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Using Systems Science for Population Health Management in Primary Care
Objectives: Population health management is becoming increasingly important to organizations managing and providing primary care services given ongoing changes in health care delivery and payment systems. The objective of this study is to show how systems science methodologies could be incorporated...
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| Published in: | Journal of primary care & community health 2014-10, Vol.5 (4), p.242-246 |
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| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
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| cites | cdi_FETCH-LOGICAL-c431t-6208f89900a3a2a56038c86841491f4b26b16c5348e5793d35794bdaf5ecc3003 |
| container_end_page | 246 |
| container_issue | 4 |
| container_start_page | 242 |
| container_title | Journal of primary care & community health |
| container_volume | 5 |
| creator | Li, Yan Kong, Nan Lawley, Mark A. Pagán, José A. |
| description | Objectives:
Population health management is becoming increasingly important to organizations managing and providing primary care services given ongoing changes in health care delivery and payment systems. The objective of this study is to show how systems science methodologies could be incorporated into population health management to compare different interventions and improve health outcomes.
Methods:
The New York Academy of Medicine Cardiovascular Health Simulation model (an agent-based model) and data from the Behavioral Risk Factor Surveillance System were used to evaluate a lifestyle program that could be implemented in primary care practice settings. The program targeted Medicare-age adults and focused on improving diet and exercise and reducing weight.
Results:
The simulation results suggest that there would be significant reductions projected in the proportion of the Medicare-age population with diabetes after the implementation of the proposed lifestyle program for a relatively long term (3 and 5 years). Similar results were found for the subpopulations with high cholesterol, but the proposed intervention would not have a significant effect in the proportion of the population with hypertension over a time period of |
| doi_str_mv | 10.1177/2150131914536400 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_AFRWT</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_291bf105574b46d3aee7093d1c7a1f25</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sage_id>10.1177_2150131914536400</sage_id><doaj_id>oai_doaj_org_article_291bf105574b46d3aee7093d1c7a1f25</doaj_id><sourcerecordid>2343087566</sourcerecordid><originalsourceid>FETCH-LOGICAL-c431t-6208f89900a3a2a56038c86841491f4b26b16c5348e5793d35794bdaf5ecc3003</originalsourceid><addsrcrecordid>eNp1kc1r3DAQxUVpSUKae05F0EsvTjX6tI5laZpASgNpzkKWx1svtrWV7EP--ypxsoFAdZDE8OY3T3qEnAO7ADDmKwfFQIAFqYSWjL0jJ4-lCgQ37w93sMfkLOcdK0tqITQckWMua2O1Uifk8j7305bePeQZx0zvQo9TQNrFRG_jfhn83MeJXqEf5j_0p5_8FkecZtpP9Db1o08PdOMTfiQfOj9kPHs-T8n95fffm6vq5teP6823mypIAXOlOau72lrGvPDcK81EHWpdS5AWOtlw3YAOSsgalbGiFWWXTes7hSEIxsQpuV65bfQ7t18duOh791SIaet8mvswoOMWmg6YUkY2UrfCIxpWmBCMh46rwvqysvYp_l0wz27sc8Bh8BPGJTtQWhSrltVF-vmNdBeXNJWXOi6kYLVRWhcVW1UhxZwTdgeDwNxjZO5tZKXl0zN4aUZsDw0vARVBtQpy-fnXqf8F_gNFDZlP</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2343087566</pqid></control><display><type>article</type><title>Using Systems Science for Population Health Management in Primary Care</title><source>SAGE Journals Open Access</source><creator>Li, Yan ; Kong, Nan ; Lawley, Mark A. ; Pagán, José A.</creator><creatorcontrib>Li, Yan ; Kong, Nan ; Lawley, Mark A. ; Pagán, José A.</creatorcontrib><description>Objectives:
Population health management is becoming increasingly important to organizations managing and providing primary care services given ongoing changes in health care delivery and payment systems. The objective of this study is to show how systems science methodologies could be incorporated into population health management to compare different interventions and improve health outcomes.
Methods:
The New York Academy of Medicine Cardiovascular Health Simulation model (an agent-based model) and data from the Behavioral Risk Factor Surveillance System were used to evaluate a lifestyle program that could be implemented in primary care practice settings. The program targeted Medicare-age adults and focused on improving diet and exercise and reducing weight.
Results:
The simulation results suggest that there would be significant reductions projected in the proportion of the Medicare-age population with diabetes after the implementation of the proposed lifestyle program for a relatively long term (3 and 5 years). Similar results were found for the subpopulations with high cholesterol, but the proposed intervention would not have a significant effect in the proportion of the population with hypertension over a time period of <5 years.
Conclusions:
Systems science methodologies can be useful to compare the health outcomes of different interventions. These tools can become an important component of population health management because they can help managers and other decision makers evaluate alternative programs in primary care settings.</description><identifier>ISSN: 2150-1319</identifier><identifier>EISSN: 2150-1327</identifier><identifier>DOI: 10.1177/2150131914536400</identifier><identifier>PMID: 24879655</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Aged ; Behavioral Risk Factor Surveillance System ; Cholesterol ; Clinical outcomes ; Decision makers ; Delivery of Health Care - organization & administration ; Diabetes ; Diabetes Mellitus - prevention & control ; Diet ; Disease Management ; Exercise ; Female ; Health care delivery ; Health status ; Humans ; Hypertension ; Intervention ; Life Style ; Lifestyles ; Male ; Medicare ; Overweight - prevention & control ; Population ; Primary care ; Primary Health Care - organization & administration ; Risk behavior ; Simulation ; Surveillance systems ; Systems science</subject><ispartof>Journal of primary care & community health, 2014-10, Vol.5 (4), p.242-246</ispartof><rights>The Author(s) 2014</rights><rights>The Author(s) 2014.</rights><rights>The Author(s) 2014. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at: https://uk.sagepub.com/en-gb/eur/reusing-open-access-and-sage-choice-content</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-6208f89900a3a2a56038c86841491f4b26b16c5348e5793d35794bdaf5ecc3003</citedby><cites>FETCH-LOGICAL-c431t-6208f89900a3a2a56038c86841491f4b26b16c5348e5793d35794bdaf5ecc3003</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/2150131914536400$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2343087566?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,12825,21945,25731,27830,27901,27902,30976,36989,36990,44566,44921,45309</link.rule.ids><linktorsrc>$$Uhttps://journals.sagepub.com/doi/full/10.1177/2150131914536400?utm_source=summon&utm_medium=discovery-provider$$EView_record_in_SAGE_Publications$$FView_record_in_$$GSAGE_Publications</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24879655$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Yan</creatorcontrib><creatorcontrib>Kong, Nan</creatorcontrib><creatorcontrib>Lawley, Mark A.</creatorcontrib><creatorcontrib>Pagán, José A.</creatorcontrib><title>Using Systems Science for Population Health Management in Primary Care</title><title>Journal of primary care & community health</title><addtitle>J Prim Care Community Health</addtitle><description>Objectives:
Population health management is becoming increasingly important to organizations managing and providing primary care services given ongoing changes in health care delivery and payment systems. The objective of this study is to show how systems science methodologies could be incorporated into population health management to compare different interventions and improve health outcomes.
Methods:
The New York Academy of Medicine Cardiovascular Health Simulation model (an agent-based model) and data from the Behavioral Risk Factor Surveillance System were used to evaluate a lifestyle program that could be implemented in primary care practice settings. The program targeted Medicare-age adults and focused on improving diet and exercise and reducing weight.
Results:
The simulation results suggest that there would be significant reductions projected in the proportion of the Medicare-age population with diabetes after the implementation of the proposed lifestyle program for a relatively long term (3 and 5 years). Similar results were found for the subpopulations with high cholesterol, but the proposed intervention would not have a significant effect in the proportion of the population with hypertension over a time period of <5 years.
Conclusions:
Systems science methodologies can be useful to compare the health outcomes of different interventions. These tools can become an important component of population health management because they can help managers and other decision makers evaluate alternative programs in primary care settings.</description><subject>Aged</subject><subject>Behavioral Risk Factor Surveillance System</subject><subject>Cholesterol</subject><subject>Clinical outcomes</subject><subject>Decision makers</subject><subject>Delivery of Health Care - organization & administration</subject><subject>Diabetes</subject><subject>Diabetes Mellitus - prevention & control</subject><subject>Diet</subject><subject>Disease Management</subject><subject>Exercise</subject><subject>Female</subject><subject>Health care delivery</subject><subject>Health status</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Intervention</subject><subject>Life Style</subject><subject>Lifestyles</subject><subject>Male</subject><subject>Medicare</subject><subject>Overweight - prevention & control</subject><subject>Population</subject><subject>Primary care</subject><subject>Primary Health Care - organization & administration</subject><subject>Risk behavior</subject><subject>Simulation</subject><subject>Surveillance systems</subject><subject>Systems science</subject><issn>2150-1319</issn><issn>2150-1327</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>7QJ</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp1kc1r3DAQxUVpSUKae05F0EsvTjX6tI5laZpASgNpzkKWx1svtrWV7EP--ypxsoFAdZDE8OY3T3qEnAO7ADDmKwfFQIAFqYSWjL0jJ4-lCgQ37w93sMfkLOcdK0tqITQckWMua2O1Uifk8j7305bePeQZx0zvQo9TQNrFRG_jfhn83MeJXqEf5j_0p5_8FkecZtpP9Db1o08PdOMTfiQfOj9kPHs-T8n95fffm6vq5teP6823mypIAXOlOau72lrGvPDcK81EHWpdS5AWOtlw3YAOSsgalbGiFWWXTes7hSEIxsQpuV65bfQ7t18duOh791SIaet8mvswoOMWmg6YUkY2UrfCIxpWmBCMh46rwvqysvYp_l0wz27sc8Bh8BPGJTtQWhSrltVF-vmNdBeXNJWXOi6kYLVRWhcVW1UhxZwTdgeDwNxjZO5tZKXl0zN4aUZsDw0vARVBtQpy-fnXqf8F_gNFDZlP</recordid><startdate>20141001</startdate><enddate>20141001</enddate><creator>Li, Yan</creator><creator>Kong, Nan</creator><creator>Lawley, Mark A.</creator><creator>Pagán, José A.</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><general>SAGE Publishing</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>7QJ</scope><scope>8C1</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>DOA</scope></search><sort><creationdate>20141001</creationdate><title>Using Systems Science for Population Health Management in Primary Care</title><author>Li, Yan ; Kong, Nan ; Lawley, Mark A. ; Pagán, José A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-6208f89900a3a2a56038c86841491f4b26b16c5348e5793d35794bdaf5ecc3003</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Aged</topic><topic>Behavioral Risk Factor Surveillance System</topic><topic>Cholesterol</topic><topic>Clinical outcomes</topic><topic>Decision makers</topic><topic>Delivery of Health Care - organization & administration</topic><topic>Diabetes</topic><topic>Diabetes Mellitus - prevention & control</topic><topic>Diet</topic><topic>Disease Management</topic><topic>Exercise</topic><topic>Female</topic><topic>Health care delivery</topic><topic>Health status</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Intervention</topic><topic>Life Style</topic><topic>Lifestyles</topic><topic>Male</topic><topic>Medicare</topic><topic>Overweight - prevention & control</topic><topic>Population</topic><topic>Primary care</topic><topic>Primary Health Care - organization & administration</topic><topic>Risk behavior</topic><topic>Simulation</topic><topic>Surveillance systems</topic><topic>Systems science</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Yan</creatorcontrib><creatorcontrib>Kong, Nan</creatorcontrib><creatorcontrib>Lawley, Mark A.</creatorcontrib><creatorcontrib>Pagán, José A.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>Public Health Database</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</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>MEDLINE - Academic</collection><collection>Open Access: DOAJ - Directory of Open Access Journals</collection><jtitle>Journal of primary care & community health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Li, Yan</au><au>Kong, Nan</au><au>Lawley, Mark A.</au><au>Pagán, José A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using Systems Science for Population Health Management in Primary Care</atitle><jtitle>Journal of primary care & community health</jtitle><addtitle>J Prim Care Community Health</addtitle><date>2014-10-01</date><risdate>2014</risdate><volume>5</volume><issue>4</issue><spage>242</spage><epage>246</epage><pages>242-246</pages><issn>2150-1319</issn><eissn>2150-1327</eissn><abstract>Objectives:
Population health management is becoming increasingly important to organizations managing and providing primary care services given ongoing changes in health care delivery and payment systems. The objective of this study is to show how systems science methodologies could be incorporated into population health management to compare different interventions and improve health outcomes.
Methods:
The New York Academy of Medicine Cardiovascular Health Simulation model (an agent-based model) and data from the Behavioral Risk Factor Surveillance System were used to evaluate a lifestyle program that could be implemented in primary care practice settings. The program targeted Medicare-age adults and focused on improving diet and exercise and reducing weight.
Results:
The simulation results suggest that there would be significant reductions projected in the proportion of the Medicare-age population with diabetes after the implementation of the proposed lifestyle program for a relatively long term (3 and 5 years). Similar results were found for the subpopulations with high cholesterol, but the proposed intervention would not have a significant effect in the proportion of the population with hypertension over a time period of <5 years.
Conclusions:
Systems science methodologies can be useful to compare the health outcomes of different interventions. These tools can become an important component of population health management because they can help managers and other decision makers evaluate alternative programs in primary care settings.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><pmid>24879655</pmid><doi>10.1177/2150131914536400</doi><tpages>5</tpages><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 2150-1319 |
| ispartof | Journal of primary care & community health, 2014-10, Vol.5 (4), p.242-246 |
| issn | 2150-1319 2150-1327 |
| language | eng |
| recordid | cdi_doaj_primary_oai_doaj_org_article_291bf105574b46d3aee7093d1c7a1f25 |
| source | SAGE Journals Open Access |
| subjects | Aged Behavioral Risk Factor Surveillance System Cholesterol Clinical outcomes Decision makers Delivery of Health Care - organization & administration Diabetes Diabetes Mellitus - prevention & control Diet Disease Management Exercise Female Health care delivery Health status Humans Hypertension Intervention Life Style Lifestyles Male Medicare Overweight - prevention & control Population Primary care Primary Health Care - organization & administration Risk behavior Simulation Surveillance systems Systems science |
| title | Using Systems Science for Population Health Management in Primary Care |
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