Cargando…

Accuracy of the electronic health record’s problem list in describing multimorbidity in patients with heart failure in the emergency department

Patients with heart failure (HF) often suffer from multimorbidity. Rapid assessment of multimorbidity is important for minimizing the risk of harmful drug-disease and drug-drug interactions. We assessed the accuracy of using the electronic health record (EHR) problem list to identify comorbid condit...

Descripción completa

Detalles Bibliográficos
Autores principales: King, Brandon L., Meyer, Michelle L., Chari, Srihari V., Hurka-Richardson, Karen, Bohrmann, Thomas, Chang, Patricia P., Rodgers, Jo Ellen, Busby-Whitehead, Jan, Casey, Martin F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747000/
https://www.ncbi.nlm.nih.gov/pubmed/36512600
http://dx.doi.org/10.1371/journal.pone.0279033
_version_ 1784849491876118528
author King, Brandon L.
Meyer, Michelle L.
Chari, Srihari V.
Hurka-Richardson, Karen
Bohrmann, Thomas
Chang, Patricia P.
Rodgers, Jo Ellen
Busby-Whitehead, Jan
Casey, Martin F.
author_facet King, Brandon L.
Meyer, Michelle L.
Chari, Srihari V.
Hurka-Richardson, Karen
Bohrmann, Thomas
Chang, Patricia P.
Rodgers, Jo Ellen
Busby-Whitehead, Jan
Casey, Martin F.
author_sort King, Brandon L.
collection PubMed
description Patients with heart failure (HF) often suffer from multimorbidity. Rapid assessment of multimorbidity is important for minimizing the risk of harmful drug-disease and drug-drug interactions. We assessed the accuracy of using the electronic health record (EHR) problem list to identify comorbid conditions among patients with chronic HF in the emergency department (ED). A retrospective chart review study was performed on a random sample of 200 patients age ≥65 years with a diagnosis of HF presenting to an academic ED in 2019. We assessed participant chronic conditions using: (1) structured chart review (gold standard) and (2) an EHR-based algorithm using the problem list. Chronic conditions were classified into 37 disease domains using the Agency for Healthcare Research Quality’s Elixhauser Comorbidity Software. For each disease domain, we report the sensitivity, specificity, positive predictive value, and negative predictive of using an EHR-based algorithm. We calculated the intra-class correlation coefficient (ICC) to assess overall agreement on Elixhauser domain count between chart review and problem list. Patients with HF had a mean of 5.4 chronic conditions (SD 2.1) in the chart review and a mean of 4.1 chronic conditions (SD 2.1) in the EHR-based problem list. The five most prevalent domains were uncomplicated hypertension (90%), obesity (42%), chronic pulmonary disease (38%), deficiency anemias (33%), and diabetes with chronic complications (30.5%). The positive predictive value and negative predictive value of using the EHR-based problem list was greater than 90% for 24/37 and 32/37 disease domains, respectively. The EHR-based problem list correctly identified 3.7 domains per patient and misclassified 2.0 domains per patient. Overall, the ICC in comparing Elixhauser domain count was 0.77 (95% CI: 0.71-0.82). The EHR-based problem list captures multimorbidity with moderate-to-good accuracy in patient with HF in the ED.
format Online
Article
Text
id pubmed-9747000
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-97470002022-12-14 Accuracy of the electronic health record’s problem list in describing multimorbidity in patients with heart failure in the emergency department King, Brandon L. Meyer, Michelle L. Chari, Srihari V. Hurka-Richardson, Karen Bohrmann, Thomas Chang, Patricia P. Rodgers, Jo Ellen Busby-Whitehead, Jan Casey, Martin F. PLoS One Research Article Patients with heart failure (HF) often suffer from multimorbidity. Rapid assessment of multimorbidity is important for minimizing the risk of harmful drug-disease and drug-drug interactions. We assessed the accuracy of using the electronic health record (EHR) problem list to identify comorbid conditions among patients with chronic HF in the emergency department (ED). A retrospective chart review study was performed on a random sample of 200 patients age ≥65 years with a diagnosis of HF presenting to an academic ED in 2019. We assessed participant chronic conditions using: (1) structured chart review (gold standard) and (2) an EHR-based algorithm using the problem list. Chronic conditions were classified into 37 disease domains using the Agency for Healthcare Research Quality’s Elixhauser Comorbidity Software. For each disease domain, we report the sensitivity, specificity, positive predictive value, and negative predictive of using an EHR-based algorithm. We calculated the intra-class correlation coefficient (ICC) to assess overall agreement on Elixhauser domain count between chart review and problem list. Patients with HF had a mean of 5.4 chronic conditions (SD 2.1) in the chart review and a mean of 4.1 chronic conditions (SD 2.1) in the EHR-based problem list. The five most prevalent domains were uncomplicated hypertension (90%), obesity (42%), chronic pulmonary disease (38%), deficiency anemias (33%), and diabetes with chronic complications (30.5%). The positive predictive value and negative predictive value of using the EHR-based problem list was greater than 90% for 24/37 and 32/37 disease domains, respectively. The EHR-based problem list correctly identified 3.7 domains per patient and misclassified 2.0 domains per patient. Overall, the ICC in comparing Elixhauser domain count was 0.77 (95% CI: 0.71-0.82). The EHR-based problem list captures multimorbidity with moderate-to-good accuracy in patient with HF in the ED. Public Library of Science 2022-12-13 /pmc/articles/PMC9747000/ /pubmed/36512600 http://dx.doi.org/10.1371/journal.pone.0279033 Text en © 2022 King et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
King, Brandon L.
Meyer, Michelle L.
Chari, Srihari V.
Hurka-Richardson, Karen
Bohrmann, Thomas
Chang, Patricia P.
Rodgers, Jo Ellen
Busby-Whitehead, Jan
Casey, Martin F.
Accuracy of the electronic health record’s problem list in describing multimorbidity in patients with heart failure in the emergency department
title Accuracy of the electronic health record’s problem list in describing multimorbidity in patients with heart failure in the emergency department
title_full Accuracy of the electronic health record’s problem list in describing multimorbidity in patients with heart failure in the emergency department
title_fullStr Accuracy of the electronic health record’s problem list in describing multimorbidity in patients with heart failure in the emergency department
title_full_unstemmed Accuracy of the electronic health record’s problem list in describing multimorbidity in patients with heart failure in the emergency department
title_short Accuracy of the electronic health record’s problem list in describing multimorbidity in patients with heart failure in the emergency department
title_sort accuracy of the electronic health record’s problem list in describing multimorbidity in patients with heart failure in the emergency department
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747000/
https://www.ncbi.nlm.nih.gov/pubmed/36512600
http://dx.doi.org/10.1371/journal.pone.0279033
work_keys_str_mv AT kingbrandonl accuracyoftheelectronichealthrecordsproblemlistindescribingmultimorbidityinpatientswithheartfailureintheemergencydepartment
AT meyermichellel accuracyoftheelectronichealthrecordsproblemlistindescribingmultimorbidityinpatientswithheartfailureintheemergencydepartment
AT charisrihariv accuracyoftheelectronichealthrecordsproblemlistindescribingmultimorbidityinpatientswithheartfailureintheemergencydepartment
AT hurkarichardsonkaren accuracyoftheelectronichealthrecordsproblemlistindescribingmultimorbidityinpatientswithheartfailureintheemergencydepartment
AT bohrmannthomas accuracyoftheelectronichealthrecordsproblemlistindescribingmultimorbidityinpatientswithheartfailureintheemergencydepartment
AT changpatriciap accuracyoftheelectronichealthrecordsproblemlistindescribingmultimorbidityinpatientswithheartfailureintheemergencydepartment
AT rodgersjoellen accuracyoftheelectronichealthrecordsproblemlistindescribingmultimorbidityinpatientswithheartfailureintheemergencydepartment
AT busbywhiteheadjan accuracyoftheelectronichealthrecordsproblemlistindescribingmultimorbidityinpatientswithheartfailureintheemergencydepartment
AT caseymartinf accuracyoftheelectronichealthrecordsproblemlistindescribingmultimorbidityinpatientswithheartfailureintheemergencydepartment