The Health Care Financing Administration maintains a wide array of data systems that are essential to the functioning of the Medicare program. These data, collected and maintained for the purposes of ensuring entitlements and payment for services, also can be used to monitor programmatic changes and to define potential problem areas. The end-stage renal disease (ESRD) Program Management and Medical Information System (PMMIS) is a subset of the larger Medicare statistical system. It is a historic record of all Medicare ESRD beneficiaries dating back to 1978. Basic Medicare enrollment information on ESRD beneficiaries is enhanced with the addition of information on the cause of renal failure, type of dialysis therapy, transplantation history, and cause of death. The ESRD PMMIS has been put to a number of uses in the past decade or so, ranging from basic descriptive epidemiology to analyses of mortality rates to assessments of programmatic issues such as the composite rate and dialyzer reuse. Because of the limited clinical detail in the PMMIS, there are many specific questions that cannot be adequately addressed. With approval of the Food and Drug Administration and Medicare coverage of erythropoietin, a erythropoietin monitoring system was developed to assess utilization trends of this anemia control drug. Within a few months it became evident that dosing levels for erythropoietin were much lower than expected from the clinical trials. Following a change in the payment method from a fixed amount to one based on dose level, dosing has increased markedly. However, hematocrit levels still remain below optimal levels. This lack of hematocrit response has led the Health Care Financing Administration, in concert with the renal community, to target anemia control as a potential health care quality improvement project. This paper presents an example of the type of data presentation that can be derived from the current PMMIS. The Health Standards and Quality Bureau has made a commitment to a program of continuous quality improvement. Part of this process is the provision of descriptive data that can be the starting point for an iterative approach to quality improvement.