Acute Predict: A Clinician-Led Cardiovascular Disease Quality Improvement Project (Predict-CVD 12)
Background New Zealand data demonstrate major disparities in cardiovascular health, particularly by ethnicity and socioeconomic deprivation. Acute Predict Aim Acute Predict, the secondary care arm of primary care based PREDICT, is a multidisciplinary project based in the coronary care unit, and is j...
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description | Background New Zealand data demonstrate major disparities in cardiovascular health, particularly by ethnicity and socioeconomic deprivation. Acute Predict Aim Acute Predict, the secondary care arm of primary care based PREDICT, is a multidisciplinary project based in the coronary care unit, and is jointly led by nursing and medical staff. The project aim is to ensure patients with acute coronary syndromes (ACS) receive appropriate evidence-based secondary prevention management short- and long-term, regardless of age, socioeconomic status or ethnicity. Methods and Results Acute Predict utilises an electronic backbone to provide the following (1) guideline-based patient-specific decision support, (2) data collection as part of routine clinical workflow, (3) linkage of patients to cardiac rehabilitation and primary care chronic care management programs, (4) clinical and management data capture, (5) real-time whole group and sub-group Key Performance Indicators reporting with drill-down to individual patient data, and (6) long-term tracking of individual patient outcome via linkage to national databases. Over the four years of the project in-hospital provision of cardiac rehabilitation has improved and appropriate discharge medication is high. There are no differences according to ethnicity. Despite this, Maori patients in the Acute Predict ACS cohort are twice as likely as Europeans to have recurrent events post-discharge, even after adjustment for known risk factors. Conclusions The built-in real-time data reporting and outcomes/prescribing linkage facilitate monitoring of the quality of CVD prevention activity across the continuum of care. It allows early identification of treatment gaps and of persistent disparities in outcome in our patients. We are learning how best to use this real-time data collection and reporting to support the design and assessment of targeted interventions to close gaps and reduce disparity. |
doi_str_mv | 10.1016/j.hlc.2010.02.016 |
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Acute Predict Aim Acute Predict, the secondary care arm of primary care based PREDICT, is a multidisciplinary project based in the coronary care unit, and is jointly led by nursing and medical staff. The project aim is to ensure patients with acute coronary syndromes (ACS) receive appropriate evidence-based secondary prevention management short- and long-term, regardless of age, socioeconomic status or ethnicity. Methods and Results Acute Predict utilises an electronic backbone to provide the following (1) guideline-based patient-specific decision support, (2) data collection as part of routine clinical workflow, (3) linkage of patients to cardiac rehabilitation and primary care chronic care management programs, (4) clinical and management data capture, (5) real-time whole group and sub-group Key Performance Indicators reporting with drill-down to individual patient data, and (6) long-term tracking of individual patient outcome via linkage to national databases. Over the four years of the project in-hospital provision of cardiac rehabilitation has improved and appropriate discharge medication is high. There are no differences according to ethnicity. Despite this, Maori patients in the Acute Predict ACS cohort are twice as likely as Europeans to have recurrent events post-discharge, even after adjustment for known risk factors. Conclusions The built-in real-time data reporting and outcomes/prescribing linkage facilitate monitoring of the quality of CVD prevention activity across the continuum of care. It allows early identification of treatment gaps and of persistent disparities in outcome in our patients. We are learning how best to use this real-time data collection and reporting to support the design and assessment of targeted interventions to close gaps and reduce disparity.</description><identifier>ISSN: 1443-9506</identifier><identifier>ISSN: 1444-2892</identifier><identifier>EISSN: 1444-2892</identifier><identifier>DOI: 10.1016/j.hlc.2010.02.016</identifier><identifier>PMID: 20392667</identifier><language>eng</language><publisher>Australia: Elsevier B.V</publisher><subject>Acute coronary syndrome ; Acute Coronary Syndrome - diagnosis ; Acute Coronary Syndrome - mortality ; Acute Coronary Syndrome - therapy ; Cardiovascular ; Cardiovascular Diseases - diagnosis ; Cardiovascular Diseases - mortality ; Cardiovascular Diseases - therapy ; Clinical decision support system ; Databases, Factual ; Decision Support Systems, Clinical - organization & administration ; Disease Management ; Evidence-Based Medicine ; Female ; Health disparities ; Health Status Disparities ; Healthcare Disparities ; Humans ; Indigenous ; Male ; New Zealand ; Outcome Assessment, Health Care ; Physician's Role ; Population Groups ; Practice Patterns, Physicians' - standards ; Practice Patterns, Physicians' - trends ; Primary Health Care - organization & administration ; Program Evaluation ; Quality Control ; Quality improvement ; Secondary prevention</subject><ispartof>Heart, lung & circulation, 2010-05, Vol.19 (5), p.378-383</ispartof><rights>Australasian Society of Cardiac and Thoracic Surgeons and the Cardiac Society of Australia and New Zealand</rights><rights>2010 Australasian Society of Cardiac and Thoracic Surgeons and the Cardiac Society of Australia and New Zealand</rights><rights>Copyright 2010 Australasian Society of Cardiac and Thoracic Surgeons and the Cardiac Society of Australia and New Zealand. Published by Elsevier B.V. All rights reserved.</rights><rights>Copyright 2010 Australasian Society of Cardiac and Thoracic Surgeons and the Cardiac Society of Australia and New Zealand. Published by Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c407t-403c974ad353612ec373b6417e330586f063dd449a6c865fc99645ddadbf2ab3</citedby><cites>FETCH-LOGICAL-c407t-403c974ad353612ec373b6417e330586f063dd449a6c865fc99645ddadbf2ab3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.hlc.2010.02.016$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20392667$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kerr, Andrew J., MBChB</creatorcontrib><creatorcontrib>Looi, Jen Li, MBChB</creatorcontrib><creatorcontrib>Garofalo, Daniel, MBChB</creatorcontrib><creatorcontrib>Wells, Sue, MBChB</creatorcontrib><creatorcontrib>McLachlan, Andy, MN</creatorcontrib><title>Acute Predict: A Clinician-Led Cardiovascular Disease Quality Improvement Project (Predict-CVD 12)</title><title>Heart, lung & circulation</title><addtitle>Heart Lung Circ</addtitle><description>Background New Zealand data demonstrate major disparities in cardiovascular health, particularly by ethnicity and socioeconomic deprivation. Acute Predict Aim Acute Predict, the secondary care arm of primary care based PREDICT, is a multidisciplinary project based in the coronary care unit, and is jointly led by nursing and medical staff. The project aim is to ensure patients with acute coronary syndromes (ACS) receive appropriate evidence-based secondary prevention management short- and long-term, regardless of age, socioeconomic status or ethnicity. Methods and Results Acute Predict utilises an electronic backbone to provide the following (1) guideline-based patient-specific decision support, (2) data collection as part of routine clinical workflow, (3) linkage of patients to cardiac rehabilitation and primary care chronic care management programs, (4) clinical and management data capture, (5) real-time whole group and sub-group Key Performance Indicators reporting with drill-down to individual patient data, and (6) long-term tracking of individual patient outcome via linkage to national databases. Over the four years of the project in-hospital provision of cardiac rehabilitation has improved and appropriate discharge medication is high. There are no differences according to ethnicity. Despite this, Maori patients in the Acute Predict ACS cohort are twice as likely as Europeans to have recurrent events post-discharge, even after adjustment for known risk factors. Conclusions The built-in real-time data reporting and outcomes/prescribing linkage facilitate monitoring of the quality of CVD prevention activity across the continuum of care. It allows early identification of treatment gaps and of persistent disparities in outcome in our patients. We are learning how best to use this real-time data collection and reporting to support the design and assessment of targeted interventions to close gaps and reduce disparity.</description><subject>Acute coronary syndrome</subject><subject>Acute Coronary Syndrome - diagnosis</subject><subject>Acute Coronary Syndrome - mortality</subject><subject>Acute Coronary Syndrome - therapy</subject><subject>Cardiovascular</subject><subject>Cardiovascular Diseases - diagnosis</subject><subject>Cardiovascular Diseases - mortality</subject><subject>Cardiovascular Diseases - therapy</subject><subject>Clinical decision support system</subject><subject>Databases, Factual</subject><subject>Decision Support Systems, Clinical - organization & administration</subject><subject>Disease Management</subject><subject>Evidence-Based Medicine</subject><subject>Female</subject><subject>Health disparities</subject><subject>Health Status Disparities</subject><subject>Healthcare Disparities</subject><subject>Humans</subject><subject>Indigenous</subject><subject>Male</subject><subject>New Zealand</subject><subject>Outcome Assessment, Health Care</subject><subject>Physician's Role</subject><subject>Population Groups</subject><subject>Practice Patterns, Physicians' - standards</subject><subject>Practice Patterns, Physicians' - trends</subject><subject>Primary Health Care - organization & administration</subject><subject>Program Evaluation</subject><subject>Quality Control</subject><subject>Quality improvement</subject><subject>Secondary prevention</subject><issn>1443-9506</issn><issn>1444-2892</issn><issn>1444-2892</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kUtv1DAUhS0Eog_4AWyQd8Aiw_UjTgIS0ijlUWkkWlGxtRz7Rjjk0drJSPPv6-lMu2CBN7avzjmyv0PIGwYrBkx97FZ_ervikO7AV2nyjJwyKWXGy4o_fziLrMpBnZCzGDsAVkhRvSQnHETFlSpOSbO2y4z0KqDzdv5E17Tu_eitN2O2QUdrE5yftibapTeBXviIJiK9Xkzv5x29HG7DtMUBxzllTB3amb4_hmX17wvK-IdX5EVr-oivj_s5ufn29ab-kW1-fr-s15vMSijmTIKwVSGNE7lQjKMVhWiUZAUKAXmpWlDCOSkro2yp8tZWlZK5c8Y1LTeNOCfvDrHpRXcLxlkPPlrsezPitERdCAm8lDkkJTsobZhiDNjq2-AHE3aagd6D1Z1OYPUerAau0yR53h7Tl2ZA9-R4JJkEnw8CTF_cegw6Wo-jTShCoqLd5P8b_-Uft32owfR_cYexm5YwJnaa6ZgM-te-2X2xDNJSZS7uAd_Jm88</recordid><startdate>20100501</startdate><enddate>20100501</enddate><creator>Kerr, Andrew J., MBChB</creator><creator>Looi, Jen Li, MBChB</creator><creator>Garofalo, Daniel, MBChB</creator><creator>Wells, Sue, MBChB</creator><creator>McLachlan, Andy, MN</creator><general>Elsevier 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>7X8</scope></search><sort><creationdate>20100501</creationdate><title>Acute Predict: A Clinician-Led Cardiovascular Disease Quality Improvement Project (Predict-CVD 12)</title><author>Kerr, Andrew J., MBChB ; Looi, Jen Li, MBChB ; Garofalo, Daniel, MBChB ; Wells, Sue, MBChB ; McLachlan, Andy, MN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c407t-403c974ad353612ec373b6417e330586f063dd449a6c865fc99645ddadbf2ab3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Acute coronary syndrome</topic><topic>Acute Coronary Syndrome - diagnosis</topic><topic>Acute Coronary Syndrome - mortality</topic><topic>Acute Coronary Syndrome - therapy</topic><topic>Cardiovascular</topic><topic>Cardiovascular Diseases - diagnosis</topic><topic>Cardiovascular Diseases - mortality</topic><topic>Cardiovascular Diseases - therapy</topic><topic>Clinical decision support system</topic><topic>Databases, Factual</topic><topic>Decision Support Systems, Clinical - organization & administration</topic><topic>Disease Management</topic><topic>Evidence-Based Medicine</topic><topic>Female</topic><topic>Health disparities</topic><topic>Health Status Disparities</topic><topic>Healthcare Disparities</topic><topic>Humans</topic><topic>Indigenous</topic><topic>Male</topic><topic>New Zealand</topic><topic>Outcome Assessment, Health Care</topic><topic>Physician's Role</topic><topic>Population Groups</topic><topic>Practice Patterns, Physicians' - standards</topic><topic>Practice Patterns, Physicians' - trends</topic><topic>Primary Health Care - organization & administration</topic><topic>Program Evaluation</topic><topic>Quality Control</topic><topic>Quality improvement</topic><topic>Secondary prevention</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kerr, Andrew J., MBChB</creatorcontrib><creatorcontrib>Looi, Jen Li, MBChB</creatorcontrib><creatorcontrib>Garofalo, Daniel, MBChB</creatorcontrib><creatorcontrib>Wells, Sue, MBChB</creatorcontrib><creatorcontrib>McLachlan, Andy, MN</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>Heart, lung & circulation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kerr, Andrew J., MBChB</au><au>Looi, Jen Li, MBChB</au><au>Garofalo, Daniel, MBChB</au><au>Wells, Sue, MBChB</au><au>McLachlan, Andy, MN</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Acute Predict: A Clinician-Led Cardiovascular Disease Quality Improvement Project (Predict-CVD 12)</atitle><jtitle>Heart, lung & circulation</jtitle><addtitle>Heart Lung Circ</addtitle><date>2010-05-01</date><risdate>2010</risdate><volume>19</volume><issue>5</issue><spage>378</spage><epage>383</epage><pages>378-383</pages><issn>1443-9506</issn><issn>1444-2892</issn><eissn>1444-2892</eissn><abstract>Background New Zealand data demonstrate major disparities in cardiovascular health, particularly by ethnicity and socioeconomic deprivation. Acute Predict Aim Acute Predict, the secondary care arm of primary care based PREDICT, is a multidisciplinary project based in the coronary care unit, and is jointly led by nursing and medical staff. The project aim is to ensure patients with acute coronary syndromes (ACS) receive appropriate evidence-based secondary prevention management short- and long-term, regardless of age, socioeconomic status or ethnicity. Methods and Results Acute Predict utilises an electronic backbone to provide the following (1) guideline-based patient-specific decision support, (2) data collection as part of routine clinical workflow, (3) linkage of patients to cardiac rehabilitation and primary care chronic care management programs, (4) clinical and management data capture, (5) real-time whole group and sub-group Key Performance Indicators reporting with drill-down to individual patient data, and (6) long-term tracking of individual patient outcome via linkage to national databases. Over the four years of the project in-hospital provision of cardiac rehabilitation has improved and appropriate discharge medication is high. There are no differences according to ethnicity. Despite this, Maori patients in the Acute Predict ACS cohort are twice as likely as Europeans to have recurrent events post-discharge, even after adjustment for known risk factors. Conclusions The built-in real-time data reporting and outcomes/prescribing linkage facilitate monitoring of the quality of CVD prevention activity across the continuum of care. It allows early identification of treatment gaps and of persistent disparities in outcome in our patients. We are learning how best to use this real-time data collection and reporting to support the design and assessment of targeted interventions to close gaps and reduce disparity.</abstract><cop>Australia</cop><pub>Elsevier B.V</pub><pmid>20392667</pmid><doi>10.1016/j.hlc.2010.02.016</doi><tpages>6</tpages></addata></record> |
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subjects | Acute coronary syndrome Acute Coronary Syndrome - diagnosis Acute Coronary Syndrome - mortality Acute Coronary Syndrome - therapy Cardiovascular Cardiovascular Diseases - diagnosis Cardiovascular Diseases - mortality Cardiovascular Diseases - therapy Clinical decision support system Databases, Factual Decision Support Systems, Clinical - organization & administration Disease Management Evidence-Based Medicine Female Health disparities Health Status Disparities Healthcare Disparities Humans Indigenous Male New Zealand Outcome Assessment, Health Care Physician's Role Population Groups Practice Patterns, Physicians' - standards Practice Patterns, Physicians' - trends Primary Health Care - organization & administration Program Evaluation Quality Control Quality improvement Secondary prevention |
title | Acute Predict: A Clinician-Led Cardiovascular Disease Quality Improvement Project (Predict-CVD 12) |
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