Administrative Databases Can Yield False Conclusions-An Example of Obesity in Total Joint Arthroplasty.

BACKGROUND: Research using large administrative databases has substantially increased in recent years. Accuracy with which comorbidities are represented in these databases has been questioned. The purpose of this study was to evaluate the extent of errors in obesity coding and its impact on arthroplasty research.

METHODS: Eighteen thousand thirty primary total knee arthroplasties (TKAs) and 10,475 total hip arthroplasties (THAs) performed at a single healthcare system from 2004-2014 were included. Patients were classified as obese or nonobese using 2 methods: (1) body mass index (BMI) ≥30 kg/m2 and (2) international classification of disease, 9th edition codes. Length of stay, operative time, and 90-day complications were collected. Effect of obesity on various outcomes was analyzed separately for both BMI- and coding-based obesity.

RESULTS: From 2004 to 2014, the prevalence of BMI-based obesity increased from 54% to 63% and 40% to 45% in TKA and THA, respectively. The prevalence of coding-based obesity increased from 15% to 28% and 8% to 17% in TKA and THA, respectively. Coding overestimated the growth of obesity in TKA and THA by 5.6 and 8.4 times, respectively. When obesity was defined by coding, obesity was falsely shown to be a significant risk factor for deep vein thrombosis (TKA), pulmonary embolism (THA), and longer hospital stay (TKA and THA).

CONCLUSION: The growth in obesity observed in administrative databases may be an artifact because of improvements in coding over the years. Obesity defined by coding can overestimate the actual effect of obesity on complications after arthroplasty. Therefore, studies using large databases should be interpreted with caution, especially when variables prone to coding errors are involved.