NEJM: Linking data is critical to ending care disparities
Collecting data and linking them to quality measures are vital for targeting efforts at reducing racial and ethnic disparities in care, according to a June 16 perspective in the New England Journal of Medicine.
Unfortunately, aside from vital statistics, health data including patients’ race or ethnic background are collected haphazardly in the U.S., wrote Joel S. Weissman, PhD, associate professor of health policy at the Mongan Institute for Health Policy at Massachusetts General Hospital in Boston; and Romana Hasnain-Wynia, PhD, senior director of research and evaluation for the Institute for Healthcare Studies’ Health Research and Educational Trust, and associate professor of research at Northwestern University in Chicago.
Currently, “no single entity has the capacity to analyze disparities for the entire country, and one of the largest and most comprehensive sources of utilization—health insurance claims—lacks basic demographic data on the race and ethnic background of enrollees,” Weissman and Hasnain-Wynia wrote.
Although most U.S. hospitals collect data on patients' race or ethnic group, few record this information systematically and only a fraction of the population is hospitalized in any given year. Although many more people visit physicians, very few practices collect race and ethnic data routinely.
Recent legislation may lead to some improvements: To qualify for meaningful use incentives for EHR use, physicians must record the race or ethnic background for at least 50 percent of their patients, the authors stated. Provisions of the Patient Protection and Affordable Care Act (PPACA) require relevant data to be collected, but only in certain federal programs such as population surveys, Medicaid and the Children's Health Insurance Program.
Payors, including commercial insurers, Medicaid and Medicare, have great potential for creating a comprehensive national database for tracking healthcare disparities, because they manage health benefits for most Americans and have an interest in assuring that care is delivered equitably, according to Weissman and Hasnain-Wynia. “The problem is collecting the data. Self-reported race or ethnic background is considered the gold standard, but insurers face sizable barriers to obtaining self-reports.”
These barriers include payors’ lack of direct contact with enrollees after enrollment; members’ fears about potential discrimination based on race and ethnicity; and states prohibiting insurers from requesting such information.
The Centers for Medicare & Medicaid Services (CMS) obtains data on race and ethnic background from Social Security Administration records, but for beneficiaries who enrolled before 1980, “categories were limited to ‘black,’ ‘white’ or 'other,’ so the data fail to identify Hispanics, Asians, and members of other groups,” they stated.
Until direct reporting measures become feasible, an interim strategy of imputing information on race or ethnic background through indirect estimation, is one data gathering option. “The most common indirect method uses geographically coded data from the U.S. Census [Bureau] to characterize people on the basis of their address or zip code as living in a high-, medium- or low-minority area,” stated the authors. “A second approach uses each person’s surname, along with Census information on the self-identification of people with that name.”
Newer methods estimate probabilities for each race or ethnic category instead of assigning a single race or ethnic background to an individual. The probabilities can then be “rolled up” to estimate racial distributions in populations or combined with utilization data to examine disparities in care, according to the authors. “Used in this way, imputed data can reveal aggregate disparities with remarkable accuracy.”
“The usefulness of indirect estimation would increase enormously if all insurers combined their data, and in fact that may happen in some areas,” they noted. For example, several states have begun constructing all-payor claims databases that include medical and pharmacy data for all providers from public and private health plans.
Statewide data could benefit consumers choosing among health plans or accountable care organizations on the basis of providers’ records in ensuring equitability of care. No state currently imputes data on race or ethnic background for all-payor databases, although Massachusetts has begun discussions regarding this, the authors reported.
“Until self-reported data become widely available, indirect estimation methods applied to all-payor databases provide an opportunity to populate vast quantities of health-claims records with racial and ethnic information,” Weissman and Hasnain-Wynia concluded. “Such an effort would launch the process of creating a national infrastructure for monitoring disparities that, we hope, will ultimately permit the achievement of widespread equity in the delivery of care.”
Unfortunately, aside from vital statistics, health data including patients’ race or ethnic background are collected haphazardly in the U.S., wrote Joel S. Weissman, PhD, associate professor of health policy at the Mongan Institute for Health Policy at Massachusetts General Hospital in Boston; and Romana Hasnain-Wynia, PhD, senior director of research and evaluation for the Institute for Healthcare Studies’ Health Research and Educational Trust, and associate professor of research at Northwestern University in Chicago.
Currently, “no single entity has the capacity to analyze disparities for the entire country, and one of the largest and most comprehensive sources of utilization—health insurance claims—lacks basic demographic data on the race and ethnic background of enrollees,” Weissman and Hasnain-Wynia wrote.
Although most U.S. hospitals collect data on patients' race or ethnic group, few record this information systematically and only a fraction of the population is hospitalized in any given year. Although many more people visit physicians, very few practices collect race and ethnic data routinely.
Recent legislation may lead to some improvements: To qualify for meaningful use incentives for EHR use, physicians must record the race or ethnic background for at least 50 percent of their patients, the authors stated. Provisions of the Patient Protection and Affordable Care Act (PPACA) require relevant data to be collected, but only in certain federal programs such as population surveys, Medicaid and the Children's Health Insurance Program.
Payors, including commercial insurers, Medicaid and Medicare, have great potential for creating a comprehensive national database for tracking healthcare disparities, because they manage health benefits for most Americans and have an interest in assuring that care is delivered equitably, according to Weissman and Hasnain-Wynia. “The problem is collecting the data. Self-reported race or ethnic background is considered the gold standard, but insurers face sizable barriers to obtaining self-reports.”
These barriers include payors’ lack of direct contact with enrollees after enrollment; members’ fears about potential discrimination based on race and ethnicity; and states prohibiting insurers from requesting such information.
The Centers for Medicare & Medicaid Services (CMS) obtains data on race and ethnic background from Social Security Administration records, but for beneficiaries who enrolled before 1980, “categories were limited to ‘black,’ ‘white’ or 'other,’ so the data fail to identify Hispanics, Asians, and members of other groups,” they stated.
Until direct reporting measures become feasible, an interim strategy of imputing information on race or ethnic background through indirect estimation, is one data gathering option. “The most common indirect method uses geographically coded data from the U.S. Census [Bureau] to characterize people on the basis of their address or zip code as living in a high-, medium- or low-minority area,” stated the authors. “A second approach uses each person’s surname, along with Census information on the self-identification of people with that name.”
Newer methods estimate probabilities for each race or ethnic category instead of assigning a single race or ethnic background to an individual. The probabilities can then be “rolled up” to estimate racial distributions in populations or combined with utilization data to examine disparities in care, according to the authors. “Used in this way, imputed data can reveal aggregate disparities with remarkable accuracy.”
“The usefulness of indirect estimation would increase enormously if all insurers combined their data, and in fact that may happen in some areas,” they noted. For example, several states have begun constructing all-payor claims databases that include medical and pharmacy data for all providers from public and private health plans.
Statewide data could benefit consumers choosing among health plans or accountable care organizations on the basis of providers’ records in ensuring equitability of care. No state currently imputes data on race or ethnic background for all-payor databases, although Massachusetts has begun discussions regarding this, the authors reported.
“Until self-reported data become widely available, indirect estimation methods applied to all-payor databases provide an opportunity to populate vast quantities of health-claims records with racial and ethnic information,” Weissman and Hasnain-Wynia concluded. “Such an effort would launch the process of creating a national infrastructure for monitoring disparities that, we hope, will ultimately permit the achievement of widespread equity in the delivery of care.”