Cargando…

Use and Customization of Risk Scores for Predicting Cardiovascular Events Using Electronic Health Record Data

BACKGROUND: Clinicians who are using the Framingham Risk Score (FRS) or the American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) to estimate risk for their patients based on electronic health data (EHD) face 4 questions. (1) Do published risk scores applied to EHD...

Descripción completa

Detalles Bibliográficos
Autores principales: Wolfson, Julian, Vock, David M., Bandyopadhyay, Sunayan, Kottke, Thomas, Vazquez‐Benitez, Gabriela, Johnson, Paul, Adomavicius, Gediminas, O'Connor, Patrick J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5532984/
https://www.ncbi.nlm.nih.gov/pubmed/28438733
http://dx.doi.org/10.1161/JAHA.116.003670
_version_ 1783253556194705408
author Wolfson, Julian
Vock, David M.
Bandyopadhyay, Sunayan
Kottke, Thomas
Vazquez‐Benitez, Gabriela
Johnson, Paul
Adomavicius, Gediminas
O'Connor, Patrick J.
author_facet Wolfson, Julian
Vock, David M.
Bandyopadhyay, Sunayan
Kottke, Thomas
Vazquez‐Benitez, Gabriela
Johnson, Paul
Adomavicius, Gediminas
O'Connor, Patrick J.
author_sort Wolfson, Julian
collection PubMed
description BACKGROUND: Clinicians who are using the Framingham Risk Score (FRS) or the American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) to estimate risk for their patients based on electronic health data (EHD) face 4 questions. (1) Do published risk scores applied to EHD yield accurate estimates of cardiovascular risk? (2) Are FRS risk estimates, which are based on data that are up to 45 years old, valid for a contemporary patient population seeking routine care? (3) Do the PCE make the FRS obsolete? (4) Does refitting the risk score using EHD improve the accuracy of risk estimates? METHODS AND RESULTS: Data were extracted from the EHD of 84 116 adults aged 40 to 79 years who received care at a large healthcare delivery and insurance organization between 2001 and 2011. We assessed calibration and discrimination for 4 risk scores: published versions of FRS and PCE and versions obtained by refitting models using a subset of the available EHD. The published FRS was well calibrated (calibration statistic K=9.1, miscalibration ranging from 0% to 17% across risk groups), but the PCE displayed modest evidence of miscalibration (calibration statistic K=43.7, miscalibration from 9% to 31%). Discrimination was similar in both models (C‐index=0.740 for FRS, 0.747 for PCE). Refitting the published models using EHD did not substantially improve calibration or discrimination. CONCLUSIONS: We conclude that published cardiovascular risk models can be successfully applied to EHD to estimate cardiovascular risk; the FRS remains valid and is not obsolete; and model refitting does not meaningfully improve the accuracy of risk estimates.
format Online
Article
Text
id pubmed-5532984
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-55329842017-08-14 Use and Customization of Risk Scores for Predicting Cardiovascular Events Using Electronic Health Record Data Wolfson, Julian Vock, David M. Bandyopadhyay, Sunayan Kottke, Thomas Vazquez‐Benitez, Gabriela Johnson, Paul Adomavicius, Gediminas O'Connor, Patrick J. J Am Heart Assoc Original Research BACKGROUND: Clinicians who are using the Framingham Risk Score (FRS) or the American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) to estimate risk for their patients based on electronic health data (EHD) face 4 questions. (1) Do published risk scores applied to EHD yield accurate estimates of cardiovascular risk? (2) Are FRS risk estimates, which are based on data that are up to 45 years old, valid for a contemporary patient population seeking routine care? (3) Do the PCE make the FRS obsolete? (4) Does refitting the risk score using EHD improve the accuracy of risk estimates? METHODS AND RESULTS: Data were extracted from the EHD of 84 116 adults aged 40 to 79 years who received care at a large healthcare delivery and insurance organization between 2001 and 2011. We assessed calibration and discrimination for 4 risk scores: published versions of FRS and PCE and versions obtained by refitting models using a subset of the available EHD. The published FRS was well calibrated (calibration statistic K=9.1, miscalibration ranging from 0% to 17% across risk groups), but the PCE displayed modest evidence of miscalibration (calibration statistic K=43.7, miscalibration from 9% to 31%). Discrimination was similar in both models (C‐index=0.740 for FRS, 0.747 for PCE). Refitting the published models using EHD did not substantially improve calibration or discrimination. CONCLUSIONS: We conclude that published cardiovascular risk models can be successfully applied to EHD to estimate cardiovascular risk; the FRS remains valid and is not obsolete; and model refitting does not meaningfully improve the accuracy of risk estimates. John Wiley and Sons Inc. 2017-04-24 /pmc/articles/PMC5532984/ /pubmed/28438733 http://dx.doi.org/10.1161/JAHA.116.003670 Text en © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial (http://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Research
Wolfson, Julian
Vock, David M.
Bandyopadhyay, Sunayan
Kottke, Thomas
Vazquez‐Benitez, Gabriela
Johnson, Paul
Adomavicius, Gediminas
O'Connor, Patrick J.
Use and Customization of Risk Scores for Predicting Cardiovascular Events Using Electronic Health Record Data
title Use and Customization of Risk Scores for Predicting Cardiovascular Events Using Electronic Health Record Data
title_full Use and Customization of Risk Scores for Predicting Cardiovascular Events Using Electronic Health Record Data
title_fullStr Use and Customization of Risk Scores for Predicting Cardiovascular Events Using Electronic Health Record Data
title_full_unstemmed Use and Customization of Risk Scores for Predicting Cardiovascular Events Using Electronic Health Record Data
title_short Use and Customization of Risk Scores for Predicting Cardiovascular Events Using Electronic Health Record Data
title_sort use and customization of risk scores for predicting cardiovascular events using electronic health record data
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5532984/
https://www.ncbi.nlm.nih.gov/pubmed/28438733
http://dx.doi.org/10.1161/JAHA.116.003670
work_keys_str_mv AT wolfsonjulian useandcustomizationofriskscoresforpredictingcardiovasculareventsusingelectronichealthrecorddata
AT vockdavidm useandcustomizationofriskscoresforpredictingcardiovasculareventsusingelectronichealthrecorddata
AT bandyopadhyaysunayan useandcustomizationofriskscoresforpredictingcardiovasculareventsusingelectronichealthrecorddata
AT kottkethomas useandcustomizationofriskscoresforpredictingcardiovasculareventsusingelectronichealthrecorddata
AT vazquezbenitezgabriela useandcustomizationofriskscoresforpredictingcardiovasculareventsusingelectronichealthrecorddata
AT johnsonpaul useandcustomizationofriskscoresforpredictingcardiovasculareventsusingelectronichealthrecorddata
AT adomaviciusgediminas useandcustomizationofriskscoresforpredictingcardiovasculareventsusingelectronichealthrecorddata
AT oconnorpatrickj useandcustomizationofriskscoresforpredictingcardiovasculareventsusingelectronichealthrecorddata