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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Veröffentlicht in:Heart, lung & circulation lung & circulation, 2010-05, Vol.19 (5), p.378-383
Hauptverfasser: Kerr, Andrew J., MBChB, Looi, Jen Li, MBChB, Garofalo, Daniel, MBChB, Wells, Sue, MBChB, McLachlan, Andy, MN
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container_end_page 383
container_issue 5
container_start_page 378
container_title Heart, lung & circulation
container_volume 19
creator Kerr, Andrew J., MBChB
Looi, Jen Li, MBChB
Garofalo, Daniel, MBChB
Wells, Sue, MBChB
McLachlan, Andy, MN
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.
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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 &amp; 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 &amp; administration ; Program Evaluation ; Quality Control ; Quality improvement ; Secondary prevention</subject><ispartof>Heart, lung &amp; 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 &amp; 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. 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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 ; 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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 &amp; 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 &amp; 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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