Background The accuracy of stroke diagnosis in administrative claims for a contemporary population of Medicare enrollees has not been studied. We assessed the validity of diagnostic coding algorithms for identifying stroke in the Medicare population by linking data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study to Medicare claims. Methods and Results The REGARDS Study enrolled 30,239 participants 45 years and older in the United States between 2003 and 2007. Stroke experts adjudicated suspected strokes using retrieved medical records. We linked data for participants enrolled in fee-for-service Medicare to claims files from 2003 through 2009. Using adjudicated strokes as the gold standard, we calculated accuracy measures for algorithms to identify incident and recurrent stroke. We linked data for 15,089 participants, among whom 422 participants had adjudicated strokes during follow-up. An algorithm using primary discharge diagnosis codes for acute ischemic or hemorrhagic stroke [ICD-9-CM codes: 430, 431, 433.x1, 434.x1, 436] had positive predictive value of 92.6% (95% Confidence Interval (CI), 88.8%-96.4%), specificity of 99.8% (99.6%-99.9%), and sensitivity of 59.5% (53.8%-65.1%). An algorithm using only acute ischemic stroke codes [433.x1, 434.x1, 436] had positive predictive value of 91.1% (95% CI, 86.6%-95.5%), specificity of 99.8% (99.7%-99.9%), and sensitivity of 58.6% (52.4%-64.7%). Conclusions Claims-based algorithms to identify stroke in a contemporary Medicare cohort had high positive predictive value and specificity, supporting their use as outcomes for etiologic and comparative effectiveness studies in similar populations. These inpatient algorithms are unsuitable for estimating stroke incidence due to low sensitivity.

Objective To assess the time-trends in utilization, clinical characteristics and outcomes of patients undergoing total ankle arthroplasty (TAA) in the U.S. Methods We used the Nationwide Inpatient Sample (NIS) data from 1998 to 2010 to examine time-trends in the utilization rates of TAA. We used the Cochran Armitage test for trend to assess time-trends across the years and the analysis of variance (ANOVA), Wilcoxon test or chi-squared test (as appropriate) to compare the first (1998–2000) and the last time periods (2009–10). Results TAA utilization rate increased significant from 1998 to 2010: 0.13 to 0.84 per 100,000 overall, 0.14 to 0.88 per 100,000 in females and from 0.11 to 0.81 per 100,000 in males (p<0.0001 for each comparison for time-trends). Compared to the 1998–2000, those undergoing TAA in 2009–10: were older (41% fewer patients <50 years, p<0.0001); less likely to have RA as the underlying diagnosis (55% fewer patients, p=0.0001); more likely to have Deyo-Charlson index of two or more (197% more, p=0.0010); and had a shorter length of stay at 2.5 days (17% reduction, p<0.0001). Mortality was rare, ranging 0 to 0.6% and discharge to inpatient facility ranged 12.6–14.1%; we noted no significant time-trends in either (p>0.05). Conclusions The utilization rate of TAA increased rapidly in the U.S. from 1998 to 2010, but post-arthroplasty mortality rate was stable. Underlying diagnosis and medical comorbidity changed over time and both can impact outcomes after TAA. Further studies should examine how the outcomes and complications of TAA have evolved over time.

We found increasing racial disparities in TSA utilization. Some disparities in outcomes exist as well. Patients, surgeons, and policy-makes should be aware of these findings and take action to reduce racial disparities.