services for people with chronic conditions. These reductions in health services arose from pandemic-associated factors such as mobility restrictions, lack of public transport, and lack of health workforce.

Eggleston and a group of colleagues set out to provide evidence on how the pandemic has impacted chronic disease care in diverse settings across Asia during COVID-19-related lockdowns. Using standardized questionnaires, the researchers surveyed 5672 participants aged 55.9 to 69.3 years with chronic conditions in India, China, Hong Kong, Korea, and Vietnam. The researchers collected data on participants’ demographic and socio-economic status, comorbidities, access to healthcare, employment status, difficulty in accessing medicines due to financial and nonfinancial (COVID-19 related) reasons, treatment satisfaction, and severity of their chronic condition symptoms.

If no immediate actions are taken to mitigate pandemic impacts, the Asia-Pacific region will struggle to achieve the 2030 Sustainable Development Goal target 3.4 to reduce premature mortality from non-communicable diseases […] and to promote mental health and wellbeing.
Karen Eggleston et al.

The results show that the pandemic’s broad social and economic impact has adversely affected population health well beyond those directly suffering from COVID-19. Study participants with chronic conditions faced significant challenges in managing their symptoms during the pandemic. They experienced a loss of income and difficulties in accessing healthcare or medications, with the resulting delayed and foregone care leading to uncertain longer-term effects. For a nontrivial portion of participants, these factors are associated with the worsening of diabetes symptoms. The threat is twofold among people living in rural populations with limited access, availability, and affordability of healthcare services.

A Global Health Priority

The unintended adverse consequences of the COVID-19 pandemic on chronic disease care may also further aggravate inequality in health outcomes. “If the trend continues and no immediate actions are taken to mitigate pandemic impacts,” Eggleston and her colleagues caution, then “the Asia-Pacific region will struggle to achieve the 2030 Sustainable Development Goal (SDG) target 3.4 to reduce premature mortality from non-communicable diseases by a third relative to 2015 levels and to promote mental health and wellbeing.”

Addressing the pandemic’s unintended negative social and economic impacts on chronic disease care is a global health priority, determine the researchers. They propose several measures to help provide timely care for people with chronic conditions in resource-constrained settings. These include implementing innovations in healthcare delivery models to improve the adoption of healthy lifestyle changes and self-management of chronic disease and mild COVID-19 symptoms, increasing investment in interventions to provide social and economic support to disadvantaged populations, and strengthening primary healthcare infrastructure and support of healthcare providers.

The study was supported in part by funding from Shorenstein APARC’s faculty research award, Stanford King Center for Global Development, and a seed grant from the Stanford Center for Asian Health Research and Education.

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Strengthening the Frontline: How Primary Health Care Improves Net Value in Chronic Disease Management

Empirical evidence by Karen Eggleston and colleagues suggests that better primary health care management of chronic disease in rural China can reduce spending while contributing to better health.
Strengthening the Frontline: How Primary Health Care Improves Net Value in Chronic Disease Management
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A New Validated Tool Helps Predict Lifetime Health Outcomes for Prediabetes and Type 2 Diabetes in Chinese Populations

A research team including APARC's Karen Eggleston developed a new simulation model that supports the economic evaluation of policy guidelines and clinical treatment pathways to tackle diabetes and prediabetes among Chinese and East Asian populations, for whom existing models may not be applicable.
A New Validated Tool Helps Predict Lifetime Health Outcomes for Prediabetes and Type 2 Diabetes in Chinese Populations
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Bargaining Behind Closed Doors: Why China’s Local Government Debt Is Not a Local Problem

New research in 'The China Journal' by APARC’s Jean Oi and colleagues suggests that the roots of China’s massive local government debt problem lie in secretive financing institutions offered as quid pro quo to localities to sustain their incentive for local state-led growth after 1994
Bargaining Behind Closed Doors: Why China’s Local Government Debt Is Not a Local Problem
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In the first report of its kind comparing the impacts of the pandemic on people with chronic conditions in five Asian regions, researchers including APARC’s Karen Eggleston document how the pandemic’s broad social and economic consequences negatively affected population health well beyond those directly suffering from COVID-19.

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Cover of Issue 34(1) of Asia Pacific Journal of Public Health, January 2022
This study aims to provide evidence on how the COVID-19 pandemic has impacted chronic disease care in diverse settings across Asia. Cross-sectional surveys were conducted to assess the health, social, and economic consequences of the pandemic in India, China, Hong Kong, Korea, and Vietnam using standardized questionnaires.

Overall, 5672 participants with chronic conditions were recruited from 5 countries. The mean age of the participants ranged from 55.9 to 69.3 years. A worsened economic status during the COVID-19 pandemic was reported by 19% to 59% of the study participants. Increased difficulty in accessing care was reported by 8% to 24% of participants, except Vietnam: 1.6%. The worsening of diabetes symptoms was reported by 5.6% to 14.6% of participants, except Vietnam: 3%. In multivariable regression analyses, increasing age, female participants, and worsened economic status were suggestive of increased difficulty in access to care, but these associations mostly did not reach statistical significance. In India and China, rural residence, worsened economic status and self-reported hypertension were statistically significantly associated with increased difficulty in access to care or worsening of diabetes symptoms.

These findings suggest that the pandemic disproportionately affected marginalized and rural populations in Asia, negatively affecting population health beyond those directly suffering from COVID-19.

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Asia Pacific Journal of Public Health
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Karen Eggleston
Kavita Singh
Yiqian Xin
Yuyin Xiao
Jianchao Quan
Daejung Kim
Thi-Phuong-Lan Nguyen
Dimple Kondal
Xinyi Yan
Guohong Li
Carmen S. Ng
Hyolim Kang
Hoang Minh Nam
Sailesh Mohan
Lijing L. Yan
Chenshu Shi
Jiayin Chen
Hoa Thi Hong Hanh
Viswanathan Mohan
Sandra Kong
Shorenstein APARC Encina Hall E301 Stanford University
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Visiting Scholar at APARC, 2021-2022
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Dr. Cynthia Chen joined the Walter H. Shorenstein Asia-Pacific Research Center (APARC) as visiting scholar with the Asia Health Policy Program during the 2022 winter and spring quarters. She is an Assistant Professor at the National University of Singapore (NUS). Her current research focuses on the well-being and older adults, healthcare financing, and the economics of ageing. She is interested in how demographic, economic and social changes can affect the burden of care, financing needs and optimal resource allocation in the future. Her research has been supported by the Singapore’s Ministry of Health, Ministry of Education, the US National Institutes of Aging, and the Thai Health Promotion Foundation among others. To date, she has published more than 45 internationally peer-reviewed journals on societal ageing, the burden of chronic diseases, and cost-effectiveness research. Dr. Chen obtained her Ph.D. in Public Health, Masters and BSc in Statistics from NUS.

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Jason Wang and his team working on a project to prevent preterm births received a $150,000 grant from the Richard King Mellon Foundation to complete their randomized control trial testing a digital app that tries to prevent recurrent preterm births.

PretermConnect uses a digital strategy for prevention and follow-up of preterm births in Allegheny County, PA, to optimize the health and well-being of mothers and children. Instead of the standard care, Stanford Health Policy is collaborating with the University of Pittsburg Medical Center (UPMC) in the randomized control trial with women who have delivered a preterm baby. The women are invited to participate and then randomly put into the group that uses the digital or a control group who received paper-based discharge packets with supplemental health education on postpartum care.

“This grant allows us to continue recruiting participants through UPMC and expanding PretermConnect’s features to enhance user engagement, including a function to search for resources by geography and topic,” said Wang, MD, a professor of pediatrics and health policy. “We also intend to scale the project with additional content on high-risk infant follow-up and preterm-specific developmental care guidelines, additional engagement features — and eventually support for different languages, starting with Spanish.”

In the long term, we hope to see an overall decrease in infant morbidity and mortality, by way of reducing preterm births.
Jason Wang
Professor of Pediatrics and Health Policy

The women in the digital app group receive in-app health education and resources to improve well-being for mothers and their infants. The app includes a social interaction feature designed to foster social connections and promote self-care. They have enrolled 30 women during the pilot phase and 15 mother-infant dyads in the randomized control trial, with a goal of reaching 250.

“The digital approach also allows us to administer brief surveys and gather information on dynamic social determinants of health more frequently than can be done through traditional means,” said Shilpa Jani, an SHP project manager. She said social determinants of health — such as persistent housing instability, food insecurity and concerns of personal safety — contribute to chronic stress and health issues as well as an increased risk of pregnancy and birth complications.

“Adverse effects of social determinants of health along with health complications of preterm deliveries may exacerbate morbidities for the mother and child,” Jani said, adding that preterm-related causes of death accounted for two-thirds of infant deaths in 2019 in the United States.

Wang and Jani said the immediate project goals include increasing health education for preterm baby care, improving postpartum maternal health, and encouraging usage of local resources in Allegheny County. They eventually hope to see reductions in risk for subsequent preterm delivery and infant mortality and postpartum depression, as well as increases in mother-infant bonding and larger proportions of breastmilk feeding.

Jason Wang Stanford Health Policy

Jason Wang

Professor of Pediatrics and Health Policy
Develops tools for assessing and improving the quality of health care
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Shilpa Jani

Shilpa Jani

Research Data Analyst
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New Study Shows Support for Paid Family Leave Grew During Pandemic

In a blow to arguments that a federal paid leave law would harm small businesses, a new study co-authored by SHP's Maya Rossin-Slater finds that support for paid leave among small employers is not only strong, but also increased as the pandemic added new strain to the work-life juggle.
New Study Shows Support for Paid Family Leave Grew During Pandemic
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Babies Born Too Early Likely to Face Educational and Lifelong Behavioral Setbacks

SHP's Lee Sanders and his Stanford colleagues found that after adjusting for socioeconomic status and compared with full-term births, moderate and late preterm births are associated with increased risk of low performance in mathematics and English language arts, as well as chronic absenteeism and suspension from school.
Babies Born Too Early Likely to Face Educational and Lifelong Behavioral Setbacks
COVID Contact Tracing
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Contact-tracing App Curbed Spread of COVID in England and Wales

SHP's Jason Wang writes in this Nature article that digital contact tracing has the potential to limit the spread of COVID-19.
Contact-tracing App Curbed Spread of COVID in England and Wales
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SHP researchers awarded grant to continue their clinical trial testing out a digital app they hope will prevent preterm births.

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Noa Ronkin
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While the coronavirus pandemic has captured the world’s attention, non-communicable chronic diseases (NCDs) such as hypertension, heart diseases, and diabetes continue to be the leading cause of mortality worldwide, accounting for about two-thirds of deaths globally. Their financial and social burden is also immense, as individuals with chronic diseases face high medical spending, limited ability to work, and financial insecurity. Primary health care (PHC) is a crucial avenue for managing and preventing chronic diseases, yet many health systems, especially in low- and middle-income countries (LMICs), lack robust primary health care settings. How can policymakers improve PHC to reduce illness and death from chronic diseases?

There is little rigorous evidence from LMICs about the effectiveness of programs seeking to improve the capacity of PHC for controlling chronic disease. Now a new study, published by the Journal of Health Economics, helps fill in this gap. It offers empirical evidence on China’s efforts to promote PHC management, showing that better PHC management of chronic diseases in rural areas can reduce spending while contributing to better health. We sat down with APARC’s Asia Health Policy Program Director Karen Eggleston, one of the study co-authors, to discuss the research and its implications beyond China. Watch:

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Challenges for Primary Health Care Services

China, a large and rapidly developing middle-income country with a hospital-based service delivery system for its aging population, makes a suitable case study of efforts to promote PHC management. Over the past several decades, PHC use in China has significantly decreased relative to hospital-based care. This trend is a natural consequence of the country’s unprecedented increases in living standards and improvements in financial risk protection, which increase patients’ demand for quality care and spur self-referral to providers with higher-perceived quality like hospital outpatient departments.

The performance differences between PHC and hospital-based care are especially stark in China’s rural areas, where management of chronic diseases relies heavily on grassroots physicians, who have limited medical education and training. That is why Eggleston and her colleagues set out to provide new empirical evidence about the effectiveness of a program that promotes PHC management of hypertension and diabetes for rural Chinese. Part of the National Basic Public Health Service Program for rural Chinese, it financially rewards PHC grassroots physicians for managing residents with chronic diseases.

Collaborative Research in the Era of Great Power Competition

Eggleston’s co-authors include her colleagues at the Zhejiang Provincial Center for Disease Control and Prevention (Zhejiang CDC). Their study is the culmination of Eggleston’s multiyear collaborative research project with the Zhejiang CDC team, "Addressing Health Disparities in China," which looks to Tongxiang county in Zhejiang as a case study of China's responses to healthcare inequalities and population aging challenges in rural and urban areas. The project also involved two Stanford doctoral students who worked with Eggleston.

The team worked together to develop the quantitative analysis even during a time of sometimes-tense bilateral relations. “We found it very important to be able to communicate directly and collaborate on an important question not only for rural China but for many other parts of the world,” says Eggleston.
Karen Eggleston speaking to staff at Zhejiang Provincial CDC, China
Eggleston with her colleagues at the Zhejiang CDC during a field visit in 2018.

“This kind of collaboration, where we utilize the data that's available to answer an important question while respecting the privacy of the individuals and hopefully delivering benefits to them through more effective or affordable programs in the future perhaps is a promising model for researchers here and elsewhere to undertake,” she notes.

Disentangling the Effect of Primary Health Care Management

To study the program’s effectiveness, the researchers assembled a unique dataset linking individual-level administrative and health information between 2011 and 2015 for rural Chinese diagnosed with hypertension or diabetes in Tongxiang, a mostly rural county of Zhejiang province in southeast China. Collected by the Tongxiang CDC and Zhejiang CDC, the compiled database links basic demographic information, health insurance claims, PHC service logs, and health check-up records — four sets of data that are rarely linked and analyzed in combination in China healthcare research.

Focusing on neighboring border-straddling villages allows us to use only variation in PHC management within pairs of neighboring villages to identify the effect.
Karen Eggleston

Targeting the program’s effects on healthcare utilization, spending, and health outcomes, Eggleston and her colleagues compare residents in neighboring villages that straddle township boundaries. These residents are similar in their individual and environmental characteristics that shape health care use but are subject to different PHC management practices. This “border sampling” allows the researchers to disentangle the effects of PHC management from other underlying spatial differences that impact health care utilization. For each township, the researchers use a management intensity index that reflects the cumulative efforts of PHC physicians to screen their communities and keep patients within the PHC management programs for controlling hypertension and diabetes. Each township’s experience with PHC management over the 5-year study period is thus a case study for rural China.

Net Value in Chronic Disease Management

The results are encouraging for China's investment in primary care management of chronic diseases. Eggleston and her colleagues find that patients residing in a village within a township with more intensive PHC management had a relative increase in PHC visits, fewer specialist visits, fewer hospital admissions, and lower spending compared to neighbors with less intensive management. They also tend to have better medication adherence and better health outcomes as measured by blood pressure control.

If we can gradually scale up these kinds of effective programs at primary care then we can build more resilient, cost-effective, affordable health care systems for populations in many different settings.
Karen Eggleston

The results suggest that PHC chronic disease management in rural China improves net value in multiple ways — increasing PHC utilization, reducing avoidable hospitalizations, decreasing medical spending, and improving intermediate- and long-run health outcomes — all while leveraging existing resources rather than restricting care.

The findings also help inform investments in primary health care in LMICs. They highlight the latent potential of frontline healthcare workers in such settings to be more productive and show that financially rewarding these grassroots workers for managing residents with chronic diseases helps improve health outcomes. Moreover, they offer empirical evidence that supports the effectiveness of chronic disease management programs as part of broader regional initiatives to address population health.

Read the study by Eggleston et al

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In China, Better Financial Coverage Increases Health Care Access and Utilization

Research evidence from China’s Tongxiang county by Karen Eggleston and colleagues indicates that enhanced financial coverage for catastrophic medical expenditures increased health care access and expenditures among resident insurance beneficiaries while decreasing out-of-pocket spending as a portion of total spending.
In China, Better Financial Coverage Increases Health Care Access and Utilization
Closeup on hands holding a glucometer
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A New Validated Tool Helps Predict Lifetime Health Outcomes for Prediabetes and Type 2 Diabetes in Chinese Populations

A research team including APARC's Karen Eggleston developed a new simulation model that supports the economic evaluation of policy guidelines and clinical treatment pathways to tackle diabetes and prediabetes among Chinese and East Asian populations, for whom existing models may not be applicable.
A New Validated Tool Helps Predict Lifetime Health Outcomes for Prediabetes and Type 2 Diabetes in Chinese Populations
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Robotics and the Future of Work: Lessons from Nursing Homes in Japan

On the Future Health podcast, Karen Eggleston discusses the findings and implications of her collaborative research into the effects of robot adoption on staffing in Japanese nursing homes.
Robotics and the Future of Work: Lessons from Nursing Homes in Japan
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Empirical evidence by Karen Eggleston and colleagues suggests that better primary health care management of chronic disease in rural China can reduce spending while contributing to better health.

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Sherri Rose, PhD  is an Associate Professor of Health Policy at the Stanford School of Medicine and Co-Director of the Health Policy Data Science Lab. Her research is centered on developing and integrating innovative statistical machine learning approaches to improve human health and health equity. Within health policy, Dr. Rose works on risk adjustment, ethical algorithms in health care, comparative effectiveness research, and health program evaluation. She has published interdisciplinary projects across varied outlets, including BiometricsJournal of the American Statistical AssociationJournal of Health EconomicsHealth Affairs, and New England Journal of Medicine. In 2011, Dr. Rose coauthored the first book on machine learning for causal inference, with a sequel text released in 2018. She has been Co-Editor-in-Chief of the journal Biostatistics since 2019.

Dr. Rose has been honored with an NIH Director's New Innovator Award, the ISPOR Bernie J. O'Brien New Investigator Award, and multiple mid-career awards, including the Gertrude M. Cox Award and the Mortimer Spiegelman Award, the nation’s highest honor in biostatistics, given to a statistician younger than 40 who has made the most significant contributions to public health statistics. She was named a Fellow of the American Statistical Association in 2020 and received the 2021 Mortimer Spiegelman Award, which recognizes the statistician under age 40 who has made the most significant contributions to public health statistics. Her research has been featured in The New York Times, USA Today, and The Boston Globe. 

Title: New and Ongoing Projects at the Interface of Machine Learning for Health Policy

 

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Sherri Rose, PhD, is a Professor of Health Policy and Director of the Health Policy Data Science Lab at Stanford University. Her research is centered on developing and integrating innovative statistical machine learning approaches to improve human health and health equity. Within health policy, Dr. Rose works on ethical algorithms in health care, risk adjustment, chronic kidney disease, and health program evaluation. She has published interdisciplinary projects across varied outlets, including Biometrics, Journal of the American Statistical Association, Journal of Health Economics, Health Affairs, and New England Journal of Medicine. In 2011, Dr. Rose co-authored the first book on machine learning for causal inference, with a sequel text released in 2018.

Dr. Rose has been honored with an NIH Director’s Pioneer Award, NIH Director's New Innovator Award, the ISPOR Bernie J. O'Brien New Investigator Award, and multiple mid-career awards, including the Gertrude M. Cox Award. She is a Fellow of the American Statistical Association and received the Mortimer Spiegelman Award, which recognizes the statistician under age 40 who has made the most significant contributions to public health statistics. In 2024, she was recognized with both the ASHEcon Willard G. Manning Memorial Award for Best Research in Health Econometrics and the American Statistical Association Outstanding Statistical Application Award. Her research has been featured in The New York Times, USA Today, and The Boston Globe. She was Co-Editor-in-Chief of the journal Biostatistics from 2019-2023.

She received her PhD in Biostatistics from the University of California, Berkeley and a BS in Statistics from The George Washington University before completing an NSF Mathematical Sciences Postdoctoral Research Fellowship at Johns Hopkins University. 

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Title: Customer Discrimination and Quality Signals: A Field Experiment with Healthcare Shoppers

Abstract: This paper provides evidence that customer discrimination in the market for doctors can be largely accounted for by statistical discrimination. I evaluate customer preferences in the field with an online platform where cash-paying consumers can shop and book a provider for medical procedures based on an experimental paradigm called validated incentivized conjoint analysis (VIC). Customers evaluate doctor options they know to be hypothetical to be matched with a customized menu of real doctors, preserving incentives. Racial discrimination reduces patient willingness-to-pay for black and Asian providers by 12.7% and 8.7% of the average colonoscopy price respectively; customers are willing to travel 100–250 miles to see a white doctor instead of a black doctor, and somewhere between 50–100 to 100–250 miles to see a white doctor instead of an Asian doctor. Further, providing signals of provider quality reduces this willingness-to-pay racial gap by about 90%, which suggests that statistical discrimination is an important cause of the gap. Actual booking behavior allows cross-validation of incentive compatibility of stated preference elicitation via VIC. 

Alex Chan, MPH

Alex Chan is a PhD candidate in Health Economics, and a Gerhard Casper Stanford Graduate Fellow. He has research interests in health economics, experimental economics, market design, and labor economics. His projects look at the causes and consequences of discrimination and diversity in medicine, U.S. Health Policy (especially organ transplantation), and market design in health policy and medicine. He holds an MPH from Harvard University. Before Stanford, he developed extensive experience in the healthcare industry starting as a McKinsey consultant, and most recently as Senior Vice President of Market Strategy with Optum/UnitedHealth before joining academia.

Personal Website: https://www.alexchan.net 

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PhD Candidate in Health Economics Department of Health Policy, Stanford University
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