: To evaluate the cost-effectiveness of osteoporosis treatments for women at high fracture risk and estimate the population-level impact of providing bisphosphonate therapy to all eligible high-risk US women.

: Fractures, healthcare costs, and quality-adjusted life-years (QALYs) were estimated over 10 years using a Markov model.

: No therapy, risedronate, alendronate, ibandronate, and teriperatide (PTH) were compared among 4 risk groups. Sensitivity analyses examined the robustness of model results for 65-year-old women with low bone density and previous vertebral fracture.

: Women treated with a bisphosphonate experienced fewer fractures and more QALYs compared with no therapy or PTH. Total costs were lowest for the untreated cohort, followed by risedronate, alendronate, ibandronate, and PTH in all risk groups except women aged 75 years with previous fracture. The incremental cost-effectiveness of risedronate compared with no therapy ranged from cost saving for the base case to $66,722 per QALY for women aged 65 years with no previous fracture. Ibandronate and PTH were dominated in all risk groups. (A dominated treatment has a higher cost and poorer outcome.) Treating all eligible women with a bisphosphonate would cost an estimated additional $5563 million (21% total increase) and would result in 390,049 fewer fractures (35% decrease). In the highest risk group, the additional cost of therapy was offset by other healthcare cost savings.

: Osteoporosis treatment of high-risk women is cost-effective, with bisphosphonates providing the most benefit at lowest cost. For highest risk women, costs are offset by savings from fracture prevention.

Osteoporosis has been defined as a skeletal disorder characterized by compromised bone strength predisposing a person to an increased risk of fracture.

 The National Health and Nutrition Examination Survey (NHANES) III estimated that 13% to 18% of women in the United States have osteoporosis.

 The prevalence of postmenopausal osteoporosis (PMO) increases with age from approximately 6% at age 50 years to more than 50% above age 80 years.

 The high osteoporosis prevalence coupled with its significant health consequences makes effective prevention and treatment leading public health concerns.

Current treatment options include bisphosphonates (eg, alendronate, risedronate, ibandronate), calcitonins, parathyroid hormone (PTH), and selective estrogen receptor modulators. 

Cost-effectiveness analysis provides important information about the value of alternative therapies that may assist decision makers who seek to equitably allocate constrained resources to achieve maximum healthcare benefits on a population level. Although several articles have addressed the economic value of specific agents,

 the cost-effectiveness of all currently available bone-specific agents approved for treatment of PMO in the United States has not been reported. Another point of differentiation is that our study includes a population-based budget impact analysis to evaluate a policy to extend treatment to all eligible patients within defined risk groups. Budget impact analysis estimates the cost of treatment on an annual basis for budgeting purposes. 

The objective of this study was to evaluate (from the healthcare system perspective) the cost-effectiveness of risedronate therapy compared with alendronate, ibandronate, and PTH for the treatment of women with PMO at high fracture risk. A secondary objective was to estimate the population-level impact of a decision to provide bisphosphonate treatment to all eligible US women not currently treated. 

For all model parameters, published data sources were used wherever possible and consisted primarily of clinical trials, economic studies, observational studies, and epidemiologic databases. Details are provided below and summarized in 

. With respect to treatment, the base-case estimates for therapy duration, offset, and discontinuation were derived from advice from clinical experts.

Our analysis focuses on treatment of postmenopausal women at high risk for fractures; therefore, fracture rates in the age-matched general population were adjusted to reflect the increased risk of new fractures in patients with low BMD and a previous vertebral fracture using the relative risk values noted in Table 1.

 This adjustment has been described fully  elsewhere.

Age-specific hip fracture incidence rates for the total US female population aged 65 to 100 years (all races) were obtained from a retrospective study on the Nationwide Inpatient Sample 2001 hospital discharge database. The analysis included only closed fractures that did not result from severe trauma, and were defined as inpatient hospital cases with 1 of the following 

International Classification of Diseases, Ninth Revision

 codes as the primary diagnosis: 820.0x (transcervical), 820.2x (pertrochanteric), 820.8x (neck of femur).

Age-specific incidence rates for clinically ascertained vertebral fracture were taken from an analysis of the Rochester  Epidemiological Project database, which captured patients treated on both an inpatient and outpatient basis (only 24% of fracture patients are hospitalized). 

Mortality in the year after hip fracture was modeled based on analysis of Medicare claims data from 1999 to 2000 with age-specific mortality rates per 10,000 estimated at 130.29 for age 65 to 69 years, 138.07 for age 70 to 74 years, 166.80 for age 75 to 79 years, 203.38 for age 80 to 84 years, 298.74 for age 85 to 89 years, and 298.74 for age 90 years and older. No excess mortality was modeled following vertebral fracture. 

The bone-specific osteoporosis treatments evaluated in the model include risedronate, alendronate, ibandronate, and PTH. These reflect current practice patterns, capturing those treatments that are used most frequently. The model did not consider possible concomitant calcium or vitamin D treatment with these therapies, as the efficacy estimates for the comparator therapies were derived from comparisons with placebo patients who received clinically appropriate calcium and/or vitamin D supplementation. To estimate fracture rates in the treated cohort, therapy-specific efficacy rates were multiplied by adjusted age-specific fracture incidence. Therapy-specific efficacy values (percent risk reduction for hip and vertebral fracture) were obtained from randomized controlled trials with a patient population similar to the base-case risk group.

 For PTH and ibandronate, where there was no evidence (statistically significant data from a randomized controlled trial) to support the effect of a treatment on the incidence of hip fracture, only the effect on the incidence of vertebral fracture was modeled. Although we modeled clinical vertebral fracture incidence, treatment effectiveness was estimated based on clinical trial data, which relies on radiographically evident vertebral fracture.

To calculate the QALYs, utility weights were applied to each health state. Utilities reflect how quality of life in a health state is valued on a scale from 0 (death) to 1 (perfect health). This analysis assumed an age-specific utility weight of 0.833 for women aged 65 to 69 years and 0.792 for women aged 75 to 79 years in the general population.28 Age-specific utilities were reduced following fracture based on published evidence (Table 1).

To test the robustness of model results, model parameters were varied in multiple 1-way sensitivity analyses for women aged 65 years with low BMD and a previous vertebral fracture. To characterize the impact of uncertainty on treatment efficacy in the cost-effectiveness analyses, analyses that utilized either upper or lower bounds of the 95% confidence intervals for treatment efficacy for each agent were undertaken. Analyses that varied the analytic time horizon from 3 years to lifetime (base case = 10 years) and modified the therapy offset to 5 years (base case = immediate offset) also were undertaken. Therapy offset, or percentage of maximum effect after cessation of therapy, was assumed to decline linearly over time at 90%, 70%, 50%, 30%, and 10% for years 1, 2, 3, 4, and 5, respectively.

 For alendronate, however, based on data from the Fracture Intervention Trial Long-term Extension (FLEX) study,

a 50% slower rate of efficacy decline was used (ie, 90%, 80%, 70%, 60%, 50%). The impact of health utilities on the base-case estimates was evaluated first by varying the utilities by &#177;25%, and then by limiting utility decrements due to fracture only to the year of the fracture.

 Additional analyses that addressed therapy discontinuation and fracture costs also were completed based on results from the Persistence Study of Ibandronate versus Alendronate (PERSIST) trial.

 We used a cumulative therapy discontinuation rate of 76%,

 except for ibandronate, for which persistence was assumed to be 50% better than it was for weekly bisphosphonate dosing.

Given that treatment efficacy is a key factor driving the results of the cost-effectiveness analysis, we explored a broad  range of comparisons for this parameter value. The trials were not able to show any statistically significant difference in effects because they may have been underpowered for hip fractures; therefore, we explored a 1-way sensitivity analysis scenario where a 90% hip fracture efficacy rate was applied to PTH. We also undertook a probabilistic sensitivity analysis, applying triangular distributions to the efficacy variables and using upper and lower 95% confidence intervals as minimum and maximum values. 

Over the 10-year period, women aged 65 years with a previous vertebral fracture who were treated with a bisphosphonate (risedronate, alendronate, or ibandronate) experienced fewer hip and vertebral fractures (a total of 441-464 fractures) compared with those receiving no therapy (550 fractures) or treatment with PTH (501 fractures) (

). Likewise, those treated with a bisphosphonate (risedronate, alendronate, or ibandronate) had more QALYs (6.646, 6.647, and 6.624 QALYs, respectively) compared with those receiving no therapy (6.580 QALYs) or treatment with PTH (6.608 QALYs). The most hip fractures (n = 137) and vertebral fractures (n = 413) were experienced by those who received no therapy. Women treated with risedronate experienced the fewest hip fractures (n = 105), whereas patients treated with ibandronate experienced the fewest vertebral fractures (n = 327). Except for those who received no therapy, women treated with PTH experienced the most vertebral fractures (n = 364), whereas those treated with ibandronate or PTH experienced the most hip fractures (n = 137). A similar pattern was observed among treatments across each risk group.

Total cost was lowest for the untreated cohort, followed by risedronate, alendronate, ibandronate, and PTH in all risk groups except patients aged 75 years with previous fracture. In that group the total costs were lowest for the risedronate cohort, followed by alendronate, no therapy, ibandronate, and PTH.

The cost-effectiveness results changed qualitatively with changes in the assumptions about treatment efficacy and analytical time horizon (

). That is, from the decision makers&#8217; point of view, when $50,000 per QALY was considered to be a decision threshold, the decision to adopt a treatment strategy changed. When the low estimates for efficacy were modeled, the cost-effectiveness for risedronate compared with no therapy changed from $22,068 per QALY gained to $114,694 per QALY gained. When a 3-year time horizon was assumed, the cost-effectiveness estimates for risedronate compared with no therapy changed from $22,068 per QALY gained to $85,391 per QALY gained, and the cost-effectiveness estimates for alendronate compared with risedronate changed from $362,845 to $258,803 per QALY gained. Although the cost-effectiveness estimates for alendronate compared with risedronate changed substantially in the sensitivity analyses, all the values were much greater than $50,000 (ie, dominated), with the only exception being the 5-year therapy offset scenario, where alendronate&#8217;s cost per QALY gained was similar to risedronate&#8217;s, so this would not likely impact the adoption decision. A comparable pattern emerged for the results reported as cost per hip fracture averted. Both ibandronate and PTH were dominated in all of the sensitivity analyses measured as both cost per QALY gained and cost per hip fracture averted, except for the therapy discontinuation analysis, where ibandronate was on the cost-effectiveness frontier for cost per QALY gained. 

Aggregating the 4 risk groups yielded an estimated 8.23 million women in the United States aged 65 to 84 years with low BMD. Currently, 27% of these women receive bisphosphonates and a further 2.9% receive PTH or calcitonin. The rest remain  untreated. Based on our estimates of cost-effectiveness of the individual therapies over a 3-year time horizon, a decision to treat the approximately 5.7 million women not receiving active therapy with bisphosphonates would cost an additional $5563 million (21% increase in total cost) and would result in an additional 83,159 QALYs (0.45% increase) and 390,049 fewer fractures (35% decrease) (

In the highest risk group (women aged 75 years with previous fracture), the additional cost of therapy was offset by the savings in inpatient, outpatient, and long-term care for a net savings of $18 million (0.2% decrease in total cost), accompanied by an additional 18,232 QALYs (0.5% increase) and 96,786 fewer fractures (28% decrease). 

Currently 48.5% of women with previous fracture (aged 65-84 years with low BMD) are treated with bisphosphonates and an additional 5.1% receive PTH or calcitonin. A policy decision to treat with bisphosphonates the approximately 1.5 million untreated women in this group would result over a 3-year period in 32,558 QALYs gained (0.46% increase) and 155,038 fractures avoided (28% decrease), at an additional societal cost of $783 million (6.2% increase) (data not shown).

2. Looker AC, Orwoll ES, Johnston CC Jr, et al.

 Prevalence of low femoral bone density in older U.S. adults from NHANES III. 

4. Bone Health and Osteoporosis: A Report of the Surgeon General.

 Rockville, MD: US Dept of Health and Human Services, Public Health Service, Office of the Surgeon General; 2004. 

http://www.surgeongeneral.gov/library/bonehealth/content.html

6. Pfister AK, Welch CA, Lester MD, Emmett MK, Saville PD, Duerring SA.

 Cost-effectiveness strategies to treat osteoporosis in elderly women. 

8. Gold MR, Siegal JE, Russell LB, Weinstein MC.

Cost-Effectiveness in Health and Medicine

. New York: Oxford University Press; 1996.

 Hip fracture rates (820XX codes, closed only). 2001. The Healthcare Cost and Utilization Project. Sponsored by the Agency for Healthcare Research and Quality. 

http://www.hcup-us.ahrq.gov/db/nation/nis/NIS_Introduction_2001.jsp

12. McClung MR, Geusens P, Miller PD, et al.

 Effect of risedronate on the risk of hip fracture in elderly women. Hip Intervention Program Study Group. 

14. Black DM, Cummings SR, Karpf DB, et al.

 Randomised trial of effect of alendronate on risk of fracture in women with existing vertebral fractures. Fracture Intervention Trial Research Group. 

 Boniva product monograph. Nutley, NJ: Roche Laboratories Inc; 2003. 

18. Agency for Healthcare Research and Quality.

 Nationwide Inpatient Sample, Release 10. Healthcare Cost and Utilization Project. 2001. 

 Osteoporosis: review of the evidence for prevention, diagnosis and treatment and cost effectiveness analysis. 

23. Chrischilles E, Shireman T, Wallace R.

 Costs and health effects of osteoporotic fractures. 

25. Tosteson AN, Gabriel SE, Grove MR, Moncur MM, Kneeland TS, Melton LJ III.

 Impact of hip and vertebral fractures on quality-adjusted life years. 

27. US Department of Labor, Bureau of Labor Statistics.

 Consumer Price Index, U.S. City Averageâ€”Medical Care. 2006. 

29. Black DM, Schwartz AV, Ensrud KE, et al.

 Effects of continuing or stopping alendronate after 5 years of treatment: the Fracture Intervention Trial Long-term Extension (FLEX): a randomized trial. 

 National Prescription Audit. Plymouth Meeting, PA: IMS Health; 2005.

 A cost effectiveness analysis of calcium and vitamin D supplementation, etidronate, and alendronate in the prevention of vertebral fractures in women treated with glucocorticoids.

36. Schousboe JT, Ensrud KE, Nyman JA, Kane RL, Melton LJ III.

 Potential cost-effective use of spine radiographs to detect vertebral deformity and select osteopenic post-menopausal women for aminobisphosphonate therapy. 

38. Borgstrom F, Carlsson A, Sintonen H, et al.

 The cost-effectiveness of risedronate in the treatment of osteoporosis: an international perspective. 

40. Chesnut CH III, Skag A, Christiansen C, et al

. Effects of oral ibandronate administered daily or intermittently on fracture risk in postmenopausal osteoporosis. 

42. Barrett-Connor E, Grady D, Sashegyi A, et al.

 Raloxifene and cardiovascular events in osteoporotic postmenopausal women: four-year results from the MORE (Multiple Outcomes of Raloxifene Evaluation) randomized trial. 

44. Cauley JA, Norton L, Lippman ME, et al.

 Continued breast cancer risk reduction in postmenopausal women treated with raloxifene: 4-year results from the MORE trial. Multiple outcomes of raloxifene evaluation. 

46. Tosteson AN, Melton LJ III, Dawson-Hughes B, et al.

 Cost-effective osteoporosis treatment thresholds: the United States perspective. 

Articles

METHODS

Osteoporosis treatment for high-risk women is cost-effective, with bisphosphonates providing the most benefit at the lowest cost.

Therapies for Treatment of Osteoporosis in US Women: Cost-effectiveness and Budget Impact Considerations

: To evaluate whether lifetime future net tax revenues from an in vitro fertilization (IVF)-conceived child are substantial enough to warrant public subsidy relative to the mean IVF treatment costs required to obtain 1 live birth.

: Mathematical generational accounting model.

: The model estimates direct financial interactions between the IVF-conceived child and the government during the childâ€™s projected lifetime. In the model, we accrue IVF costs required to conceive the child to the government, and then we estimate future net tax revenue to the federal and state governments from this individual, offset by direct financial transfers from the government (eg, child allowances, education, Medicare, and Social Security). We discount lifetime costs and gross tax payments at Treasury Department rates to establish the present value of investing in IVF. We applied US Congressional Budget Office projected changes in tax rates over the course of the model. 

: An IVF-conceived child, average in every respect (eg, future earnings, healthcare consumption, and life expectancy), represents a net positive return to the government. Based on an average employed individual born in 2005, the projected net lifetime tax contribution is US $606,200. Taking into consideration IVF costs and all direct financial interactions, the net present value is US $155,870.

: Lifetime net taxes paid from a child relative to the childâ€™s initial IVF investment represent a 700% net return to the government in discounted US dollars from fully employed individuals. This suggests that removing barriers to IVF would have positive tax benefits for the government, notwithstanding its beneficial effect on overall economic growth.

Financial and legislative barriers to fertility treatments prevent many couples from achieving their desired family size, resulting in fewer children being born. 

The costs attributed to in vitro fertilization (IVF) treatment are insignificant in light of the lifetime net tax contributions of IVF-conceived children. 

Minimizing barriers to fertility treatments is likely to have long-term economic benefits

Based on the US GA model developed by Kotlikoff,

 a basic mathematical model was developed taking the perspective of the US government to estimate the discounted lifetime net tax contribution derived from a single individual. The model describes the financial position between the child and the government during the child&#8217;s projected lifetime. For comparison, the model estimates lifetime net tax contributions for a naturally conceived versus an IVF-conceived child, where the major cost difference is assumed to be IVF treatment costs and any extra costs related to the child&#8217;s care. In this model, we assign IVF costs to the government to assess the merits of funding such a policy. All direct government expenditures and tax contributions were discounted using Treasury Department rates.

Conceptually, there are 3 broad stages in lifetime financial interactions, each with differing components of the financial exchange, as follows: (1) early life, when the government primarily contributes resources to individuals through child tax credits, healthcare, and educational expenses; (2) employment, when individuals begin returning resources to the government through federal, state, and local taxes; and (3) retirement, when the government expends additional resources on Social Security and old-age programs. Two general models are estimated. The first model assumes that individuals graduate from high school and then follow the average higher education, employment, and unemployment trends (hereafter referred to as average employment). The second model assumes full-time education from ages 6 to 19 years, with full-time employment from age 20 years until  retirement at age 65 years (hereafter referred to as full employment). The models assume that successful IVF treatment results in a single live birth (with a mean life expectancy of 79 years) and that the child is identical to a naturally conceived individual.

 In all scenarios, the model includes hospital delivery costs, taking into consideration additional costs frequently accrued to IVF-conceived children attributed to low birth weight.

 Age-graded government expenses and tax contributions were assessed across a hypothetical individual&#8217;s lifetime to derive discounted lifetime net tax contributions using net present value (NPV) calculations and undiscounted lifetime net tax contributions. Following similar GA calculations used to assess US immigration policy, we consider various costs generated and taxes paid.

Revenues collected by the government include federal and state income tax (the national mean rate in this model), corporate tax, excise tax, Federal Insurance Contributions Act tax, Supplemental Medical Insurance contributions, federal retirement tax, property tax, and sales tax. To calculate the accounting models, age profiles of each expenditure and revenue component were identified from existing data sources. Because the models describe financial interactions across an individual&#8217;s lifetime, these age profiles are adjusted to account for depreciation of money over time through the application of a discount rate. The US Congressional Budget Office 2007 projections were used as the basis for estimates of inflation, individual earnings increases, tax rate increases, increases in Supplemental Medical Insurance revenue, and Medicare and Medicaid expenditures.

 Increases in expenditures on schooling are based on historical rates of increase.

 Beyond the period for which these long-term forecasts are available, we assume that particular components grow to keep pace with demographic and productivity growth. A discount rate of 4% was applied to lifetime tax revenue and transfer payments. The discount rate was compounded continuously.

. The mean IVF treatment costs to produce a live birth are considered herein as a further expense unique to an individual conceived using IVF. The national mean cost per IVF treatment cycle in 2003 is US $12,400.

 Cost per live birth is calculated as the mean cost per cycle divided by the age-adjusted probability of a live birth, where the treatment efficacy is known to vary primarily by the age of the mother (ie, lower success rates with older age) and by other factors.

 The age-adjusted cost per live birth is given in 

. Analyses are based primarily on 2 waves of the annual March Current Population Survey.

 The Current Population Survey is a monthly survey of about 50,000 households conducted by the Bureau of the Census for the Bureau of Labor Statistics and is the primary source of information on the labor force characteristics of the US population. The sample is representative of the civilian noninstitutional population. Estimated sales tax revenue is obtained from the Consumer Expenditure Survey, also conducted by the Bureau of Labor Statistics. Government expenditures on congestible goods are obtained from the US Statistical Abstract, following prior work.

 Educational expenditures are taken from the Digest of Education Statistics.

. Given the baseline assumptions for the age profiles of expenditures and revenues, the net financial exchange of an individual at any age is derived in the accounting models simply as the discounted sum of all the economic components up to that age. Specifically, lifetime individual NPV is the discounted sum of all revenues to the government at all ages minus expenditures at all ages as follows:

The projected lifetime net tax contribution trajectories for an average employment naturally conceived child and for an IVF-conceived child are shown in the 

. There is a net increase in government revenue by age 37 years for naturally conceived children versus by age 40 years for an IVF-conceived child. The additional costs attributed to conceiving an IVF child are shown as an increased cost at birth. In all simulations, the financial position between the child and the government changes as the child enters the workforce and again at the point of leaving full-time employment, with a net profit to the taxing authority. In vitro fertilization coverage represents a minor component of the net cost for creation of new taxpayers. 

The projected combined returns to the federal and state governments in lifetime net tax contributions from an IVFconceived child and from a naturally conceived child are given in Table 1. For a naturally conceived child, the mean discounted lifetime tax contribution amounts to US $292,285 for full employment; the projected net undiscounted lifetime tax contribution for a full employment individual born in 2005 is US $1,103,000 (

). For IVF-conceived children, the net undiscounted lifetime tax contribution is similar to that for naturally conceived children even after IVF investment costs are factored into the analysis.

The age at which the financial position between a naturally conceived child and an IVF-conceived child changes with respect to the taxing authority is given in Table 1. We have labeled this as the breakeven age to highlight the age at which the government has  recouped all direct financial transfers (discounted) in the early years to achieve working-age participation. Assuming full employment, the breakeven ages with net profit to the government are 34 years for naturally conceived children and 36 to 38 years for IVF children conceived to mothers younger than 41 years. The difference in the breakeven age for IVF-conceived children compared with naturally conceived children differs by 2 to 5 years depending on variations in increasing IVF investment costs attributed to older mothers.

The principal aim of this research was to assess the net tax contributions of an IVF-conceived child, with the intention of informing future policy directives that may influence access to fertility treatments. In reality, there are many good reasons to justify improved IVF access, including medical need, equity, and respect for an individual&#8217;s human right to a family, and reproductive rights. However, in many countries, including the United States, access to fertility care is limited, and many couples are unable to afford treatment. Based on the results shown herein, one could easily argue on the basis of economics that financial or legislative barriers to IVF treatments for infertile couples should be removed.

: We are grateful for comments and guidance provided by Dr Craig Currie from Cardiff Medical School.

: From Ferring International Center (MPC), St Prex, Switzerland; the RAND Corporation (MSP), Santa Monica, CA; the RAND Corporation (SH), Cambridge, England; the Fertility Centers of Illinois (BR K), Chicago; the Boston IVF and the Department of Obstetrics, Gynecology and Reproductive Biology, Harvard Medical School (SP O), Boston, MA; and the Infertility Center of St Louis at St Lukeâ€™s Hospital (SJS), St Louis, MO. 

: This study was funded by the not-for-profit RAND Corporation and by Ferring International Center.

: Mr Connolly is an employee of Ferring International Center, a funder of this study. Dr Pollard and Mr Hoorens report receiving grant funding from Ferring International Center. Dr Oskowitz is a board member of Columbia Labs, a manufacturer of hormones used in IVF treatment, and reports owning stock in that company. Drs Kaplan and Silber report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article. 

: Concept and design (MPC, MSP, SH, SJS); acquisition of data (MSP); analysis and interpretation of data (MPC, MSP, SPO, SJS); drafting of the manuscript (MPC, MSP, SH, BRK, SPO, SJS); critical revision of the manuscript for important intellectual content (MPC, MSP, SH, BRK, SPO, SJS); statistical analysis (MSP); obtaining funding (MPC, MSP, SH); administrative, technical, or logistic support (MPC); and supervision (MPC). 

: Sherman J. Silber, MD, Infertility Center of St Louis at St Lukeâ€™s Hospital, 224 S Woods Mill Rd, St Louis, MO 63017. E-mail: 

1. Andersen AN, Gianaroli L, Felberbaum R, de Mouzon J, Nygren KG; European IVF-Monitoring Programme (EIM) for the European Society of Human Reproduction and Embryology (ESHRE).

 Assisted reproductive technology in Europe, 2002: results generated from European registers by ESHRE. 

2. Andersen AN, Goossens V, Gianaroli L, Felberbaum R, de Mouzon J, Nygren KG.

 Assisted reproductive technology in Europe, 2003: results generated from European registers by ESHRE. 

4. National Institute for Health and Clinical Excellence.

 Clinical Guideline 11. Fertility: assessment and treatment for people with fertility problems. February 2004. 

http://www.nice.org.uk/Guidance/CG77/Guidance/pdf/English

 Current practices and controversies in assisted reproduction: report of a meeting on â€œMedical, Ethical and Social Aspects of Assisted Reproductionâ€ held at WHO headquarters in Geneva, Switzerland, 17-21 September 2001. 

http://www.who.int/reproductive-health/infertility/report.pdf

The Demographic Dividend: A New Perspective on the Economic Consequences of Population Change.

 Europeâ€™s declining population and the contribution of ART. 

. An international survey of the health economics of IVF and ICSI. 

. Utilization of infertility services: how much does money matter? 

16. Finkelstein BS, Silvers JB, Marrero U, Neuhauser D, Cuttler L.

 Insurance coverage, physician recommendations, and access to emerging treatments: growth hormone therapy for childhood short stature. 

18. Soumerai SB, McLaughlin TJ, Ross-Degnan D, Casteris CS, Bollini P.

 Effects of limiting Medicaid drug-reimbursement benefits on the use of psychotropic agents and acute mental health services by patients with schizophrenia. 

20. Cardarelli R, Sefton J, Kotlikoff LJ.

22. Bonduelle M, Liebaers I, Deketelaere V, et al.

 Neonatal data on a cohort of 2889 infants born after ICSI (1991-1999) and of 2995 infants born after IVF (1983-1999). 

. The current fiscal impact of immigrants and their descendants: beyond the immigrant household. In: Smith JP, Edmonston B, eds. 

The Immigration Debate: Studies on the Economic, Demographic, and Fiscal Effects of Immigration

. Washington, DC: National Academy Press; 1998:183-205.

28. MaCurdy T, Nechyba T, Bhattacharya J.

 An economic framework for assessing the fiscal impacts of immigration. In: Smith JP, Edmonston B, eds. 

. Washington, DC: National Academy Press; 1998:13-65.

 Digest of Education Statistics 2005 (NCES 2006-030). Washington, DC: National Center for Education Statistics, US Dept Education; 2006.

32. Centers for Disease Control and Prevention.

 Assisted Reproductive Technology Success Rates: National Summary and Fertility Clinic Report (2004). Atlanta, GA: Centers for Disease Control and Prevention, US Dept Health and Human Services; 2006.

34. Callahan TL, Hall JE, Ettner SL, Christiansen CL, Greene ME, Crowley WF.

 The economic impact of multiple-gestation pregnancies and the contribution of assisted-reproduction techniques to their incidence. 

 Diagnosis and management of female infertility. 

 Access to assisted reproduction services and infertility treatment in Belgium in the context of the European countries. 

. Explaining disparities in treatment seeking: the case of infertility. 

. Use of infertility services in the United States: 1995. 

44. Leunens L, Celestin-Westreich S, Bonduelle M, Liebaers I, Ponjaert-Kristoffersen I.

 Cognitive and motor development of 8-yearold children born after ICSI compared to spontaneously conceived children. 

 Effects of infertility insurance mandates on fertility. 

. Cheaper than a newcomer: on the social production of IVF policy in Israel. 

POLICY

We estimate the future net tax contributions from an IVF-conceived child to highlight that removing barriers to fertility treatments can have long-term economic benefits.

Long-term Economic Benefits Attributed to IVF-conceived Children: A Lifetime Tax Calculation

: To evaluate the private third-party payer return on investment for bariatric surgery the United States.

: Morbidly obese patients aged 18 years or older were identified in an employer claims database of more than 5 million beneficiaries (1999-2005) using International Classification of Diseases, Ninth Revision, Clinical Modification code 278.01. Each of 3651 patients who underwent bariatric surgery during this period was matched to a control subject who was morbidly obese and never underwent bariatric surgery. Bariatric surgery patients and controls were matched based on patient demographics, selected comorbidities, and costs.

: Total healthcare costs for bariatric surgery patients and their controls were recorded for 6 months before surgery through the end their continuous enrollment. To account for potential differences in patient characteristics, we calculated the cost differential by estimating a Tobit model. A return on investment was estimated from the resulting coefficients. Costs were inflation adjusted to 2005 US dollars using the Consumer Price Index for Medical Care, and the cost savings were discounted by 3.07%, the month Treasury bill rate during the same period.

: The mean bariatric surgery investment ranged from approximately $17,000 to $26,000. After controlling for observable patient characteristics, we estimated all costs to have been recouped within 2 years for laparoscopic surgery patients and within 4 years for open surgery patients.

: Downstream savings associated with bariatric surgery are estimated to offset the initial costs in 2 to 4 years. Randomized or quasiexperimental studies would be useful to confirm this conclusion, as unobserved characteristics may influence the decision to undergo surgery and cannot be controlled for in this analysis.

The rate of bariatric surgery use has increased in the past decade to more than 170,000 surgical procedures per year in the United States.

The initial investment for bariatric surgery is approximately $26,000 for open surgery and $17,000 for laparoscopic surgery. 

After taking into account age, sex, and comorbidities, the initial investment is returned within 4 years for patients who undergo open surgery and within 2 years for patients who undergo laparoscopic surgery. 

Even ignoring potential quality-of-life and length-of-life benefits, as well as disability and work loss, third-party payers can rely on bariatric surgery paying for itself through decreased comorbidities within 2 to 4 years.

The prevalence of obesity among the US adult population has increased steadily to reach one third of the US adult population.

More alarming yet, the trend in morbid obesity outpaces that of nonmorbid obesity. From 2000 through 2005, the US obesity rate increased by 24%, while the rate of morbid obesity (body mass index [BMI], calculated as weight in kilograms divided by height in meters squared >40) grew by 50%, and the rate of patients with a BMI exceeding 50 grew by 75%.

 This trend in morbid obesity results in increased healthcare utilization and costs, as healthcare costs for the morbidly obese are 81% above those for the nonobese population and 47% above costs for the non—morbidly obese population.

Morbid obesity is associated with a myriad of serious comorbid conditions, including hypertension, type 2 diabetes mellitus, dyslipidemia, osteoarthritis, and gallbladder disease.

 Bariatric surgery has been demonstrated to be an effective weight-loss alternative for the morbidly obese

 and is associated with marked resolution of comorbidities.

 have found similar results, with reductions in morbidity, cardiovascular risk, healthcare utilization, and costs in bariatric surgery patients compared with control subjects. Although most of the current literature examines health benefits associated with bariatric surgery,

 studies have also documented quality-of-life improvements,

Despite the extensive literature on the clinical effects of bariatric surgery, little research has been published on the economic impact of the procedure. This represents a growing gap in the literature as the clinical outcomes become better known and the procedure becomes more commonplace (>170,000 surgical procedures in 2005), while its economic costs or benefits remain unclear.

 The present analysis is unique in its use of actual patient-level cost data for 3651 patients who underwent the procedure. The resulting return on investment is calculated based on up to 5 years of postoperative cost data.

This study quantifies the effect of bariatric surgery on direct medical costs. We focus on the time required for third-party payers to recover the initial investment associated with bariatric surgery (ie, the return on investment).

 Using the Ingenix private insurer claims database and a matched cohort method and focusing only on costs incurred and saved by the private insurer, we build on findings of a previous study

 that suggested a 9-year period to recoup the cost of bariatric surgery. We further examine changes in return on investment over time as bariatric surgery techniques have improved and focus on laparoscopic surgery outcomes.

 This analysis should help evaluate the cost-benefit implications of bariatric surgery.

We used a privately insured administrative claims database containing medical and drug claims from 1999 through 2005 covering more than 5 million lives from 31 large companies that provided extensive health insurance coverage, including mental health. These companies have operations nationwide in a broad array of industries and job classifications (eg, financial services, manufacturing, telecommunications, energy, and food and beverage). The data contain deidentified information on patients’ demographics (eg, age and sex) and monthly enrollment history, as well as medical and pharmacy claims. Specifically, patients’ utilization of medical services is recorded with the date of service, place of service, associated diagnoses, performed procedures, billed charges, and actual amount of payments. Patients’ pharmacy claims contain prescribed medications identified by National Drug Code, the date a prescription was filled, days of supply, quantity, and actual payment amount. The study sample for this analysis included claimants having a diagnosis of morbid obesity (International Classification of Diseases, Ninth Revision, Clinical Modification code 278.01). Patients 18 years or older who underwent bariatric surgery were identified using Health Care Financing Administration Common Procedural Coding System and Current Procedural Terminology codes 43644, 43645, 43842, 43843, 43845, 43846, 43847, S2085, S2082, and S2083. Of these procedures, 73% were gastric restrictions with bypass (codes 43845, 43846, and 43847), 11% were gastric restrictions without bypass (codes 43842 and 43843), 12% were laparoscopic surgical procedures with bypass (codes 43644, 43645, and S2085), and 4% were laparoscopic surgical procedures without bypass (codes S2082 and S2083).

The initial date of bariatric surgery was defined as the index date for the relevant patient, as well as his or her control. All claimants in the study sample were required to have at least 6 months of continuous enrollment before the index date and 1 month following the index date.

Because patients with a morbid obesity claim may be sicker, on average, than patients with no such claim recorded, surgery-eligible controls (morbidly obese patients with no bariatric surgery procedure code) were matched to bariatric surgery patients based on age group, sex, state of  residence, comorbidities, and 5-month presurgery direct costs (months −6 to −2, excluding month −1 immediately before surgery, which is often characterized by increased costs associated with preparation for surgery). Each bariatric surgery patient was matched to a specific control drawn from the morbidly obese control population that never underwent bariatric surgery.

For each bariatric surgery patient, a control was considered a match if (1) the control's age was within the same 10-year age range as that of the bariatric surgery patient, (2) the control was of the same sex, (3) the control resided in the same state as the bariatric surgery patient, (4) the control had the same 10 comorbidities as the bariatric surgery patient (

), and (5) the control’s healthcare costs fell within 1 SD of the cumulative costs (during months −6 to −2) incurred by the bariatric surgery patient. The matching of bariatric surgery patients with their controls is performed based on 10 comorbidities, although findings in a review of the existing literature

 and the guidelines of the American Society for Bariatric Surgery

 suggest that 18 comorbidities could cause imbalance between the 2 samples. However, not every patient could be matched on the demographics and on all 18 comorbidities because patients with the corresponding combination of comorbidities may not be observed in the control group. Hence, patients were matched to controls using a subset of the following 10 comorbidities: asthma, coronary artery disease, diabetes mellitus, dyslipidemia, gallstones, gastroesophageal reflux, hypertension, nonalcoholic steatohepatitis or nonalcoholic fatty liver disease, sleep apnea, and urinary incontinence. Multivariate analysis was used to account for the remaining 8 comorbidities, thereby addressing any remaining imbalance across matched samples. These 8 comorbidities are breast cancer, congestive heart failure, lymphedema, major depression, osteoarthritis, polycystic ovary syndrome, pseudotumor cerebri, and venous stasis or leg ulcers.

Because calculating a return on investment requires a comparison of costs for the bariatric surgery and control patients during multiple years, 2 adjustments were made. First, costs were inflation adjusted to 2005 US dollars using the Consumer Price Index for Medical Care because a dollar spent today would purchase more goods and services than a dollar spent in 2 years (as long as inflation is positive). Second, cost savings were discounted by a 3.07% interest rate, the mean return on a 3-month Treasury bill, because a dollar saved today would, if invested in a risk-free Treasury bill, be worth more than a dollar in 2 years (roughly $1.06 at the stated rate). However, the shorter the time horizon to recoup costs, the less effect discounting will have on the estimated return on investment. The multivariate analysis modeled normalized monthly costs as a function of bariatric surgery interacting with discrete indicators of time from surgery. A positive coefficient indicates that costs incurred by the bariatric surgery patients are higher; a negative coefficient indicates that costs are lower relative to their controls. Therefore, positive coefficients indicate incremental third-party payer costs associated with bariatric surgery (the “investment”), and negative coefficients indicate savings from bariatric surgery (the “return”). The return on investment calculations combine these estimates to determine the number of months necessary for cumulative savings associated with improved comorbidity outcomes following surgery to cover the initial investments. The point estimates are reported with 95% confidence intervals (CIs). Indicator variables in 6-month increments are included to allow for nonlinear savings. In addition to the indicator variables, the multivariate model controlled for age and the 8 comorbidities already mentioned. The comorbidities were tracked at 3-month intervals to record changes in prevalence.

Healthcare costs cannot be negative, rendering ordinary least squares analysis biased and  inefficient.

 Therefore, we estimated a maximum likelihood Tobit model with a cluster option to account for panel-level heterogeneity

 to reflect the truncated normal distribution. A sensitivity analysis was conducted using an interval model, which yielded similar results. We calculated the cost differential by estimating the model on the pooled population (patients and controls) and using the coefficient on the variable interacting bariatric surgery with the relevant time period. Based on this coeffincient, a return on investment is calculated by offsetting the initial bariatric investment against incremental cost savings for bariatric surgery patients following surgery.

Overall results across all bariatric surgical procedures are reported using the complete time series available from 1999 through 2005. For open surgical procedures, results are further reported separately for patients who received their surgical procedure from 1999 through 2002 and for patients who received their surgical procedure from 2003 through 2005. This tests our clinical experience of shorter lengths of stay and improved outcomes associated in part with the development of centers of excellence in the later years, which may in turn shorten the estimated return on investment relative to the earlier period. This approach cannot be used for laparoscopic surgery because a code specific to that type of surgery did not exist until 2004. Hence, we report results for patients who underwent laparoscopic surgery from 2004 through 2005 separately. All estimations were performed using statistical software (Intercooled STATA 9.2 [StataCorp LP, College Station, Texas] and SAS 9.1 [SAS Institute, Cary, North Carolina]).

Table 1 compares bariatric surgery patients and their controls at baseline after matching on age group, sex, costs, state of residence, and 10 comorbidities. The sample is predominantly female (86%), with a mean age of 44 years. More than one third of the sample had hypertension, and close to 20% had dyslipidemia or diabetes mellitus. Major depression and osteoarthritis are the only 2 comorbidities with statistically different prevalences across groups. Both comorbidities are included as control variables in the multivariate analysis. Both study groups have similar prescription drug costs. Bariatric surgery patients have somewhat higher baseline medical service costs (20%) and total healthcare costs (14%). The absence of any statistically significant difference in weight-loss medication use or in visits to nutritionists suggests that these differences are not driven by differences in presurgery reimbursable weight-loss efforts. Patients were observed for 6 months before surgery and for a mean of 17 months and 18 months following the index date for the bariatric surgery group and the control group, respectively.

Multivariate regression analysis results summarized in 

 demonstrate total incremental costs of approximately $24,500 for all types of bariatric surgery combined, $26,000 for open surgery, and $17,000 for laparoscopic surgery during the period from 1 month before surgery to 2 months following surgery. The total incremental cost is the sum of costs incurred in the month before the surgery, costs incurred in surgery, and costs incurred in the first 2 months following surgery. Starting at month 3, cost savings associated with the bariatric surgery patients start accruing. One and a half years after surgery, monthly savings associated with bariatric surgery reach more than $500 for the whole sample and $400 (1999-2002) to $600 (2003-2005) for open surgery depending on the period (P <.01). Monthly savings associated with laparoscopic bariatric surgery reach more than $900 as early as 13 months following surgery (P <.01). The 

This study analyzes the return on investment for bariatric surgery in the United States.

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