Impact of bariatric surgery on health care costs of obese persons: a 6-year follow-up of surgical and comparison cohorts using health plan data.

IMPORTANCE: Bariatric surgery is a well-documented treatment for obesity, but there are uncertainties about the degree to which such surgery is associated with health care cost reductions that are sustained over time. OBJECTIVE: To provide a comprehensive, multiyear analysis of health care costs by type of procedure within a large cohort of privately insured persons who underwent bariatric surgery compared with a matched nonsurgical cohort. DESIGN: Longitudinal analysis of 2002-2008 claims data comparing a bariatric surgery cohort with a matched nonsurgical cohort. SETTING: Seven BlueCross BlueShield health insurance plans with a total enrollment of more than 18 million persons. PARTICIPANTS: A total of 29 820 plan members who underwent bariatric surgery between January 1, 2002, and December 31, 2008, and a 1:1 matched comparison group of persons not undergoing surgery but with diagnoses closely associated with obesity. MAIN OUTCOME MEASURES: Standardized costs (overall and by type of care) and adjusted ratios of the surgical group's costs relative to those of the comparison group. RESULTS: Total costs were greater in the bariatric surgery group during the second and third years following surgery but were similar in the later years. However, the bariatric group's prescription and office visit costs were lower and their inpatient costs were higher. Those undergoing laparoscopic surgery had lower costs in the first few years after surgery, but these differences did not persist. CONCLUSIONS AND RELEVANCE: Bariatric surgery does not reduce overall health care costs in the long term. Also, there is no evidence that any one type of surgery is more likely to reduce long-term health care costs. To assess the value of bariatric surgery, future studies should focus on the potential benefit of improved health and well-being of persons undergoing the procedure rather than on cost savings.

Effect of cost-sharing reductions on preventive service use among Medicare fee-for-service beneficiaries.

BACKGROUND: Section 4104 of the Patient Protection and Affordable Care Act (ACA) waives previous cost-sharing requirements for many Medicare-covered preventive services. In 1997, Congress passed similar legislation waiving the deductible only for mammograms and Pap smears. The purpose of this study is to examine the effect of the deductible waiver on mammogram and Pap smear utilization rates. METHODS: Using 1995-2003 Medicare claims from a sample of female, elderly Medicare fee-for-service beneficiaries, two pre/post analyses were conducted comparing mammogram and Pap smear utilization rates before and after implementation of the deductible waiver. Receipt of screening mammograms and Pap smears served as the outcome measures, and two time measures, representing two post-test observation periods, were used to examine the short- and long-term impacts on utilization. RESULTS: There was a 20 percent short-term and a 25 percent longer term increase in the probability of having had a mammogram in the four years following the 1997 deductible waiver. Beneficiaries were no more likely to receive a Pap smear following the deductible waiver. CONCLUSIONS: Elimination of cost sharing may be an effective strategy for increasing preventive service use, but the impact could depend on the characteristics of the procedure, its cost, and the disease and populations it targets. These historical findings suggest that, with implementation of Section 4104, the greatest increases in utilization will be seen for preventive services that screen for diseases with high incidence or prevalence rates that increase with age, that are expensive, and that are performed on a frequent basis.

Development of a claims-based risk score to identify obese individuals.

Obesity is underdiagnosed, hampering system-based health promotion and research. Our objective was to develop and validate a claims-based risk model to identify obese persons using medical diagnosis and prescription records. We conducted a cross-sectional analysis of de-identified claims data from enrollees of 3 Blue Cross Blue Shield plans who completed a health risk assessment capturing height and weight. The final sample of 71,057 enrollees was randomly split into 2 subsamples for development and validation of the obesity risk model. Using the Johns Hopkins Adjusted Clinical Groups case-mix/predictive risk methodology, we categorized study members' diagnosis (ICD) codes. Logistic regression was used to determine which claims-based risk markers were associated with a body mass index (BMI) > or = 35 kg/m(2). The sensitivities of the scores > or =90(th) percentile to detect obesity were 26% to 33%, while the specificities were >90%. The areas under the receiver operator curve ranged from 0.67 to 0.73. In contrast, a diagnosis of obesity or an obesity medication alone had very poor sensitivity (10% and 1%, respectively); the obesity risk model identified an additional 22% of obese members. Varying the percentile cut-point from the 70(th) to the 99(th) percentile resulted in positive predictive values ranging from 15.5 to 59.2. An obesity risk score was highly specific for detecting a BMI > or = 35 kg/m(2) and substantially increased the detection of obese members beyond a provider-coded obesity diagnosis or medication claim. This model could be used for obesity care management and health promotion or for obesity-related research.