Characteristics Associated with Patient-Centered Medical Home Capability in Health Centers: A Cross-Sectional Analysis
Background The patient-centered medical home (PCMH) model is being implemented in health centers (HCs) that provide comprehensive primary care to vulnerable populations. Objective To identify characteristics associated with HCs’ PCMH capability. Design Cross-sectional analysis of a national dataset...
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| Veröffentlicht in: | Journal of general internal medicine : JGIM 2016-09, Vol.31 (9), p.1041-1051 |
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| creator | Gao, Yue Nocon, Robert S. Gunter, Kathryn E. Sharma, Ravi Ngo-Metzger, Quyen Casalino, Lawrence P. Chin, Marshall H. |
| description | Background
The patient-centered medical home (PCMH) model is being implemented in health centers (HCs) that provide comprehensive primary care to vulnerable populations.
Objective
To identify characteristics associated with HCs’ PCMH capability.
Design
Cross-sectional analysis of a national dataset of Federally Qualified Health Centers (FQHCs) in 2009. Data for PCMH capability, HC, patient, neighborhood, and regional characteristics were combined from multiple sources.
Participants
A total of 706 (70 %) of 1014 FQHCs from the Health Resources and Services Administration Community Health Center Program, representing all 50 states and the District of Columbia.
Main Measures
PCMH capability was scored via the Commonwealth Fund National Survey of FQHCs through the Safety Net Medical Home Scale (0 [worst] to 100 [best]). HC, patient, neighborhood, and regional characteristics (all analyzed at the HC level) were measured from the Commonwealth survey, Uniform Data System, American Community Survey, American Medical Association physician data, and National Academy for State Health Policy data.
Key Results
Independent correlates of high PCMH capability included having an electronic health record (EHR) (11.7-point [95 % confidence interval, CI 10.2–13.3]), more types of financial performance incentives (0.7-point [95 % CI 0.2–1.1] higher total score per one additional type, maximum possible = 10), more types of hospital–HC affiliations (1.6-point [95 % CI 1.1–2.1] higher total score per one additional type, maximum possible = 6), and location in certain US census divisions. Among HCs with an EHR, location in a state with state-supported PCMH initiatives and PCMH payments was associated with high PCMH capability (2.8-point, 95 % CI 0.2–5.5). Other characteristics had small effect size based on the measure unit (e.g. 0.04-point [95 % CI 0-0.08] lower total score per one percentage point more minority patients), but the effects could be practically large at the extremes.
Conclusions
EHR adoption likely played a role in HCs’ improvement in PCMH capability. Factors that appear to hold promise for supporting PCMH capability include a greater number of types of financial performance incentives, more types of hospital–HC affiliations, and state-level support and payment for PCMH activities. |
| doi_str_mv | 10.1007/s11606-016-3729-8 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4978681</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1815697566</sourcerecordid><originalsourceid>FETCH-LOGICAL-c503t-8ddb393675a8559183a043636bd5de9e2e9d75da58ce42915557eefb9232cde33</originalsourceid><addsrcrecordid>eNqNkk2LFDEQhoMo7uzqD_AiDV72EjcfnS8PwtDojrCioJ5DOqnZydLTPSaZlfn3Zuh1dQXBSwVSz1upVL0IvaDkNSVEXWRKJZGYUIm5YgbrR2hBBROYtkY9RguidYu14u0JOs35hhDKGdNP0QlTjMpWkwW67TYuOV8gxVyiz80y58lHVyA0P2LZNJ9diTAW3NUAqd5-hBC9G5rVtIWmczvXxyGWQxPHZgVuqJIZzW-aZdOlKWf8BXyJ01hFyxoOOeZn6MnaDRme351n6Nv7d1-7Fb76dPmhW15hLwgvWIfQc8OlEk4LYajmjrRcctkHEcAAAxOUCE5oDy0zVAihANa9YZz5AJyfobdz3d2-30LwtbPkBrtLcevSwU4u2oeZMW7s9XRr6wC11LQWOL8rkKbve8jFbmP2MAxuhGmfLdVUSKOElP-DEi2F0qKir_5Cb6Z9qrPJlh23pLWgplJ0pvxxignW931TYo8GsLMBbDWAPRrA6qp5-eeH7xW_Nl4BNgO5psZrSL-f_nfVn9orvDw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2001388519</pqid></control><display><type>article</type><title>Characteristics Associated with Patient-Centered Medical Home Capability in Health Centers: A Cross-Sectional Analysis</title><source>MEDLINE</source><source>Springer Journals</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><source>EZB Electronic Journals Library</source><creator>Gao, Yue ; Nocon, Robert S. ; Gunter, Kathryn E. ; Sharma, Ravi ; Ngo-Metzger, Quyen ; Casalino, Lawrence P. ; Chin, Marshall H.</creator><creatorcontrib>Gao, Yue ; Nocon, Robert S. ; Gunter, Kathryn E. ; Sharma, Ravi ; Ngo-Metzger, Quyen ; Casalino, Lawrence P. ; Chin, Marshall H.</creatorcontrib><description>Background
The patient-centered medical home (PCMH) model is being implemented in health centers (HCs) that provide comprehensive primary care to vulnerable populations.
Objective
To identify characteristics associated with HCs’ PCMH capability.
Design
Cross-sectional analysis of a national dataset of Federally Qualified Health Centers (FQHCs) in 2009. Data for PCMH capability, HC, patient, neighborhood, and regional characteristics were combined from multiple sources.
Participants
A total of 706 (70 %) of 1014 FQHCs from the Health Resources and Services Administration Community Health Center Program, representing all 50 states and the District of Columbia.
Main Measures
PCMH capability was scored via the Commonwealth Fund National Survey of FQHCs through the Safety Net Medical Home Scale (0 [worst] to 100 [best]). HC, patient, neighborhood, and regional characteristics (all analyzed at the HC level) were measured from the Commonwealth survey, Uniform Data System, American Community Survey, American Medical Association physician data, and National Academy for State Health Policy data.
Key Results
Independent correlates of high PCMH capability included having an electronic health record (EHR) (11.7-point [95 % confidence interval, CI 10.2–13.3]), more types of financial performance incentives (0.7-point [95 % CI 0.2–1.1] higher total score per one additional type, maximum possible = 10), more types of hospital–HC affiliations (1.6-point [95 % CI 1.1–2.1] higher total score per one additional type, maximum possible = 6), and location in certain US census divisions. Among HCs with an EHR, location in a state with state-supported PCMH initiatives and PCMH payments was associated with high PCMH capability (2.8-point, 95 % CI 0.2–5.5). Other characteristics had small effect size based on the measure unit (e.g. 0.04-point [95 % CI 0-0.08] lower total score per one percentage point more minority patients), but the effects could be practically large at the extremes.
Conclusions
EHR adoption likely played a role in HCs’ improvement in PCMH capability. Factors that appear to hold promise for supporting PCMH capability include a greater number of types of financial performance incentives, more types of hospital–HC affiliations, and state-level support and payment for PCMH activities.</description><identifier>ISSN: 0884-8734</identifier><identifier>EISSN: 1525-1497</identifier><identifier>DOI: 10.1007/s11606-016-3729-8</identifier><identifier>PMID: 27216480</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Adult ; Communities ; Community Health Centers - standards ; Confidence intervals ; Cross-Sectional Studies ; Databases, Factual - standards ; Electronic health records ; Electronic medical records ; Female ; Health care ; Health facilities ; Health policy ; Health services ; Humans ; Incentives ; Internal Medicine ; Male ; Medicine ; Medicine & Public Health ; Original Research ; Patient-centered care ; Patient-Centered Care - economics ; Patient-Centered Care - standards ; Payments ; Primary care ; Quality of Health Care - economics ; Quality of Health Care - standards ; Regional analysis</subject><ispartof>Journal of general internal medicine : JGIM, 2016-09, Vol.31 (9), p.1041-1051</ispartof><rights>Society of General Internal Medicine 2016</rights><rights>Journal of General Internal Medicine is a copyright of Springer, (2016). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c503t-8ddb393675a8559183a043636bd5de9e2e9d75da58ce42915557eefb9232cde33</citedby><cites>FETCH-LOGICAL-c503t-8ddb393675a8559183a043636bd5de9e2e9d75da58ce42915557eefb9232cde33</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/PMC4978681/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4978681/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,41464,42533,51294,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27216480$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gao, Yue</creatorcontrib><creatorcontrib>Nocon, Robert S.</creatorcontrib><creatorcontrib>Gunter, Kathryn E.</creatorcontrib><creatorcontrib>Sharma, Ravi</creatorcontrib><creatorcontrib>Ngo-Metzger, Quyen</creatorcontrib><creatorcontrib>Casalino, Lawrence P.</creatorcontrib><creatorcontrib>Chin, Marshall H.</creatorcontrib><title>Characteristics Associated with Patient-Centered Medical Home Capability in Health Centers: A Cross-Sectional Analysis</title><title>Journal of general internal medicine : JGIM</title><addtitle>J GEN INTERN MED</addtitle><addtitle>J Gen Intern Med</addtitle><description>Background
The patient-centered medical home (PCMH) model is being implemented in health centers (HCs) that provide comprehensive primary care to vulnerable populations.
Objective
To identify characteristics associated with HCs’ PCMH capability.
Design
Cross-sectional analysis of a national dataset of Federally Qualified Health Centers (FQHCs) in 2009. Data for PCMH capability, HC, patient, neighborhood, and regional characteristics were combined from multiple sources.
Participants
A total of 706 (70 %) of 1014 FQHCs from the Health Resources and Services Administration Community Health Center Program, representing all 50 states and the District of Columbia.
Main Measures
PCMH capability was scored via the Commonwealth Fund National Survey of FQHCs through the Safety Net Medical Home Scale (0 [worst] to 100 [best]). HC, patient, neighborhood, and regional characteristics (all analyzed at the HC level) were measured from the Commonwealth survey, Uniform Data System, American Community Survey, American Medical Association physician data, and National Academy for State Health Policy data.
Key Results
Independent correlates of high PCMH capability included having an electronic health record (EHR) (11.7-point [95 % confidence interval, CI 10.2–13.3]), more types of financial performance incentives (0.7-point [95 % CI 0.2–1.1] higher total score per one additional type, maximum possible = 10), more types of hospital–HC affiliations (1.6-point [95 % CI 1.1–2.1] higher total score per one additional type, maximum possible = 6), and location in certain US census divisions. Among HCs with an EHR, location in a state with state-supported PCMH initiatives and PCMH payments was associated with high PCMH capability (2.8-point, 95 % CI 0.2–5.5). Other characteristics had small effect size based on the measure unit (e.g. 0.04-point [95 % CI 0-0.08] lower total score per one percentage point more minority patients), but the effects could be practically large at the extremes.
Conclusions
EHR adoption likely played a role in HCs’ improvement in PCMH capability. Factors that appear to hold promise for supporting PCMH capability include a greater number of types of financial performance incentives, more types of hospital–HC affiliations, and state-level support and payment for PCMH activities.</description><subject>Adult</subject><subject>Communities</subject><subject>Community Health Centers - standards</subject><subject>Confidence intervals</subject><subject>Cross-Sectional Studies</subject><subject>Databases, Factual - standards</subject><subject>Electronic health records</subject><subject>Electronic medical records</subject><subject>Female</subject><subject>Health care</subject><subject>Health facilities</subject><subject>Health policy</subject><subject>Health services</subject><subject>Humans</subject><subject>Incentives</subject><subject>Internal Medicine</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Original Research</subject><subject>Patient-centered care</subject><subject>Patient-Centered Care - economics</subject><subject>Patient-Centered Care - standards</subject><subject>Payments</subject><subject>Primary care</subject><subject>Quality of Health Care - economics</subject><subject>Quality of Health Care - standards</subject><subject>Regional analysis</subject><issn>0884-8734</issn><issn>1525-1497</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqNkk2LFDEQhoMo7uzqD_AiDV72EjcfnS8PwtDojrCioJ5DOqnZydLTPSaZlfn3Zuh1dQXBSwVSz1upVL0IvaDkNSVEXWRKJZGYUIm5YgbrR2hBBROYtkY9RguidYu14u0JOs35hhDKGdNP0QlTjMpWkwW67TYuOV8gxVyiz80y58lHVyA0P2LZNJ9diTAW3NUAqd5-hBC9G5rVtIWmczvXxyGWQxPHZgVuqJIZzW-aZdOlKWf8BXyJ01hFyxoOOeZn6MnaDRme351n6Nv7d1-7Fb76dPmhW15hLwgvWIfQc8OlEk4LYajmjrRcctkHEcAAAxOUCE5oDy0zVAihANa9YZz5AJyfobdz3d2-30LwtbPkBrtLcevSwU4u2oeZMW7s9XRr6wC11LQWOL8rkKbve8jFbmP2MAxuhGmfLdVUSKOElP-DEi2F0qKir_5Cb6Z9qrPJlh23pLWgplJ0pvxxignW931TYo8GsLMBbDWAPRrA6qp5-eeH7xW_Nl4BNgO5psZrSL-f_nfVn9orvDw</recordid><startdate>20160901</startdate><enddate>20160901</enddate><creator>Gao, Yue</creator><creator>Nocon, Robert S.</creator><creator>Gunter, Kathryn E.</creator><creator>Sharma, Ravi</creator><creator>Ngo-Metzger, Quyen</creator><creator>Casalino, Lawrence P.</creator><creator>Chin, Marshall H.</creator><general>Springer US</general><general>Springer Nature B.V</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>3V.</scope><scope>7QL</scope><scope>7RV</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>8AO</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2O</scope><scope>M7N</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>7QO</scope><scope>5PM</scope></search><sort><creationdate>20160901</creationdate><title>Characteristics Associated with Patient-Centered Medical Home Capability in Health Centers: A Cross-Sectional Analysis</title><author>Gao, Yue ; Nocon, Robert S. ; Gunter, Kathryn E. ; Sharma, Ravi ; Ngo-Metzger, Quyen ; Casalino, Lawrence P. ; Chin, Marshall H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c503t-8ddb393675a8559183a043636bd5de9e2e9d75da58ce42915557eefb9232cde33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adult</topic><topic>Communities</topic><topic>Community Health Centers - standards</topic><topic>Confidence intervals</topic><topic>Cross-Sectional Studies</topic><topic>Databases, Factual - standards</topic><topic>Electronic health records</topic><topic>Electronic medical records</topic><topic>Female</topic><topic>Health care</topic><topic>Health facilities</topic><topic>Health policy</topic><topic>Health services</topic><topic>Humans</topic><topic>Incentives</topic><topic>Internal Medicine</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Original Research</topic><topic>Patient-centered care</topic><topic>Patient-Centered Care - economics</topic><topic>Patient-Centered Care - standards</topic><topic>Payments</topic><topic>Primary care</topic><topic>Quality of Health Care - economics</topic><topic>Quality of Health Care - standards</topic><topic>Regional analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gao, Yue</creatorcontrib><creatorcontrib>Nocon, Robert S.</creatorcontrib><creatorcontrib>Gunter, Kathryn E.</creatorcontrib><creatorcontrib>Sharma, Ravi</creatorcontrib><creatorcontrib>Ngo-Metzger, Quyen</creatorcontrib><creatorcontrib>Casalino, Lawrence P.</creatorcontrib><creatorcontrib>Chin, Marshall H.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Nursing & Allied Health Database</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>ProQuest Healthcare Administration Database</collection><collection>Medical Database</collection><collection>ProQuest research library</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of general internal medicine : JGIM</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gao, Yue</au><au>Nocon, Robert S.</au><au>Gunter, Kathryn E.</au><au>Sharma, Ravi</au><au>Ngo-Metzger, Quyen</au><au>Casalino, Lawrence P.</au><au>Chin, Marshall H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Characteristics Associated with Patient-Centered Medical Home Capability in Health Centers: A Cross-Sectional Analysis</atitle><jtitle>Journal of general internal medicine : JGIM</jtitle><stitle>J GEN INTERN MED</stitle><addtitle>J Gen Intern Med</addtitle><date>2016-09-01</date><risdate>2016</risdate><volume>31</volume><issue>9</issue><spage>1041</spage><epage>1051</epage><pages>1041-1051</pages><issn>0884-8734</issn><eissn>1525-1497</eissn><abstract>Background
The patient-centered medical home (PCMH) model is being implemented in health centers (HCs) that provide comprehensive primary care to vulnerable populations.
Objective
To identify characteristics associated with HCs’ PCMH capability.
Design
Cross-sectional analysis of a national dataset of Federally Qualified Health Centers (FQHCs) in 2009. Data for PCMH capability, HC, patient, neighborhood, and regional characteristics were combined from multiple sources.
Participants
A total of 706 (70 %) of 1014 FQHCs from the Health Resources and Services Administration Community Health Center Program, representing all 50 states and the District of Columbia.
Main Measures
PCMH capability was scored via the Commonwealth Fund National Survey of FQHCs through the Safety Net Medical Home Scale (0 [worst] to 100 [best]). HC, patient, neighborhood, and regional characteristics (all analyzed at the HC level) were measured from the Commonwealth survey, Uniform Data System, American Community Survey, American Medical Association physician data, and National Academy for State Health Policy data.
Key Results
Independent correlates of high PCMH capability included having an electronic health record (EHR) (11.7-point [95 % confidence interval, CI 10.2–13.3]), more types of financial performance incentives (0.7-point [95 % CI 0.2–1.1] higher total score per one additional type, maximum possible = 10), more types of hospital–HC affiliations (1.6-point [95 % CI 1.1–2.1] higher total score per one additional type, maximum possible = 6), and location in certain US census divisions. Among HCs with an EHR, location in a state with state-supported PCMH initiatives and PCMH payments was associated with high PCMH capability (2.8-point, 95 % CI 0.2–5.5). Other characteristics had small effect size based on the measure unit (e.g. 0.04-point [95 % CI 0-0.08] lower total score per one percentage point more minority patients), but the effects could be practically large at the extremes.
Conclusions
EHR adoption likely played a role in HCs’ improvement in PCMH capability. Factors that appear to hold promise for supporting PCMH capability include a greater number of types of financial performance incentives, more types of hospital–HC affiliations, and state-level support and payment for PCMH activities.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>27216480</pmid><doi>10.1007/s11606-016-3729-8</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 0884-8734 |
| ispartof | Journal of general internal medicine : JGIM, 2016-09, Vol.31 (9), p.1041-1051 |
| issn | 0884-8734 1525-1497 |
| language | eng |
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| source | MEDLINE; Springer Journals; PubMed Central; Alma/SFX Local Collection; EZB Electronic Journals Library |
| subjects | Adult Communities Community Health Centers - standards Confidence intervals Cross-Sectional Studies Databases, Factual - standards Electronic health records Electronic medical records Female Health care Health facilities Health policy Health services Humans Incentives Internal Medicine Male Medicine Medicine & Public Health Original Research Patient-centered care Patient-Centered Care - economics Patient-Centered Care - standards Payments Primary care Quality of Health Care - economics Quality of Health Care - standards Regional analysis |
| title | Characteristics Associated with Patient-Centered Medical Home Capability in Health Centers: A Cross-Sectional Analysis |
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