Discrepancy between admission diagnosis and discharge diagnosis in cardiovascular diseases: An analysis based on the groups of international classification disease, 10th revision

Document Type : Original Article

Authors

1 Department of Pathology Psychology, Zanjan University of medical sciences (ZUMS), Zanjan, Iran

2 Department of Education and Psychology, Islamic Azad University of Zanjan, Zanjan, Iran

3 Medical Informatics, Zanjan University of medical sciences (ZUMS), Zanjan, Iran

Abstract

Introduction: There is a significant relationship between the appropriate treatment plans and accurate medical diagnosis. Admission and discharge diagnoses in hospitals are often different and this has significant implications on patient care and safety. The aim of this study was to explore  the discrepancies between the admission diagnosis and the discharge diagnosis.
Method: This was a longitudinal study conducted at Zanjan University of Medical Sciences (ZUMS). The study sample included admitted patients in hospitals during 2012-2019. The ICD-10 codes between I00 and I99 were selected as Cardiovascular Diseases. Data analysis was conducted by R (v3.6.0) and Rstudio (v1.2.1335) software. Agreement analysis was conducted by Cohen’s Kappa statistics, and Chi Square statistic was used for examining the relationships between categorical variables.
Results: Agreement analysis of cardiovascular diseases subgroups showed that the values of Kappa coefficient range were varied between κ = 0.34 for Chronic rheumatic heart diseases and κ = 0.93 for Acute rheumatic fever diseases. The values of the Kappa coefficient for the 10 most common ICD-10 codes were in the range from κ = 0. 44 for I25.9 to κ = 0. 77 for I80.2.
Conclusion: The results of this study showed that there was a significant difference between ADx and DDx, and the values of kappa coefficient were not the same between CVDs subgroups. There are definite needs for improvement on diagnostic accuracy, especially in regard to CVDs cases with acute condition.

Keywords

References

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Health Management & Information Science
Volume 7, Issue 2
April 2020
Pages 100-106

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