The differences in health care utilization between Medical Aid and health insurance: a longitudinal study using propensity score matching
Health care utilization has progressively increased, especially among Medical Aid beneficiaries in South Korea. The Medical Aid classifies beneficiaries into two categories, type 1 and 2, on the basis of being incapable (those under 18 or over 65 years of age, or disabled) or capable of working, res...
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| description | Health care utilization has progressively increased, especially among Medical Aid beneficiaries in South Korea. The Medical Aid classifies beneficiaries into two categories, type 1 and 2, on the basis of being incapable (those under 18 or over 65 years of age, or disabled) or capable of working, respectively. Medical Aid has a high possibility for health care utilization due to high coverage level. In South Korea, the national health insurance (NHI) achieved very short time to establish coverage for the entire Korean population. However there there remaine a number of problems to be solved. Therefore, the objective of this study was to investigate the differences in health care utilization between Medical Aid beneficiaries and Health Insurance beneficiaries.
Data were collected from the Korean Welfare Panel Study from 2008 to 2012 using propensity score matching. Of the 2,316 research subjects, 579 had Medical Aid and 1,737 had health insurance. We also analyzed three dependent variables: days spent in the hospital, number of outpatient visits, and hospitalizations per year. Analysis of variance and longitudinal data analysis were used.
The number of outpatient visits was 1.431 times higher (p |
| doi_str_mv | 10.1371/journal.pone.0119939 |
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Data were collected from the Korean Welfare Panel Study from 2008 to 2012 using propensity score matching. Of the 2,316 research subjects, 579 had Medical Aid and 1,737 had health insurance. We also analyzed three dependent variables: days spent in the hospital, number of outpatient visits, and hospitalizations per year. Analysis of variance and longitudinal data analysis were used.
The number of outpatient visits was 1.431 times higher (p<0.0001) in Medical Aid beneficiaries, the number of hospitalizations per year was 1.604 times higher (p<0.0001) in Medical Aid beneficiaries, and the number of days spent in the hospital per year was 1.282 times higher (p<0.268) for Medical Aid beneficiaries than in individuals with Health Insurance. Medical Aid patients had a 0.874 times lower frequency of having an unmet needs due to economic barrier (95% confidence interval: 0.662-1.156).
Health insurance coverage has an impact on health care utilization. More health care utilization among Medical Aid beneficiaries appears to have a high possibility of a moral hazard risk under the Health Insurance program. Therefore, the moral hazard for Medical Aid beneficiaries should be avoided.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0119939</identifier><identifier>PMID: 25816234</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Ambulatory Care - statistics & numerical data ; Analysis ; Chronic illnesses ; Confidence intervals ; Correlation analysis ; Data analysis ; Data processing ; Dependent variables ; Diabetes ; Expenditures ; Female ; Health care ; Health care policy ; Health risks ; Health services utilization ; Households ; Humans ; Insurance ; Insurance, Health - statistics & numerical data ; Length of Stay - statistics & numerical data ; Longitudinal Studies ; Male ; Marital status ; Matching ; Medical aid ; Medical care utilization ; Medical research ; Middle Aged ; National health insurance ; Occupational health ; Patient Acceptance of Health Care - statistics & numerical data ; Preventive medicine ; Propensity Score ; Studies ; Utilization ; Variance analysis ; Welfare ; Young Adult</subject><ispartof>PloS one, 2015-03, Vol.10 (3), p.e0119939-e0119939</ispartof><rights>COPYRIGHT 2015 Public Library of Science</rights><rights>2015 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Kim et al 2015 Kim et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c758t-23e4a7411095723c615b8b53aaedeaf2ae5f095dbf733f98c3fa8705456030393</citedby><cites>FETCH-LOGICAL-c758t-23e4a7411095723c615b8b53aaedeaf2ae5f095dbf733f98c3fa8705456030393</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4376904/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4376904/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,728,781,785,865,886,2103,2929,23871,27929,27930,53796,53798</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25816234$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Caylà, Joan A</contributor><creatorcontrib>Kim, Jae-Hyun</creatorcontrib><creatorcontrib>Lee, Kwang-Soo</creatorcontrib><creatorcontrib>Yoo, Ki-Bong</creatorcontrib><creatorcontrib>Park, Eun-Cheol</creatorcontrib><title>The differences in health care utilization between Medical Aid and health insurance: a longitudinal study using propensity score matching</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Health care utilization has progressively increased, especially among Medical Aid beneficiaries in South Korea. The Medical Aid classifies beneficiaries into two categories, type 1 and 2, on the basis of being incapable (those under 18 or over 65 years of age, or disabled) or capable of working, respectively. Medical Aid has a high possibility for health care utilization due to high coverage level. In South Korea, the national health insurance (NHI) achieved very short time to establish coverage for the entire Korean population. However there there remaine a number of problems to be solved. Therefore, the objective of this study was to investigate the differences in health care utilization between Medical Aid beneficiaries and Health Insurance beneficiaries.
Data were collected from the Korean Welfare Panel Study from 2008 to 2012 using propensity score matching. Of the 2,316 research subjects, 579 had Medical Aid and 1,737 had health insurance. We also analyzed three dependent variables: days spent in the hospital, number of outpatient visits, and hospitalizations per year. Analysis of variance and longitudinal data analysis were used.
The number of outpatient visits was 1.431 times higher (p<0.0001) in Medical Aid beneficiaries, the number of hospitalizations per year was 1.604 times higher (p<0.0001) in Medical Aid beneficiaries, and the number of days spent in the hospital per year was 1.282 times higher (p<0.268) for Medical Aid beneficiaries than in individuals with Health Insurance. Medical Aid patients had a 0.874 times lower frequency of having an unmet needs due to economic barrier (95% confidence interval: 0.662-1.156).
Health insurance coverage has an impact on health care utilization. More health care utilization among Medical Aid beneficiaries appears to have a high possibility of a moral hazard risk under the Health Insurance program. Therefore, the moral hazard for Medical Aid beneficiaries should be avoided.</description><subject>Adult</subject><subject>Ambulatory Care - statistics & numerical data</subject><subject>Analysis</subject><subject>Chronic illnesses</subject><subject>Confidence intervals</subject><subject>Correlation analysis</subject><subject>Data analysis</subject><subject>Data processing</subject><subject>Dependent variables</subject><subject>Diabetes</subject><subject>Expenditures</subject><subject>Female</subject><subject>Health care</subject><subject>Health care policy</subject><subject>Health risks</subject><subject>Health services utilization</subject><subject>Households</subject><subject>Humans</subject><subject>Insurance</subject><subject>Insurance, Health - statistics & numerical data</subject><subject>Length of Stay - statistics & numerical data</subject><subject>Longitudinal Studies</subject><subject>Male</subject><subject>Marital status</subject><subject>Matching</subject><subject>Medical aid</subject><subject>Medical care utilization</subject><subject>Medical research</subject><subject>Middle Aged</subject><subject>National health insurance</subject><subject>Occupational health</subject><subject>Patient Acceptance of Health Care - statistics & numerical data</subject><subject>Preventive medicine</subject><subject>Propensity Score</subject><subject>Studies</subject><subject>Utilization</subject><subject>Variance analysis</subject><subject>Welfare</subject><subject>Young Adult</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk9-LEzEQxxdRvPP0PxANCKIPrckm-8sHoRz-KJwc6OlrmM1O2pRtUpOsev4H_temdnu0cg-Sh4TMZ76Tmcxk2WNGp4xX7NXKDd5CP904i1PKWNPw5k52yhqeT8qc8rsH55PsQQgrSgtel-X97CQvalbmXJxmv6-WSDqjNXq0CgMxliwR-rgkCjySIZre_IJonCUtxh-IlnzEzijoycx0BGy3540Ng4ck8poA6Z1dmDh0Jj2RhHS4JkMwdkE23m3QBhOvSVAuRVhDVMtkeZjd09AHfDTuZ9mXd2-vzj9MLi7fz89nFxNVFXWc5BwFVIIx2hRVzlXJirZuCw6AHYLOAQudTF2rK851Uyuuoa5oIYqScsobfpY93eluehfkWMUgWVlWrGhyUSViviM6Byu58WYN_lo6MPLvhfMLCT4a1aMUoq07nUJonouc1aBZRfOWF6ItOxQ8ab0Zow3tGjuFNnroj0SPLdYs5cJ9l4JXZUNFEngxCnj3bcAQ5doEhX0PFt2we3dTMlrnCX32D3p7diO1gJSAsdqluGorKmfbFFKX1GWiprdQaXW4Niq1nDbp_sjh5ZFDYiL-jAsYQpDzz5_-n738esw-P2B3rRZcP2w7MhyDYgcq70LwqG-KzKjcTsy-GnI7MXKcmOT25PCDbpz2I8L_AGVyEjA</recordid><startdate>20150327</startdate><enddate>20150327</enddate><creator>Kim, Jae-Hyun</creator><creator>Lee, Kwang-Soo</creator><creator>Yoo, Ki-Bong</creator><creator>Park, Eun-Cheol</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20150327</creationdate><title>The differences in health care utilization between Medical Aid and health insurance: a longitudinal study using propensity score matching</title><author>Kim, Jae-Hyun ; Lee, Kwang-Soo ; Yoo, Ki-Bong ; Park, Eun-Cheol</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c758t-23e4a7411095723c615b8b53aaedeaf2ae5f095dbf733f98c3fa8705456030393</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adult</topic><topic>Ambulatory Care - statistics & numerical data</topic><topic>Analysis</topic><topic>Chronic illnesses</topic><topic>Confidence intervals</topic><topic>Correlation analysis</topic><topic>Data analysis</topic><topic>Data processing</topic><topic>Dependent variables</topic><topic>Diabetes</topic><topic>Expenditures</topic><topic>Female</topic><topic>Health care</topic><topic>Health care policy</topic><topic>Health risks</topic><topic>Health services utilization</topic><topic>Households</topic><topic>Humans</topic><topic>Insurance</topic><topic>Insurance, Health - statistics & numerical data</topic><topic>Length of Stay - statistics & numerical data</topic><topic>Longitudinal Studies</topic><topic>Male</topic><topic>Marital status</topic><topic>Matching</topic><topic>Medical aid</topic><topic>Medical care utilization</topic><topic>Medical research</topic><topic>Middle Aged</topic><topic>National health insurance</topic><topic>Occupational health</topic><topic>Patient Acceptance of Health Care - statistics & numerical data</topic><topic>Preventive medicine</topic><topic>Propensity Score</topic><topic>Studies</topic><topic>Utilization</topic><topic>Variance analysis</topic><topic>Welfare</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Jae-Hyun</creatorcontrib><creatorcontrib>Lee, Kwang-Soo</creatorcontrib><creatorcontrib>Yoo, Ki-Bong</creatorcontrib><creatorcontrib>Park, Eun-Cheol</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Opposing Viewpoints In Context</collection><collection>Gale in Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Proquest Nursing & Allied Health Source</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health Medical collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Database (1962 - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Jae-Hyun</au><au>Lee, Kwang-Soo</au><au>Yoo, Ki-Bong</au><au>Park, Eun-Cheol</au><au>Caylà, Joan A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The differences in health care utilization between Medical Aid and health insurance: a longitudinal study using propensity score matching</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2015-03-27</date><risdate>2015</risdate><volume>10</volume><issue>3</issue><spage>e0119939</spage><epage>e0119939</epage><pages>e0119939-e0119939</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Health care utilization has progressively increased, especially among Medical Aid beneficiaries in South Korea. The Medical Aid classifies beneficiaries into two categories, type 1 and 2, on the basis of being incapable (those under 18 or over 65 years of age, or disabled) or capable of working, respectively. Medical Aid has a high possibility for health care utilization due to high coverage level. In South Korea, the national health insurance (NHI) achieved very short time to establish coverage for the entire Korean population. However there there remaine a number of problems to be solved. Therefore, the objective of this study was to investigate the differences in health care utilization between Medical Aid beneficiaries and Health Insurance beneficiaries.
Data were collected from the Korean Welfare Panel Study from 2008 to 2012 using propensity score matching. Of the 2,316 research subjects, 579 had Medical Aid and 1,737 had health insurance. We also analyzed three dependent variables: days spent in the hospital, number of outpatient visits, and hospitalizations per year. Analysis of variance and longitudinal data analysis were used.
The number of outpatient visits was 1.431 times higher (p<0.0001) in Medical Aid beneficiaries, the number of hospitalizations per year was 1.604 times higher (p<0.0001) in Medical Aid beneficiaries, and the number of days spent in the hospital per year was 1.282 times higher (p<0.268) for Medical Aid beneficiaries than in individuals with Health Insurance. Medical Aid patients had a 0.874 times lower frequency of having an unmet needs due to economic barrier (95% confidence interval: 0.662-1.156).
Health insurance coverage has an impact on health care utilization. More health care utilization among Medical Aid beneficiaries appears to have a high possibility of a moral hazard risk under the Health Insurance program. Therefore, the moral hazard for Medical Aid beneficiaries should be avoided.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>25816234</pmid><doi>10.1371/journal.pone.0119939</doi><oa>free_for_read</oa></addata></record> |
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| source | PubMed Central Free; MEDLINE; Directory of Open Access Journals; Public Library of Science; Free Full-Text Journals in Chemistry; EZB Electronic Journals Library |
| subjects | Adult Ambulatory Care - statistics & numerical data Analysis Chronic illnesses Confidence intervals Correlation analysis Data analysis Data processing Dependent variables Diabetes Expenditures Female Health care Health care policy Health risks Health services utilization Households Humans Insurance Insurance, Health - statistics & numerical data Length of Stay - statistics & numerical data Longitudinal Studies Male Marital status Matching Medical aid Medical care utilization Medical research Middle Aged National health insurance Occupational health Patient Acceptance of Health Care - statistics & numerical data Preventive medicine Propensity Score Studies Utilization Variance analysis Welfare Young Adult |
| title | The differences in health care utilization between Medical Aid and health insurance: a longitudinal study using propensity score matching |
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