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Background: The link between body weight status and spinal diseases has been suggested by a number of cross-sectional and cohort studies with a limited range of patient populations. No population-representative samples have been used to examine the link between obesity and spinal diseases. The present study is based on a nationally representative sample drawn from the Medical Expenditure Panel Survey. Methods: Using the cross-sectional sample of the 2014 Medical Expenditure Panel Study, we built four weighted logistic regression analyses of the associations between body weight status and the following four spinal diseases: low back pain, spondylosis, other cervical disorders and intervertebral disc disorder (IDD). Each respondent’s body weight status was used as the key independent variable with three categories: normal/underweight, overweight, and obese. We controlled for marital status, gender, age, smoking status, household income, health insurance coverage, educational attainment and the use of health services for other major categories of diseases. Results: A total sample of 23,048 respondents was used in our analysis. Overweight and obese respondents, as compared to normal/underweight respondents, were more likely to develop lower back problems (Overweight: logged odds = 0.218, p < 0.01; Obese: logged odds = 0.395, p < 0.001) and IDD (Overweight: logged odds = 0.441, p < 0.05; Obese: logged odds = 0.528, p < 0.001). The associations between bodyweight status and spondylitis were statistically insignificant (Overweight: logged odds = 0.281, p = 0.442; Obese: logged odds = 0.680, p = 0.104). The associations between body weight status and other cervical disorders (Overweight: logged odds = −0.116, p = 0.304; Obese: logged odds = −0.160, p = 0.865) were statistically insignificant. Conclusions: As the first study using a national sample to study bodyweight and spinal diseases, our paper supports the hypothesis that obesity adds to the burden of low back pain and IDD. Longitudinal and interventional studies are needed to understand the specific mechanisms behind these positive associations.

BackgroundDemand for total hip arthroplasty (THA) is high and expected to continue to grow during the next decade. Although much of this growth includes working-aged patients, cost-effectiveness studies on THA have not fully incorporated the productivity effects from surgery.Questions/PurposesWe asked: (1) What is the expected effect of THA on patients’ employment and earnings? (2) How does accounting for these effects influence the cost-effectiveness of THA relative to nonsurgical treatment?MethodsTaking a societal perspective, we used a Markov model to assess the overall cost-effectiveness of THA compared with nonsurgical treatment. We estimated direct medical costs using Medicare claims data and indirect costs (employment status and worker earnings) using regression models and nonparametric simulations. For direct costs, we estimated average spending 1 year before and after surgery. Spending estimates included physician and related services, hospital inpatient and outpatient care, and postacute care. For indirect costs, we estimated the relationship between functional status and productivity, using data from the National Health Interview Survey and regression analysis. Using regression coefficients and patient survey data, we ran a nonparametric simulation to estimate productivity (probability of working multiplied by earnings if working minus the value of missed work days) before and after THA. We used the Australian Orthopaedic Association National Joint Replacement Registry to obtain revision rates because it contained osteoarthritis-specific THA revision rates by age and gender, which were unavailable in other registry reports. Other model assumptions were extracted from a previously published cost-effectiveness analysis that included a comprehensive literature review. We incorporated all parameter estimates into Markov models to assess THA effects on quality-adjusted life years and lifetime costs. We conducted threshold and sensitivity analyses on direct costs, indirect costs, and revision rates to assess the robustness of our Markov model results.ResultsCompared with nonsurgical treatments, THA increased average annual productivity of patients by USD 9503 (95% CI, USD 1446–USD 17,812). We found that THA increases average lifetime direct costs by USD 30,365, which were offset by USD 63,314 in lifetime savings from increased productivity. With net societal savings of USD 32,948 per patient, total lifetime societal savings were estimated at almost USD 10 billion from more than 300,000 THAs performed in the United States each year.ConclusionsUsing a Markov model approach, we show that THA produces societal benefits that can offset the costs of THA. When comparing THA with other nonsurgical treatments, policymakers should consider the long-term benefits associated with increased productivity from surgery.Level of EvidenceLevel III, economic and decision analysis.Electronic supplementary materialThe online version of this article (doi:10.1007/s11999-016-5084-9) contains supplementary material, which is availab...

PurposeGlucarpidase (Voraxaze) is used to treat methotrexate (Mtx) toxicity in patients with delayed Mtx clearance due to impaired renal function. We examine hospital length of stay (LOS), mortality, and readmission rates for Medicare cancer patients with delayed clearance of Mtx treated with glucarpidase.MethodsUsing 2010–2017 Medicare claims data, we identified glucarpidase patients as those hospitalized with indications of select lymphomas or leukemia, inpatient chemotherapy, and glucarpidase treatment. We assessed outcomes of glucarpidase patients relative to those experienced by patients treated for presumed Mtx toxicity using other therapies. These nonglucarpidase patients were identified with a diagnosis of primary central nervous system lymphoma, indications of cancer-chemotherapy toxicity, and acute kidney injury during hospitalization (not present on admission), and were divided into two groups: treated with dialysis (dialysis+) and treated with or without dialysis (dialysis+/−). Inverse-probability treatment weighting using propensity scores was used to adjust for differences between groups.ResultsPatients treated with glucarpidase (n=30) had an average LOS of 14.7 days. They had inpatient, 30-day, and 90-day mortality rates of 3.3%, 13.3%, and 16.7%, respectively, and a 90-day all-cause unplanned readmission rate of 24.1%. The dialysis+ and dialysis+/− groups, respectively, had higher average LOS (40.2, 21.9), higher inpatient mortality (50.6%, 20.8%), and higher 90-day mortality (58.6%, 37.6%). No statistically significant differences in 30-day mortality or 90-day readmission rates were detected between the glucarpidase group and either of the nonglucarpidase groups. Unobservable differences in patient severity may impact the interpretation of our findings.ConclusionMedicare cancer patients with presumed Mtx toxicity receiving conventional treatment experience long hospitalizations, high intensive-care unit use and high mortality. Glucarpidase patients had lower LOS, inpatient mortality, and 90-day mortality than the non-glucarpidase patients.

Adverse selection predicts that individuals with lower health status would be more likely to sign up for health insurance. This hypothesis was tested among the long-term uninsured population in South Carolina (SC). This study used data from an in-person survey conducted from May 2014 to January 2015. Interviews were held with the long-term uninsured individuals at multiple sites throughout the state, using a multistage sampling method. SC residents aged 18 to 64 years who had had no health insurance for at least 24 consecutive months were eligible for the survey. The dependent variable is the participants’ attempt to obtain insurance coverage. Key independent variables are self-reported health status, hospitalization in the past year, use of emergency department in the past year, and presence of serious long-standing health problems. The analysis is stratified by the awareness of the Affordable Care Act (ACA)’s individual mandate while controlling for age, gender, race/ethnicity, and household income. Participants’ self-reported health status was not significantly associated with the attempt to sign up for health insurance in both groups (those aware and those unaware of the individual mandate). Being hospitalized in the previous year was significantly associated with their attempt to sign up for insurance in both groups. Participants with serious long-term health problems were more likely to have attempted to sign up for insurance among those who were not aware of the ACA. However, this association was statistically insignificant among those who had heard of ACA. Sicker people were more likely to attempt to sign up for insurance. However, being aware of the ACA’s individual mandate seemed to play a role in reducing adverse selection.