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Improving Diagnostic Fidelity: An Approach to Standardizing the Process in Patients With Emerging Critical Illness

OBJECTIVE: To reliably improve diagnostic fidelity and identify delays using a standardized approach applied to the electronic medical records of patients with emerging critical illness. PATIENTS AND METHODS: This retrospective observational study at Mayo Clinic, Rochester, Minnesota, conducted June...

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Autores principales: Jayaprakash, Namita, Chae, Junemee, Sabov, Moldovan, Samavedam, Sandhya, Gajic, Ognjen, Pickering, Brian W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713917/
https://www.ncbi.nlm.nih.gov/pubmed/31485571
http://dx.doi.org/10.1016/j.mayocpiqo.2019.06.001
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author Jayaprakash, Namita
Chae, Junemee
Sabov, Moldovan
Samavedam, Sandhya
Gajic, Ognjen
Pickering, Brian W.
author_facet Jayaprakash, Namita
Chae, Junemee
Sabov, Moldovan
Samavedam, Sandhya
Gajic, Ognjen
Pickering, Brian W.
author_sort Jayaprakash, Namita
collection PubMed
description OBJECTIVE: To reliably improve diagnostic fidelity and identify delays using a standardized approach applied to the electronic medical records of patients with emerging critical illness. PATIENTS AND METHODS: This retrospective observational study at Mayo Clinic, Rochester, Minnesota, conducted June 1, 2016, to June 30, 2017, used a standard operating procedure applied to electronic medical records to identify variations in diagnostic fidelity and/or delay in adult patients with a rapid response team evaluation, at risk for critical illness. Multivariate logistic regression analysis identified predictors and compared outcomes for those with and without varying diagnostic fidelity and/or delay. RESULTS: The sample included 130 patients. Median age was 65 years (interquartile range, 56-76 years), and 47.0% (52 of 130) were women. Clinically significant diagnostic error or delay was agreed in 23 (17.7%) patients (κ=0.57; 95% CI, 0.40-0.74). Median age was 65.4 years (interquartile range, 60.3-74.8) and 9 of the 23 (30.1%) were female. Of those with diagnostic error or delay, 60.9% (14 of 23) died in the hospital compared with 19.6% (21 of 107) without; P<.001. Diagnostic error or delay was associated with higher Charlson comorbidity index score, cardiac arrest triage score, and do not intubate/do not resuscitate status. Adjusting for age, do not intubate/do not resuscitate status, and Charlson comorbidity index score, diagnostic error or delay was associated with increased mortality; odds ratio, 5.7; 95% CI, 2.0-17.8. CONCLUSION: Diagnostic errors or delays can be reliably identified and are associated with higher comorbidity burden and increased mortality.
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spelling pubmed-67139172019-09-04 Improving Diagnostic Fidelity: An Approach to Standardizing the Process in Patients With Emerging Critical Illness Jayaprakash, Namita Chae, Junemee Sabov, Moldovan Samavedam, Sandhya Gajic, Ognjen Pickering, Brian W. Mayo Clin Proc Innov Qual Outcomes Original Article OBJECTIVE: To reliably improve diagnostic fidelity and identify delays using a standardized approach applied to the electronic medical records of patients with emerging critical illness. PATIENTS AND METHODS: This retrospective observational study at Mayo Clinic, Rochester, Minnesota, conducted June 1, 2016, to June 30, 2017, used a standard operating procedure applied to electronic medical records to identify variations in diagnostic fidelity and/or delay in adult patients with a rapid response team evaluation, at risk for critical illness. Multivariate logistic regression analysis identified predictors and compared outcomes for those with and without varying diagnostic fidelity and/or delay. RESULTS: The sample included 130 patients. Median age was 65 years (interquartile range, 56-76 years), and 47.0% (52 of 130) were women. Clinically significant diagnostic error or delay was agreed in 23 (17.7%) patients (κ=0.57; 95% CI, 0.40-0.74). Median age was 65.4 years (interquartile range, 60.3-74.8) and 9 of the 23 (30.1%) were female. Of those with diagnostic error or delay, 60.9% (14 of 23) died in the hospital compared with 19.6% (21 of 107) without; P<.001. Diagnostic error or delay was associated with higher Charlson comorbidity index score, cardiac arrest triage score, and do not intubate/do not resuscitate status. Adjusting for age, do not intubate/do not resuscitate status, and Charlson comorbidity index score, diagnostic error or delay was associated with increased mortality; odds ratio, 5.7; 95% CI, 2.0-17.8. CONCLUSION: Diagnostic errors or delays can be reliably identified and are associated with higher comorbidity burden and increased mortality. Elsevier 2019-07-19 /pmc/articles/PMC6713917/ /pubmed/31485571 http://dx.doi.org/10.1016/j.mayocpiqo.2019.06.001 Text en © 2019 THE AUTHORS https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Jayaprakash, Namita
Chae, Junemee
Sabov, Moldovan
Samavedam, Sandhya
Gajic, Ognjen
Pickering, Brian W.
Improving Diagnostic Fidelity: An Approach to Standardizing the Process in Patients With Emerging Critical Illness
title Improving Diagnostic Fidelity: An Approach to Standardizing the Process in Patients With Emerging Critical Illness
title_full Improving Diagnostic Fidelity: An Approach to Standardizing the Process in Patients With Emerging Critical Illness
title_fullStr Improving Diagnostic Fidelity: An Approach to Standardizing the Process in Patients With Emerging Critical Illness
title_full_unstemmed Improving Diagnostic Fidelity: An Approach to Standardizing the Process in Patients With Emerging Critical Illness
title_short Improving Diagnostic Fidelity: An Approach to Standardizing the Process in Patients With Emerging Critical Illness
title_sort improving diagnostic fidelity: an approach to standardizing the process in patients with emerging critical illness
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713917/
https://www.ncbi.nlm.nih.gov/pubmed/31485571
http://dx.doi.org/10.1016/j.mayocpiqo.2019.06.001
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