Health insurance claims data as a means of assessing reduction in co-morbidities 6 months after bariatric surgery

Obes Surg. 2006 Jul;16(7):852-8. doi: 10.1381/096089206777822241.


Background: We measured the very short-term change in obesity-related co-morbidities following bariatric surgery.

Methods: Claims data were analyzed for 933 patients aged 18-62 who were covered by one of 11 New York State health plans and underwent bariatric surgery during calendar year 2002. Data covered 6 months before to 6 months after surgery. Logit regression and fixed effects logit regressions were estimated, to analyze change in the following co-morbidities after bariatric surgery: diabetes, hyperlipidemia, hypertension, asthma, sleep apnea, degenerative joint disease, gastroesophageal reflux, and depression.

Results: There were statistically significant post-surgery decreases in each outcome studied. Controlling for individual fixed effects, the probability of a diabetes diagnosis fell by 20% after bariatric surgery. The probability of sleep apnea fell by 33%, and the probability of the other obesity-related co-morbidities fell by 11 to 19% at 6 months.

Conclusion: Claims data are useful for assessing changes in a wide range of co-morbidities following bariatric surgery. The data indicate significant decreases in obesity-related co-morbidities after bariatric surgery, although considerably smaller than those found in previous studies, which underscores the need for randomized controlled trials of bariatric surgery. Limitations of this study include: follow-up only at 6 months, non-experimental data, and an unknown degree of under-reporting of co-morbidities in claims data.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Bariatric Surgery / economics*
  • Comorbidity / trends*
  • Female
  • Humans
  • Insurance, Health*
  • Male
  • Medicare
  • Middle Aged
  • New York
  • Obesity, Morbid / epidemiology
  • Obesity, Morbid / surgery*
  • Postoperative Period
  • Regression Analysis
  • United States