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Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations identified if/when they are shared with providers;
Ways to address the challenges of defining and collecting accurate and standardized self-identified demographic information, including information on race and ethnicity and disability, for the purposes of reporting, measure stratification and other data collection efforts relating to quality.
Recommendations for other types of readily available data elements for measuring disadvantage and discrimination for the purposes of reporting, measure stratification and other data collection efforts relating to quality, in addition, or in combination with race and ethnicity.
Recommendations for types of quality measures or measurement domains to prioritize for stratified reporting by dual eligibility, race and ethnicity, and disability.
Examples of approaches, methods, research, and considerations or any combination of these for use of datadriven technologies that do not facilitate exacerbation of health inequities, recognizing that biases may occur in methodology or be encoded in datasets.
We received comments on these topics.
Comments: Many commenters expressed support for the collection of data to support stratifying or otherwise measuring disparities in care related to dual-eligibility, race and ethnicity, and disability. Some commenters specifically supported the confidential reporting of stratified results to facilities. Several commenters urged CMS to expand data collection and measure stratification to include factors such as language preference, veteran status, health literacy, gender identity, and sexual orientation to provide a more comprehensive assessment of health equity. One commenter urged CMS to collect data on race and ethnicity specifically for patients suffering from psychiatric disorders, while another noted that for the IPF patient population risk factors, such as substance abuse, may be of more importance. One commenter also provided examples of how their health system has successfully collected and begun to analyze patient-level demographic data.
Another commenter referred to an existing effort by the National Committee for Quality Assurance to improve the collection of race and ethnicity data as a possible model for improving data collection. This commenter also supported the use of indirect estimation of race and ethnicity for Medicare beneficiaries, noting some concern about the lack of granularity, especially with respect to Native
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American and Asian populations. One commenter urged CMS to explore how to best identify social determinants of health using current claims data.
While many commenters expressed support for stratification of claims-based measures, many commenters expressed concern that the existing chartabstracted measures would face limitations when stratified and thus felt the burden of collecting stratification data for these measures significantly outweighed any potential benefit of doing so. Specifically, commenters noted that stratifying the IPF patient population is more vulnerable to statistical concerns during the stratification process than other patient populations for example, numbers of patients in one or more strata may be insufficient for reliable sampling and calculations due to low patient volume in some facilities. One commenter suggested that for this and other reasons CMS should develop disparities reporting specifically for the IPF
program rather than adopt an approach developed for a different program. A
few commenters also questioned the value of stratification of these measures given the current high levels of performance by many IPFs.
One commenter noted that stratified claims-based measures would exclude all privately insured care and thus be less useful. Several commenters stated that interoperability issues such as a lack of EHRs, particularly for IPFs that are smaller or not part of a large hospital or health system, further add to the burden of stratifying chart-abstracted measures and may contribute to bias in the data.
Several commenters also noted that stratification may be challenging due to differences in the patient population served by IPFs compared to other Medicare programs such as acute and long-term care hospitals, for example, age, proportion and reason for dualeligibility income versus disability, and substance abuse disorder prevalence. However, several commenters noted many of these same characteristics, as well as the mental and behavioral health needs of patients cared for by IPFs, are evidence of the need to improve data collection and measurement in IPFs. A commenter also recommended further analysis on the predictive power of social risk factors on mental and behavioral health patient outcomes compared to that of the diagnosis requiring treatment. Several commenters recommended CMS further address issues related to the potential stratification of data such as: Patient privacy and the collection and sharing of social risk factors from patient
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records or through indirect estimation, differing requirements for collection of race and ethnicity data, transparency regarding indirect estimation methods, and differing Medicaid eligibility requirements by state. One commenter related these concerns to public reporting, suggesting support for confidential reporting until these issues are addressed.
We appreciate all of the comments and interest in this topic. We believe that this input is very valuable in the continuing development of the CMS
health equity quality measurement efforts. We will continue to take all concerns, comments, and suggestions into account for future development and expansion of our health equity quality measurement efforts.
Improving Demographic Data Collection Experiences of users of certified health IT regarding local adoption of practices for collection of social, psychological, and behavioral data elements, the perceived value of using these data for improving decisionmaking and care delivery, and the potential challenges and benefits of collecting more granular, structured demographic information, such as the Race & EthnicityCDC code system.
The possible collection of a minimum set of social, psychological, and behavioral data elements by hospitals at the time of admission using structured, interoperable data standards, for the purposes of reporting, measure stratification and other data collection efforts relating to quality.
We received comments on these topics.
Comments: We received mixed feedback regarding demographic data collection. Many commenters supported the need for and use of such data, noting that structured, interoperable electronic health data are the gold standard. They also noted that many barriers exist to adopting electronic health information technology systems necessary for capture of these data, particularly in freestanding psychiatric facilities. A
commenter stated that the commenters organization cannot support demographic data collection due to the workload burden it would place on both the IPF and patients and their families.
This commenter also noted that the likelihood of patients and families comfortably answering multiple sensitive demographic questions is low, especially upon admission. Another commenter expressed concerns with the current capabilities of the industry to collect these data, specifying a lack of standardization in screening and data collection and need for staff training.

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