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Beth Duff-Brown
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The Supreme Court ruling eliminating the constitutional right to an abortion could also result in women’s personal reproductive health data being used against them, warns Stanford Health Policy’s Michelle Mello.

The Dobbs v. Jackson Women’s Health Organization ruling could, for example, lead to a woman’s health data in clinician emails, electronic medical records, and online period-tracking platforms being used to incriminate her or her health-care providers, Mello said.

“Ultimately, broader information privacy laws are needed to fully protect patients and clinicians and facilities providing abortion services,” writes Mello, a professor of health policy and law in this JAMA Health Forum article with colleague Kayte Spector-Bagdady, a bioethicist from the University of Michigan. “As states splinter on abortion rights after the Dobbs Supreme Court decision, the stakes for providing robust federal protection for reproductive health information have never been higher.”

Eight states banned abortions on the same day the Dobbs ruling came down, and 13 states that had “trigger bans” that, if Roe v. Wade were struck down, would automatically prohibit abortion within 30 days. Other states are considering reactivating pre-Roe abortion bans and legislators in some states intend to introduce new legislation to curb or ban the medical procedure.”

Three Potential Scenarios

The authors note these new abortion restrictions may clash with privacy protections for health information, laying out three scenarios that could impact millions of women. And, they note, “despite popular misconceptions about the breadth of the Privacy Rule of the Health Information Portability and Accountability Act (HIPAA) and other information privacy laws, current federal law provides little protection against these scenarios.”

The first scenario is that a patient’s private health information may be sought in connection with a law-enforcement proceeding or civil lawsuit for obtaining an illegal abortion. HIPAA privacy regulations and Fourth Amendment rights against unreasonable searches and seizures won’t help physicians and hospitals resist such investigative demands, the authors write. And though physician-patient communications are ordinarily considered privileged information, the scope of that privilege varies greatly from state to state. “In many cases medical record information has been successfully used to substantiate a criminal charge,” the authors write.

Ultimately, broader information privacy laws are needed to fully protect patients and clinicians and facilities providing abortion services.
Michelle Mello
Professor of Health Policy, Law

The second privacy concern is the potential use of health-care facility records to incriminate an institution or its clinicians for providing abortion services. Relevant records could include electronic health records, employee emails or paging information and mandatory reports to state agencies. Clinicians may not realize that if they are using an institutional email address or server, their institution likely has direct access to information and communications stored there, which can be used to search for violations. State Freedom of Information Act (FOIA) laws also allow citizens to request public records from employees of government hospitals and clinics.

“Additionally, state mandatory reporting laws for child abuse might be interpreted to cover abortions — particularly if life is defined as beginning at fertilization,” the authors note.

The third scenario is that information generated from a woman’s online activity could be used to show she sought an abortion or helped someone to do so. Many women use websites and apps that are not HIPAA-regulated or protected by patient-physician privilege, such as period-tracking apps used by millions of women that collect information on the timing of menstruation and sexual activity.

“There are many instances of internet service providers sharing user data with law enforcement, and prosecutors obtaining and using cellphone data in criminal prosecutions,” write Mello and Spector-Bagdady, adding commercially collected data are also frequently sold to or shared with third parties.

“Thus, pregnant persons may unwittingly create incriminating documentation that has scant legal protection and is useful for enforcing abortion restrictions,” they said.

The immediate problem, Mello notes, is in the states that have already banned abortion or passed restrictive laws.

“There could be a problem with states trying to reach outside their borders to prosecute people, but that could well be unconstitutional,” Mello said.

Some states’ laws sweep abortion pills into the definition of illegal abortions, she said, and there are legal obstacles to supplying the pills across state lines.

“There is a lot of energy going into figuring out a workaround right now, but it’s too soon to call,” Mello said.

Recommended Protections

So how can clinicians and health-care facilities protect their patients and themselves?

When counseling patients of childbearing age about reproductive health issues, clinicians should caution their patients about putting too much medical data online and refer them to expert organizations that will help them minimize their digital footprint.

When documenting reproductive health encounters, the authors said, clinicians should ask themselves: “What information needs to be in the medical record to assure safe, good-quality care, buttress our claim for reimbursement, or comply with clear legal directives?” For example, does information about why a patient may have experienced a miscarriage need to be recorded?

Patients and clinicians should be aware that email and texting may be seen by others, so conversations among staff about reproductive health issues may best be conducted by phone or in person.

Finally, if abortion-related patient information is sought by state law enforcement officials, a facility’s attorney should be consulted about asserting physician-patient privilege and determining whether the disclosure is mandated by law.

Michelle Mello

Michelle Mello

Professor of Health Policy, Law
Focuses on issues at the intersection of law, ethics and health policy.
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Michelle Mello writes that the overturning of Roe v. Wade — ending federal protection over a woman's right to an abortion — could also expose her personal health data in court.

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This press release was originally published by the University of Tokyo. It discusses a new study, published by Lancet Public Health and co-authored by researchers from the University of Tokyo along with FSI Senior Fellow Karen Eggleston, director of the Asia Health Policy Program at APARC, and Jay Bhattacharya, Professor of Health Policy and director of the Center for Demography and Economics of Health and Aging at Stanford.


A new detailed microsimulation, using a database of 40 million people, has examined the future of Japan’s aging population up to 2043. It projects that more people will live longer, and that overall years spent living with dementia will decrease. However, the model highlighted the diversity of impacts on different segments of the population, as Japanese women with a less than high school education aged 75 and over may be disproportionately affected by both dementia and frailty. Better understanding where health gaps like this exist can help inform public health planning, to minimize future economic costs and support those most in need.

Taking care of the older members of society is a common concern around the world. Japan is famous for its long-lived residents, the number of which continues to rise. In 2020, almost 30% of the Japanese population was aged 65 years or older, and this age group is not projected to peak until 2034. Caring for people with age-related ailments, such as dementia and frailty, poses a challenge both to individuals and public health care systems.

Microsimulation models, which are computer models that can provide detailed analysis on an individual basis, are currently used to project future population health in some countries, such as the U.K. and the U.S. Professor Hideki Hashimoto and researchers at the University of Tokyo, along with researchers from Stanford University in the U.S., wanted to create a new microsimulation model for Japan, which would take into account more diverse conditions than had been considered before.

“We developed a new Japanese microsimulation model that accounts for 13 chronic conditions (including heart disease, stroke, diabetes, depression and dependency), as well as frailty and dementia,” explained Hashimoto. “Using an ultralarge data system, we were able to ‘follow’ a virtual cohort of more than 40 million people aged 60 and over from 2016 to 2043.”

According to Hashimoto, projections of aging in Japan usually rely on the “average” status of older people and so don’t consider the diversity of the population. “I believe that problems of aging are a matter of health gaps over the course of people’s lives,” he said. “Our projection brings attention to a widening health gap among older people. It highlighted that women with a less than high school education aged 75 or over are more likely to be affected.”

Identifying where health gaps like this exist could be used to better inform public policy, not only about health care but other influential aspects of life. “Japan’s case may suggest that improvement in educational attainment, as well as population health, could be a key to making a healthier and more manageable aging society,” said Hashimoto.

Positively, this study shows hope for a future where many people live longer and more healthy lives. “People might believe that an increase in cases of dementia is inescapable, given population aging. However, in this study we found that in Japan, despite an aging population, the number of people with dementia is expected to decrease over the next two decades,” said Hashimoto. “Population aging does not necessarily mean an increase of social burden for care, but it does bring a diversity of problems that requires careful study and science-based policy attention, to close the health gap.”

Karen Eggleston 4X4

Karen Eggleston

Senior Fellow at FSI and Director of the Asia Health Policy Program, Shorenstein APARC
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A new microsimulation projects that over the next 20 years, Japanese people will live longer without dementia, but older women with a less than high school education will benefit less than men.

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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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Noa Ronkin
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Diabetes is one of the fastest-growing health challenges of the 21st century. On the frontlines of the epidemic rise in the number of people with diabetes is the Asia-Pacific region. China, in particular, has by far the largest absolute burden of diabetes, with an estimated 116 million adults living with the disease accounting for one-quarter of patients with diabetes globally. By 2045, the number of adults living with diabetes in the country is expected to increase to 147 million, not including the large diaspora community China provides worldwide.

Evaluating the health and economic outcomes of diabetes and its complications is vital for formulating health policy. The existing predictive outcomes models for type 2 diabetes, however, were developed and validated in historical European populations and may not be applicable for East Asian populations with their distinct epidemiology and complications. Additionally, the existing models are typically limited to diabetes alone and ignore the progression from prediabetes to diabetes. The lack of an appropriate simulation model for East Asian individuals and prediabetes is a major gap for the economic evaluation of health interventions.

New collaborative research now addresses these limitations. The research team includes APARC’s Asia Health Policy Program Director Karen Eggleston. The researchers developed and validated a patient-level simulation model for predicting lifetime health outcomes of prediabetes and type 2 diabetes in East Asian populations. They report on their findings in the journal PLOS Medicine


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Modeling Health Outcomes Among East Asian Populations

The chronic progression to diabetes-related complications is apt for computer simulation modeling due to the long-term nature of health outcomes and the time lag for interventions to impact patient outcomes. It is problematic, however, to estimate the impacts of health interventions on East Asian populations with diabetes using existing models, which were developed and validated in European and North American populations with different epidemiology and outcomes.

To fill in this gap, Eggleston and her colleagues set out to develop and validate an outcomes model for the progression of diabetes and related complications in Chinese populations. They compared this new model, called the Chinese Hong Kong Integrated Modeling and Evaluation (CHIME), to two widely used existing models developed and validated in the United Kingdom (known as the United Kingdom Prospective Diabetes Study Outcomes Model 2, or UKPDS-OM2) and in the United States/Canada (called Risk Equations for Complications of type 2 Diabetes, or RECODe). Despite the continuum of risk across the spectrum of risk factor values, these two existing models ignore the progression from prediabetes to diabetes.

The CHIME integrates prediabetes and diabetes into a comprehensive model comprising 13 outcomes. These include mortality, micro- and macrovascular complications, and the development of diabetes. The researchers developed the CHIME simulation model using data from a population-based cohort of 97,628 participants in Hong Kong with type 2 diabetes (43.5%) or prediabetes (56.5%) from 2006 to 2017. Known as the Hong Kong Clinical Management System (CMS), this cohort makes one of the largest Chinese electronic health informatics systems with detailed clinical records. 

The CHIME outperformed the widely used United Kingdom Prospective Diabetes Study Outcomes Model 2 (UKPDS-OM2) and Risk Equations for Complications of type 2 Diabetes (RECODe) models on real-world data.
Karen Eggleston et al

The next step was to externally validate the CHIME model against individual-level data from the China Health and Retirement Longitudinal Study (CHARLS) cohort (2011-2018), a nationally representative longitudinal cohort of middle-aged and elderly Chinese residents age 45 and older. The researchers validated the CHIME model against six outcomes measures recorded in the CHARLS data and an additional 80 endpoints from nine published trials of diabetes patients using simulated cohorts of 100,000 individuals.

Towards Reducing the Disease Burden of Diabetes

The researchers found that the CHIME model outperformed the widely used UKPDS-OM2 and RECODe models on the data used, meaning that the validation of the CHIME model was more accurate for trials with mainly Asian participants than trials with mostly non-Asian participants. The results indicate that the CHIME model is a validated tool for predicting the progression of diabetes and its outcomes, particularly among Chinese and East Asian populations, for which the existing models have been unsuitable.

With the new model, clinicians and health economists can evaluate population health status for prediabetes and diabetes using routinely recorded data and therapies related to the long-term management of diabetes. In particular, the CHIME outcomes model enables them to assess patients' quality of life and measure cost per quality-adjusted life-years over the long-time horizon of chronic disease conditions. The new model thus supports the economic evaluation of policy guidelines and clinical treatment pathways to tackle diabetes and prediabetes, address micro- and macrovascular complications associated with these conditions, and improve life expectancy.

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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.

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Pascal Geldsetzer, PhD 
Assistant Professor of Medicine in the Division of Primary Care and Population Health

Title:  Regression Discontinuity in Electronic Health Record Data

Abstract: Regression discontinuity in electronic health record (EHR) data combines the main advantage of randomized controlled trials (causal inference without needing to adjust for confounders) with the large size, low cost, and representativeness of observational studies in routinely collected medical data. Regression discontinuity could be an important tool to help clinical medicine move away from a “one size fits all” approach because, along with the increasing size and availability of EHR data, it would allow for a rigorous examination of how treatment effects vary across highly granular patient subgroups. In addition, given the broad range of health outcomes recorded in EHR data, this design could be used to systematically test for a wide range of unexpected beneficial and adverse health effects of different treatments. I will talk about the broad motivation for this research and discuss examples from some of our ongoing work in this area. If there is time, I will also discuss some of my ongoing research on improving healthcare services for chronic conditions in low- and middle-income country settings. 

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Stanford Medicine Innovation Professor
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Alyce Adams is a Professor of Health Policy and of Epidemiology and Population Health in the Stanford School of Medicine; Associate Chair, Partnership and Community Engagement for the Department of Health Policy; and Associate Director for Health Equity and Community Engagement in the Stanford Cancer Institute. Focusing on racial and socioeconomic disparities in chronic disease treatment outcomes, Dr. Adams' interdisciplinary research seeks to evaluate the impact of changes in drug coverage policy on access to essential medications, understand the drivers of disparities in treatment adherence among insured populations, and test strategies for maximizing the benefits of treatment outcomes while minimizing harms through informed decision-making. Prior to joining Stanford School of Medicine, Dr. Adams was Associate Director for Health Care Delivery and Policy and a Research Scientist at the Kaiser Permanente Division of Research, as well as a Professor at the Bernard J. Tyson Kaiser Permanente School of Medicine. From 2000 to 2008, she was an Assistant Professor in the Department of Population Medicine (formerly Ambulatory Care and Prevention) at Harvard Medical School and Harvard Pilgrim Health care. She received her PhD in Health Policy and an MPP in Social Policy from Harvard University. She is Vice Chair of the Board of Directors for AcademyHealth and a former recipient of the John M. Eisenberg Excellence in Mentoring Award from Agency for Healthcare Research and Quality and an invited lecturer on racial disparities in health care in the 2014/2015 National Institute of Mental Health Director’s Innovation Speaker Series.

Professor, Epidemiology and Population Health
Professor, Health Policy
Professor, Pediatrics (by courtesy)
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