Background and Objective: With visits to ambulatory surgery centers (ASCs) on the rise, accountability in the care provided by these facilities and the surgeons who staff them is required. This requires the ability to measure and monitor ASC-based care over time. For this reason, we developed and validated a claims-based algorithm to identify ASCs.
Research Design: Using a 20% sample of Medicare claims (2002-2008), we developed 3 ASC definitions. Definition 1 identified unique facilities with tax identification numbers and appropriate Place of Service and Type of Service codes. Definition 2 had the same conditions but also required specific Specialty codes. Definition 3 involved a multistep cleansing stage, in which facilities with indeterminate information in the fields of interest were eliminated. We assessed agreement between these definitions and findings from alternative data sources.
Results: Placing additional requirements on how a freestanding ASC was defined within Medicare claims helped in the refinement of our algorithm. Agreement on the number of unique ASCs in Florida over the study interval was greatest between Definition 3 and the State Ambulatory Surgery Databases (concordance correlation coefficient=0.984; 95%, confidence interval, 0.967-0.992). With the Provider of Services Extract serving as the reference standard, our algorithm (based on Definition 3) had a positive predictive value of 99.0% (95% confidence interval, 98.6%-99.4%) for determining health care markets that experienced the opening of an ASC.
Conclusions: The consequent inference is that our algorithm represents an accurate tool for distinguishing and tracking ASCs in Medicare data.
(C) 2014 by Lippincott Williams & Wilkins.