Tara Becker, PhD, is a senior public administration analyst at the UCLA Center for Health Policy Research. Her duties include conducting research on gender, racial, and ethnic disparities in health insurance coverage in California and collaborating with California Health Interview Survey (CHIS) funders and researchers in designing and implementing policy evaluation studies. Her research at CHIS focuses on survey measurement and data quality. Becker co-leads the CHIS sexual orientation and gender identity workgroup.

Becker's research interests focus on quantitative methodology, measurement, and the relationship between labor market and family decisions. Her recent work assesses how the provision of employer-sponsored coverage shapes family formation and dissolution decisions. She has expertise in demographic methods, multilevel modeling, latent class analysis, survey research methods, and nonparametric methods for small data sets.

Prior to joining the Center, Becker worked as a UCLA/RAND postdoctoral fellow in the Department of Health Policy and Management at UCLA, where she trained in U.S. health policy. She also previously worked as a biostatistician at the University of Wisconsin–Madison's Department of Biostatistics and Medical Informatics, where she provided statistical consultation, study design, data analysis, and grant-writing support services to medical and public health researchers. 

She has collaborated with researchers on a diverse array of topics such as racial disparities in obesity among adolescents, health-related quality of life among children and adolescents with cystic fibrosis, Internet addiction among college students, and comparing physician and patient assessments of risk for stent and coronary bypass surgery among patients at risk of a heart attack or stroke.

Becker received her PhD in sociology, an MS in statistics, and a BS in mathematics and sociology from the University of Wisconsin–Madison.

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Breaking Barriers with Data Equity: The Essential Role of Data Disaggregation in Achieving Health Equity
Journal Article
Journal Article

Breaking Barriers with Data Equity: The Essential Role of Data Disaggregation in Achieving Health Equity

Achieving health equity necessitates high-quality data to address disparities that have remained stagnant or even worsened over time despite public health interventions. Data disaggregation, the breakdown of data into detailed subcategories, is crucial in health disparities research. It reveals and contextualizes hidden trends and patterns about marginalized populations and guides resource allocation and program development for specific needs in these populations.

Data disaggregation underpins data equity, which uses community engagement to democratize data and develop better solutions for communities. Years of research on disaggregation show that researchers must collaborate closely with communities for adequate representation. However, despite generally positive support for this approach in health disparities research, data disaggregation faces methodological and political challenges.

This review offers a framework for understanding data disaggregation in the context of data equity and highlights critical aspects of implementation, including challenges, opportunities, and recent policy and community-based efforts to address hurdles.
 

Without Data Equity, We Will Not Achieve Health Equity
Journal Article
Journal Article

Without Data Equity, We Will Not Achieve Health Equity

Data equity emphasizes the creation and distribution of inclusive, high-quality, and actionable data. It involves improving practices in data collection, processing, analysis, and sharing to ensure fair representation and utility for diverse communities. Central to data equity is the accurate and inclusive capture of community needs, which influences decisions and resource allocation.

The Office of Management and Budget's (OMB) revised Statistical Policy Directive No. 15, updated on March 28, 2024, after nearly three decades. This revision replaces the previous racial and ethnic categories with a new, single-question format that includes updated categories like Middle Eastern or North African and mandates more detailed subgroup data collection. These changes are designed to better reflect community diversity and improve the effectiveness of federal programs.

The Robert Wood Johnson Foundation funded the UCLA Data Equity Center (DEC) to support organizations in implementing these new standards by offering technical assistance and resources to turn data equity goals into concrete actions. The DEC is housed at the UCLA Center for Health Policy Research. The DEC promotes equity in data by offering resources and technical assistance that will inform, support and promote data systems becoming more representative, inclusive, and collaborative with the communities they serve. The overall strategy includes compiling curated resources that outline actionable steps organizations can take to improve data equity, developing targeted trainings for staff, and providing technical assistance to organizations as they improve their data collection, processing, reporting, and dissemination.
 

ACA
Journal Article
Journal Article

How Has Access to Care for Medi-Cal Enrollees Fared Relative to Employer-Sponsored Insurance Four Years After the Affordable Care Act Expansion? (Journal of General Internal Medicine)

Summary: The number of Californians covered by Medi-Cal increased more than 50% between 2013 and 2018, largely due to expansion under the Affordable Care Act (ACA). This rapid expansion of Medicaid rolls prompted concerns that Medi-Cal enrollees would face greater difficulty accessing health care. 

Authors examine whether gaps in access to care between Medi-Cal and employer-sponsored insurance (ESI) present in 2013 (prior to ACA implementation) had changed by 2018 (several years post implementation). They also conducted secondary analysis of data from the 2013 and 2018 California Health Interview Survey. The sample included adults ages 1864 insured all year and covered by ESI or Medi-Cal at time of interview. Logistic regressions were used to examine variation across years in the association between access to care and insurance type. Five access to care outcomes were assessed: no usual source of care, not accepted as new patient in past year, insurance not accepted in past year, delayed medical care in past year, and difficulty getting timely appointment. The main predictors of interest were type of insurance (Medi-Cal or ESI) and survey year (2013 and 2018).

Findings: The association between insurance type and access to care changed significantly over time for three outcomes: not accepted as new patient in past year, delayed medical care in past year, and difficulty getting timely appointment. Predicted probabilities indicate gaps between Medi-Cal and ESI narrowed for not accepted as new patient in past year and difficulty getting timely appointment but widened for delayed medical care. 
Despite the rapid expansion of the Californians covered by Medi-Cal, most gaps in access to care between Medi-Cal and ESI enrollees improved or did not significantly change between 2013 and 2018:
 

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Measuring Up? Access to Care in Medi-Cal Compared to Other Types of Health Insurance (2018)
Research Report
Research Report

Measuring Up? Access to Care in Medi-Cal Compared to Other Types of Health Insurance (2018)

Summary: Medi-Cal is California’s Medicaid program, providing health insurance to Californians with low incomes, including about 40% of the state’s children, half of Californians with disabilities, over a million seniors, and about one in six working adults. In total, the program covers around 13 million Californians, nearly one-third of the state’s population.

However, coverage alone does not guarantee access to health care services or affordability. To see how Californians with Medi-Cal coverage are faring in accessing health care, this report examines data from the 20172018 California Health Interview Survey (CHIS). This analysis focuses on one main question: Do Medi-Cal enrollees face greater difficulty accessing health care services than Californians with employer-sponsored insurance (ESI) or coverage purchased through the individual market (IM)?

Findings: The findings broadly suggest the need for improvement in several areas: ensuring a usual source of care, increasing the supply of providers that will take Medi-Cal patients, and facilitating access to specialists who will see Medi-Cal patients. Addressing these critical areas would help close the gaps in access to care for many California adults and children.


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Breaking Barriers with Data Equity: The Essential Role of Data Disaggregation in Achieving Health Equity
Journal Article
Journal Article

Breaking Barriers with Data Equity: The Essential Role of Data Disaggregation in Achieving Health Equity

Achieving health equity necessitates high-quality data to address disparities that have remained stagnant or even worsened over time despite public health interventions. Data disaggregation, the breakdown of data into detailed subcategories, is crucial in health disparities research. It reveals and contextualizes hidden trends and patterns about marginalized populations and guides resource allocation and program development for specific needs in these populations.

Data disaggregation underpins data equity, which uses community engagement to democratize data and develop better solutions for communities. Years of research on disaggregation show that researchers must collaborate closely with communities for adequate representation. However, despite generally positive support for this approach in health disparities research, data disaggregation faces methodological and political challenges.

This review offers a framework for understanding data disaggregation in the context of data equity and highlights critical aspects of implementation, including challenges, opportunities, and recent policy and community-based efforts to address hurdles.
 

View All Publications

Without Data Equity, We Will Not Achieve Health Equity
Journal Article
Journal Article

Without Data Equity, We Will Not Achieve Health Equity

Data equity emphasizes the creation and distribution of inclusive, high-quality, and actionable data. It involves improving practices in data collection, processing, analysis, and sharing to ensure fair representation and utility for diverse communities. Central to data equity is the accurate and inclusive capture of community needs, which influences decisions and resource allocation.

The Office of Management and Budget's (OMB) revised Statistical Policy Directive No. 15, updated on March 28, 2024, after nearly three decades. This revision replaces the previous racial and ethnic categories with a new, single-question format that includes updated categories like Middle Eastern or North African and mandates more detailed subgroup data collection. These changes are designed to better reflect community diversity and improve the effectiveness of federal programs.

The Robert Wood Johnson Foundation funded the UCLA Data Equity Center (DEC) to support organizations in implementing these new standards by offering technical assistance and resources to turn data equity goals into concrete actions. The DEC is housed at the UCLA Center for Health Policy Research. The DEC promotes equity in data by offering resources and technical assistance that will inform, support and promote data systems becoming more representative, inclusive, and collaborative with the communities they serve. The overall strategy includes compiling curated resources that outline actionable steps organizations can take to improve data equity, developing targeted trainings for staff, and providing technical assistance to organizations as they improve their data collection, processing, reporting, and dissemination.
 

ACA
Journal Article
Journal Article

How Has Access to Care for Medi-Cal Enrollees Fared Relative to Employer-Sponsored Insurance Four Years After the Affordable Care Act Expansion? (Journal of General Internal Medicine)

Summary: The number of Californians covered by Medi-Cal increased more than 50% between 2013 and 2018, largely due to expansion under the Affordable Care Act (ACA). This rapid expansion of Medicaid rolls prompted concerns that Medi-Cal enrollees would face greater difficulty accessing health care. 

Authors examine whether gaps in access to care between Medi-Cal and employer-sponsored insurance (ESI) present in 2013 (prior to ACA implementation) had changed by 2018 (several years post implementation). They also conducted secondary analysis of data from the 2013 and 2018 California Health Interview Survey. The sample included adults ages 1864 insured all year and covered by ESI or Medi-Cal at time of interview. Logistic regressions were used to examine variation across years in the association between access to care and insurance type. Five access to care outcomes were assessed: no usual source of care, not accepted as new patient in past year, insurance not accepted in past year, delayed medical care in past year, and difficulty getting timely appointment. The main predictors of interest were type of insurance (Medi-Cal or ESI) and survey year (2013 and 2018).

Findings: The association between insurance type and access to care changed significantly over time for three outcomes: not accepted as new patient in past year, delayed medical care in past year, and difficulty getting timely appointment. Predicted probabilities indicate gaps between Medi-Cal and ESI narrowed for not accepted as new patient in past year and difficulty getting timely appointment but widened for delayed medical care. 
Despite the rapid expansion of the Californians covered by Medi-Cal, most gaps in access to care between Medi-Cal and ESI enrollees improved or did not significantly change between 2013 and 2018:
 

Read the Publications:

 

Qandaimage
Ask the Expert

Three Questions with Tara Becker on Health Insurance

Tara Becker is a CHIS senior public administration analyst and author of a new policy brief that analyzes the latest health insurance trends in California. In this interview, Becker discusses changes in employer-sponsored insurance (ESI) and the effects of actual and potential federal policy changes regarding elements of the ACA.

Q: ESI enrollment hit a low of 48.2 percent in 2016. But this year the rate rebounded to 51.2 percent. Meanwhile, Medi-Cal's steadily-rising enrollment rate declined from 33 percent in 2016 to 29 percent in 2017. What does that suggest to you? 

Enrollment in employer-sponsored insurance coverage improved as the economy continued to improve. During this period, more Californians entered the labor force and fewer were unemployed. These changes lead to an increase in the rate of employer-provided coverage both because Californians are more likely to be working, and in a tight labor market, employers are more likely to offer health insurance coverage to attract and retain employees. 
 

Q: The individual mandate feature of the ACA will be eliminated in January. What effect will that have on insurance rates? 

The purpose of the individual mandate was to encourage younger and healthier people to purchase insurance so that the pool of Californians with health insurance coverage would have lower average health care costs. This in turn would lower health insurance premiums and make health insurance more affordable for those who have higher medical costs.

Without this incentive to purchase health insurance coverage, many younger and healthier people might opt out of purchasing insurance because their expected medical costs are lower than the cost of insurance coverage. This may reduce the pool of insured Californians primarily to those who are older and less healthy, meaning the average medical costs incurred by each individual in the pool will increase, leading to higher health insurance premiums. This may discourage even more young healthy Californians from purchasing coverage, further increasing the average costs for those who remain insured, and in an extreme case, leading to an insurance market death spiral.

In the long-term, this will make health coverage more expensive for these younger and healthier Californians when they do need to purchase health insurance in the future.


Q: Although Medi-Cal enrollment dropped in 2017, 29 percent of nonelderly Californians are covered by the state health program for low-income and disabled Californians. Which groups stand to lose most if the federal government tightens Medi-Cal funding? 

Low-income Californians are the most likely to lose coverage if changes to Medi-Cal are made. In 2017, more than 60 percent of nonelderly Californians with family incomes below 139 percent of the federal poverty guidelines (FPG) were insured through Medi-Cal, as were more than 40 percent of those with family incomes between 139 percent and 200 percent FPG. Because more than 40 percent of Latinos and 30 percent of African-Americans are covered through Medi-Cal, the uninsured rate will likely rise for these groups if Medi-Cal eligibility is restricted.

Regionally, any restrictions on Medi-Cal eligibility would hit the San Joaquin Valley the hardest, because more than 40 percent of residents in this region are enrolled in the program. Both Los Angeles County (34 percent enrolled) and the Northern and Sierra counties (31 percent enrolled) also experience high rates of Medi-Cal enrollment and would likely experience an increase in the number of uninsured.

 

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Video

Advanced Weighting Strategies for Disaggregated Racial/Ethnic Data

This workshop shares the ways in which survey weighting processes can and cannot be used to improve the representativeness of data on small and disaggregated populations within population surveys. The presentations cover the purpose of providing survey weights that account for specific subpopulations, things to consider when selecting a control population to use for calibration, and methods of accounting for small subgroups in weighting data.

Presenters:
Ninez A. Ponce, PhD, MPP, Director, UCLA Center for Health Policy Research
Brian Wells, PhD, Former Survey Methodologist, California Health Interview Survey
Tara Becker, PhD, Senior Public Administration Analyst, UCLA Center for Health Policy Research

About the National Network of Health Surveys' Advancing Health Equity Through Data Disaggregation Workshop Series

Disaggregated race/ethnicity data is needed to expose gaps in health equities and inform policies and programs and close those gaps. The National Network of Health Surveys, part of the UCLA Center for Health Policy Research, offers a series of workshops designed to improve the disaggregation of race and ethnicity measures in health data sources. Our goal is to boost the number of subpopulation categories made available to key constituencies working to improve health equity. This is especially important for representing communities that are often “hidden” in large health data sets.

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Online

Overcoming Invisibility: Better Health Data for American Indians and Alaska Natives

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