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The American Journal of Managed Care August 2016
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Variation in US Outpatient Antibiotic Prescribing Quality Measures According to Health Plan and Geography
Rebecca M. Roberts, MS; Lauri A. Hicks, DO; and Monina Bartoces, PhD
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Variation in US Outpatient Antibiotic Prescribing Quality Measures According to Health Plan and Geography

Rebecca M. Roberts, MS; Lauri A. Hicks, DO; and Monina Bartoces, PhD
Antibiotic prescribing has become viewed as a patient safety and quality-of-care issue. The authors analyzed quality measures related to appropriate antibiotic prescribing and testing.
We analyzed the following 3 HEDIS measures: 1) “Appropriate Testing for Children With Pharyngitis” (pharyngitis testing), which is defined as the proper diagnosis of streptococcal pharyngitis for children aged between 2 and 18 years. This requires a diagnosis of pharyngitis, an antibiotic being prescribed, and a group A Streptococcus (strep) test administered for the episode in eligible children; 2) “Appropriate Treatment for Children With Upper Respiratory Infections” (URIs), which is defined as the percent of antibiotic prescriptions for eligible children aged between 3 months and 18 years who were diagnosed with a URI (common cold) and not prescribed an antibiotic on or within 3 days of the episode date; and 3) “Avoidance of Antibiotic Treatment in Adults With Acute Bronchitis” (bronchitis), which is defined as the percent of eligible adults diagnosed with acute bronchitis and not prescribed an antibiotic.
For all 3 measures, a higher percent indicates better performance. The technical specifications for the measures, including how eligible populations are determined and reported by participating health plans, have been previously published by NCQA.12
We obtained a data set from NCQA containing the 3 measures for the years 2008 to 2012. This data set only included commercial health plans (Medicaid and Medicare were excluded) and all lines of business (health maintenance organization [HMO], preferred provider organization [PPO], and point of service [POS]).13 The data included confidence intervals for each measure and for each year, according to health plan. We also received national, US Census division,14 and state means and medians for each measure. Not every health plan reported data for each relevant measure for each year; therefore, some health plans and states are missing data for 1 or more measures in any given year. No identifying characteristics related to the individual health plans were included in this analysis, as the intent was to learn more about the overall performance on the measures of interest and not to identify specific health plans by name or to provide a ranking of individual plans based on performance.
We first assessed whether there were extreme observations, or outliers, in the data at the individual health plan level. We computed simple statistics, describing the variation of the individual plan rates using mean and standard deviation by year. We determined if there was a decreasing or increasing linear trend in the average of each relevant HEDIS measure from 2008 to 2012 and explored variability between, and within, health plans over time. We also performed descriptive statistics based on whether the reporting product was an HMO, a PPO, a POS, or a combination of these, to determine if this had an impact on performance. However, we did not perform descriptive statistics for plans with sample sizes of less than 10, so the reporting products included in these analyses were HMO, HMO/POS combined, and PPO. We also determined whether there were differences in mean rates among these 3 reporting products for each HEDIS measure by year using SAS Proc GLM (SAS Institute, Cary, North Carolina) to account for unequal sample sizes. For multiple comparisons, we also adjusted means using the Tukey method. Additionally, we explored geographic variation in HEDIS measure performance by Census division for all years (2008-2012) using the mean for each measure in each Census division for each year. Data management and all analyses were performed using SAS version 9.3 (SAS Institute, Cary, North Carolina).
During 2008 to 2012, an average of 373 (347-394) individual plans reported on the 3 measures to NCQA (Table). Wide variations were observed at the individual health plan level within measures for the years 2008 to 2012. Across all years and all reporting health plans, the overall mean of children tested for group A Streptococcus and prescribed an antibiotic (pharyngitis testing) was 77% (range = 2.23%-96.6%). For URIs, the mean percent of children treated appropriately was 84% (range = 31.1%-99.4%). The avoidance of antibiotic treatment for adults with bronchitis was 24% (range = 7.4%-90.5%). 
Testing for pharyngitis improved over time (P <.01), with the lowest average of 74.6% in 2008 and the highest of 79.9% in 2012. The proportion of children to whom antibiotics were not prescribed for URIs did not change significantly over the study period (P = .93); the highest average was 85% in 2011 and the lowest was 83.4% in 2012. The bronchitis measure did not improve over the time period; in fact, there was a decreasing trend in antibiotic avoidance for bronchitis (P = .03), with the highest (best) average of 26.6% in 2008 and the lowest (worst) of 22.1% in 2011, with no improvement in 2012 (22.7%).

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