The effect of a public transportation expansion on no‐show appointments
Objective To test whether there were fewer missed medical appointments (“no‐shows”) for patients and clinics affected by a significant public transportation expansion. Study setting A new light rail line was opened in a major metropolitan area in June 2014. We obtained electronic health records data...
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| Veröffentlicht in: | Health services research 2022-06, Vol.57 (3), p.472-481 |
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| creator | Smith, Laura Barrie Yang, Zhiyou Golberstein, Ezra Huckfeldt, Peter Mehrotra, Ateev Neprash, Hannah T. |
| description | Objective
To test whether there were fewer missed medical appointments (“no‐shows”) for patients and clinics affected by a significant public transportation expansion.
Study setting
A new light rail line was opened in a major metropolitan area in June 2014. We obtained electronic health records data from an integrated health delivery system in the area with over three million appointments at 97 clinics between 2013 and 2016.
Study design
We used a difference‐in‐differences research design to compare whether no‐show appointment rates differentially changed among patients and clinics located near versus far from the new light rail line after it opened. Models included fixed effects to account for underlying differences across clinics, patient zip codes, and time.
Data extraction methods
We obtained data from an electronic health records system representing all appointments scheduled at 97 outpatient clinics in this system. We excluded same‐day, urgent care, and canceled appointments.
Principal findings
The probability of no‐show visits differentially declined by 0.5 percentage points (95% confidence interval [CI]: −0.9 to −0.1), or 4.5% relative to baseline, for patients living near the new light rail compared to those living far from it, after the light rail opened. The effects were stronger among patients covered by Medicaid (−1.6 percentage points [95% CI: −2.4 to −0.8] or 9.5% relative to baseline).
Conclusions
Improvements to public transit may improve access to health care, especially for people with low incomes. |
| doi_str_mv | 10.1111/1475-6773.13899 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9108053</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A707524247</galeid><sourcerecordid>A707524247</sourcerecordid><originalsourceid>FETCH-LOGICAL-c7139-36b83a21d94bc9c3f45fe901b031172e6499798a0e928d00ca6da1b6c6a7618d3</originalsourceid><addsrcrecordid>eNqFktGK1DAUhoso7rp67Z0UBFGws0mTJs2NsAzr7sLAgq7XIU1P2yydpDatu3vnI_iMPompMw5TGTQNbZN8589Jzh9FLzFa4NBOMeVZwjgnC0xyIR5Fx7uZx9ExQpgnAqf0KHrm_S1CKCc5fRodEcpTQgQ9jq5uGoihqkAPsatiFXdj0RodD72yvnP9oAbjbAz3XRhPf6Fb9_P7D9-4u1h1nTN2WIMd_PPoSaVaDy-235Poy8fzm-Vlsrq-uFqerRLNMREJYUVOVIpLQQstNKloVoFAuEAEY54Co0JwkSsEIs1LhLRipcIF00xxhvOSnEQfNroh0zWUOuzdq1Z2vVmr_kE6ZeR8xZpG1u6bFBjlKCNB4O1WoHdfR_CDXBuvoW2VBTd6mWbhynCeIRbQ13-ht27sbTieTBmjjAi2T9WqBWls5cK-ehKVZxzxLKUp5YFKDlA1WAhJOguVCdMzfnGAD08Ja6MPBrybBQRmgPuhVqP3Mr9Y_SuZLatd20INMhRseT3n3-zxDah2aLxrx8kcfg6-3wOL0RsLPry8qZvBb3KZ4acbXPfO-x6qXR0xkpPD5eRnOflZ_nZ4iHi1X_4d_8fSAWAb4C7cz8P_9OTl-edPG-VfZXUBkQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2664639606</pqid></control><display><type>article</type><title>The effect of a public transportation expansion on no‐show appointments</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Sociological Abstracts</source><source>Applied Social Sciences Index & Abstracts (ASSIA)</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><creator>Smith, Laura Barrie ; Yang, Zhiyou ; Golberstein, Ezra ; Huckfeldt, Peter ; Mehrotra, Ateev ; Neprash, Hannah T.</creator><creatorcontrib>Smith, Laura Barrie ; Yang, Zhiyou ; Golberstein, Ezra ; Huckfeldt, Peter ; Mehrotra, Ateev ; Neprash, Hannah T.</creatorcontrib><description>Objective
To test whether there were fewer missed medical appointments (“no‐shows”) for patients and clinics affected by a significant public transportation expansion.
Study setting
A new light rail line was opened in a major metropolitan area in June 2014. We obtained electronic health records data from an integrated health delivery system in the area with over three million appointments at 97 clinics between 2013 and 2016.
Study design
We used a difference‐in‐differences research design to compare whether no‐show appointment rates differentially changed among patients and clinics located near versus far from the new light rail line after it opened. Models included fixed effects to account for underlying differences across clinics, patient zip codes, and time.
Data extraction methods
We obtained data from an electronic health records system representing all appointments scheduled at 97 outpatient clinics in this system. We excluded same‐day, urgent care, and canceled appointments.
Principal findings
The probability of no‐show visits differentially declined by 0.5 percentage points (95% confidence interval [CI]: −0.9 to −0.1), or 4.5% relative to baseline, for patients living near the new light rail compared to those living far from it, after the light rail opened. The effects were stronger among patients covered by Medicaid (−1.6 percentage points [95% CI: −2.4 to −0.8] or 9.5% relative to baseline).
Conclusions
Improvements to public transit may improve access to health care, especially for people with low incomes.</description><identifier>ISSN: 0017-9124</identifier><identifier>EISSN: 1475-6773</identifier><identifier>DOI: 10.1111/1475-6773.13899</identifier><identifier>PMID: 34723394</identifier><language>eng</language><publisher>Oxford, UK: Blackwell Publishing Ltd</publisher><subject>access ; Ambulatory Care ; Appointments and Schedules ; Archives & records ; Company business management ; Computerized medical records ; Confidence intervals ; demand ; determinants of health ; Electronic health records ; Electronic medical records ; Extraction ; Forecasts and trends ; Government programs ; Health care ; Health care access ; health care organizations and systems ; Health records ; Health services ; Humans ; Influence ; Light rail transportation ; Management ; Market trend/market analysis ; Medicaid ; Medical appointments and schedules ; Medical records ; Medical scheduling ; Medicine ; Metropolitan areas ; Outpatient clinics ; Patients ; population health ; Public transportation ; Research design ; Social Factors, Racism and Health ; Social services delivery ; socioeconomic causes of health ; Statistical analysis ; Transportation planning ; United States ; Urban rail ; utilization of services</subject><ispartof>Health services research, 2022-06, Vol.57 (3), p.472-481</ispartof><rights>2021 Health Research and Educational Trust</rights><rights>2021 Health Research and Educational Trust.</rights><rights>COPYRIGHT 2022 Health Research and Educational Trust</rights><rights>2022 Health Research and Educational Trust</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c7139-36b83a21d94bc9c3f45fe901b031172e6499798a0e928d00ca6da1b6c6a7618d3</citedby><cites>FETCH-LOGICAL-c7139-36b83a21d94bc9c3f45fe901b031172e6499798a0e928d00ca6da1b6c6a7618d3</cites><orcidid>0000-0003-1593-4167 ; 0000-0003-2223-1582 ; 0000-0002-2693-1802</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9108053/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9108053/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,1411,27903,27904,30978,33753,45553,45554,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34723394$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Smith, Laura Barrie</creatorcontrib><creatorcontrib>Yang, Zhiyou</creatorcontrib><creatorcontrib>Golberstein, Ezra</creatorcontrib><creatorcontrib>Huckfeldt, Peter</creatorcontrib><creatorcontrib>Mehrotra, Ateev</creatorcontrib><creatorcontrib>Neprash, Hannah T.</creatorcontrib><title>The effect of a public transportation expansion on no‐show appointments</title><title>Health services research</title><addtitle>Health Serv Res</addtitle><description>Objective
To test whether there were fewer missed medical appointments (“no‐shows”) for patients and clinics affected by a significant public transportation expansion.
Study setting
A new light rail line was opened in a major metropolitan area in June 2014. We obtained electronic health records data from an integrated health delivery system in the area with over three million appointments at 97 clinics between 2013 and 2016.
Study design
We used a difference‐in‐differences research design to compare whether no‐show appointment rates differentially changed among patients and clinics located near versus far from the new light rail line after it opened. Models included fixed effects to account for underlying differences across clinics, patient zip codes, and time.
Data extraction methods
We obtained data from an electronic health records system representing all appointments scheduled at 97 outpatient clinics in this system. We excluded same‐day, urgent care, and canceled appointments.
Principal findings
The probability of no‐show visits differentially declined by 0.5 percentage points (95% confidence interval [CI]: −0.9 to −0.1), or 4.5% relative to baseline, for patients living near the new light rail compared to those living far from it, after the light rail opened. The effects were stronger among patients covered by Medicaid (−1.6 percentage points [95% CI: −2.4 to −0.8] or 9.5% relative to baseline).
Conclusions
Improvements to public transit may improve access to health care, especially for people with low incomes.</description><subject>access</subject><subject>Ambulatory Care</subject><subject>Appointments and Schedules</subject><subject>Archives & records</subject><subject>Company business management</subject><subject>Computerized medical records</subject><subject>Confidence intervals</subject><subject>demand</subject><subject>determinants of health</subject><subject>Electronic health records</subject><subject>Electronic medical records</subject><subject>Extraction</subject><subject>Forecasts and trends</subject><subject>Government programs</subject><subject>Health care</subject><subject>Health care access</subject><subject>health care organizations and systems</subject><subject>Health records</subject><subject>Health services</subject><subject>Humans</subject><subject>Influence</subject><subject>Light rail transportation</subject><subject>Management</subject><subject>Market trend/market analysis</subject><subject>Medicaid</subject><subject>Medical appointments and schedules</subject><subject>Medical records</subject><subject>Medical scheduling</subject><subject>Medicine</subject><subject>Metropolitan areas</subject><subject>Outpatient clinics</subject><subject>Patients</subject><subject>population health</subject><subject>Public transportation</subject><subject>Research design</subject><subject>Social Factors, Racism and Health</subject><subject>Social services delivery</subject><subject>socioeconomic causes of health</subject><subject>Statistical analysis</subject><subject>Transportation planning</subject><subject>United States</subject><subject>Urban rail</subject><subject>utilization of services</subject><issn>0017-9124</issn><issn>1475-6773</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>N95</sourceid><sourceid>7QJ</sourceid><sourceid>BHHNA</sourceid><recordid>eNqFktGK1DAUhoso7rp67Z0UBFGws0mTJs2NsAzr7sLAgq7XIU1P2yydpDatu3vnI_iMPompMw5TGTQNbZN8589Jzh9FLzFa4NBOMeVZwjgnC0xyIR5Fx7uZx9ExQpgnAqf0KHrm_S1CKCc5fRodEcpTQgQ9jq5uGoihqkAPsatiFXdj0RodD72yvnP9oAbjbAz3XRhPf6Fb9_P7D9-4u1h1nTN2WIMd_PPoSaVaDy-235Poy8fzm-Vlsrq-uFqerRLNMREJYUVOVIpLQQstNKloVoFAuEAEY54Co0JwkSsEIs1LhLRipcIF00xxhvOSnEQfNroh0zWUOuzdq1Z2vVmr_kE6ZeR8xZpG1u6bFBjlKCNB4O1WoHdfR_CDXBuvoW2VBTd6mWbhynCeIRbQ13-ht27sbTieTBmjjAi2T9WqBWls5cK-ehKVZxzxLKUp5YFKDlA1WAhJOguVCdMzfnGAD08Ja6MPBrybBQRmgPuhVqP3Mr9Y_SuZLatd20INMhRseT3n3-zxDah2aLxrx8kcfg6-3wOL0RsLPry8qZvBb3KZ4acbXPfO-x6qXR0xkpPD5eRnOflZ_nZ4iHi1X_4d_8fSAWAb4C7cz8P_9OTl-edPG-VfZXUBkQ</recordid><startdate>202206</startdate><enddate>202206</enddate><creator>Smith, Laura Barrie</creator><creator>Yang, Zhiyou</creator><creator>Golberstein, Ezra</creator><creator>Huckfeldt, Peter</creator><creator>Mehrotra, Ateev</creator><creator>Neprash, Hannah T.</creator><general>Blackwell Publishing Ltd</general><general>Health Research and Educational Trust</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>N95</scope><scope>XI7</scope><scope>8GL</scope><scope>7QJ</scope><scope>7U3</scope><scope>BHHNA</scope><scope>K9.</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-1593-4167</orcidid><orcidid>https://orcid.org/0000-0003-2223-1582</orcidid><orcidid>https://orcid.org/0000-0002-2693-1802</orcidid></search><sort><creationdate>202206</creationdate><title>The effect of a public transportation expansion on no‐show appointments</title><author>Smith, Laura Barrie ; Yang, Zhiyou ; Golberstein, Ezra ; Huckfeldt, Peter ; Mehrotra, Ateev ; Neprash, Hannah T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c7139-36b83a21d94bc9c3f45fe901b031172e6499798a0e928d00ca6da1b6c6a7618d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>access</topic><topic>Ambulatory Care</topic><topic>Appointments and Schedules</topic><topic>Archives & records</topic><topic>Company business management</topic><topic>Computerized medical records</topic><topic>Confidence intervals</topic><topic>demand</topic><topic>determinants of health</topic><topic>Electronic health records</topic><topic>Electronic medical records</topic><topic>Extraction</topic><topic>Forecasts and trends</topic><topic>Government programs</topic><topic>Health care</topic><topic>Health care access</topic><topic>health care organizations and systems</topic><topic>Health records</topic><topic>Health services</topic><topic>Humans</topic><topic>Influence</topic><topic>Light rail transportation</topic><topic>Management</topic><topic>Market trend/market analysis</topic><topic>Medicaid</topic><topic>Medical appointments and schedules</topic><topic>Medical records</topic><topic>Medical scheduling</topic><topic>Medicine</topic><topic>Metropolitan areas</topic><topic>Outpatient clinics</topic><topic>Patients</topic><topic>population health</topic><topic>Public transportation</topic><topic>Research design</topic><topic>Social Factors, Racism and Health</topic><topic>Social services delivery</topic><topic>socioeconomic causes of health</topic><topic>Statistical analysis</topic><topic>Transportation planning</topic><topic>United States</topic><topic>Urban rail</topic><topic>utilization of services</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Smith, Laura Barrie</creatorcontrib><creatorcontrib>Yang, Zhiyou</creatorcontrib><creatorcontrib>Golberstein, Ezra</creatorcontrib><creatorcontrib>Huckfeldt, Peter</creatorcontrib><creatorcontrib>Mehrotra, Ateev</creatorcontrib><creatorcontrib>Neprash, Hannah T.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale Business: Insights</collection><collection>Business Insights: Essentials</collection><collection>Gale In Context: High School</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>Social Services Abstracts</collection><collection>Sociological Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Health services research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Smith, Laura Barrie</au><au>Yang, Zhiyou</au><au>Golberstein, Ezra</au><au>Huckfeldt, Peter</au><au>Mehrotra, Ateev</au><au>Neprash, Hannah T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The effect of a public transportation expansion on no‐show appointments</atitle><jtitle>Health services research</jtitle><addtitle>Health Serv Res</addtitle><date>2022-06</date><risdate>2022</risdate><volume>57</volume><issue>3</issue><spage>472</spage><epage>481</epage><pages>472-481</pages><issn>0017-9124</issn><eissn>1475-6773</eissn><abstract>Objective
To test whether there were fewer missed medical appointments (“no‐shows”) for patients and clinics affected by a significant public transportation expansion.
Study setting
A new light rail line was opened in a major metropolitan area in June 2014. We obtained electronic health records data from an integrated health delivery system in the area with over three million appointments at 97 clinics between 2013 and 2016.
Study design
We used a difference‐in‐differences research design to compare whether no‐show appointment rates differentially changed among patients and clinics located near versus far from the new light rail line after it opened. Models included fixed effects to account for underlying differences across clinics, patient zip codes, and time.
Data extraction methods
We obtained data from an electronic health records system representing all appointments scheduled at 97 outpatient clinics in this system. We excluded same‐day, urgent care, and canceled appointments.
Principal findings
The probability of no‐show visits differentially declined by 0.5 percentage points (95% confidence interval [CI]: −0.9 to −0.1), or 4.5% relative to baseline, for patients living near the new light rail compared to those living far from it, after the light rail opened. The effects were stronger among patients covered by Medicaid (−1.6 percentage points [95% CI: −2.4 to −0.8] or 9.5% relative to baseline).
Conclusions
Improvements to public transit may improve access to health care, especially for people with low incomes.</abstract><cop>Oxford, UK</cop><pub>Blackwell Publishing Ltd</pub><pmid>34723394</pmid><doi>10.1111/1475-6773.13899</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-1593-4167</orcidid><orcidid>https://orcid.org/0000-0003-2223-1582</orcidid><orcidid>https://orcid.org/0000-0002-2693-1802</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0017-9124 |
| ispartof | Health services research, 2022-06, Vol.57 (3), p.472-481 |
| issn | 0017-9124 1475-6773 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9108053 |
| source | MEDLINE; Wiley Online Library Journals Frontfile Complete; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Sociological Abstracts; Applied Social Sciences Index & Abstracts (ASSIA); PubMed Central; Alma/SFX Local Collection |
| subjects | access Ambulatory Care Appointments and Schedules Archives & records Company business management Computerized medical records Confidence intervals demand determinants of health Electronic health records Electronic medical records Extraction Forecasts and trends Government programs Health care Health care access health care organizations and systems Health records Health services Humans Influence Light rail transportation Management Market trend/market analysis Medicaid Medical appointments and schedules Medical records Medical scheduling Medicine Metropolitan areas Outpatient clinics Patients population health Public transportation Research design Social Factors, Racism and Health Social services delivery socioeconomic causes of health Statistical analysis Transportation planning United States Urban rail utilization of services |
| title | The effect of a public transportation expansion on no‐show appointments |
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