Differences in ICSI Utilization Rates Among States With Insurance Mandates for ART Coverage

Differences in ICSI Utilization Rates Among States With Insurance Mandates for ART Coverage | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Differences in ICSI Utilization Rates Among States With Insurance Mandates for ART Coverage Pavel Zagadailov, Kyung S CHO, David B SEIFER This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-970725/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Nov, 2021 Read the published version in Reproductive Biology and Endocrinology → Version 1 posted 11 You are reading this latest preprint version Abstract Background Assisted reproductive technology (ART) insurance mandates promote more selective utilization of ART clinic resources including intracytoplasmic sperm injection (ICSI). Our objective was to examine whether ICSI utilization differs by state insurance mandates for ART coverage and assess if such a difference is associated with male factor, preimplantation genetic testing (PGT), and/or live birth rates. Methods In this retrospective analysis of the Centers for Disease Control (CDC) data from 2018, ART clinics in ART-mandated states (n=8, AR, CT, HI, IL, MD, MA, NJ, RI) were compared individually to one another and with non-mandated states in aggregate (n=42) for use of ICSI, male factor, PGT, and live birth rates. ANOVA was used to evaluate differences between ART-mandated states and non-mandated states. Individual ART-mandated states were compared using Welch t-tests. Statistical significance was determined by Bonferroni Correction. Results There were significant differences in ICSI rates (%, mean ± SD) between MA (53.3 ± 21.3) and HI (90.7 ± 19.6), p = 0.028; IL (86.5 ± 18.7) and MA, p = 0.002; IL and MD (57.2 ± 30.8), p = 0.039; IL and NJ (62.0 ± 26.8), p = 0.007; between non-mandated states in aggregate (79.9 ± 19.9) and MA, p = 0.006, and NJ (62.0 ± 26.8), p = 0.02. Male factor rates of HI (65.8 ± 16.0) were significantly greater compared to CT (18.8 ± 8.7), IL (26.0 ± 11.9), MA (26.9 ± 6.6), MD (29.3 ± 9.9), NJ (30.6 ± 17.9), and non-mandated states in aggregate (29.7 ± 13.7), all p < 0.0001. No significant differences were reported for use of PGT and/or live birth rates across all age groups regardless of mandate status. Conclusions ICSI use varied significantly among ART-mandated states while demonstrating no differences in live birth rates. These data suggest that the prevalence of male factor and the presence of a state insurance mandate are not the only factors influencing ICSI use. It is suggested that other non-clinical factors may impact the rate of ICSI utilization in a given state. Endocrinology & Metabolism Assisted reproductive technology In-Vitro fertilization State insurance mandates Intracytoplasmic sperm injection utilization rates live birth rate male factor Background Intracytoplasmic sperm injection (ICSI) is indicated for couples with a history of failed fertilization after conventional insemination or with severe male factor (MF) infertility. While ICSI is often used for the treatment of unexplained infertility and low oocyte yield, it has not been demonstrated to improve clinical outcomes [ 1 ]. A 2018 report found that assisted reproductive technologies (ART) state mandates were associated with increased ICSI use for non-male factor indications [ 2 ]. Sixteen U.S. states have now passed laws that require insurers to offer coverage for infertility diagnosis and treatment. Before 2018, eight states (AR, CT, HI, IL, MA, MD, NJ, RI) had ART-mandates. Four states (IL, MA, NJ, and RI) have included ICSI as a covered benefit. [ 3 – 6 ] Our previous studies have suggested that ICSI may be overutilized and not accompanied by increase in male factor or improved live birth rates [ 7 , 8 ]. In ART-mandated states, lower ICSI rates were accompanied by a positive correlation with live birth rates (LBR). Such findings suggested that ART mandates may promote more selective utilization of ART clinic resources [ 9 ]. However, these previous analyses were comparing ART-mandated versus non-mandated states in aggregate. The present study was designed to evaluate the differences in utilization of ICSI between individual ART-mandated states and to compare these rates with non-mandated states in aggregate. Furthermore, to better understand some of the underlying factors contributing to differences in ICSI use among individual ART-mandated states, we examined the frequency of male factor, PGT and singleton live birth rates among these states. Methods Data Source This retrospective analysis was conducted using the National Assisted Reproductive Technology Surveillance System (NASS), maintained by the Centers for Disease Control and Prevention (CDC). A publicly available NASS dataset for 2018 was downloaded from the CDC website [ 10 ]. Clinics within this yearly report were grouped by ART-mandated state, then evaluated individually and compared to a group of non-mandated states in aggregate. Study Design and Outcomes We evaluated eight ART-mandated states (AR, CT, HI, IL, MD, MA, NJ, RI) individually, comparing them to one another as well as comparing each of them to the remaining non-mandated states (n=42, 382 ART clinics) in aggregate. We hypothesized that the use of ICSI, frequency of male factor, PGT rates, and singleton live birth rates across all age groups significantly varied among each of the ART-mandated states. Age groups were categorized by the Society for Assisted Reproductive Technology (SART) groupings as 42 years old. Only autologous, non-donor embryo transfers were included in this analysis. Frozen autologous and donor embryo transfers were excluded. Specific for each age group, ICSI utilization rates, frequency of male factor, PGT rates, and singleton live birth rates for individual ART-mandated states and non-mandated states combined in aggregate were evaluated. ICSI utilization rates and MF infertility rates are examined to assess the potential overutilization of ICSI in ART-mandated states if any. Statistical Analysis Statistical analysis was performed utilizing R (version 3.5.1, R Core Team, University of Auckland, New Zealand). Analysis of variance (ANOVA) was used to evaluate whether there were statistical differences among individual ART-mandated states and non-mandated states in aggregate. Individual states were compared in pairs using Welch t-tests to determine whether utilization of ICSI, male factor, PGT rates, and live birth rates per transfer were statistically different among ART-mandated states and non-mandated states in aggregate. Statistical significance was determined after multiple testing adjustments using Bonferroni Correction. Results Results are organized by age group. < 35 years old There were significant differences between ICSI utilization rates (%, mean ± SD) of MA (53.3 ± 21.3) and HI (90.7 ± 19.6), p = 0.028, 95% CI [11.4, 63.4]; IL (86.5 ± 18.7) and MA, p = 0.002, 95% CI [14.5, 51.9]; IL and MD (57.2 ± 30.8), p = 0.04, 95% CI [2.9, 61.5]; IL and NJ (62.0 ± 26.8), p = 0.007, 95% CI [8, 41.1]; non-mandated states combined (79.9 ± 19.9) and MA, p = 0.006, 95% CI [8.8, 44.4]; non-mandated states and NJ (62.0 ± 26.8), p = 0.02, 95% CI [3, 32.9]. Male factor rates of HI (65.8 ± 16.0) were greater compared to CT (18.8 ± 8.7), IL (26.0 ± 11.9), MA (26.9 ± 6.6), MD (29.3 ± 9.9), NJ (30.6 ± 17.9) and non-mandated states (29.7 ± 13.7), all p < 0.0001, 95% Cl’s are [29.7, 64.3], [23, 56.6], [22.1, 55.8], [19.2, 53.9], [17.9, 52.7], [19.3, 52.9] respectively. (Table 1 ) 35 – 37 years old There were significant differences between ICSI utilization rates of MA (51.85 ± 19) and HI (87.7 ± 20), p = 0.0459, 95% CI [10.2, 61.5]; IL (84.7 ± 21) and MA, p = 0.0024, 95% CI [15.5, 50.2]; NJ (61.9 ± 24.6) and IL, p = 0.0327, 95% CI [5.8, 39.7]; non-mandated states combined (77 ± 20.2) and MA, p = 0.0135, 95% CI [9.2, 41.1]. (Appendix A) 38 – 40 years old There were significant differences between ICSI utilization rates of MA (54.5 ± 20.4) and IL (86 ± 11.6), p = 0.004, 95% CI [11.9, 48.6]. (Appendix B) 41 – 42 years old and 42 > years old No statistically significant differences were reported for ICSI utilization rates in two age groups between ART-mandated and non-mandated states. (Appendix C, D) No statistically significant differences were reported for PGT rates and singleton live birth rates between ART-mandated and non-mandated states for all age groups. Discussion These data demonstrate significant differences in ICSI utilization between individual ART-mandated states as well as compared to non-mandated state aggregate data. Covered infertility benefits in ART-mandated states vary dramatically (Table 2 ). Multiple factors may influence the decision of whether to use ICSI or conventional IVF. Clinic-specific policies, discretion of treating physicians, and/or embryology laboratory personnel preference to use ICSI in patients with low oocyte yields, perceived poor oocyte quality or unexplained infertility are factors that can influence the use of ICSI. The two ART-mandated states with the highest utilization of ICSI were HI and IL. Remarkably, a large portion of the ART clinics in Hawaii (80%) and in Illinois (48%) reported >75% ICSI usage, in contrast to no ART clinics in MA. HI reported dramatically higher male factor infertility rates (65.8%) than any other ART-mandated and non-mandated state. Furthermore, CT and MA showed a similar trend of lower ICSI use associated with more favorable clinical outcomes than reported in HI and IL. However, significantly greater male factor rates in HI than in other ART-mandated states and non-mandated states in aggregate may justify greater utilization of ICSI. This observation raises speculation of whether increased concern for potential poor, failed fertilization, unexplained infertility, or the perception of increased competition in specific geographic locations may have contributed to greater utilization of ICSI. Interestingly, further analysis of the states with mandated ART coverage identified two states (IL and MA) with similar ART mandate structure and demographics but dramatically different ICSI utilization profiles. Both state mandates have a similar timeline for infertility diagnosis, covered cost of diagnostic tests, laboratory procedures that include ICSI, plan-dependent cost of medication and embryo cryopreservation (Table 2 ). Both states have heterogeneous, racially diverse populations within major metropolitan centers (Chicago and Boston) that are the homes of multiple academic teaching medical centers as well as many IVF private practices. However, IL had remarkably higher ICSI rates compared with ICSI rates of MA. Yet, in contrast, male factor diagnosis rates did not differ significantly between these two states, nor did PGT or singleton live birth rates. This wide difference in ICSI rates between IL and MA may in part be due to a fewer number of clinics and thus a greater annual ART cycle volume per IVF clinic in MA than in IL. It is speculated that lower and more selective use of ICSI utilization in MA could contribute to greater uniformity and less variability in employing ICSI by MA clinics compared to those clinics in IL. Furthermore, several unique factors may explain why HI demonstrated the highest rate of ICSI among the ART-mandated states. Such factors contributing to increased ICSI utilization may include the limited number of ART clinics with significantly lower annual clinical volume, island-specific demographic distribution and a limited number of laboratory directors. Thus, we believe trends of ICSI use in HI may not be as representative nor as generalizable to ICSI and outcome rates of states in the continental U.S. ICSI use varied significantly among the ART-mandated states while demonstrating no differences in live birth rates. This analysis of individual ART-mandated states suggests that the prevalence of male factor and the presence of a state insurance mandate are not the only factors influencing ICSI use. It is suggested that other possible non-clinical factors, such as the number of ART clinics in a given geographic area, clinic-specific policies, and/or patient/physician preferences, may impact the rate of ICSI utilization in a given state and will require further examination. There are several strengths and limitations to this study. The primary strength is the use of the CDC dataset that incorporates >98% of ART cycles performed in the U. S. The improvement in the reporting of the 2018 data set compared to previous years included outcomes specific for each age group. Live birth rates were reported per transfer and specific for fresh non-donor embryos resulting from ICSI use. Limitations include the fact that states with single clinics (AR, RI) were excluded as the variance calculation was possible only for states with two or more clinics. Hence, we could not assess the impact of every state’s ART mandate. Provided by the CDC, male factor rates are “per clinic” and are not age group-specific nor do they include details regarding the specific types of male factor diagnosis. An additional limitation of this study is that semen parameters were not collected nor available from the CDC dataset to help better understand the origin of the greater rates of male factor in HI. Conclusions ICSI use varied significantly among ART-mandated states while demonstrating no differences in live birth rates. These data suggest that the prevalence of male factor and the presence of a state insurance mandate are not the only factors influencing ICSI use. It is suggested that other non-clinical factors may impact the rate of ICSI utilization in a given state. List Of Abbreviations ANOVA - Analysis of variance ART - Assisted reproductive technology CDC - Centers for Disease Control and Prevention ICSI - Intracytoplasmic sperm injection LBR - Live birth rate MF - Male factor NASS - National Assisted Reproductive Technology Surveillance System PGT - Preimplantation genetic testing SART - Society for Assisted Reproductive Technology Declarations Ethics approval and consent to participate This study qualified as “not human subject research” Consent for publication Not applicable. Availability of data and materials NASS datasets for 2018 are publicly available from the CDC website: https://www.cdc.gov/art/nass/ See reference [10] Competing interests The authors declare that they have no competing interests. Funding None. Authors' contributions All authors equally participated in study design, data analysis, results interpretation and drafting of the manuscript. All authors read and approved the final manuscript. Acknowledgements None. References Practice Committees of the American Society for Reproductive Medicine and the Society for Assisted Reproductive Technology. Intracytoplasmic sperm injection (ICSI) for non-male factor indications: a committee opinion. Fertil Steril. 2020 Aug;114(2):239–45. doi: 10.1016/j.fertnstert.2020.05.032 . Epub 2020 Jul 9. PMID: 32654822. Dieke AC, Mehta A, Kissin DM, Nangia AK, Warner L, Boulet SL. Intracytoplasmic sperm injection use in states with and without insurance coverage mandates for infertility treatment, United States, 2000-2015. Fertil Steril. 2018;109(4):691–7. Ill. Rev. Stat. ch. 215, § 5/356m (1991, 1996). Available at: http://www.ilga.gov/legislation/ilcs/ Accessed: July 2018. Mass G. Laws Ann. ch. 175, § 47H, ch. 176A, § 8K, ch. 176B, § 4J, ch. 176G, § 4 and 211 Code of Massachusetts Regulations 37.00 (1987, 2010). Available at: https://malegislature.gov/Laws/GeneralLaws/ Accessed: May 2021. Stat NJ. Ann. § 17:48-6x, § 17:48A-7w, § 17:48E-35.22 and § 17B:27-46.1x (2001) Available at: https://law.justia.com/codes/new-jersey/ Accessed: May 2021. Gen RI. Laws § 27-18-30, § 27-19-23, § 27-20-20 and § 27-41-33 (1989, 2007) Available at: http://webserver.rilin.state.ri.us /Statutes/ Accessed: May 2021. Zagadailov P, Hsu A, Seifer DB, Stern JE. Differences in utilization of Intracytoplasmic sperm injection (ICSI) within human services (HHS) regions and metropolitan megaregions in the U.S. Reprod Biol Endocrinol. 2017 Jun 12;15(1):45. doi: 10.1186/s12958-017-0263-4 . PMID: 28606175; PMCID: PMC5469007. Zagadailov P, Hsu A, Stern JE, Seifer DB. Temporal Differences in Utilization of Intracytoplasmic Sperm Injection Among U.S. Regions. Obstet Gynecol. 2018 Aug;132(2):310-320. doi: 10.1097/AOG.0000000000002730 . PMID: 29995722. Zagadailov P, Seifer DB, Shan H, Zarek SM, Hsu AL. Do state insurance mandates alter ICSI utilization? Reprod Biol Endocrinol. 2020 Apr 25;18(1):33. doi: 10.1186/s12958-020-00589-w . PMID: 32334609; PMCID: PMC7183130. Centers for Disease Control and Prevention National ART Surveillance System, ART National Data. Available at: https://www.cdc.gov/art/nass/ Accessed: March 2021. Tables Table 1: Age group <35 States Live Birth Rate (%, mean ± SD) ICSI Rate (%, mean ± SD) PGT Rate (%, mean ± SD) Male Factor Rate (%, mean ± SD) AR 30.7 70.2 0.8 18 CT 46.2 11.7 72.1 16.8 28.4 17.1 18.8 8.7 HI 45.1 19.8 90.7 19.6 25.8 13.7 65.8 16 IL 34.8 12.8 86.5 18.7 20.1 21 26 11.9 MD 39.9 8.5 57.3 30.8 11.3 11.3 29.3 9.9 MA 36.7 6.7 53.3 21.3 20 24.2 26.9 6.6 NJ 40.6 9.1 62 26.8 32.6 22.4 30.6 17.9 RI 33.1 55.1 7.2 23 non-mandated states 40.9 10.6 79.9 19.9 35.6 28.6 29.7 13.7 Table 2: Comparison of insurance coverage for infertility diagnosis and treatment in ART-mandated states ART-Mandated State (n/clinic) Enacted (and Revised) Diagnoses Cycle type Lifetime maximum Costs of diagnostic tests Medications ICSI Cryopreservation Coverage of other ART procedures Arkansas (n=1) 1987 2011 2-years of infertility OR Endometriosis Tubal factor Male factor Autologous only $15.000 Not covered Not covered Not specified Covered Plan-dependent Connecticut (n=6) 1989 2005 2017 1-year of infertility Not specified 3 IUI 2 IVF cycles Covered Covered, plan-dependent Not specified Not covered Not specified Hawaii (n=6) 1989 2003 5-year of infertility OR Endometriosis Tubal factor Male factor Autologous only 1 IVF cycle Partially covered Not covered Not specified, plan-dependent Covered, plan-dependent Plan-dependent Illinois (n=26) 1991 1997 1-year of infertility Autologous and Donor 6 IVF cycles Covered Covered Covered Covered, plan-dependent Plan-dependent Maryland (n=7) 1985 2000 2-year of infertility OR Endometriosis Tubal factor Male factor Autologous only $100.000 3 IVF cycles Covered Not covered Not specified, plan-dependent Not covered Not specified Massachusetts (n=8) 1987 2010 1-year of infertility for <35 years old 6-months infertility ≥35 years old Not specified None Covered, plan-dependent Covered, plan-dependent Covered Covered Plan-dependent New Jersey (n=19) 2001 2017 1-year of infertility for <35 years old 6-months infertility ≥35-46 years old OR Tubal factor Male factor Autologous and Donor 4 IVF cycles Covered Covered Covered Not covered Not specified Rhode Island (n=1) 1989 2006 2017 1-year of infertility between 25 and 42 years old Autologous only $100.000 Covered Covered Covered Covered, plan-dependent Not specified Supplementary Files AppendixA.docx AppendixB.docx AppendixC.docx AppendixD.docx Cite Share Download PDF Status: Published Journal Publication published 30 Nov, 2021 Read the published version in Reproductive Biology and Endocrinology → Version 1 posted Editorial decision: Minor revision 20 Oct, 2021 Review # 1 received at journal 19 Oct, 2021 Reviews received at journal 15 Oct, 2021 Reviewers invited by journal 15 Oct, 2021 Editor assigned by journal 14 Oct, 2021 Reviewer # 2 agreed at journal 14 Oct, 2021 Reviewer # 1 agreed at journal 14 Oct, 2021 Review # 2 received at journal 14 Oct, 2021 First submitted to journal 14 Oct, 2021 Submission checks completed at journal 13 Oct, 2021 Editor invited by journal 13 Oct, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-970725","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":56843118,"identity":"0320798b-02ee-4eeb-bb20-135641c9db62","order_by":0,"name":"Pavel Zagadailov","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYLACHgYJGQYG5gNAJohBpBYeBga2BJAWHmK1gJEBlE0AyLcfv/jhTY0FD79EzudXN4AMBvbDRzfg08LYk1MsOeeYBI/kjNxt1jlABgNPWtoNfFqYGXISpHnYJHgMzpzdZpwDZAC9Y4ZXCxv/m+TfPP9AWs48M875R4QWHon0Y9K8bUAtx3uYH+e2EaFFQuINm+XcPqBf2tvMmHOBDDZCfpHvT3984823Ojl+ZubHn3NADPbDx/BqgUUH2F8SYBK/chBgfwBjMX8grHoUjIJRMApGIgAAJgk/9hrfW8wAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-5433-1118","institution":"Clinical Outcomes Research Group, CORG LLC","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Pavel","middleName":"","lastName":"Zagadailov","suffix":""},{"id":56843119,"identity":"977fd44f-270e-4c9e-afa7-7c9e893bf529","order_by":1,"name":"Kyung S CHO","email":"","orcid":"","institution":"Columbia University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kyung","middleName":"S","lastName":"CHO","suffix":""},{"id":56843120,"identity":"0b5a30f0-8574-498f-ad70-e351d7f3285c","order_by":2,"name":"David B SEIFER","email":"","orcid":"","institution":"Yale University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"David","middleName":"B","lastName":"SEIFER","suffix":""}],"badges":[],"createdAt":"2021-10-15 10:40:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-970725/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-970725/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12958-021-00856-4","type":"published","date":"2021-11-30T18:23:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":16035449,"identity":"d5c52f48-5f95-461d-b6d3-07f277c0d3ac","added_by":"auto","created_at":"2021-11-30 18:23:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":276346,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-970725/v1/e54b6b4c-96b4-47b9-8ed1-437b43d4b557.pdf"},{"id":14668109,"identity":"e4543343-17ad-40a2-be9f-19a0baa5be64","added_by":"auto","created_at":"2021-10-19 14:16:02","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":14140,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixA.docx","url":"https://assets-eu.researchsquare.com/files/rs-970725/v1/3c5aa00d4f1ab30f9e62c708.docx"},{"id":14668110,"identity":"b963be71-b2b4-4523-8756-1db07c7b024b","added_by":"auto","created_at":"2021-10-19 14:16:02","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":14070,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixB.docx","url":"https://assets-eu.researchsquare.com/files/rs-970725/v1/9ea4b29e9f6ad355e43bf37d.docx"},{"id":14668112,"identity":"34ba116b-46d3-4fa0-a591-3e228a5145b8","added_by":"auto","created_at":"2021-10-19 14:16:02","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":14009,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixC.docx","url":"https://assets-eu.researchsquare.com/files/rs-970725/v1/c831737cf9a8e176c87830df.docx"},{"id":14668459,"identity":"a8705202-c192-4ffc-882b-907ce84993cf","added_by":"auto","created_at":"2021-10-19 14:19:02","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":14004,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixD.docx","url":"https://assets-eu.researchsquare.com/files/rs-970725/v1/732455eb1c56b619d5fd06c1.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eDifferences in ICSI Utilization Rates Among States With Insurance Mandates for ART Coverage\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eIntracytoplasmic sperm injection (ICSI) is indicated for couples with a history of failed fertilization after conventional insemination or with severe male factor (MF) infertility. While ICSI is often used for the treatment of unexplained infertility and low oocyte yield, it has not been demonstrated to improve clinical outcomes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A 2018 report found that assisted reproductive technologies (ART) state mandates were associated with increased ICSI use for non-male factor indications [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSixteen U.S. states have now passed laws that require insurers to offer coverage for infertility diagnosis and treatment. Before 2018, eight states (AR, CT, HI, IL, MA, MD, NJ, RI) had ART-mandates. Four states (IL, MA, NJ, and RI) have included ICSI as a covered benefit. [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eOur previous studies have suggested that ICSI may be overutilized and not accompanied by increase in male factor or improved live birth rates [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In ART-mandated states, lower ICSI rates were accompanied by a positive correlation with live birth rates (LBR). Such findings suggested that ART mandates may promote more selective utilization of ART clinic resources [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, these previous analyses were comparing ART-mandated versus non-mandated states in aggregate.\u003c/p\u003e \u003cp\u003eThe present study was designed to evaluate the differences in utilization of ICSI between individual ART-mandated states and to compare these rates with non-mandated states in aggregate. Furthermore, to better understand some of the underlying factors contributing to differences in ICSI use among individual ART-mandated states, we examined the frequency of male factor, PGT and singleton live birth rates among these states.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source\u003c/h2\u003e \u003cp\u003eThis retrospective analysis was conducted using the National Assisted Reproductive Technology Surveillance System (NASS), maintained by the Centers for Disease Control and Prevention (CDC). A publicly available NASS dataset for 2018 was downloaded from the CDC website [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Clinics within this yearly report were grouped by ART-mandated state, then evaluated individually and compared to a group of non-mandated states in aggregate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Outcomes\u003c/h2\u003e \u003cp\u003eWe evaluated eight ART-mandated states (AR, CT, HI, IL, MD, MA, NJ, RI) individually, comparing them to one another as well as comparing each of them to the remaining non-mandated states (n=42, 382 ART clinics) in aggregate. We hypothesized that the use of ICSI, frequency of male factor, PGT rates, and singleton live birth rates across all age groups significantly varied among each of the ART-mandated states. Age groups were categorized by the Society for Assisted Reproductive Technology (SART) groupings as \u0026lt;35 years old, 35 \u0026ndash; 37, 38 \u0026ndash; 40, 41 \u0026ndash; 42, and \u0026gt;42 years old.\u003c/p\u003e \u003cp\u003eOnly autologous, non-donor embryo transfers were included in this analysis. Frozen autologous and donor embryo transfers were excluded. Specific for each age group, ICSI utilization rates, frequency of male factor, PGT rates, and singleton live birth rates for individual ART-mandated states and non-mandated states combined in aggregate were evaluated. ICSI utilization rates and MF infertility rates are examined to assess the potential overutilization of ICSI in ART-mandated states if any.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed utilizing R (version 3.5.1, R Core Team, University of Auckland, New Zealand). Analysis of variance (ANOVA) was used to evaluate whether there were statistical differences among individual ART-mandated states and non-mandated states in aggregate. Individual states were compared in pairs using Welch t-tests to determine whether utilization of ICSI, male factor, PGT rates, and live birth rates per transfer were statistically different among ART-mandated states and non-mandated states in aggregate. Statistical significance was determined after multiple testing adjustments using Bonferroni Correction.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eResults are organized by age group.\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003e\u0026lt; 35 years old\u003c/h2\u003e\n \u003cp\u003eThere were significant differences between ICSI utilization rates (%, mean \u0026plusmn; SD) of MA (53.3 \u0026plusmn; 21.3) and HI (90.7 \u0026plusmn; 19.6), p = 0.028, 95% CI [11.4, 63.4]; IL (86.5 \u0026plusmn; 18.7) and MA, p = 0.002, 95% CI [14.5, 51.9]; IL and MD (57.2 \u0026plusmn; 30.8), p = 0.04, 95% CI [2.9, 61.5]; IL and NJ (62.0 \u0026plusmn; 26.8), p = 0.007, 95% CI [8, 41.1]; non-mandated states combined (79.9 \u0026plusmn; 19.9) and MA, p = 0.006, 95% CI [8.8, 44.4]; non-mandated states and NJ (62.0 \u0026plusmn; 26.8), p = 0.02, 95% CI [3, 32.9]. Male factor rates of HI (65.8 \u0026plusmn; 16.0) were greater compared to CT (18.8 \u0026plusmn; 8.7), IL (26.0 \u0026plusmn; 11.9), MA (26.9 \u0026plusmn; 6.6), MD (29.3 \u0026plusmn; 9.9), NJ (30.6 \u0026plusmn; 17.9) and non-mandated states (29.7 \u0026plusmn; 13.7), all p \u0026lt; 0.0001, 95% Cl\u0026rsquo;s are [29.7, 64.3], [23, 56.6], [22.1, 55.8], [19.2, 53.9], [17.9, 52.7], [19.3, 52.9] respectively. (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003e35 \u0026ndash; 37 years old\u003c/h2\u003e\n \u003cp\u003eThere were significant differences between ICSI utilization rates of MA (51.85 \u0026plusmn; 19) and HI (87.7 \u0026plusmn; 20), p = 0.0459, 95% CI [10.2, 61.5]; IL (84.7 \u0026plusmn; 21) and MA, p = 0.0024, 95% CI [15.5, 50.2]; NJ (61.9 \u0026plusmn; 24.6) and IL, p = 0.0327, 95% CI [5.8, 39.7]; non-mandated states combined (77 \u0026plusmn; 20.2) and MA, p = 0.0135, 95% CI [9.2, 41.1]. (Appendix A)\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec9\"\u003e\n \u003ch2\u003e38 \u0026ndash; 40 years old\u003c/h2\u003e\n \u003cp\u003eThere were significant differences between ICSI utilization rates of MA (54.5 \u0026plusmn; 20.4) and IL (86 \u0026plusmn; 11.6), p = 0.004, 95% CI [11.9, 48.6]. (Appendix B)\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003e41 \u0026ndash; 42 years old and 42 \u0026gt; years old\u003c/h2\u003e\n \u003cp\u003eNo statistically significant differences were reported for ICSI utilization rates in two age groups between ART-mandated and non-mandated states. (Appendix C, D)\u003c/p\u003e\n \u003cp\u003eNo statistically significant differences were reported for PGT rates and singleton live birth rates between ART-mandated and non-mandated states for all age groups.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThese data demonstrate significant differences in ICSI utilization between individual ART-mandated states as well as compared to non-mandated state aggregate data. Covered infertility benefits in ART-mandated states vary dramatically (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Multiple factors may influence the decision of whether to use ICSI or conventional IVF. Clinic-specific policies, discretion of treating physicians, and/or embryology laboratory personnel preference to use ICSI in patients with low oocyte yields, perceived poor oocyte quality or unexplained infertility are factors that can influence the use of ICSI.\u003c/p\u003e \u003cp\u003eThe two ART-mandated states with the highest utilization of ICSI were HI and IL. Remarkably, a large portion of the ART clinics in Hawaii (80%) and in Illinois (48%) reported \u0026gt;75% ICSI usage, in contrast to no ART clinics in MA. HI reported dramatically higher male factor infertility rates (65.8%) than any other ART-mandated and non-mandated state. Furthermore, CT and MA showed a similar trend of lower ICSI use associated with more favorable clinical outcomes than reported in HI and IL. However, significantly greater male factor rates in HI than in other ART-mandated states and non-mandated states in aggregate may justify greater utilization of ICSI. This observation raises speculation of whether increased concern for potential poor, failed fertilization, unexplained infertility, or the perception of increased competition in specific geographic locations may have contributed to greater utilization of ICSI.\u003c/p\u003e \u003cp\u003eInterestingly, further analysis of the states with mandated ART coverage identified two states (IL and MA) with similar ART mandate structure and demographics but dramatically different ICSI utilization profiles. Both state mandates have a similar timeline for infertility diagnosis, covered cost of diagnostic tests, laboratory procedures that include ICSI, plan-dependent cost of medication and embryo cryopreservation (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Both states have heterogeneous, racially diverse populations within major metropolitan centers (Chicago and Boston) that are the homes of multiple academic teaching medical centers as well as many IVF private practices. However, IL had remarkably higher ICSI rates compared with ICSI rates of MA. Yet, in contrast, male factor diagnosis rates did not differ significantly between these two states, nor did PGT or singleton live birth rates. This wide difference in ICSI rates between IL and MA may in part be due to a fewer number of clinics and thus a greater annual ART cycle volume per IVF clinic in MA than in IL. It is speculated that lower and more selective use of ICSI utilization in MA could contribute to greater uniformity and less variability in employing ICSI by MA clinics compared to those clinics in IL.\u003c/p\u003e \u003cp\u003eFurthermore, several unique factors may explain why HI demonstrated the highest rate of ICSI among the ART-mandated states. Such factors contributing to increased ICSI utilization may include the limited number of ART clinics with significantly lower annual clinical volume, island-specific demographic distribution and a limited number of laboratory directors. Thus, we believe trends of ICSI use in HI may not be as representative nor as generalizable to ICSI and outcome rates of states in the continental U.S.\u003c/p\u003e \u003cp\u003eICSI use varied significantly among the ART-mandated states while demonstrating no differences in live birth rates. This analysis of individual ART-mandated states suggests that the prevalence of male factor and the presence of a state insurance mandate are not the only factors influencing ICSI use. It is suggested that other possible non-clinical factors, such as the number of ART clinics in a given geographic area, clinic-specific policies, and/or patient/physician preferences, may impact the rate of ICSI utilization in a given state and will require further examination.\u003c/p\u003e \u003cp\u003eThere are several strengths and limitations to this study. The primary strength is the use of the CDC dataset that incorporates \u0026gt;98% of ART cycles performed in the U. S. The improvement in the reporting of the 2018 data set compared to previous years included outcomes specific for each age group. Live birth rates were reported per transfer and specific for fresh non-donor embryos resulting from ICSI use.\u003c/p\u003e \u003cp\u003eLimitations include the fact that states with single clinics (AR, RI) were excluded as the variance calculation was possible only for states with two or more clinics. Hence, we could not assess the impact of every state\u0026rsquo;s ART mandate. Provided by the CDC, male factor rates are \u0026ldquo;per clinic\u0026rdquo; and are not age group-specific nor do they include details regarding the specific types of male factor diagnosis. An additional limitation of this study is that semen parameters were not collected nor available from the CDC dataset to help better understand the origin of the greater rates of male factor in HI.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eICSI use varied significantly among ART-mandated states while demonstrating no differences in live birth rates. These data suggest that the prevalence of male factor and the presence of a state insurance mandate are not the only factors influencing ICSI use. It is suggested that other non-clinical factors may impact the rate of ICSI utilization in a given state.\u003c/p\u003e"},{"header":"List Of Abbreviations","content":"\u003cp\u003eANOVA - Analysis of variance\u003c/p\u003e\n\u003cp\u003eART - Assisted reproductive technology\u003c/p\u003e\n\u003cp\u003eCDC - Centers for Disease Control and Prevention\u003c/p\u003e\n\u003cp\u003eICSI - Intracytoplasmic sperm injection\u003c/p\u003e\n\u003cp\u003eLBR - Live birth rate\u003c/p\u003e\n\u003cp\u003eMF - Male factor\u003c/p\u003e\n\u003cp\u003eNASS - National Assisted Reproductive Technology Surveillance System\u003c/p\u003e\n\u003cp\u003ePGT - Preimplantation genetic testing\u003c/p\u003e\n\u003cp\u003eSART - Society for Assisted Reproductive Technology\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study qualified as \u0026ldquo;not human subject research\u0026rdquo;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNASS datasets for 2018 are publicly available from the CDC website: https://www.cdc.gov/art/nass/ See reference [10]\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll authors equally participated in study design, data analysis, results interpretation and drafting of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePractice Committees of the American Society for Reproductive Medicine and the Society for Assisted Reproductive Technology. Intracytoplasmic sperm injection (ICSI) for non-male factor indications: a committee opinion. Fertil Steril. 2020 Aug;114(2):239\u0026ndash;45. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.fertnstert.2020.05.032\u003c/span\u003e\u003c/span\u003e. Epub 2020 Jul 9. PMID: 32654822.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDieke AC, Mehta A, Kissin DM, Nangia AK, Warner L, Boulet SL. Intracytoplasmic sperm injection use in states with and without insurance coverage mandates for infertility treatment, United States, 2000-2015. Fertil Steril. 2018;109(4):691\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIll. Rev. Stat. ch. 215, \u0026sect; 5/356m (1991, 1996). Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ilga.gov/legislation/ilcs/\u003c/span\u003e\u003c/span\u003e Accessed: July 2018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMass G. Laws Ann. ch. 175, \u0026sect; 47H, ch. 176A, \u0026sect; 8K, ch. 176B, \u0026sect; 4J, ch. 176G, \u0026sect; 4 and 211 Code of Massachusetts Regulations 37.00 (1987, 2010). Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://malegislature.gov/Laws/GeneralLaws/\u003c/span\u003e\u003c/span\u003e Accessed: May 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStat NJ. Ann. \u0026sect; 17:48-6x, \u0026sect; 17:48A-7w, \u0026sect; 17:48E-35.22 and \u0026sect; 17B:27-46.1x (2001) Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://law.justia.com/codes/new-jersey/\u003c/span\u003e\u003c/span\u003e Accessed: May 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGen RI. Laws \u0026sect; 27-18-30, \u0026sect; 27-19-23, \u0026sect; 27-20-20 and \u0026sect; 27-41-33 (1989, 2007) Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://webserver.rilin.state.ri.us\u003c/span\u003e\u003c/span\u003e/Statutes/ Accessed: May 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZagadailov P, Hsu A, Seifer DB, Stern JE. Differences in utilization of Intracytoplasmic sperm injection (ICSI) within human services (HHS) regions and metropolitan megaregions in the U.S. Reprod Biol Endocrinol. 2017 Jun 12;15(1):45. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12958-017-0263-4\u003c/span\u003e\u003c/span\u003e. PMID: 28606175; PMCID: PMC5469007.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZagadailov P, Hsu A, Stern JE, Seifer DB. Temporal Differences in Utilization of Intracytoplasmic Sperm Injection Among U.S. Regions. Obstet Gynecol. 2018 Aug;132(2):310-320. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/AOG.0000000000002730\u003c/span\u003e\u003c/span\u003e. PMID: 29995722.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZagadailov P, Seifer DB, Shan H, Zarek SM, Hsu AL. Do state insurance mandates alter ICSI utilization? Reprod Biol Endocrinol. 2020 Apr 25;18(1):33. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12958-020-00589-w\u003c/span\u003e\u003c/span\u003e. PMID: 32334609; PMCID: PMC7183130.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention National ART Surveillance System, ART National Data. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/art/nass/\u003c/span\u003e\u003c/span\u003e Accessed: March 2021.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eAge group \u0026lt;35\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.169984686064318%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.592649310872893%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLive Birth Rate\u003cbr\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003e(%, mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e\u003cstrong\u003eICSI Rate\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(%, mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePGT Rate\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(%, mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.133231240428792%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale Factor Rate\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(%, mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.169984686064318%\"\u003e\n \u003cp\u003eAR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.592649310872893%\"\u003e\n \u003cp\u003e30.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e70.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e0.8\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.133231240428792%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.169984686064318%\"\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.592649310872893%\"\u003e\n \u003cp\u003e46.2\u0026nbsp;\u0026nbsp;11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e72.1\u0026nbsp;\u0026nbsp;16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e28.4\u0026nbsp;\u0026nbsp;17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.133231240428792%\"\u003e\n \u003cp\u003e18.8\u0026nbsp;\u0026nbsp;8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.169984686064318%\"\u003e\n \u003cp\u003eHI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.592649310872893%\"\u003e\n \u003cp\u003e45.1\u0026nbsp;\u0026nbsp;19.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e90.7\u0026nbsp;\u0026nbsp;19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e25.8\u0026nbsp;\u0026nbsp;13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.133231240428792%\"\u003e\n \u003cp\u003e65.8\u0026nbsp;\u0026nbsp;16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.169984686064318%\"\u003e\n \u003cp\u003eIL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.592649310872893%\"\u003e\n \u003cp\u003e34.8\u0026nbsp;\u0026nbsp;12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e86.5\u0026nbsp;\u0026nbsp;18.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e20.1\u0026nbsp;\u0026nbsp;21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.133231240428792%\"\u003e\n \u003cp\u003e26\u0026nbsp;\u0026nbsp;11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.169984686064318%\"\u003e\n \u003cp\u003eMD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.592649310872893%\"\u003e\n \u003cp\u003e39.9\u0026nbsp;\u0026nbsp;8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e57.3\u0026nbsp;\u0026nbsp;30.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e11.3\u0026nbsp;\u0026nbsp;11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.133231240428792%\"\u003e\n \u003cp\u003e29.3\u0026nbsp;\u0026nbsp;9.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.169984686064318%\"\u003e\n \u003cp\u003eMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.592649310872893%\"\u003e\n \u003cp\u003e36.7\u0026nbsp;\u0026nbsp;6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e53.3\u0026nbsp;\u0026nbsp;21.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e20\u0026nbsp;\u0026nbsp;24.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.133231240428792%\"\u003e\n \u003cp\u003e26.9\u0026nbsp;\u0026nbsp;6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.169984686064318%\"\u003e\n \u003cp\u003eNJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.592649310872893%\"\u003e\n \u003cp\u003e40.6\u0026nbsp;\u0026nbsp;9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e62\u0026nbsp;\u0026nbsp;26.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e32.6\u0026nbsp;\u0026nbsp;22.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.133231240428792%\"\u003e\n \u003cp\u003e30.6\u0026nbsp;\u0026nbsp;17.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.169984686064318%\"\u003e\n \u003cp\u003eRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.592649310872893%\"\u003e\n \u003cp\u003e33.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e55.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.133231240428792%\"\u003e\n \u003cp\u003e23\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.169984686064318%\"\u003e\n \u003cp\u003enon-mandated states\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.592649310872893%\"\u003e\n \u003cp\u003e40.9\u0026nbsp;\u0026nbsp;10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e79.9\u0026nbsp;\u0026nbsp;19.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.052067381317%\"\u003e\n \u003cp\u003e35.6\u0026nbsp;\u0026nbsp;28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.133231240428792%\"\u003e\n \u003cp\u003e29.7 \u0026nbsp;13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: \u003c/strong\u003eComparison of insurance coverage for infertility diagnosis and treatment in ART-mandated states\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"11.261730969760167%\"\u003e\n \u003cp\u003eART-Mandated State (n/clinic)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.465067778936392%\"\u003e\n \u003cp\u003eEnacted (and Revised)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.200208550573514%\"\u003e\n \u003cp\u003eDiagnoses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eCycle type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003eLifetime maximum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003eCosts of diagnostic tests\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eMedications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eICSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.51303441084463%\"\u003e\n \u003cp\u003eCryopreservation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eCoverage of other ART procedures\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"11.261730969760167%\"\u003e\n \u003cp\u003eArkansas\u003cbr\u003e\u0026nbsp;(n=1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.465067778936392%\"\u003e\n \u003cp\u003e1987\u003c/p\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.200208550573514%\"\u003e\n \u003cp\u003e2-years of infertility\u003c/p\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003cp\u003eEndometriosis\u003c/p\u003e\n \u003cp\u003eTubal factor\u003c/p\u003e\n \u003cp\u003eMale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eAutologous only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003e$15.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003eNot covered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eNot covered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.51303441084463%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003ePlan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"11.261730969760167%\"\u003e\n \u003cp\u003eConnecticut\u003cbr\u003e\u0026nbsp;(n=6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.465067778936392%\"\u003e\n \u003cp\u003e1989\u003c/p\u003e\n \u003cp\u003e2005\u003c/p\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.200208550573514%\"\u003e\n \u003cp\u003e1-year of infertility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003e3 IUI\u003c/p\u003e\n \u003cp\u003e2 IVF cycles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eCovered, plan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.51303441084463%\"\u003e\n \u003cp\u003eNot covered\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"11.261730969760167%\"\u003e\n \u003cp\u003eHawaii\u003cbr\u003e\u0026nbsp;(n=6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.465067778936392%\"\u003e\n \u003cp\u003e1989\u003c/p\u003e\n \u003cp\u003e2003\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.200208550573514%\"\u003e\n \u003cp\u003e5-year of infertility\u003c/p\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003cp\u003eEndometriosis\u003c/p\u003e\n \u003cp\u003eTubal factor\u003c/p\u003e\n \u003cp\u003eMale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eAutologous only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003e1 IVF cycle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003ePartially covered\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eNot covered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eNot specified, plan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.51303441084463%\"\u003e\n \u003cp\u003eCovered,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eplan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003ePlan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"11.261730969760167%\"\u003e\n \u003cp\u003eIllinois\u003cbr\u003e\u0026nbsp;(n=26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.465067778936392%\"\u003e\n \u003cp\u003e1991\u003c/p\u003e\n \u003cp\u003e1997\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.200208550573514%\"\u003e\n \u003cp\u003e1-year of infertility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eAutologous and Donor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003e6 IVF cycles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.51303441084463%\"\u003e\n \u003cp\u003eCovered,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eplan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003ePlan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"11.261730969760167%\"\u003e\n \u003cp\u003eMaryland\u003cbr\u003e\u0026nbsp;(n=7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.465067778936392%\"\u003e\n \u003cp\u003e1985\u003c/p\u003e\n \u003cp\u003e2000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.200208550573514%\"\u003e\n \u003cp\u003e2-year of infertility\u003c/p\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003cp\u003eEndometriosis\u003c/p\u003e\n \u003cp\u003eTubal factor\u003c/p\u003e\n \u003cp\u003eMale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eAutologous only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003e$100.000\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3 IVF cycles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eNot covered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eNot specified, plan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.51303441084463%\"\u003e\n \u003cp\u003eNot covered\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"11.261730969760167%\"\u003e\n \u003cp\u003eMassachusetts\u003cbr\u003e\u0026nbsp;(n=8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.465067778936392%\"\u003e\n \u003cp\u003e1987\u003c/p\u003e\n \u003cp\u003e2010\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.200208550573514%\"\u003e\n \u003cp\u003e1-year of infertility for \u0026lt;35 years old\u003c/p\u003e\n \u003cp\u003e6-months infertility \u0026ge;35 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003eCovered, plan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eCovered, plan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.51303441084463%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003ePlan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"11.261730969760167%\"\u003e\n \u003cp\u003eNew Jersey\u003cbr\u003e\u0026nbsp;(n=19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.465067778936392%\"\u003e\n \u003cp\u003e2001\u003c/p\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.200208550573514%\"\u003e\n \u003cp\u003e1-year of infertility for \u0026lt;35 years old\u003c/p\u003e\n \u003cp\u003e6-months infertility \u0026ge;35-46 years old\u003c/p\u003e\n \u003cp\u003eOR\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTubal factor\u003c/p\u003e\n \u003cp\u003eMale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eAutologous and Donor\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003e4 IVF cycles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.51303441084463%\"\u003e\n \u003cp\u003eNot covered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"11.261730969760167%\"\u003e\n \u003cp\u003eRhode Island\u003cbr\u003e\u0026nbsp;(n=1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.465067778936392%\"\u003e\n \u003cp\u003e1989\u003c/p\u003e\n \u003cp\u003e2006\u003c/p\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.200208550573514%\"\u003e\n \u003cp\u003e1-year of infertility between 25 and 42 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eAutologous only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003e$100.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.636079249217936%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.75912408759124%\"\u003e\n \u003cp\u003eCovered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.51303441084463%\"\u003e\n \u003cp\u003eCovered,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eplan-dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.384775808133472%\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"reproductive-biology-and-endocrinology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rbej","sideBox":"Learn more about [Reproductive Biology and Endocrinology](http://rbej.biomedcentral.com)","snPcode":"12958","submissionUrl":"https://submission.nature.com/new-submission/12958/3","title":"Reproductive Biology and Endocrinology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Assisted reproductive technology, In-Vitro fertilization, State insurance mandates, Intracytoplasmic sperm injection, utilization rates, live birth rate, male factor","lastPublishedDoi":"10.21203/rs.3.rs-970725/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-970725/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAssisted reproductive technology (ART) insurance mandates promote more selective utilization of ART clinic resources including intracytoplasmic sperm injection (ICSI). Our objective was to examine whether ICSI utilization differs by state insurance mandates for ART coverage and assess if such a difference is associated with male factor, preimplantation genetic testing (PGT), and/or live birth rates.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this retrospective analysis of the Centers for Disease Control (CDC) data from 2018, ART clinics in ART-mandated states (n=8, AR, CT, HI, IL, MD, MA, NJ, RI) were compared individually to one another and with non-mandated states in aggregate (n=42) for use of ICSI, male factor, PGT, and live birth rates. ANOVA was used to evaluate differences between ART-mandated states and non-mandated states. Individual ART-mandated states were compared using Welch t-tests. Statistical significance was determined by Bonferroni Correction.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThere were significant differences in ICSI rates (%, mean \u0026plusmn; SD) between MA (53.3 \u0026plusmn; 21.3) and HI (90.7 \u0026plusmn; 19.6), p = 0.028; IL (86.5 \u0026plusmn; 18.7) and MA, p = 0.002; IL and MD (57.2 \u0026plusmn; 30.8), p = 0.039; IL and NJ (62.0 \u0026plusmn; 26.8), p = 0.007; between non-mandated states in aggregate (79.9 \u0026plusmn; 19.9) and MA, p = 0.006, and NJ (62.0 \u0026plusmn; 26.8), p = 0.02. Male factor rates of HI (65.8 \u0026plusmn; 16.0) were significantly greater compared to CT (18.8 \u0026plusmn; 8.7), IL (26.0 \u0026plusmn; 11.9), MA (26.9 \u0026plusmn; 6.6), MD (29.3 \u0026plusmn; 9.9), NJ (30.6 \u0026plusmn; 17.9), and non-mandated states in aggregate (29.7 \u0026plusmn; 13.7), all p \u0026lt; 0.0001. No significant differences were reported for use of PGT and/or live birth rates across all age groups regardless of mandate status.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eICSI use varied significantly among ART-mandated states while demonstrating no differences in live birth rates. These data suggest that the prevalence of male factor and the presence of a state insurance mandate are not the only factors influencing ICSI use. It is suggested that other non-clinical factors may impact the rate of ICSI utilization in a given state.\u003c/p\u003e","manuscriptTitle":"Differences in ICSI Utilization Rates Among States With Insurance Mandates for ART Coverage","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-10-19 14:16:00","doi":"10.21203/rs.3.rs-970725/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2021-10-20T23:55:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-10-20T00:00:00+00:00","index":1,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"editorInvitedReview","content":"","date":"2021-10-15T07:44:10+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-10-15T07:27:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-10-15T02:52:22+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-10-15T01:00:00+00:00","index":2,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-10-15T00:00:00+00:00","index":1,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-10-15T00:00:00+00:00","index":2,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"submitted","content":"Reproductive Biology and Endocrinology","date":"2021-10-14T07:55:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-10-13T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-10-13T23:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"reproductive-biology-and-endocrinology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rbej","sideBox":"Learn more about [Reproductive Biology and Endocrinology](http://rbej.biomedcentral.com)","snPcode":"12958","submissionUrl":"https://submission.nature.com/new-submission/12958/3","title":"Reproductive Biology and Endocrinology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"60e6aaf7-b7eb-41e1-995a-3d4301e0453a","owner":[],"postedDate":"October 19th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":7949966,"name":"Endocrinology \u0026 Metabolism"}],"tags":[],"updatedAt":"2021-11-30T18:23:09+00:00","versionOfRecord":{"articleIdentity":"rs-970725","link":"https://doi.org/10.1186/s12958-021-00856-4","journal":{"identity":"reproductive-biology-and-endocrinology","isVorOnly":false,"title":"Reproductive Biology and Endocrinology"},"publishedOn":"2021-11-30 18:23:09","publishedOnDateReadable":"November 30th, 2021"},"versionCreatedAt":"2021-10-19 14:16:00","video":"","vorDoi":"10.1186/s12958-021-00856-4","vorDoiUrl":"https://doi.org/10.1186/s12958-021-00856-4","workflowStages":[]},"version":"v1","identity":"rs-970725","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-970725","identity":"rs-970725","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}