Determining the Value of Disease Management Programs
Increasing prevalence, rising costs, and persisting deficiencies in quality of care for chronic diseases pose economic and policy challenges to providers and purchasers. Disease management (DM) programs may address these challenges, but neither purchasers nor providers can assess their value. The po...
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Veröffentlicht in: | Joint Commission journal on quality and safety 2003-09, Vol.29 (9), p.491-499 |
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creator | Selby, Joe V. Scanlon, Dennis Lafata, Jennifer Elston Villagra, Victor Beich, Jeff Salber, Patricia R. |
description | Increasing prevalence, rising costs, and persisting deficiencies in quality of care for chronic diseases pose economic and policy challenges to providers and purchasers. Disease management (DM) programs may address these challenges, but neither purchasers nor providers can assess their value. The potpourri of current quality indicators provides limited insight into the actual clinical benefit achieved. A conference sponsored by the Agency for Healthcare Research and Quality (AHRQ) and held in October 2002 explored new approaches to measuring and reporting the value of DM for diabetes mellitus.
Quantifying the value of DM requires measuring clinical benefit and net impact on health care costs for the entire population with diabetes. If quality is measured with indicators that are clearly linked to outcomes, clinical benefit can be estimated. Natural history models combine the expected benefits of improvements in multiple indicators to yield a single, composite measure, the quality-adjusted life-year. Such metrics could fairly express, in terms of survival and complications prevention, relatively disparate DM programs’ benefits. Measuring and comparing health care costs requires data validation and appropriate case-mix adjustment. Comparing value across programs may provide more accurate assessments of performance, enhance quality improvement efforts within systems, and contribute generalizable knowledge on the utility of DM approaches.
Conference attendees recommended pilot projects to further explore use of natural history models for measuring and reporting the value of DM. |
doi_str_mv | 10.1016/S1549-3741(03)29059-6 |
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Quantifying the value of DM requires measuring clinical benefit and net impact on health care costs for the entire population with diabetes. If quality is measured with indicators that are clearly linked to outcomes, clinical benefit can be estimated. Natural history models combine the expected benefits of improvements in multiple indicators to yield a single, composite measure, the quality-adjusted life-year. Such metrics could fairly express, in terms of survival and complications prevention, relatively disparate DM programs’ benefits. Measuring and comparing health care costs requires data validation and appropriate case-mix adjustment. Comparing value across programs may provide more accurate assessments of performance, enhance quality improvement efforts within systems, and contribute generalizable knowledge on the utility of DM approaches.
Conference attendees recommended pilot projects to further explore use of natural history models for measuring and reporting the value of DM.</description><identifier>ISSN: 1549-3741</identifier><identifier>EISSN: 1549-425X</identifier><identifier>DOI: 10.1016/S1549-3741(03)29059-6</identifier><identifier>PMID: 14513673</identifier><language>eng</language><publisher>United States</publisher><subject>Chronic Disease ; Diabetes Mellitus - diagnosis ; Diabetes Mellitus - economics ; Diabetes Mellitus - prevention & control ; Disease Management ; Health Services Research ; Humans ; Quality Indicators, Health Care ; Quality-Adjusted Life Years ; Review Literature as Topic ; United States - epidemiology</subject><ispartof>Joint Commission journal on quality and safety, 2003-09, Vol.29 (9), p.491-499</ispartof><rights>2003 Joint Commission on Accreditation of Healthcare Organizations</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c276t-ee2db9ab14a74baa98b616e48e9201a8dd5472b943d3c05207a70489f7735a2b3</citedby><cites>FETCH-LOGICAL-c276t-ee2db9ab14a74baa98b616e48e9201a8dd5472b943d3c05207a70489f7735a2b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>309,310,314,780,784,789,790,23930,23931,25140,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/14513673$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Selby, Joe V.</creatorcontrib><creatorcontrib>Scanlon, Dennis</creatorcontrib><creatorcontrib>Lafata, Jennifer Elston</creatorcontrib><creatorcontrib>Villagra, Victor</creatorcontrib><creatorcontrib>Beich, Jeff</creatorcontrib><creatorcontrib>Salber, Patricia R.</creatorcontrib><title>Determining the Value of Disease Management Programs</title><title>Joint Commission journal on quality and safety</title><addtitle>Jt Comm J Qual Saf</addtitle><description>Increasing prevalence, rising costs, and persisting deficiencies in quality of care for chronic diseases pose economic and policy challenges to providers and purchasers. Disease management (DM) programs may address these challenges, but neither purchasers nor providers can assess their value. The potpourri of current quality indicators provides limited insight into the actual clinical benefit achieved. A conference sponsored by the Agency for Healthcare Research and Quality (AHRQ) and held in October 2002 explored new approaches to measuring and reporting the value of DM for diabetes mellitus.
Quantifying the value of DM requires measuring clinical benefit and net impact on health care costs for the entire population with diabetes. If quality is measured with indicators that are clearly linked to outcomes, clinical benefit can be estimated. Natural history models combine the expected benefits of improvements in multiple indicators to yield a single, composite measure, the quality-adjusted life-year. Such metrics could fairly express, in terms of survival and complications prevention, relatively disparate DM programs’ benefits. Measuring and comparing health care costs requires data validation and appropriate case-mix adjustment. Comparing value across programs may provide more accurate assessments of performance, enhance quality improvement efforts within systems, and contribute generalizable knowledge on the utility of DM approaches.
Conference attendees recommended pilot projects to further explore use of natural history models for measuring and reporting the value of DM.</description><subject>Chronic Disease</subject><subject>Diabetes Mellitus - diagnosis</subject><subject>Diabetes Mellitus - economics</subject><subject>Diabetes Mellitus - prevention & control</subject><subject>Disease Management</subject><subject>Health Services Research</subject><subject>Humans</subject><subject>Quality Indicators, Health Care</subject><subject>Quality-Adjusted Life Years</subject><subject>Review Literature as Topic</subject><subject>United States - epidemiology</subject><issn>1549-3741</issn><issn>1549-425X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkE1Lw0AQhhdRrFZ_gpKT6CG6n9nsSaT1CyoKfuBtmSSTutIkdTcR_PembcCjp3kZnplhHkKOGD1nlCUXz0xJEwst2SkVZ9xQZeJki-yt25Kr9-0hr5AR2Q_hk9I-K7pLRkwqJhIt9oicYou-crWr51H7gdEbLDqMmjKauoAQMHqAGuZYYd1GT76Ze6jCAdkpYRHwcKhj8npz_TK5i2ePt_eTq1mcc520MSIvMgMZk6BlBmDSLGEJyhQNpwzSolBS88xIUYicKk41aCpTU2otFPBMjMnJZu_SN18dhtZWLuS4WECNTResVpppJUUPqg2Y-yYEj6VdeleB_7GM2pUuu9ZlVy4sFXatyyb93PFwoMsqLP6mBj89cLkBsH_z26G3IXdY51g4j3lri8b9c-IX01l4qw</recordid><startdate>200309</startdate><enddate>200309</enddate><creator>Selby, Joe V.</creator><creator>Scanlon, Dennis</creator><creator>Lafata, Jennifer Elston</creator><creator>Villagra, Victor</creator><creator>Beich, Jeff</creator><creator>Salber, Patricia R.</creator><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>7X8</scope></search><sort><creationdate>200309</creationdate><title>Determining the Value of Disease Management Programs</title><author>Selby, Joe V. ; Scanlon, Dennis ; Lafata, Jennifer Elston ; Villagra, Victor ; Beich, Jeff ; Salber, Patricia R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c276t-ee2db9ab14a74baa98b616e48e9201a8dd5472b943d3c05207a70489f7735a2b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Chronic Disease</topic><topic>Diabetes Mellitus - diagnosis</topic><topic>Diabetes Mellitus - economics</topic><topic>Diabetes Mellitus - prevention & control</topic><topic>Disease Management</topic><topic>Health Services Research</topic><topic>Humans</topic><topic>Quality Indicators, Health Care</topic><topic>Quality-Adjusted Life Years</topic><topic>Review Literature as Topic</topic><topic>United States - epidemiology</topic><toplevel>online_resources</toplevel><creatorcontrib>Selby, Joe V.</creatorcontrib><creatorcontrib>Scanlon, Dennis</creatorcontrib><creatorcontrib>Lafata, Jennifer Elston</creatorcontrib><creatorcontrib>Villagra, Victor</creatorcontrib><creatorcontrib>Beich, Jeff</creatorcontrib><creatorcontrib>Salber, Patricia R.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Joint Commission journal on quality and safety</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Selby, Joe V.</au><au>Scanlon, Dennis</au><au>Lafata, Jennifer Elston</au><au>Villagra, Victor</au><au>Beich, Jeff</au><au>Salber, Patricia R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Determining the Value of Disease Management Programs</atitle><jtitle>Joint Commission journal on quality and safety</jtitle><addtitle>Jt Comm J Qual Saf</addtitle><date>2003-09</date><risdate>2003</risdate><volume>29</volume><issue>9</issue><spage>491</spage><epage>499</epage><pages>491-499</pages><issn>1549-3741</issn><eissn>1549-425X</eissn><abstract>Increasing prevalence, rising costs, and persisting deficiencies in quality of care for chronic diseases pose economic and policy challenges to providers and purchasers. Disease management (DM) programs may address these challenges, but neither purchasers nor providers can assess their value. The potpourri of current quality indicators provides limited insight into the actual clinical benefit achieved. A conference sponsored by the Agency for Healthcare Research and Quality (AHRQ) and held in October 2002 explored new approaches to measuring and reporting the value of DM for diabetes mellitus.
Quantifying the value of DM requires measuring clinical benefit and net impact on health care costs for the entire population with diabetes. If quality is measured with indicators that are clearly linked to outcomes, clinical benefit can be estimated. Natural history models combine the expected benefits of improvements in multiple indicators to yield a single, composite measure, the quality-adjusted life-year. Such metrics could fairly express, in terms of survival and complications prevention, relatively disparate DM programs’ benefits. Measuring and comparing health care costs requires data validation and appropriate case-mix adjustment. Comparing value across programs may provide more accurate assessments of performance, enhance quality improvement efforts within systems, and contribute generalizable knowledge on the utility of DM approaches.
Conference attendees recommended pilot projects to further explore use of natural history models for measuring and reporting the value of DM.</abstract><cop>United States</cop><pmid>14513673</pmid><doi>10.1016/S1549-3741(03)29059-6</doi><tpages>9</tpages></addata></record> |
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subjects | Chronic Disease Diabetes Mellitus - diagnosis Diabetes Mellitus - economics Diabetes Mellitus - prevention & control Disease Management Health Services Research Humans Quality Indicators, Health Care Quality-Adjusted Life Years Review Literature as Topic United States - epidemiology |
title | Determining the Value of Disease Management Programs |
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