D. VanNasdale, Matthew L. Robich, Lisa A. Jones-Jordan, Erica R. Shelton, Megan S. Hurley, Andrew Wapner, S. Williams, David Monder, Marc Molea, J. Crews
{"title":"Vision Care Utilization and Insurance Coverage Prior to and Following Medicaid Expansion in Ohio","authors":"D. VanNasdale, Matthew L. Robich, Lisa A. Jones-Jordan, Erica R. Shelton, Megan S. Hurley, Andrew Wapner, S. Williams, David Monder, Marc Molea, J. Crews","doi":"10.18061/ojph.v5i1.8685","DOIUrl":null,"url":null,"abstract":"Background: Increased access and utilization of vision care services has the potential to reduce preventable vision loss. The state of Ohio has been uniquely proactive when collecting vision-oriented data through population health surveys, including the Behavioral Risk Factor Surveillance System (BRFSS). These data can be used to better understand vision care utilization patterns and access to insurance.\nMethods: Responses to 3 items administered in the Ohio BRFSS that assess vision care utilization and insurance coverage were compared between 2 different administration periods, 2005-2011 and 2018-2019, using chi-square tests. Comparable data from 2 items assessing eye care utilization were available in 2005-2011 and 2019. Comparable data for insurance coverage were available in 2005-2011 and in 2018-2019. Responses were further stratified by population characteristics, including age, gender, household income, and education level.\nResults: The percentages of those reporting eye exams in the previous year were not significantly different between 2005-2011 and 2019 (chi-square, p = 0.06). In Ohio, the primary reason for not seeing a vision care provider in the past 12 months was “No reason to go” in 2005-2011 and in 2019. The second most common reason for not seeing a vision care provider in the past 12 months was “Cost/insurance,” which decreased between 2005-2011 and 2019 (chi-square, p <0.001). Insurance coverage for eye care increased between 2005-2011 and 2018-2019 (chi-square, p <0.001). Important differences were found within the demographic stratification.\nConclusion: Population health surveillance data provide useful insight into vision care utilization and insurance coverage. Despite the increase in insurance coverage, eye care provider utilization remains relatively stable.","PeriodicalId":74337,"journal":{"name":"Ohio journal of public health","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ohio journal of public health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18061/ojph.v5i1.8685","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Increased access and utilization of vision care services has the potential to reduce preventable vision loss. The state of Ohio has been uniquely proactive when collecting vision-oriented data through population health surveys, including the Behavioral Risk Factor Surveillance System (BRFSS). These data can be used to better understand vision care utilization patterns and access to insurance.
Methods: Responses to 3 items administered in the Ohio BRFSS that assess vision care utilization and insurance coverage were compared between 2 different administration periods, 2005-2011 and 2018-2019, using chi-square tests. Comparable data from 2 items assessing eye care utilization were available in 2005-2011 and 2019. Comparable data for insurance coverage were available in 2005-2011 and in 2018-2019. Responses were further stratified by population characteristics, including age, gender, household income, and education level.
Results: The percentages of those reporting eye exams in the previous year were not significantly different between 2005-2011 and 2019 (chi-square, p = 0.06). In Ohio, the primary reason for not seeing a vision care provider in the past 12 months was “No reason to go” in 2005-2011 and in 2019. The second most common reason for not seeing a vision care provider in the past 12 months was “Cost/insurance,” which decreased between 2005-2011 and 2019 (chi-square, p <0.001). Insurance coverage for eye care increased between 2005-2011 and 2018-2019 (chi-square, p <0.001). Important differences were found within the demographic stratification.
Conclusion: Population health surveillance data provide useful insight into vision care utilization and insurance coverage. Despite the increase in insurance coverage, eye care provider utilization remains relatively stable.
背景:增加视力保健服务的获取和利用有可能减少可预防的视力丧失。俄亥俄州在通过包括行为风险因素监测系统(BRFSS)在内的人口健康调查收集以视力为导向的数据方面具有独特的前瞻性。这些数据可以用来更好地了解视力保健的使用模式和获得保险。方法:采用卡方检验,比较2005-2011年和2018-2019年两个不同给药期对俄亥俄州BRFSS中评估视力保健利用和保险覆盖率的3个项目的反应。2005-2011年和2019年有两个评估眼科保健利用情况的项目的可比数据。2005-2011年和2018-2019年的保险覆盖率可比较数据。根据人口特征(包括年龄、性别、家庭收入和教育水平)进一步分层。结果:2005-2011年与2019年报告前一年眼科检查的比例差异无统计学意义(χ 2, p = 0.06)。在俄亥俄州,2005-2011年和2019年,过去12个月没有去看视力保健提供者的主要原因是“没有理由去”。在过去的12个月里,不去看视力保健提供者的第二个最常见的原因是“成本/保险”,在2005-2011年和2019年之间下降了(卡方,p <0.001)。2005-2011年和2018-2019年期间,眼科保健的保险覆盖率有所增加(χ 2, p <0.001)。在人口分层中发现了重要的差异。结论:人口健康监测数据为视力保健利用和保险覆盖率提供了有用的信息。尽管保险覆盖范围有所增加,眼科医生的使用率仍然相对稳定。