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Optimisation of lipids for prevention of cardiovascular disease in a primary care
The 2013 American College of Cardiology/American Heart Association (ACC/AHA) guidelines focus on atherosclerotic cardiovascular disease (ASCVD) risk reduction, using a Pooled Cohort Equation to calculate a patient’s 10-year risk score, which is used to guide initiation of statin therapy. We identifi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6109820/ https://www.ncbi.nlm.nih.gov/pubmed/30167469 http://dx.doi.org/10.1136/bmjoq-2017-000071 |
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author | Bakhai, Smita Bhardwaj, Aishwarya Sandhu, Parteet Reynolds, Jessica L. |
author_facet | Bakhai, Smita Bhardwaj, Aishwarya Sandhu, Parteet Reynolds, Jessica L. |
author_sort | Bakhai, Smita |
collection | PubMed |
description | The 2013 American College of Cardiology/American Heart Association (ACC/AHA) guidelines focus on atherosclerotic cardiovascular disease (ASCVD) risk reduction, using a Pooled Cohort Equation to calculate a patient’s 10-year risk score, which is used to guide initiation of statin therapy. We identified a gap of evidence-based treatment for hyperlipidaemia in the Internal Medicine Clinic. Therefore, the aim of this study was to increase calculation of ASCVD risk scores in patients between the ages of 40 and 75 years from a baseline rate of less than 1% to 10%, within 12 months, for primary prevention of ASCVD. Root cause analysis was performed to identify materials/methods, provider and patient-related barriers. Plan-Do-Study-Act cycles included: (1) creation of customised workflow in electronic health records for documentation of calculated ASCVD risk score; (2) physician education regarding guidelines and electronic health record workflow; (3) refresher training for residents and a chart alert and (4) patient education and physician reminders. The outcome measures were ASCVD risk score completion rate and percentage of new prescriptions for statin therapy. Process measures included lipid profile order and completion rates. Increase in patient wait time, and blood test and medications costs were the balanced measures. We used weekly statistical process control charts for data analysis. The average ASCVD risk completion rate was 14.2%. The mean ASCVD risk completion rate was 4.0%. In eligible patients, the average lipid profile completion rate was 18%. ASCVD risk score completion rate was 33% 1-year postproject period. A team-based approach led to a sustainable increase in ASCVD risk score completion rate. Lack of automation in ASCVD risk score calculation and physician prompts in electronic health records were identified as major barriers. Furthermore, the team identified multiple barriers to lipid blood tests and treatment of increased ASCVD risk based on ACC/AHA guidelines. |
format | Online Article Text |
id | pubmed-6109820 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-61098202018-08-30 Optimisation of lipids for prevention of cardiovascular disease in a primary care Bakhai, Smita Bhardwaj, Aishwarya Sandhu, Parteet Reynolds, Jessica L. BMJ Open Qual Original Article The 2013 American College of Cardiology/American Heart Association (ACC/AHA) guidelines focus on atherosclerotic cardiovascular disease (ASCVD) risk reduction, using a Pooled Cohort Equation to calculate a patient’s 10-year risk score, which is used to guide initiation of statin therapy. We identified a gap of evidence-based treatment for hyperlipidaemia in the Internal Medicine Clinic. Therefore, the aim of this study was to increase calculation of ASCVD risk scores in patients between the ages of 40 and 75 years from a baseline rate of less than 1% to 10%, within 12 months, for primary prevention of ASCVD. Root cause analysis was performed to identify materials/methods, provider and patient-related barriers. Plan-Do-Study-Act cycles included: (1) creation of customised workflow in electronic health records for documentation of calculated ASCVD risk score; (2) physician education regarding guidelines and electronic health record workflow; (3) refresher training for residents and a chart alert and (4) patient education and physician reminders. The outcome measures were ASCVD risk score completion rate and percentage of new prescriptions for statin therapy. Process measures included lipid profile order and completion rates. Increase in patient wait time, and blood test and medications costs were the balanced measures. We used weekly statistical process control charts for data analysis. The average ASCVD risk completion rate was 14.2%. The mean ASCVD risk completion rate was 4.0%. In eligible patients, the average lipid profile completion rate was 18%. ASCVD risk score completion rate was 33% 1-year postproject period. A team-based approach led to a sustainable increase in ASCVD risk score completion rate. Lack of automation in ASCVD risk score calculation and physician prompts in electronic health records were identified as major barriers. Furthermore, the team identified multiple barriers to lipid blood tests and treatment of increased ASCVD risk based on ACC/AHA guidelines. BMJ Publishing Group 2018-08-13 /pmc/articles/PMC6109820/ /pubmed/30167469 http://dx.doi.org/10.1136/bmjoq-2017-000071 Text en © Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Original Article Bakhai, Smita Bhardwaj, Aishwarya Sandhu, Parteet Reynolds, Jessica L. Optimisation of lipids for prevention of cardiovascular disease in a primary care |
title | Optimisation of lipids for prevention of cardiovascular disease in a primary care |
title_full | Optimisation of lipids for prevention of cardiovascular disease in a primary care |
title_fullStr | Optimisation of lipids for prevention of cardiovascular disease in a primary care |
title_full_unstemmed | Optimisation of lipids for prevention of cardiovascular disease in a primary care |
title_short | Optimisation of lipids for prevention of cardiovascular disease in a primary care |
title_sort | optimisation of lipids for prevention of cardiovascular disease in a primary care |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6109820/ https://www.ncbi.nlm.nih.gov/pubmed/30167469 http://dx.doi.org/10.1136/bmjoq-2017-000071 |
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