Innovative Informatics Approaches for Peripheral Artery Disease: Current State and Provider Survey of Strategies for Improving Guideline-Based Care
Objective: To quantify compliance with guideline recommendations for secondary prevention in peripheral artery disease (PAD) using natural language processing (NLP) tools deployed to an electronic health record (EHR) and investigate provider opinions regarding clinical decision support (CDS) to prom...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2018-06-01
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| Series: | Mayo Clinic Proceedings: Innovations, Quality & Outcomes |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S254245481830016X |
| _version_ | 1828978326410100736 |
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| author | Alisha P. Chaudhry Naveed Afzal, PhD Mohamed M. Abidian, MD Vishnu Priya Mallipeddi, MBBS Ravikumar K. Elayavilli, PhD Christopher G. Scott, MS Iftikhar J. Kullo, MD Paul W. Wennberg, MD Joshua J. Pankratz, MS Hongfang Liu, PhD Rajeev Chaudhry, MBBS, MPH Adelaide M. Arruda-Olson, MD, PhD |
| author_facet | Alisha P. Chaudhry Naveed Afzal, PhD Mohamed M. Abidian, MD Vishnu Priya Mallipeddi, MBBS Ravikumar K. Elayavilli, PhD Christopher G. Scott, MS Iftikhar J. Kullo, MD Paul W. Wennberg, MD Joshua J. Pankratz, MS Hongfang Liu, PhD Rajeev Chaudhry, MBBS, MPH Adelaide M. Arruda-Olson, MD, PhD |
| author_sort | Alisha P. Chaudhry |
| collection | DOAJ |
| description | Objective: To quantify compliance with guideline recommendations for secondary prevention in peripheral artery disease (PAD) using natural language processing (NLP) tools deployed to an electronic health record (EHR) and investigate provider opinions regarding clinical decision support (CDS) to promote improved implementation of these strategies. Patients and Methods: Natural language processing was used for automated identification of moderate to severe PAD cases from narrative clinical notes of an EHR of patients seen in consultation from May 13, 2015, to July 27, 2015. Guideline-recommended strategies assessed within 6 months of PAD diagnosis included therapy with statins, antiplatelet agents, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and smoking abstention. Subsequently, a provider survey was used to assess provider knowledge regarding PAD clinical practice guidelines, comfort in recommending secondary prevention strategies, and potential role for CDS. Results: Among 73 moderate to severe PAD cases identified by NLP, only 12 (16%) were on 4 guideline-recommended strategies. A total of 207 of 760 (27%) providers responded to the survey; of these 141 (68%) were generalists and 66 (32%) were specialists. Although 183 providers (88%) managed patients with PAD, 51 (25%) indicated they were uncomfortable doing so; 138 providers (67%) favored the development of a CDS system tailored for their practice and 146 (71%) agreed that an automated EHR-derived mortality risk score calculator for patients with PAD would be helpful. Conclusion: Natural language processing tools can identify cases from EHRs to support quality metric studies. Findings of this pilot study demonstrate gaps in application of guideline-recommended strategies for secondary risk prevention for patients with moderate to severe PAD. Providers strongly support the development of CDS systems tailored to assist them in providing evidence-based care to patients with PAD at the point of care. |
| first_indexed | 2024-12-14T15:15:57Z |
| format | Article |
| id | doaj.art-608f110d178a48878b40466bc46ef02f |
| institution | Directory Open Access Journal |
| issn | 2542-4548 |
| language | English |
| last_indexed | 2024-12-14T15:15:57Z |
| publishDate | 2018-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Mayo Clinic Proceedings: Innovations, Quality & Outcomes |
| spelling | doaj.art-608f110d178a48878b40466bc46ef02f2022-12-21T22:56:20ZengElsevierMayo Clinic Proceedings: Innovations, Quality & Outcomes2542-45482018-06-0122129136Innovative Informatics Approaches for Peripheral Artery Disease: Current State and Provider Survey of Strategies for Improving Guideline-Based CareAlisha P. Chaudhry0Naveed Afzal, PhD1Mohamed M. Abidian, MD2Vishnu Priya Mallipeddi, MBBS3Ravikumar K. Elayavilli, PhD4Christopher G. Scott, MS5Iftikhar J. Kullo, MD6Paul W. Wennberg, MD7Joshua J. Pankratz, MS8Hongfang Liu, PhD9Rajeev Chaudhry, MBBS, MPH10Adelaide M. Arruda-Olson, MD, PhD11Department of Cardiovascular Diseases, Mayo Clinic and Mayo Foundation, Rochester, MNDepartment of Health Sciences Research, Mayo Clinic and Mayo Foundation, Rochester, MNDepartment of Cardiovascular Diseases, Mayo Clinic and Mayo Foundation, Rochester, MNDepartment of Cardiovascular Diseases, Mayo Clinic and Mayo Foundation, Rochester, MNDepartment of Health Sciences Research, Mayo Clinic and Mayo Foundation, Rochester, MNDepartment of Health Sciences Research, Mayo Clinic and Mayo Foundation, Rochester, MNDepartment of Cardiovascular Diseases, Mayo Clinic and Mayo Foundation, Rochester, MNDepartment of Cardiovascular Diseases, Mayo Clinic and Mayo Foundation, Rochester, MNDepartment of Information Technology, Mayo Clinic and Mayo Foundation, Rochester, MNDepartment of Health Sciences Research, Mayo Clinic and Mayo Foundation, Rochester, MNDepartment of Primary Care Internal Medicine, Mayo Clinic and Mayo Foundation, Rochester, MN; Center for Translational Informatics and Knowledge Management, Mayo Clinic and Mayo Foundation, Rochester, MNDepartment of Cardiovascular Diseases, Mayo Clinic and Mayo Foundation, Rochester, MN; Correspondence: Address to Adelaide M. Arruda-Olson, MD, PhD, Department of Cardiovascular Diseases, Mayo Clinic, 200 First Street SW, Rochester, MN 55905.Objective: To quantify compliance with guideline recommendations for secondary prevention in peripheral artery disease (PAD) using natural language processing (NLP) tools deployed to an electronic health record (EHR) and investigate provider opinions regarding clinical decision support (CDS) to promote improved implementation of these strategies. Patients and Methods: Natural language processing was used for automated identification of moderate to severe PAD cases from narrative clinical notes of an EHR of patients seen in consultation from May 13, 2015, to July 27, 2015. Guideline-recommended strategies assessed within 6 months of PAD diagnosis included therapy with statins, antiplatelet agents, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and smoking abstention. Subsequently, a provider survey was used to assess provider knowledge regarding PAD clinical practice guidelines, comfort in recommending secondary prevention strategies, and potential role for CDS. Results: Among 73 moderate to severe PAD cases identified by NLP, only 12 (16%) were on 4 guideline-recommended strategies. A total of 207 of 760 (27%) providers responded to the survey; of these 141 (68%) were generalists and 66 (32%) were specialists. Although 183 providers (88%) managed patients with PAD, 51 (25%) indicated they were uncomfortable doing so; 138 providers (67%) favored the development of a CDS system tailored for their practice and 146 (71%) agreed that an automated EHR-derived mortality risk score calculator for patients with PAD would be helpful. Conclusion: Natural language processing tools can identify cases from EHRs to support quality metric studies. Findings of this pilot study demonstrate gaps in application of guideline-recommended strategies for secondary risk prevention for patients with moderate to severe PAD. Providers strongly support the development of CDS systems tailored to assist them in providing evidence-based care to patients with PAD at the point of care.http://www.sciencedirect.com/science/article/pii/S254245481830016X |
| spellingShingle | Alisha P. Chaudhry Naveed Afzal, PhD Mohamed M. Abidian, MD Vishnu Priya Mallipeddi, MBBS Ravikumar K. Elayavilli, PhD Christopher G. Scott, MS Iftikhar J. Kullo, MD Paul W. Wennberg, MD Joshua J. Pankratz, MS Hongfang Liu, PhD Rajeev Chaudhry, MBBS, MPH Adelaide M. Arruda-Olson, MD, PhD Innovative Informatics Approaches for Peripheral Artery Disease: Current State and Provider Survey of Strategies for Improving Guideline-Based Care Mayo Clinic Proceedings: Innovations, Quality & Outcomes |
| title | Innovative Informatics Approaches for Peripheral Artery Disease: Current State and Provider Survey of Strategies for Improving Guideline-Based Care |
| title_full | Innovative Informatics Approaches for Peripheral Artery Disease: Current State and Provider Survey of Strategies for Improving Guideline-Based Care |
| title_fullStr | Innovative Informatics Approaches for Peripheral Artery Disease: Current State and Provider Survey of Strategies for Improving Guideline-Based Care |
| title_full_unstemmed | Innovative Informatics Approaches for Peripheral Artery Disease: Current State and Provider Survey of Strategies for Improving Guideline-Based Care |
| title_short | Innovative Informatics Approaches for Peripheral Artery Disease: Current State and Provider Survey of Strategies for Improving Guideline-Based Care |
| title_sort | innovative informatics approaches for peripheral artery disease current state and provider survey of strategies for improving guideline based care |
| url | http://www.sciencedirect.com/science/article/pii/S254245481830016X |
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