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Measuring Quality of Care for Rheumatic Diseases Using an Electronic Medical Record
  1. Jessica C Agnew-Blais (jagnew{at}
  1. Harvard School of Public Health, United States
    1. John S Coblyn (jcoblyn{at}
    1. Brigham and Women's Hospital, United States
      1. Jeffrey N Katz (jnkatz{at}
      1. Brigham and Women's Hospital, United States
        1. Ronald J Anderson (randerson{at}
        1. Brigham and Women's Hospital, United States
          1. Jyotsna Mehta (jmehta{at}
          1. Brigham and Women's Hospital, United States
            1. Daniel H Solomon (dhsolomon{at}
            1. Brigham and Women's Hospital, United States


              Objectives: The objective of this study was two-fold: one, to determine how best to measure adherence with time-dependent quality indicators (QIs) related to laboratory monitoring, and two, to assess the accuracy and efficiency of gathering QI adherence information from an electronic medical record (EMR).

              Methods: We selected a random sample of 100 patients who had at least three visits with the diagnosis of rheumatoid arthritis (RA) at Brigham and Women’s Hospital Arthritis Center in 2005. Using the EMR, we determined whether patients had been prescribed a DMARD (QI #1) and if patients starting therapy received appropriate baseline laboratory testing (QI # 2). For patients consistently prescribed a DMARD, we calculated adherence with follow-up testing (QI #3) using three different methods, the Calendar, Interval and Rolling Interval Methods.

              Results: We found 97% of patients were prescribed a DMARD (QI #1) and baseline tests were completed in 50% of patients (QI #2). For follow-up testing (QI #3), mean adherence was 60% for the Calendar Method, 35% for the Interval Method, and 48% for the Rolling Interval Method. Using the Rolling Interval Method, adherence rates were similar across drug and laboratory testing type.

              Conclusions: Results for adherence with laboratory testing QIs for DMARD use differed depending on how the QIs were measured, suggesting that care must be taken in clearly defining methods. While EMRs will provide important opportunities for measuring adherence with QIs, they also present challenges that must be examined before widespread adoption of these data collection methods.

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