Health and Medicine

FSI’s researchers assess health and medicine through the lenses of economics, nutrition and politics. They’re studying and influencing public health policies of local and national governments and the roles that corporations and nongovernmental organizations play in providing health care around the world. Scholars look at how governance affects citizens’ health, how children’s health care access affects the aging process and how to improve children’s health in Guatemala and rural China. They want to know what it will take for people to cook more safely and breathe more easily in developing countries.

FSI professors investigate how lifestyles affect health. What good does gardening do for older Americans? What are the benefits of eating organic food or growing genetically modified rice in China? They study cost-effectiveness by examining programs like those aimed at preventing the spread of tuberculosis in Russian prisons. Policies that impact obesity and undernutrition are examined; as are the public health implications of limiting salt in processed foods and the role of smoking among men who work in Chinese factories. FSI health research looks at sweeping domestic policies like the Affordable Care Act and the role of foreign aid in affecting the price of HIV drugs in Africa.

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Objective

To determine whether the Supplemental Nutrition Assistance Program (SNAP), which addresses food insecurity, can reduce health care expenditures.

Main Outcomes and Measures

Total health care expenditures (all paid claims and out-of-pocket costs) in the 2012-2013 period. To test whether SNAP participation was associated with lower subsequent health care expenditures, we used generalized linear modeling (gamma distribution, log link, with survey design information), adjusting for demographics (age, gender, race/ethnicity), socioeconomic factors (income, education, Social Security Disability Insurance disability, urban/rural), census region, health insurance, and self-reported medical conditions.We also conducted sensitivity analyses as a robustness check for these modeling assumptions.

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JAMA Internal Medicine
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Encina Commons Room 114, 615 Crothers Way, Stanford, CA 94305-6006
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Professor, Health Policy
Senior Fellow, Freeman Spogli Institute for International Studies
josh_salomon-headshot_2023.jpg PhD

Joshua Salomon is a Professor of Health Policy in the Department of Health Policy at Stanford School of Medicine, Senior Fellow in the Freeman Spogli Institute for International Studies, and founding Director of the Prevention Policy Modeling Lab. Trained in health policy and decision science, Dr. Salomon leads multidisciplinary research teams dedicated to producing rigorous, actionable evidence to improve the public’s health and reduce health disparities. His work — supported by the National Institutes of Health, Centers for Disease Control and Prevention, and the Bill & Melinda Gates Foundation — combines data synthesis and mathematical modeling to measure and forecast health outcomes and evaluate public health programs and strategies, with particular emphasis on infectious diseases. He has spearheaded methodological innovation in measurement and valuation of health, infectious disease modeling and forecasting, and cost-effectiveness analysis. His applied modeling work on HIV/AIDS, tuberculosis, viral hepatitis, COVID-19 and other major health challenges informs local, state, national and international policies to improve health and wellbeing, particularly among under-served populations in the United States and around the world.  

Dr. Salomon established the multi-institution Prevention Policy Modeling Lab in 2014 to conduct health and economic modeling that guides reasoned public health decision-making relating to infectious disease. He has co-authored more than three hundred original peer-reviewed research articles and mentored dozens of graduate and post-graduate trainees in health policy, medicine and public health. Prior to joining the Stanford Faculty, Dr. Salomon served as a policy analyst in the Department of Evidence and Information for Policy at the World Health Organization in Geneva, and as Professor of Global Health at Harvard T.H. Chan School of Public Health. As Associate Chair for Academic Affairs and Strategy in the Department of Health Policy at Stanford, he works on faculty recruitment and development, and leads strategic initiatives to promote interdisciplinary collaborative research, practice partnerships and policy translation.

Collaboration

In this recent Stanford Report article, Salomon talks about how he helped gather faculty, trainees, and other researchers from Stanford and elsewhere to lend expertise in infectious disease modeling and data analytics in hopes of informing the public health response to the COVID-19 pandemic locally and nationwide. This quickly-assembled unit used county data to build models that were updated in real-time and shared with county epidemiologists to track the impact of the epidemic, underlying transmission trends, and potential effectiveness of public health measures.

The unit also advised county epidemiologists on developing their own models for planning and envisioning different scenarios. “In the early weeks especially, we were learning more about the virus every day,” Salomon explained, “but we hadn’t yet seen the first peak of what would eventually turn into multiple waves, so there was a lot of uncertainty about when that peak might arrive, how high it could be, and what would happen next.”

Read Stanford Report Article

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Objective

To systematically review and meta-analyze evidence of nonpharmacological interventions for postoperative pain management after total knee arthroplasty. 

Results 

Of 5509 studies, 39 randomized clinical trials were included in the meta-analysis (2391 patients). The most commonly performed interventions included continuous passive motion, preoperative exercise, cryotherapy, electrotherapy, and acupuncture. Moderate-certainty evidence showed that electrotherapy reduced the use of opioids (mean difference, −3.50; 95% CI, −5.90 to −1.10 morphine equivalents in milligrams per kilogram per 48 hours; P = .004; I 2 = 17%) and that acupuncture delayed opioid use (mean difference, 46.17; 95% CI, 20.84 to 71.50 minutes to the first patient-controlled analgesia; P < .001; I 2 = 19%). There was low-certainty evidence that acupuncture improved pain (mean difference, −1.14; 95% CI, −1.90 to −0.38 on a visual analog scale at 2 days; P = .003; I 2 = 0%). Very low-certainty evidence showed that cryotherapy was associated with a reduction in opioid consumption (mean difference, −0.13; 95% CI, −0.26 to −0.01 morphine equivalents in milligrams per kilogram per 48 hours; P = .03; I 2 = 86%) and in pain improvement (mean difference, −0.51; 95% CI, −1.00 to −0.02 on the visual analog scale; P < .05; I 2 = 62%). Low-certainty or very low-certainty evidence showed that continuous passive motion and preoperative exercise had no pain improvement and reduction in opioid consumption: for continuous passive motion, the mean differences were −0.05 (95% CI, −0.35 to 0.25) on the visual analog scale (P = .74; I 2 = 52%) and 6.58 (95% CI, −6.33 to 19.49) opioid consumption at 1 and 2 weeks (P = .32, I 2 = 87%), and for preoperative exercise, the mean difference was −0.14 (95% CI, −1.11 to 0.84) on the Western Ontario and McMaster Universities Arthritis Index Scale (P = .78, I 2 = 65%). CONCLUSIONS AND RELEVANCE In this meta-analysis, electrotherapy and acupuncture after total knee arthroplasty were associated with reduced and delayed opioid consumption.

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JAMA Surgery
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Steven M. Asch
Tina Hernandez-Boussard
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Capitated payments in the form of fixed monthly payments to cover all of the costs associated with delivering primary care could encourage primary care practices to transform the way they deliver care. Using a microsimulation model incorporating data from 969 US practices, we sought to understand whether shifting to team- and non-visit-based care is financially sustainable for practices under traditional fee-for-service, capitated payment, or a mix of the two. Practice revenues and costs were computed for fee-for-service payments and a range of capitated payments, before and after the substitution of team- and non-visit-based services for low-complexity in-person physician visits. The substitution produced financial losses for simulated practices under fee-for-service payment of $42,398 per full-time-equivalent physician per year; however, substitution produced financial gains under capitated payment in 95 percent of cases, if more than 63 percent of annual payments were capitated. Shifting to capitated payment might create an incentive for practices to increase their delivery of team- and non-visit-based primary care, if capitated payment levels were sufficiently high.
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Health Affairs
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With nearly half of U.S. births occurring out of wedlock, understanding how parents navigate their relationship options is important. This paper examines the consequences of a large exogenous change to parental relationship contract options on parental behavior and child well-being. Identification comes from the staggered timing of state reforms that substantially lowered the cost of legal paternity establishment. I show that the resulting increases in paternity establishment are partially driven by reductions in parental marriage. Although unmarried fathers become more involved with their children along some dimensions, the net effects on father involvement and child well-being are negative or zero.

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America Economic Journal: Applied Economics
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Maya Rossin-Slater
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This paper examines the long-term impacts of early childhood exposure to air pollution on adult outcomes using U.S. administrative data. We exploit changes in air pollution driven by the 1970 Clean Air Act to analyze the difference in outcomes between cohorts born in counties before and after large improvements in air pollution relative to those same cohorts born in counties that had no improvements. We find a significant relationship between pollution exposure in the year of birth and later life outcomes. A higher pollution level in the year of birth is associated with lower labor force participation and lower earnings at age 30.

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Journal of Political Economy
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Maya Rossin-Slater
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3

Title: Optimal Clinical Trials for Personalizing Medical Care: The Expected Value of Oversampling Information

Abstract: Personalizing patient care frequently involves selecting treatments based on risk predictions, with patients at lower risk being recommended less aggressive treatment or no treatment at all. Because risk predictions are uncertain, treatments selected based on them may not be optimal. Collecting additional information could, therefore, be valuable. Designing studies to collect the needed information most efficiently is important given that studies have become increasingly expensive to conduct. Methods exist to support such endeavors (i.e., expected value of sample information (EVSI)). However, to date, EVSI calculations consider only studies that estimate overall population means efficiently. Studies to support the personalization of medical care require deciding how much information to collect about which patient subgroups: on which locations along the risk spectrum should studies focus? We develop the Expected Value of Oversampling Information (EVOSI) framework by introducing EVSI into a previously proposed Expected Value of Individualized Care (EVIC) framework, narrowing prediction uncertainty where doing so maximally increases the overall value of individualized treatment choices. With the EVOSI framework, we analyze the features of patient risk subgroups that increase the value of oversampling and conduct numerical simulations to consider trade-offs between these features (i.e., how much to oversample). Results show that studies designed with EVOSI can be expected to achieve more value than those designed with EVSI at a given sample size or the same expected value as EVSI at a smaller sample size. Features that determine optimal oversampling in EVOSI include: subgroup prevalence; one’s priors on the relative distance to the threshold risk at which one should initiate treatment for each subgroup; the amount of uncertainty in these priors for each subgroup; and the amount of available sample for the new study (i.e., the new study’s total sample budget). Deciding to personalize medical care based on patients’ predicted but uncertain risks also requires decisions about collecting additional information. Such risk heterogeneity calls for an EVOSI analysis if, given available sample, the value of personalized care is to be maximized.

 

Please note: All research in progress seminars are off-the-record unless otherwise noted. Any information about methodology and/or results are embargoed until publication.

 

Encina Commons, Room 220
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Stanford, CA 94305-6006

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Professor, Health Policy
jeremy-fisch_profile_compressed.jpg PhD

Jeremy Goldhaber-Fiebert, PhD, is a Professor of Health Policy, a Core Faculty Member at the Center for Health Policy and the Department of Health Policy, and a Faculty Affiliate of the Stanford Center on Longevity and Stanford Center for International Development. His research focuses on complex policy decisions surrounding the prevention and management of increasingly common, chronic diseases and the life course impact of exposure to their risk factors. In the context of both developing and developed countries including the US, India, China, and South Africa, he has examined chronic conditions including type 2 diabetes and cardiovascular diseases, human papillomavirus and cervical cancer, tuberculosis, and hepatitis C and on risk factors including smoking, physical activity, obesity, malnutrition, and other diseases themselves. He combines simulation modeling methods and cost-effectiveness analyses with econometric approaches and behavioral economic studies to address these issues. Dr. Goldhaber-Fiebert graduated magna cum laude from Harvard College in 1997, with an A.B. in the History and Literature of America. After working as a software engineer and consultant, he conducted a year-long public health research program in Costa Rica with his wife in 2001. Winner of the Lee B. Lusted Prize for Outstanding Student Research from the Society for Medical Decision Making in 2006 and in 2008, he completed his PhD in Health Policy concentrating in Decision Science at Harvard University in 2008. He was elected as a Trustee of the Society for Medical Decision Making in 2011.

Past and current research topics:

  1. Type 2 diabetes and cardiovascular risk factors: Randomized and observational studies in Costa Rica examining the impact of community-based lifestyle interventions and the relationship of gender, risk factors, and care utilization.
  2. Cervical cancer: Model-based cost-effectiveness analyses and costing methods studies that examine policy issues relating to cervical cancer screening and human papillomavirus vaccination in countries including the United States, Brazil, India, Kenya, Peru, South Africa, Tanzania, and Thailand.
  3. Measles, haemophilus influenzae type b, and other childhood infectious diseases: Longitudinal regression analyses of country-level data from middle and upper income countries that examine the link between vaccination, sustained reductions in mortality, and evidence of herd immunity.
  4. Patient adherence: Studies in both developing and developed countries of the costs and effectiveness of measures to increase successful adherence. Adherence to cervical cancer screening as well as to disease management programs targeting depression and obesity is examined from both a decision-analytic and a behavioral economics perspective.
  5. Simulation modeling methods: Research examining model calibration and validation, the appropriate representation of uncertainty in projected outcomes, the use of models to examine plausible counterfactuals at the biological and epidemiological level, and the reflection of population and spatial heterogeneity.
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Seminars
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This paper studies how in utero exposure to maternal stress from family ruptures affects later mental health. We find that prenatal exposure to the death of a maternal relative increases take-up of ADHD medications during childhood and anti-anxiety and depression medications in adulthood. Further, family ruptures during pregnancy depress birth outcomes and raise the risk of perinatal complications necessitating hospitalization. Our results suggest large welfare gains from preventing fetal stress from family ruptures and possibly from economically induced stressors such as unemployment. They further suggest that greater stress exposure among the poor may partially explain the intergenerational persistence of poverty.

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American Economic Review
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Maya Rossin-Slater

Encina Commons,
615 Crothers Way Room 184,
Stanford, CA 94305-6006

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Associate Professor, Health Policy
Senior Fellow, Stanford Institute for Economic Policy Research
Associate Professor, Economics (by courtesy)
rossin-slater_ar21_12_f-cr_compressed.jpg PhD

Maya Rossin-Slater is an Associate Professor of Health Policy at Stanford University School of Medicine. She is also a Senior Fellow at the Stanford Institute for Economic and Policy Research (SIEPR), a Research Associate at the National Bureau of Economic Research (NBER) and a Research Fellow at the Institute of Labor Economics (IZA). She received her PhD in Economics from Columbia University in 2013, and was an Assistant Professor of Economics at the University of California, Santa Barbara from 2013 to 2017, prior to coming to Stanford. Rossin-Slater’s research includes work in health, public, and labor economics. She focuses on issues in maternal and child well-being, family structure and behavior, and policies targeting disadvantaged populations in the United States and other developed countries.

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For forty years, the Tuskegee Study of Untreated Syphilis in the Negro Male passively monitored hundreds of adult black males with syphilis despite the availability of effective treatment. The study's methods have become synonymous with exploitation and mistreatment by the medical community. We find that the historical disclosure of the study in 1972 is correlated with increases in medical mistrust and mortality and decreases in both outpatient and inpatient physician interactions for older black men. Our estimates imply life expectancy at age 45 for black men fell by up to 1.4 years in response to the disclosure, accounting for approximately 35% of the 1980 life expectancy gap between black and white men.

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The Quarterly Journal of Economics
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