OBJECTIVE: To describe the annual care, direct health care, and indirect work loss costs for women with a diagnosis of uterine leiomyomata. METHODS: We examined data from an employer claims database of 1.2 million beneficiaries (1999 to 2003). Analysis was restricted to women with at least 12 months of continuous coverage and ages 18 to 64 years with at least one diagnosis of leiomyomata (International Classification of Diseases, 9th Revision, 218.xx, 654.1x). We selected a comparison group of women without a leiomyoma diagnosis using a 1:1 match on age, employment, region, health plan type, and length of enrollment. We compared resource use, disability claims, and excess costs in the year after the index diagnosis. RESULTS: The average age of women diagnosed with leiomyomata in this study was 43.7 years. Women with leiomyomata (N = 5,122) had more clinic visits (relative risk [RR] 1.2, 95% confidence interval [CI] 1.2-1.2), diagnostic tests (RR 3.1, 95% CI 2.9-3.2), and procedures (RR 34.6, 95% CI 25.8-46.5) than controls (N = 5,122). Within 1 year of the diagnosis of leiomyomata, 42% of women had a complete blood count, 66% had pelvic imaging, and 30% had surgery (68% of surgical procedures involved hysterectomy). Women with leiomyomata were 3-fold more likely to have disability claims (RR 3.1, 95% CI 2.7-3.6). Estimated average annual excess cost for each woman with leiomyomata (adjusted for confounders) was Dollars 4,624 (Dollars 771 in work loss costs). Total costs for women with leiomyomata were 2.6 times greater than for controls. CONCLUSION: Diagnosed uterine leiomyomata are associated with increased resource use and with substantially higher health care and work loss costs. LEVEL OF EVIDENCE: II-3.
OBJECTIVE: To describe the annual care, direct health care, and indirect work loss costs for women with a diagnosis of uterine leiomyomata. METHODS: We examined data from an employer claims database of 1.2 million beneficiaries (1999 to 2003). Analysis was restricted to women with at least 12 months of continuous coverage and ages 18 to 64 years with at least one diagnosis of leiomyomata (International Classification of Diseases, 9th Revision, 218.xx, 654.1x). We selected a comparison group of women without a leiomyoma diagnosis using a 1:1 match on age, employment, region, health plan type, and length of enrollment. We compared resource use, disability claims, and excess costs in the year after the index diagnosis. RESULTS: The average age of women diagnosed with leiomyomata in this study was 43.7 years. Women with leiomyomata (N = 5,122) had more clinic visits (relative risk [RR] 1.2, 95% confidence interval [CI] 1.2-1.2), diagnostic tests (RR 3.1, 95% CI 2.9-3.2), and procedures (RR 34.6, 95% CI 25.8-46.5) than controls (N = 5,122). Within 1 year of the diagnosis of leiomyomata, 42% of women had a complete blood count, 66% had pelvic imaging, and 30% had surgery (68% of surgical procedures involved hysterectomy). Women with leiomyomata were 3-fold more likely to have disability claims (RR 3.1, 95% CI 2.7-3.6). Estimated average annual excess cost for each woman with leiomyomata (adjusted for confounders) was Dollars 4,624 (Dollars 771 in work loss costs). Total costs for women with leiomyomata were 2.6 times greater than for controls. CONCLUSION: Diagnosed uterine leiomyomata are associated with increased resource use and with substantially higher health care and work loss costs. LEVEL OF EVIDENCE: II-3.
Authors: Zehra Ordulu; Paola Dal Cin; Wilson W S Chong; Kwong Wai Choy; Charles Lee; Michael G Muto; Bradley J Quade; Cynthia C Morton Journal: Genes Chromosomes Cancer Date: 2010-12 Impact factor: 5.006
Authors: Kellen L Meadows; Danica M K Andrews; Zongli Xu; Gleta K Carswell; Shannon K Laughlin; Donna D Baird; Jack A Taylor Journal: Exp Mol Pathol Date: 2011-04-08 Impact factor: 3.362
Authors: Karen L Huyck; Carolien I M Panhuysen; Karen T Cuenco; Jingmei Zhang; Hilary Goldhammer; Emlyn S Jones; Priya Somasundaram; Allison M Lynch; Bernard L Harlow; Hang Lee; Elizabeth A Stewart; Cynthia C Morton Journal: Am J Obstet Gynecol Date: 2008-02 Impact factor: 8.661
Authors: Lani Feingold-Link; Todd L Edwards; Sarah Jones; Katherine E Hartmann; Digna R Velez Edwards Journal: J Womens Health (Larchmt) Date: 2014-12 Impact factor: 2.681
Authors: Jennelle C Hodge; Peter J Park; Jonathan M Dreyfuss; Iman Assil-Kishawi; Priya Somasundaram; Luwam G Semere; Bradley J Quade; Allison M Lynch; Elizabeth A Stewart; Cynthia C Morton Journal: Genes Chromosomes Cancer Date: 2009-10 Impact factor: 5.006
Authors: Netta Mäkinen; Pia Vahteristo; Kati Kämpjärvi; Johanna Arola; Ralf Bützow; Lauri A Aaltonen Journal: Eur J Hum Genet Date: 2013-02-27 Impact factor: 4.246
Authors: Shyamal D Peddada; Shannon K Laughlin; Kelly Miner; Jean-Philippe Guyon; Karen Haneke; Heather L Vahdat; Richard C Semelka; Ania Kowalik; Diane Armao; Barbara Davis; Donna Day Baird Journal: Proc Natl Acad Sci U S A Date: 2008-12-01 Impact factor: 11.205
Authors: Amy K O'Sullivan; David Thompson; Paula Chu; David W Lee; Elizabeth A Stewart; Milton C Weinstein Journal: Int J Technol Assess Health Care Date: 2009-01 Impact factor: 2.188