Real-World Evidence of COVID-19 Patients’ Data Quality in the Electronic Health Records

Binkheder, Samar; Asiri, Mohammed Ahmed; Altowayan, Khaled Waleed; Alshehri, Turki Mohammed; Alzarie, Mashhour Faleh; Aldekhyyel, Raniah N.; Almaghlouth, Ibrahim A.; Almulhem, Jwaher A.

doi:10.3390/healthcare9121648

Open AccessArticle

Real-World Evidence of COVID-19 Patients’ Data Quality in the Electronic Health Records

by

Samar Binkheder

^1,*

,

Mohammed Ahmed Asiri

^1,2,

Khaled Waleed Altowayan

^1,2,

Turki Mohammed Alshehri

^1,2,

Mashhour Faleh Alzarie

^1,2,

Raniah N. Aldekhyyel

¹,

Ibrahim A. Almaghlouth

²

and

Jwaher A. Almulhem

¹

Medical Informatics and E-Learning Unit, Medical Education Department, College of Medicine, King Saud University, Riyadh 12372, Saudi Arabia

²

Department of Medicine, College of Medicine, King Saud University, Riyadh 12372, Saudi Arabia

^*

Author to whom correspondence should be addressed.

Healthcare 2021, 9(12), 1648; https://doi.org/10.3390/healthcare9121648

Submission received: 12 October 2021 / Revised: 18 November 2021 / Accepted: 25 November 2021 / Published: 28 November 2021

(This article belongs to the Special Issue Health Informatics: The Foundations of Public Health)

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Abstract

Despite the importance of electronic health records data, less attention has been given to data quality. This study aimed to evaluate the quality of COVID-19 patients’ records and their readiness for secondary use. We conducted a retrospective chart review study of all COVID-19 inpatients in an academic healthcare hospital for the year 2020, which were identified using ICD-10 codes and case definition guidelines. COVID-19 signs and symptoms were higher in unstructured clinical notes than in structured coded data. COVID-19 cases were categorized as 218 (66.46%) “confirmed cases”, 10 (3.05%) “probable cases”, 9 (2.74%) “suspected cases”, and 91 (27.74%) “no sufficient evidence”. The identification of “probable cases” and “suspected cases” was more challenging than “confirmed cases” where laboratory confirmation was sufficient. The accuracy of the COVID-19 case identification was higher in laboratory tests than in ICD-10 codes. When validating using laboratory results, we found that ICD-10 codes were inaccurately assigned to 238 (72.56%) patients’ records. “No sufficient evidence” records might indicate inaccurate and incomplete EHR data. Data quality evaluation should be incorporated to ensure patient safety and data readiness for secondary use research and predictive analytics. We encourage educational and training efforts to motivate healthcare providers regarding the importance of accurate documentation at the point-of-care.

Keywords: data quality; electronic health record; COVID-19; case identification; clinical documentation; medical informatics

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MDPI and ACS Style

Binkheder, S.; Asiri, M.A.; Altowayan, K.W.; Alshehri, T.M.; Alzarie, M.F.; Aldekhyyel, R.N.; Almaghlouth, I.A.; Almulhem, J.A. Real-World Evidence of COVID-19 Patients’ Data Quality in the Electronic Health Records. Healthcare 2021, 9, 1648. https://doi.org/10.3390/healthcare9121648

AMA Style

Binkheder S, Asiri MA, Altowayan KW, Alshehri TM, Alzarie MF, Aldekhyyel RN, Almaghlouth IA, Almulhem JA. Real-World Evidence of COVID-19 Patients’ Data Quality in the Electronic Health Records. Healthcare. 2021; 9(12):1648. https://doi.org/10.3390/healthcare9121648

Chicago/Turabian Style

Binkheder, Samar, Mohammed Ahmed Asiri, Khaled Waleed Altowayan, Turki Mohammed Alshehri, Mashhour Faleh Alzarie, Raniah N. Aldekhyyel, Ibrahim A. Almaghlouth, and Jwaher A. Almulhem. 2021. "Real-World Evidence of COVID-19 Patients’ Data Quality in the Electronic Health Records" Healthcare 9, no. 12: 1648. https://doi.org/10.3390/healthcare9121648

APA Style

Binkheder, S., Asiri, M. A., Altowayan, K. W., Alshehri, T. M., Alzarie, M. F., Aldekhyyel, R. N., Almaghlouth, I. A., & Almulhem, J. A. (2021). Real-World Evidence of COVID-19 Patients’ Data Quality in the Electronic Health Records. Healthcare, 9(12), 1648. https://doi.org/10.3390/healthcare9121648

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Real-World Evidence of COVID-19 Patients’ Data Quality in the Electronic Health Records

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