{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/86393"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/86393","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Access to Healthcare in a Free Clinic Population: What Are the Barriers","abstract":"Objectives. This exploratory study examined the barriers to health care and the levels of access to health care that were achieved by a convenience sample of people who were seeking health care at a free clinic in Champaign, Illinois during the summer of 2006. Methods. Survey of a convenience sample of 131 people which contained a new set of measures for Achieved Access to Health Care that utilized a Likert scale, 40 barrier questions that were aggregated into 10 barrier variables, the Quality Metric 12-v2 survey instrument for measuring health status, and demographic questions. An ordinal regression model used barriers, health status, and demographics to predict achieved access to health care. Follow-up interviews of 24 patients who were referred for chronic or specialty care provided additional qualitative data. Results. 6% achieved access to all needed care in the past year, while 30 to 50% got none of the care they needed depending on type of care. Three barrier types had statistically significant effects, and number of barriers had a large effect in the regression model. Better health status had a negative effect on achieving access to care in the regression model. Conclusions. Finances was a severe and prevalent barrier that nearly everyone experienced and there was no variance with which to measure the effect on access in the regression model. Transportation, Knowledge, and Bad Experiences were less prevalent barriers that had large and significantly negative effects on ability to achieve access to needed healthcare. Medical Debt was a major barrier to accessing needed healthcare and, compared to a survey of the same population from five years earlier, had become more severe and more prevalent for this population. Some people who manage to gain access to safety net services in the area fare well and are able to get the care they need, but many more are left to do without.","abstract_html":"Objectives. This exploratory study examined the barriers to health care and the levels of access to health care that were achieved by a convenience sample of people who were seeking health care at a free clinic in Champaign, Illinois during the summer of 2006. Methods. Survey of a convenience sample of 131 people which contained a new set of measures for Achieved Access to Health Care that utilized a Likert scale, 40 barrier questions that were aggregated into 10 barrier variables, the Quality Metric 12-v2 survey instrument for measuring health status, and demographic questions. An ordinal regression model used barriers, health status, and demographics to predict achieved access to health care. Follow-up interviews of 24 patients who were referred for chronic or specialty care provided additional qualitative data. Results. 6% achieved access to all needed care in the past year, while 30 to 50% got none of the care they needed depending on type of care. Three barrier types had statistically significant effects, and number of barriers had a large effect in the regression model. Better health status had a negative effect on achieving access to care in the regression model. Conclusions. Finances was a severe and prevalent barrier that nearly everyone experienced and there was no variance with which to measure the effect on access in the regression model. Transportation, Knowledge, and Bad Experiences were less prevalent barriers that had large and significantly negative effects on ability to achieve access to needed healthcare. Medical Debt was a major barrier to accessing needed healthcare and, compared to a survey of the same population from five years earlier, had become more severe and more prevalent for this population. Some people who manage to gain access to safety net services in the area fare well and are able to get the care they need, but many more are left to do without.","abstract_has_math":false,"creators":["Elkins, Cinthia Lisa"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Kinesiology and Community Health","degree_department":null,"school":null,"contributors":["Rich, Robert F."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-28T15:04:27Z","date_published":"2015-09-28T15:04:27Z","updated_at":"2026-07-22T22:26:27Z","subjects":["Sociology, Public and Social Welfare"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3314763"],"render_values":[{"text":"(MiAaPQ)AAI3314763","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/86393","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Rich, Robert F."]},{"key":"dc:creator","label":"Author","values":["Elkins, Cinthia Lisa"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-28T15:04:27Z","10000-01-01","2008"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Kinesiology and Community Health"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Sociology, Public and Social Welfare"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/86393","(MiAaPQ)AAI3314763"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Objectives. This exploratory study examined the barriers to health care and the levels of access to health care that were achieved by a convenience sample of people who were seeking health care at a free clinic in Champaign, Illinois during the summer of 2006. Methods. Survey of a convenience sample of 131 people which contained a new set of measures for Achieved Access to Health Care that utilized a Likert scale, 40 barrier questions that were aggregated into 10 barrier variables, the Quality Metric 12-v2 survey instrument for measuring health status, and demographic questions. An ordinal regression model used barriers, health status, and demographics to predict achieved access to health care. Follow-up interviews of 24 patients who were referred for chronic or specialty care provided additional qualitative data. Results. 6% achieved access to all needed care in the past year, while 30 to 50% got none of the care they needed depending on type of care. Three barrier types had statistically significant effects, and number of barriers had a large effect in the regression model. Better health status had a negative effect on achieving access to care in the regression model. Conclusions. Finances was a severe and prevalent barrier that nearly everyone experienced and there was no variance with which to measure the effect on access in the regression model. Transportation, Knowledge, and Bad Experiences were less prevalent barriers that had large and significantly negative effects on ability to achieve access to needed healthcare. Medical Debt was a major barrier to accessing needed healthcare and, compared to a survey of the same population from five years earlier, had become more severe and more prevalent for this population. Some people who manage to gain access to safety net services in the area fare well and are able to get the care they need, but many more are left to do without.","Made available in DSpace on 2015-09-28T15:04:27Z (GMT). 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This exploratory study examined the barriers to health care and the levels of access to health care that were achieved by a convenience sample of people who were seeking health care at a free clinic in Champaign, Illinois during the summer of 2006. Methods. Survey of a convenience sample of 131 people which contained a new set of measures for Achieved Access to Health Care that utilized a Likert scale, 40 barrier questions that were aggregated into 10 barrier variables, the Quality Metric 12-v2 survey instrument for measuring health status, and demographic questions. An ordinal regression model used barriers, health status, and demographics to predict achieved access to health care. Follow-up interviews of 24 patients who were referred for chronic or specialty care provided additional qualitative data. Results. 6% achieved access to all needed care in the past year, while 30 to 50% got none of the care they needed depending on type of care. Three barrier types had statistically significant effects, and number of barriers had a large effect in the regression model. Better health status had a negative effect on achieving access to care in the regression model. Conclusions. Finances was a severe and prevalent barrier that nearly everyone experienced and there was no variance with which to measure the effect on access in the regression model. Transportation, Knowledge, and Bad Experiences were less prevalent barriers that had large and significantly negative effects on ability to achieve access to needed healthcare. Medical Debt was a major barrier to accessing needed healthcare and, compared to a survey of the same population from five years earlier, had become more severe and more prevalent for this population. Some people who manage to gain access to safety net services in the area fare well and are able to get the care they need, but many more are left to do without.","Made available in DSpace on 2015-09-28T15:04:27Z (GMT). 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