The Medicare Current Beneficiary Survey (MCBS) is a continuous, multi-purpose longitudinal survey representing the population of Medicare beneficiaries living in the United States. This survey is authorized by section 1875 (42 USC 139511) of the Social Security Act and is conducted by NORC at the University of Chicago (NORC) for the U.S. Department of Health and Human Services. The MCBS is sponsored by the Office of Enterprise Data and Analytics (OEDA) of the Centers for Medicare & Medicaid Services (CMS). The MCBS is designed to aid CMS in administering, monitoring, and evaluating the Medicare program, and is essential in providing important information on beneficiaries that is not otherwise collected through operational or administrative data from the Medicare program.
For more information about the MCBS, including unique features of the survey and the types of data available, see NORC’s project page.
To access additional resources on the MCBS, check out the following links:
To learn more about or download publicly available MCBS data, check out the Survey File or COVID-19 Public Use Files (PUFs).
Download the MCBS Questionnaire Specifications.
For data user documentation, including codebooks and information about the survey design, sampling methodology, interviewing procedures, weighting, and more, check out the MCBS Data User’s Guides, Methodology Reports, and Frequently Asked Questions (FAQs).
For more information about using MCBS data and analytic guidance, check out the New and Advanced User Tutorials.
To see how MCBS data have been studied in the past, check out the MCBS Bibliographies.
With the emergence of COVID-19 in the U.S., CMS was uniquely positioned to quickly collect vital information on how the pandemic is impacting the Medicare population by using the MCBS as a vehicle to collect data. The MCBS COVID-19 Rapid Response Community Supplements are nationally representative, cross-sectional telephone surveys that collect data on topics such as the availability of telemedicine visits, deferred medical care, social distancing and other preventive health behaviors, COVID-19 testing, and the consequences of the COVID-19 pandemic for social, emotional, and financial well-being.
The first MCBS COVID-19 Summer 2020 Community Supplement was a telephone survey of 11,114 Medicare beneficiaries administered from June 10, 2020 through July 15, 2020. This data collection was conducted by NORC as a supplement to MCBS annual data collection. The second MCBS COVID-19 Fall 2020 Community Supplement was a telephone survey of 9,686 Medicare beneficiaries administered from October 5, 2020 through November 15, 2020 as part of regular MCBS annual data collection.
To enable researchers to analyze the data collected through the COVID-19 Community Supplements, data are combined with demographic and health status data collected during prior interviews and made publically available through the MCBS COVID-19 Supplement PUFs, which include analytic weights to ensure data are statistically accurate. The COVID-19 Summer 2020 Supplement PUF was released in October 2020, and the COVID-19 Fall 2020 Supplement PUF was released in January 2021. The PUFs are evaluated for disclosure risk and do not require a Data Use Agreement (DUA). The estimates in this web tool use the MCBS COVID-19 Supplement PUFs with the appropriate weights. See below for more information about the methodology.
To learn more about the COVID-19 Community Supplements and how to appropriately analyze the data, see the following resources:
Download the MCBS COVID-19 Supplement Questionnaires.
Download the MCBS COVID-19 Supplement PUFs, including the analytic weights, data user documentation, and codebook.
The MCBS COVID-19 Data Tool presents findings from the MCBS COVID-19 Summer 2020 Supplement PUF and MCBS COVID-19 Fall 2020 Supplement PUF. Estimates represent the population of beneficiaries who were continuously enrolled in Medicare from the beginning of 2020 and were alive, living in the community, and eligible and enrolled in Medicare at the time of the COVID-19 Summer or Fall 2020 Supplement interviews.
This tool is comprised of a series of dashboards related to how COVID-19 has affected the lives of Medicare beneficiaries. In addition, estimates for different demographic subgroups and health factor status subgroups are also presented.
The tool presents a visual approximation of the analysis; all conclusions should be verified through appropriate analysis of the publically available datasets.
The MCBS COVID-19 Data Tool incorporates questions and responses from the COVID-19 Summer 2020 and Fall 2020 Supplement PUFs that meet certain inclusion criteria.
Questions are included in the MCBS COVID-19 Data Tool if the question received enough valid responses to produce a reliable estimate. Read more about MCBS analytical guidance in the user tutorials.
Several measures included in the dashboards are created using derived variables. These derived variables combine information from one or more variables available in the MCBS COVID-19 Supplement PUFs:
Washed hands/used hand sanitizer: Respondents were asked whether they have practiced different behaviors in response to the COVID-19 pandemic. Responses to “Washed hands for 20 seconds with soap and water” and “Used hand sanitizer” were collapsed into a single measure. A “yes” response to either behavior is considered a “yes” response in the derived variable.
Purchased extra food/supplies/medicines: Respondents were asked whether they have practiced different behaviors in response to the COVID-19 pandemic. “Purchased extra food,” “Purchased extra cleaning supplies,” and “Purchased or picked up extra prescription medicines beyond usual purchases” were collapsed into a single measure. A “yes” response to any of the three behaviors is considered a “yes” response in the derived variable.
Number of chronic conditions: Respondents were asked whether they have ever had any of the following conditions: Alzheimer’s/dementia, any heart condition, cancer (non-skin), hypertension/high blood pressure, diabetes/high blood sugar, any arthritis, stroke/brain hemorrhage, emphysema/asthma/chronic obstructive pulmonary disease (COPD), depression, high cholesterol, osteoporosis/soft bones. Responses were combined to calculate the total number of listed conditions.
Dual Eligible Status: Beneficiaries who are either eligible for partial Medicaid as non-Qualified Medicare Beneficiary (non-QMB) or eligible for partial Medicaid as a Qualified Medicare Beneficiary (QMB) were collapsed into a single category, “Partial-Benefit Dual Eligible”.
Views on COVID-19 Vaccines: “Reason(s) for not getting a COVID-19 vaccine if one were available” was only asked of respondents who reported they would “Probably Not” or “Definitely Not” get a COVID-19 vaccine. Respondents were able to report more than one reason.
Perceptions of Severity of COVID-19: Respondents were asked whether they agreed with the following statements: “Coronavirus is more contagious than the flu”; “Coronavirus is more deadly than the flu”; “It is important for everyone to take precautions to prevent the spread of the Coronavirus, even if they are not in a high-risk group”. Examples of high-risk groups include elderly or chronically ill individuals. For the three severity measures, responses of “Strongly Agree” were collapsed under “Agree”.
Questions on vaccine uptake and beneficiaries’ perceptions of COVID-19 were added starting with the COVID-19 Fall 2020 Community Supplement. As such, the Views on COVID-19 Vaccines and Perceptions of COVID-19 Severity dashboards are not available for Summer 2020. Please note, because a COVID-19 vaccine was not publically available when the Fall 2020 Community Supplement was fielded, respondents were asked if they would get a COVID-19 vaccine if one were available.
In addition, the reference period changed between supplements, including for questions on COVID-19 preventive health behaviors, the impact of COVID-19 on daily life, experiences with forgone care, availability and utilization of telemedicine, participation in video/voice calls, and the impact of COVID-19 on well-being. The COVID-19 Summer 2020 Community Supplement used a reference period of “since the coronavirus pandemic began” while the COVID-19 Fall 2020 Community Supplement used a reference period of “since July 1, 2020”.
Percentage estimates are calculated using the survey weights supplied in the PUF. Variance estimates (which are needed to derive standard errors and confidence intervals) are calculated using replicate weights supplied in the file. See documentation for MCBS weights.
Within the dashboard, the confidence intervals within each dot plot are adjusted using the Goldstein-Healy method as described in:
Wright, Tommy, Martin Klein, and Jerzy Wieczorek. “A Primer on Visualizations for Comparing Populations, Including the Issue of Overlapping Confidence Intervals.” The American Statistician 73, no. 2 (2019): 165-178. DOI: 10.1080/00031305.2017.1392359
To link to this article: https://doi.org/10.1080/00031305.2017.1392359
This adjustment is done so that the confidence intervals can be readily used to determine if two estimates within a chart are, statistically speaking, different (see the use of confidence intervals to compare groups).
The MCBS COVID-19 Data Tool was created using R Shiny and D3.js.
Each dashboard consists of a bar chart presenting outcome variables related to a theme. For example, the dashboard on Preventive Behaviors shows the percent of beneficiaries who have changed their behavior in response to COVID-19. The dashboard also shows a series of dot plots which dynamically update to show the demographic breakdown of responses for a particular behavior.
Select the text “Click here to learn more” to open a drop-down box with instructions and a link to the methodology.
Click on a single bar within the bar chart to see how that topic differs within each group displayed in the dot plots. The dot plots include confidence intervals which can be used to identify potential meaningful differences.
Clicking on a bar in the bar chart on the left adjusts the universe of respondents in the dot plots on the right. For example, clicking on the bar corresponding to “Wore a facemask” in the Preventive Behaviors module updates the universe of respondents in the dot plots to all respondents who had a valid response to the question: “Have you worn a facemask when out in public in response to the outbreak of COVID-19?”
Click on the time period (e.g., Fall 2020) in the dashboard description to change the data source. The Summer 2020 option shows data collected between June-July 2020, while the Fall 2020 option shows data collected between October-November 2020.
Toggle between the Demographics and Health tabs on the right to see how topics differ by beneficiary characteristics. The Demographics tab includes breakdowns by different demographic variables such as Sex, Age, and Total Household Income. The Health tab includes breakdowns by different health factors such as Current Smoker and Chronic Conditions.
Scales on the dot plots are dynamic. Estimates should only be compared within groups in the dot plots, not across. For example, the “Male” group should not be compared to the “75+ years” group.
Hovering over a particular bar or dot in the tool allows users to view additional details about that particular question and the survey responses. For example, hovering over the bar corresponding to “Wore a facemask” in the Preventive Behaviors module will provide the following information: “% of Medicare beneficiaries responded ‘yes’ to the question: Have you worn a facemask when out in public in response to the outbreak of COVID-19?”
Users can perform statistical hypothesis tests (p = 0.05) to determine if there is a meaningful difference between two percentages within a chart. The width of the intervals indicates the measure of uncertainty in the estimates.
Given the method used to construct the confidence intervals (see note in the Methodology section), if two confidence intervals within a chart overlap, then there is no meaningful difference between the percentages for those two groups. However, if two confidence intervals within a chart do not overlap, then there is a meaningful difference between the percentages for those two groups.
Confidence intervals are adjusted for direct comparison across groups; the confidence interval associated with each demographic group does NOT represent a univariate confidence interval for that group’s proportion. Confidence intervals should not be interpreted for a single demographic group, only used for hypothesis tests of differences between groups. However, the width of the confidence interval does provide a visual sense of the uncertainty of the estimate. All conclusions should be verified through appropriate analysis of the data.
For more information, contact us.