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Harnessing Event Report Data to Identify Diagnostic Error During the COVID-19 Pandemic.
Jt Comm J Qual Patient Saf ; 48(2): 71-80, 2022 02.
Article in English | MEDLINE | ID: covidwho-1487819
ABSTRACT

INTRODUCTION:

COVID-19 exposed systemic gaps with increased potential for diagnostic error. This project implemented a new approach leveraging electronic safety reporting to identify and categorize diagnostic errors during the pandemic.

METHODS:

All safety event reports from March 1, 2020, to February 28, 2021, at an academic medical center were evaluated using two complementary pathways (Pathway 1 all reports with explicit mention of COVID-19; Pathway 2 all reports without explicit mention of COVID-19 where natural language processing [NLP] plus logic-based stratification was applied to identify potential cases). Cases were evaluated by manual review to identify diagnostic error/delay and categorize error type using a recently proposed classification framework of eight categories of pandemic-related diagnostic errors.

RESULTS:

A total of 14,230 reports were included, with 95 (0.7%) identified as cases of diagnostic error/delay. Pathway 1 (n = 1,780 eligible reports) yielded 45 reports with diagnostic error/delay (positive predictive value [PPV] = 2.5%), of which 35.6% (16/45) were attributed to pandemic-related strain. In Pathway 2, the NLP-based algorithm flagged 110 safety reports for manual review from 12,450 eligible reports. Of these, 50 reports had diagnostic error/delay (PPV = 45.5%); 94.0% (47/50) were related to strain. Errors from all eight categories of the taxonomy were found on analysis.

CONCLUSION:

An event reporting-based strategy including use of simple-NLP-identified COVID-19-related diagnostic errors/delays uncovered several safety concerns related to COVID-19. An NLP-based approach can complement traditional reporting and be used as a just-in-time monitoring system to enable early detection of emerging risks from large volumes of safety reports.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Experimental Studies / Prognostic study Limits: Humans Language: English Journal: Jt Comm J Qual Patient Saf Journal subject: Health Services Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Experimental Studies / Prognostic study Limits: Humans Language: English Journal: Jt Comm J Qual Patient Saf Journal subject: Health Services Year: 2022 Document Type: Article