On this page: About the National Data | Methodology | History
About the National Data
Data
Data Source: United States Renal Data System (USRDS), NIH/NIDDK
Baseline: 48.4 percent of Medicare beneficiaries with diabetes mellitus had urinary albumin testing in 2016
Target: 66.4 percent
Methodology
Methodology notes
Data for previous years are recalculated for each Annual Data Report from the USRDS data, due to data collection procedures and delay of reporting of some information to the USRDS database. Values displayed are revised accordingly. Codes used to determine urinary albumin testing are taken directly from the Health Plan Employer Data and Information Set (HEDIS) 2002 specification. HEDIS is a set of standardized measures designed to ensure that purchasers and consumers have the information they need to reliably compare the performance of managed health care plans. They are CPT (current procedure and terminology) codes 82042, 82043, and 82044. CPT is a listing of descriptive terms and identifying codes for reporting medical services and procedures. The cohort includes patients enrolled in Medicare before January 1 of each year, alive and remaining in the program through December 31, and who have diabetes diagnosed during the same year. Patients enrolled in an HMO, or with Medicare as secondary payer, or diagnosed with ESRD during the year are excluded. Urine albumin testing is tracked in each year. Age is calculated on Dec. 31 of each year.
History
Data for previous years are recalculated for each Annual Data Report from the USRDS data, due to data collection procedures and delay of reporting of some information to the USRDS database. Values displayed are revised accordingly. As a result, in 2021 the baseline was revised from 48.7% to 48.4% of Medicare beneficiaries with diabetes obtained an annual urinary albumin measurement in 2016. The target was revised from 66.6% to 66.4% using the original target setting method.
1. Because Healthy People 2030 objectives have a desired direction (e.g., increase or decrease), the confidence level of a one-sided prediction interval can be used as an indication of how likely a target will be to achieve based on the historical data and fitted trend.