Use of Medicare Administrative Claims to Identify a Population at High Risk for Adverse Drug Events and Hospital Use for Quality Improvement.

Abstract

A system using administrative claims to monitor medication use patterns and associated adverse events is not currently available. Establishment of a standardized method to identify Medicare beneficiaries at high risk for adverse events, by assessing Medicare Part D medication claim patterns and associated outcomes, including outpatient adverse drug events (ADEs) and hospital use, enhances prevention efforts and monitoring for quality improvement efforts. To (a) demonstrate that Medicare claims data can be used to identify a population of beneficiaries at high risk for adverse events for quality improvement and (b) define trends associated with adverse health outcomes in identified high-risk beneficiaries for quality improvement opportunities. We used Medicare fee-for-service Part D claims data to identify a population at high risk for adverse events by evaluating medication use patterns. This population was taking at least 3 medications, 1 of which was an anticoagulant, an opioid, or an antidiabetic agent. Next, we used associated Part A claims to calculate rates of outpatient ADEs, looking for specific ICD-9-CM or ICD-10-CM codes in the principal diagnosis code position. Rates of hospital use (inpatient hospitalization, observation stays, emergency department visits, and 30-day rehospitalizations) were also evaluated for the identified high-risk population. The data were then shared for targeted quality improvement. We identified 8,178,753 beneficiaries at high risk for adverse events, or 20.7% of the total eligible fee-for-service population (time frame of October 2016-September 2017). The overall rate of outpatient ADEs for beneficiaries at high risk was 46.28 per 1,000, with anticoagulant users demonstrating the highest rate of ADEs (68.52/1,000), followed by opioid users (42.11/1,000) and diabetic medication users (20.72/1,000). As expected, the primary setting for beneficiaries at high risk to seek care for outpatient ADEs was the emergency department, followed by inpatient hospitalizations and observation stays. Medicare claims are an accessible source of data, which can be used to establish for quality improvement a population at high risk for ADEs and increased hospital use. Using medication use patterns to attribute risk and associated outcomes, such as outpatient ADEs and hospital use, is a simple process that can be readily implemented. The described method has the potential to be further validated and used as a foundation to monitor population-based quality improvement efforts for medication safety. This work was performed under contract HHSM-500-2014-QINNCC, Modification No. 000004, funded by Centers for Medicare & Medicaid Services (CMS), an agency of the U.S. Department of Health and Human Services. CMS did not have a role in the analysis. At the time of this analysis, Digmann, Peppercorn, Zhang, Irby, and Brock were employees of Telligen, which was awarded the National Coordinating Center-Quality Improvement Organization contract from CMS, which supported the work. Ryan was an employee at Qsource, which was awarded the Quality Innovation Network-Quality Improvement Organization contract from CMS, which supported the work. Thomas was employed by CMS. The content is solely the responsibility of the authors and does not necessarily represent the official views or policies of the CMS. This work is posted on the QIOprogram.org website, as recommended in the Common Rule ( https://www.hhs.gov/ohrp/regulations-and-policy/regulations/common-rule/index.html ).