Vision Care Utilization and Insurance Coverage Prior to and Following Medicaid Expansion in Ohio

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 (BR...

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Veröffentlicht in:Ohio journal of public health 2022-08, Vol.5 (1), p.54-63
Hauptverfasser: VanNasdale, Dean A., Robich, Matthew L., Jones-Jordan, Lisa A., Shelton, Erica R., Hurley, Megan S., Wapner, Andrew, Williams, Sherry, Monder, David, Molea, Marcus J., Crews, John E.
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container_end_page 63
container_issue 1
container_start_page 54
container_title Ohio journal of public health
container_volume 5
creator VanNasdale, Dean A.
Robich, Matthew L.
Jones-Jordan, Lisa A.
Shelton, Erica R.
Hurley, Megan S.
Wapner, Andrew
Williams, Sherry
Monder, David
Molea, Marcus J.
Crews, John E.
description 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
doi_str_mv 10.18061/ojph.v5i1.8685
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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 &lt;0.001). Insurance coverage for eye care increased between 2005-2011 and 2018-2019 (chi-square, p &lt;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.</description><identifier>ISSN: 2578-6180</identifier><identifier>EISSN: 2578-6180</identifier><identifier>DOI: 10.18061/ojph.v5i1.8685</identifier><language>eng</language><ispartof>Ohio journal of public health, 2022-08, Vol.5 (1), p.54-63</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,864,27924,27925</link.rule.ids></links><search><creatorcontrib>VanNasdale, Dean A.</creatorcontrib><creatorcontrib>Robich, Matthew L.</creatorcontrib><creatorcontrib>Jones-Jordan, Lisa A.</creatorcontrib><creatorcontrib>Shelton, Erica R.</creatorcontrib><creatorcontrib>Hurley, Megan S.</creatorcontrib><creatorcontrib>Wapner, Andrew</creatorcontrib><creatorcontrib>Williams, Sherry</creatorcontrib><creatorcontrib>Monder, David</creatorcontrib><creatorcontrib>Molea, Marcus J.</creatorcontrib><creatorcontrib>Crews, John E.</creatorcontrib><title>Vision Care Utilization and Insurance Coverage Prior to and Following Medicaid Expansion in Ohio</title><title>Ohio journal of public health</title><description>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 &lt;0.001). Insurance coverage for eye care increased between 2005-2011 and 2018-2019 (chi-square, p &lt;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. 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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 &lt;0.001). Insurance coverage for eye care increased between 2005-2011 and 2018-2019 (chi-square, p &lt;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.</abstract><doi>10.18061/ojph.v5i1.8685</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record>
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