Evan M Chen1, Ninani Kombo1, Christopher C Teng1, Prithvi Mruthyunjaya2, Kristen Nwanyanwu1, Ravi Parikh3. 1. Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, Connecticut. 2. Byers Eye Institute, Department of Ophthalmology, Stanford University School of Medicine, Palo Alto, California. 3. Department of Ophthalmology, NYU Langone Health, New York University School of Medicine, New York, New York; Manhattan Retina and Eye Consultants, New York, New York. Electronic address: Rap120@mail.harvard.edu.
Abstract
PURPOSE: To estimate temporal trends in total and out-of-pocket (OOP) expenditures for ophthalmic prescription medications among adults in the United States. DESIGN: Retrospective, longitudinal cohort study. PARTICIPANTS: Participants in the 2007 through 2016 Medical Expenditure Panel Survey (MEPS) 18 years of age or older. The MEPS is a nationally representative survey of the noninstitutionalized, civilian United States population. METHODS: We estimated trends in national and per capita annual ophthalmic prescription expenditures by pooling data into 2-year cycles and using weighted linear regressions. We also identified characteristics associated with greater total or OOP expenditures with multivariate weighted linear regression. Costs were adjusted to 2016 United States dollars using the gross domestic product price index. MAIN OUTCOME MEASURES: Trends in total and OOP annual expenditures for ophthalmic medications from 2007 through 2016 as well as factors associated with greater expenditures. RESULTS: From 2007 through 2016, 9989 MEPS participants (4.2%) reported ophthalmic medication prescription use. Annual ophthalmic medication use increased from 10.0 to 12.2 million individuals from 2007 and 2008 through 2015 and 2016. In this same period, national expenditures for ophthalmic medications increased from $3.39 billion to $6.08 billion and OOP expenditures decreased from $1.34 to $1.18 billion. Per capita expenditure increased from $338.72 to $499.42 (P < 0.001), and per capita OOP expenditure decreased from $133.48 to $96.67 (P < 0.001) from 2007 and 2008 through 2015 and 2016, respectively. From 2015 through 2016, dry eye (29.5%) and glaucoma (42.7%) medications accounted for 72.2% of all ophthalmic medication expenditures. Patients who were older than 65 years (P < 0.001), uninsured (P < 0.001), and visually impaired (P < 0.001) were significantly more likely to have greater OOP spending on ophthalmic medications. CONCLUSIONS: Total ophthalmic medication expenditure in the United States increased significantly over the last decade, whereas OOP expenses decreased. Increases in coverage, copayment assistance, and use of expensive brand drugs may be contributing to these trends. Policy makers and physicians should be aware that rising overall drug expenditures ultimately may increase indirect costs to the patient and offset a decline in OOP prescription drug spending.
PURPOSE: To estimate temporal trends in total and out-of-pocket (OOP) expenditures for ophthalmic prescription medications among adults in the United States. DESIGN: Retrospective, longitudinal cohort study. PARTICIPANTS: Participants in the 2007 through 2016 Medical Expenditure Panel Survey (MEPS) 18 years of age or older. The MEPS is a nationally representative survey of the noninstitutionalized, civilian United States population. METHODS: We estimated trends in national and per capita annual ophthalmic prescription expenditures by pooling data into 2-year cycles and using weighted linear regressions. We also identified characteristics associated with greater total or OOP expenditures with multivariate weighted linear regression. Costs were adjusted to 2016 United States dollars using the gross domestic product price index. MAIN OUTCOME MEASURES: Trends in total and OOP annual expenditures for ophthalmic medications from 2007 through 2016 as well as factors associated with greater expenditures. RESULTS: From 2007 through 2016, 9989 MEPS participants (4.2%) reported ophthalmic medication prescription use. Annual ophthalmic medication use increased from 10.0 to 12.2 million individuals from 2007 and 2008 through 2015 and 2016. In this same period, national expenditures for ophthalmic medications increased from $3.39 billion to $6.08 billion and OOP expenditures decreased from $1.34 to $1.18 billion. Per capita expenditure increased from $338.72 to $499.42 (P < 0.001), and per capita OOP expenditure decreased from $133.48 to $96.67 (P < 0.001) from 2007 and 2008 through 2015 and 2016, respectively. From 2015 through 2016, dry eye (29.5%) and glaucoma (42.7%) medications accounted for 72.2% of all ophthalmic medication expenditures. Patients who were older than 65 years (P < 0.001), uninsured (P < 0.001), and visually impaired (P < 0.001) were significantly more likely to have greater OOP spending on ophthalmic medications. CONCLUSIONS: Total ophthalmic medication expenditure in the United States increased significantly over the last decade, whereas OOP expenses decreased. Increases in coverage, copayment assistance, and use of expensive brand drugs may be contributing to these trends. Policy makers and physicians should be aware that rising overall drug expenditures ultimately may increase indirect costs to the patient and offset a decline in OOP prescription drug spending.
Authors: Dana M Blumberg; Alisa J Prager; Jeffrey M Liebmann; George A Cioffi; C Gustavo De Moraes Journal: JAMA Ophthalmol Date: 2015-09 Impact factor: 7.389
Authors: Haider J Warraich; Joseph A Salami; Rohan Khera; Javier Valero-Elizondo; Victor Okunrintemi; Khurram Nasir Journal: JAMA Intern Med Date: 2018-05-01 Impact factor: 21.873
Authors: Dan Gong; Jonathan S Chang; Miriam Barbany; Borja F Corcostegui; Mehmet Fatih Kağan Değirmenci; Hiroto Ishikawa; Zaid Mammo; Emin Ozmert; Tommaso Rossi; Stanley Chang Journal: Ophthalmology Date: 2019-05-27 Impact factor: 12.079
Authors: Joseph A Salami; Haider Warraich; Javier Valero-Elizondo; Erica S Spatz; Nihar R Desai; Jamal S Rana; Salim S Virani; Ron Blankstein; Amit Khera; Michael J Blaha; Roger S Blumenthal; Donald Lloyd-Jones; Khurram Nasir Journal: JAMA Cardiol Date: 2017-01-01 Impact factor: 14.676
Authors: Wouter Schakel; Hilde P A van der Aa; Christina Bode; Carel T J Hulshof; Ger H M B van Rens; Ruth M A van Nispen Journal: Invest Ophthalmol Vis Sci Date: 2018-04-01 Impact factor: 4.799
Authors: Anna L Goldman; Steffie Woolhandler; David U Himmelstein; David H Bor; Danny McCormick Journal: JAMA Intern Med Date: 2018-03-01 Impact factor: 21.873
Authors: Brook I Martin; Richard A Deyo; Sohail K Mirza; Judith A Turner; Bryan A Comstock; William Hollingworth; Sean D Sullivan Journal: JAMA Date: 2008-02-13 Impact factor: 56.272
Authors: Paul McCann; Alison G Abraham; Darren G Gregory; Scott Hauswirth; Cristos Ifantides; Su-Hsun Liu; Ian J Saldanha; Tianjing Li Journal: BMJ Open Date: 2021-11-23 Impact factor: 2.692