Validity of the RAI-MDS for ascertaining diabetes and comorbid conditions in long-term care facility residents
This study assessed the validity of the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0 for diagnoses of diabetes and comorbid conditions in residents of long-term care facilities (LTCFs). Hospital inpatient, outpatient physician billing, RAI-MDS, and population registry data f...
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| Veröffentlicht in: | BMC health services research 2014-01, Vol.14 (1), p.17-17, Article 17 |
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| creator | Lix, Lisa M Yan, Lin Blackburn, David Hu, Nianping Schneider-Lindner, Verena Teare, Gary F |
| description | This study assessed the validity of the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0 for diagnoses of diabetes and comorbid conditions in residents of long-term care facilities (LTCFs).
Hospital inpatient, outpatient physician billing, RAI-MDS, and population registry data for 1997 to 2011 from Saskatchewan, Canada were used to ascertain cases of diabetes and 12 comorbid conditions. Prevalence estimates were calculated for both RAI-MDS and administrative health data. Sensitivity, specificity, and positive and negative predictive values (PPV and NPV) were calculated using population-based administrative health data as the validation data source. Cohen's κ was used to estimate agreement between the two data sources.
23,217 LTCF residents were in the diabetes case ascertainment cohort. Diabetes prevalence was 25.3% in administrative health data and 21.9% in RAI-MDS data. Overall sensitivity of a RAI-MDS diabetes diagnoses was 0.79 (95% CI: 0.79, 0.80) and the PPV was 0.92 (95% CI: 0.91, 0.92), when compared to administrative health data. Sensitivity of the RAI-MDS for ascertaining comorbid conditions ranged from 0.21 for osteoporosis to 0.92 for multiple sclerosis; specificity was high for most conditions.
RAI-MDS clinical assessment data are sensitive to ascertain diabetes cases in LTCF populations when compared to administrative health data. For many comorbid conditions, RAI-MDS data have low validity when compared to administrative data. Risk-adjustment measures based on these comorbidities might not produce consistent results for RAI-MDS and administrative health data, which could affect the conclusions of studies about health outcomes and quality of care across facilities. |
| doi_str_mv | 10.1186/1472-6963-14-17 |
| format | Article |
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Hospital inpatient, outpatient physician billing, RAI-MDS, and population registry data for 1997 to 2011 from Saskatchewan, Canada were used to ascertain cases of diabetes and 12 comorbid conditions. Prevalence estimates were calculated for both RAI-MDS and administrative health data. Sensitivity, specificity, and positive and negative predictive values (PPV and NPV) were calculated using population-based administrative health data as the validation data source. Cohen's κ was used to estimate agreement between the two data sources.
23,217 LTCF residents were in the diabetes case ascertainment cohort. Diabetes prevalence was 25.3% in administrative health data and 21.9% in RAI-MDS data. Overall sensitivity of a RAI-MDS diabetes diagnoses was 0.79 (95% CI: 0.79, 0.80) and the PPV was 0.92 (95% CI: 0.91, 0.92), when compared to administrative health data. Sensitivity of the RAI-MDS for ascertaining comorbid conditions ranged from 0.21 for osteoporosis to 0.92 for multiple sclerosis; specificity was high for most conditions.
RAI-MDS clinical assessment data are sensitive to ascertain diabetes cases in LTCF populations when compared to administrative health data. For many comorbid conditions, RAI-MDS data have low validity when compared to administrative data. Risk-adjustment measures based on these comorbidities might not produce consistent results for RAI-MDS and administrative health data, which could affect the conclusions of studies about health outcomes and quality of care across facilities.</description><identifier>ISSN: 1472-6963</identifier><identifier>EISSN: 1472-6963</identifier><identifier>DOI: 10.1186/1472-6963-14-17</identifier><identifier>PMID: 24423071</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Activities of daily living ; Aged ; Aged, 80 and over ; Alzheimer's disease ; Biomedical research ; Care and treatment ; Chronic diseases ; Chronic illnesses ; Comorbidity ; Decision Support Techniques ; Diabetes ; Diabetes Mellitus - diagnosis ; Diabetes Mellitus - epidemiology ; Diagnosis ; Female ; Fiscal years ; Health insurance ; Heart attacks ; Hospitals ; Humans ; Insurance coverage ; Long term health care ; Long-Term Care - methods ; Long-Term Care - statistics & numerical data ; Male ; Medical care ; Medical research ; Medicine, Experimental ; Mortality ; Multiple sclerosis ; Nursing Homes - statistics & numerical data ; Personal health ; Population ; Prevalence ; Quality management ; Reproducibility of Results ; Retrospective Studies ; Saskatchewan - epidemiology ; Sensitivity and Specificity ; Studies ; Technology application ; Validity</subject><ispartof>BMC health services research, 2014-01, Vol.14 (1), p.17-17, Article 17</ispartof><rights>COPYRIGHT 2014 BioMed Central Ltd.</rights><rights>2014 Lix et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><rights>Copyright © 2014 Lix et al.; licensee BioMed Central Ltd. 2014 Lix et al.; licensee BioMed Central Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c521t-1e0d5f2e63bc9a93d1622811e737df5587a117cd21c8dcc2cd4acab02dad2fc53</citedby><cites>FETCH-LOGICAL-c521t-1e0d5f2e63bc9a93d1622811e737df5587a117cd21c8dcc2cd4acab02dad2fc53</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/PMC3898220/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3898220/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24423071$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lix, Lisa M</creatorcontrib><creatorcontrib>Yan, Lin</creatorcontrib><creatorcontrib>Blackburn, David</creatorcontrib><creatorcontrib>Hu, Nianping</creatorcontrib><creatorcontrib>Schneider-Lindner, Verena</creatorcontrib><creatorcontrib>Teare, Gary F</creatorcontrib><title>Validity of the RAI-MDS for ascertaining diabetes and comorbid conditions in long-term care facility residents</title><title>BMC health services research</title><addtitle>BMC Health Serv Res</addtitle><description>This study assessed the validity of the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0 for diagnoses of diabetes and comorbid conditions in residents of long-term care facilities (LTCFs).
Hospital inpatient, outpatient physician billing, RAI-MDS, and population registry data for 1997 to 2011 from Saskatchewan, Canada were used to ascertain cases of diabetes and 12 comorbid conditions. Prevalence estimates were calculated for both RAI-MDS and administrative health data. Sensitivity, specificity, and positive and negative predictive values (PPV and NPV) were calculated using population-based administrative health data as the validation data source. Cohen's κ was used to estimate agreement between the two data sources.
23,217 LTCF residents were in the diabetes case ascertainment cohort. Diabetes prevalence was 25.3% in administrative health data and 21.9% in RAI-MDS data. Overall sensitivity of a RAI-MDS diabetes diagnoses was 0.79 (95% CI: 0.79, 0.80) and the PPV was 0.92 (95% CI: 0.91, 0.92), when compared to administrative health data. Sensitivity of the RAI-MDS for ascertaining comorbid conditions ranged from 0.21 for osteoporosis to 0.92 for multiple sclerosis; specificity was high for most conditions.
RAI-MDS clinical assessment data are sensitive to ascertain diabetes cases in LTCF populations when compared to administrative health data. For many comorbid conditions, RAI-MDS data have low validity when compared to administrative data. Risk-adjustment measures based on these comorbidities might not produce consistent results for RAI-MDS and administrative health data, which could affect the conclusions of studies about health outcomes and quality of care across facilities.</description><subject>Activities of daily living</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Alzheimer's disease</subject><subject>Biomedical research</subject><subject>Care and treatment</subject><subject>Chronic diseases</subject><subject>Chronic illnesses</subject><subject>Comorbidity</subject><subject>Decision Support Techniques</subject><subject>Diabetes</subject><subject>Diabetes Mellitus - diagnosis</subject><subject>Diabetes Mellitus - epidemiology</subject><subject>Diagnosis</subject><subject>Female</subject><subject>Fiscal years</subject><subject>Health insurance</subject><subject>Heart attacks</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Insurance coverage</subject><subject>Long term health care</subject><subject>Long-Term Care - methods</subject><subject>Long-Term Care - statistics & numerical data</subject><subject>Male</subject><subject>Medical care</subject><subject>Medical research</subject><subject>Medicine, Experimental</subject><subject>Mortality</subject><subject>Multiple sclerosis</subject><subject>Nursing Homes - statistics & numerical data</subject><subject>Personal health</subject><subject>Population</subject><subject>Prevalence</subject><subject>Quality management</subject><subject>Reproducibility of Results</subject><subject>Retrospective Studies</subject><subject>Saskatchewan - epidemiology</subject><subject>Sensitivity and Specificity</subject><subject>Studies</subject><subject>Technology application</subject><subject>Validity</subject><issn>1472-6963</issn><issn>1472-6963</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqNks1vFSEUxSdGYz907c6QuHEzLRdmBtiYvLRWm9SY-LUlPLi80sxAhXkm_e9lbH22xoVhwc3ldw_kcJrmBdAjADkcQydYO6iBt9C1IB41-7vO43v1XnNQyhWlICQTT5s91nWMUwH7TfxmxuDCfEOSJ_Mlkk-r8_bD6WfiUyamWMyzCTHEDXHBrHHGQkx0xKYp5XVYilinQ4qFhEjGFDftjHki1mQk3tgwLtoZS3AY5_KseeLNWPD53X7YfD17--XkfXvx8d35yeqitT2DuQWkrvcMB762yijuYGBMAqDgwvm-l8IACOsYWOmsZdZ1xpo1Zc445m3PD5s3t7rX2_WEzta7sxn1dQ6TyTc6maAfnsRwqTfph-ZSScZoFXh9J5DT9y2WWU-hujGOJmLaFg2dGqQalOL_gwIdWA-ioq_-Qq_SNsfqRKUkA8o57_5QGzOiDtGn-kS7iOpVz9UgpGKL1tE_qLocTqF-C_pQ-w8Gjm8HbE6lZPQ7O4DqJU16yYte8lIr_eu5L--7uON_x4f_BAxcxIc</recordid><startdate>20140115</startdate><enddate>20140115</enddate><creator>Lix, Lisa M</creator><creator>Yan, Lin</creator><creator>Blackburn, David</creator><creator>Hu, Nianping</creator><creator>Schneider-Lindner, Verena</creator><creator>Teare, Gary F</creator><general>BioMed Central Ltd</general><general>BioMed Central</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>7RV</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88C</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>K60</scope><scope>K6~</scope><scope>K9.</scope><scope>KB0</scope><scope>L.-</scope><scope>M0C</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>7T2</scope><scope>7U1</scope><scope>7U2</scope><scope>C1K</scope><scope>5PM</scope></search><sort><creationdate>20140115</creationdate><title>Validity of the RAI-MDS for ascertaining diabetes and comorbid conditions in long-term care facility residents</title><author>Lix, Lisa M ; Yan, Lin ; Blackburn, David ; Hu, Nianping ; Schneider-Lindner, Verena ; Teare, Gary F</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c521t-1e0d5f2e63bc9a93d1622811e737df5587a117cd21c8dcc2cd4acab02dad2fc53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Activities of daily living</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Alzheimer's disease</topic><topic>Biomedical research</topic><topic>Care and treatment</topic><topic>Chronic diseases</topic><topic>Chronic illnesses</topic><topic>Comorbidity</topic><topic>Decision Support Techniques</topic><topic>Diabetes</topic><topic>Diabetes Mellitus - diagnosis</topic><topic>Diabetes Mellitus - epidemiology</topic><topic>Diagnosis</topic><topic>Female</topic><topic>Fiscal years</topic><topic>Health insurance</topic><topic>Heart attacks</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Insurance coverage</topic><topic>Long term health care</topic><topic>Long-Term Care - methods</topic><topic>Long-Term Care - statistics & numerical data</topic><topic>Male</topic><topic>Medical care</topic><topic>Medical research</topic><topic>Medicine, Experimental</topic><topic>Mortality</topic><topic>Multiple sclerosis</topic><topic>Nursing Homes - statistics & numerical data</topic><topic>Personal health</topic><topic>Population</topic><topic>Prevalence</topic><topic>Quality management</topic><topic>Reproducibility of Results</topic><topic>Retrospective Studies</topic><topic>Saskatchewan - epidemiology</topic><topic>Sensitivity and Specificity</topic><topic>Studies</topic><topic>Technology application</topic><topic>Validity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lix, Lisa M</creatorcontrib><creatorcontrib>Yan, Lin</creatorcontrib><creatorcontrib>Blackburn, David</creatorcontrib><creatorcontrib>Hu, Nianping</creatorcontrib><creatorcontrib>Schneider-Lindner, Verena</creatorcontrib><creatorcontrib>Teare, Gary F</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>Nursing & Allied Health Database</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</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 Basic</collection><collection>MEDLINE - Academic</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Risk Abstracts</collection><collection>Safety Science and Risk</collection><collection>Environmental Sciences and Pollution Management</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BMC health services research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lix, Lisa M</au><au>Yan, Lin</au><au>Blackburn, David</au><au>Hu, Nianping</au><au>Schneider-Lindner, Verena</au><au>Teare, Gary F</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Validity of the RAI-MDS for ascertaining diabetes and comorbid conditions in long-term care facility residents</atitle><jtitle>BMC health services research</jtitle><addtitle>BMC Health Serv Res</addtitle><date>2014-01-15</date><risdate>2014</risdate><volume>14</volume><issue>1</issue><spage>17</spage><epage>17</epage><pages>17-17</pages><artnum>17</artnum><issn>1472-6963</issn><eissn>1472-6963</eissn><abstract>This study assessed the validity of the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0 for diagnoses of diabetes and comorbid conditions in residents of long-term care facilities (LTCFs).
Hospital inpatient, outpatient physician billing, RAI-MDS, and population registry data for 1997 to 2011 from Saskatchewan, Canada were used to ascertain cases of diabetes and 12 comorbid conditions. Prevalence estimates were calculated for both RAI-MDS and administrative health data. Sensitivity, specificity, and positive and negative predictive values (PPV and NPV) were calculated using population-based administrative health data as the validation data source. Cohen's κ was used to estimate agreement between the two data sources.
23,217 LTCF residents were in the diabetes case ascertainment cohort. Diabetes prevalence was 25.3% in administrative health data and 21.9% in RAI-MDS data. Overall sensitivity of a RAI-MDS diabetes diagnoses was 0.79 (95% CI: 0.79, 0.80) and the PPV was 0.92 (95% CI: 0.91, 0.92), when compared to administrative health data. Sensitivity of the RAI-MDS for ascertaining comorbid conditions ranged from 0.21 for osteoporosis to 0.92 for multiple sclerosis; specificity was high for most conditions.
RAI-MDS clinical assessment data are sensitive to ascertain diabetes cases in LTCF populations when compared to administrative health data. For many comorbid conditions, RAI-MDS data have low validity when compared to administrative data. Risk-adjustment measures based on these comorbidities might not produce consistent results for RAI-MDS and administrative health data, which could affect the conclusions of studies about health outcomes and quality of care across facilities.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>24423071</pmid><doi>10.1186/1472-6963-14-17</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Activities of daily living Aged Aged, 80 and over Alzheimer's disease Biomedical research Care and treatment Chronic diseases Chronic illnesses Comorbidity Decision Support Techniques Diabetes Diabetes Mellitus - diagnosis Diabetes Mellitus - epidemiology Diagnosis Female Fiscal years Health insurance Heart attacks Hospitals Humans Insurance coverage Long term health care Long-Term Care - methods Long-Term Care - statistics & numerical data Male Medical care Medical research Medicine, Experimental Mortality Multiple sclerosis Nursing Homes - statistics & numerical data Personal health Population Prevalence Quality management Reproducibility of Results Retrospective Studies Saskatchewan - epidemiology Sensitivity and Specificity Studies Technology application Validity |
| title | Validity of the RAI-MDS for ascertaining diabetes and comorbid conditions in long-term care facility residents |
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