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Conformance Analysis of Clinical Pathway Using Electronic Health Record Data

Overview of attention for article published in Healthcare Informatics Research, July 2015
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Title
Conformance Analysis of Clinical Pathway Using Electronic Health Record Data
Published in
Healthcare Informatics Research, July 2015
DOI 10.4258/hir.2015.21.3.161
Pubmed ID
Authors

Sooyoung Yoo, Minsu Cho, Seok Kim, Eunhye Kim, So Min Park, Kidong Kim, Hee Hwang, Minseok Song

Abstract

The objective of this study was to confirm the conformance rate of the actual usage of the clinical pathway (CP) using Electronic Health Record (EHR) log data in a tertiary general university hospital to improve the CP by reflecting real-world care processes. We analyzed the application and matching rates of clinicians' orders with predefined CP order sets based on data from 164 inpatients who received appendectomies out of all patients who were hospitalized from August 2013 to June 2014. We collected EHR log data on patient information, medication orders, operation performed, diagnosis, transfer, and CP order sets. The data were statistically analyzed. The average value of the actual application rate of the prescribed CP order ranged from 0.75 to 0.89. The application rate decreased when the order date was factored in along with the order code and type. Among CP pre-operation, intra-operation, post-operation, routine, and discharge orders, orders pertaining to operations had higher application rates than other types of orders. Routine orders and discharge orders had lower application rates. This analysis of the application and matching rates of CP orders suggests that it is possible to improve these rates by updating the existing CP order sets for routine discharge orders to reflect data-driven evidence. This study shows that it is possible to improve the application and matching rates of the CP using EHR log data. However, further research should be performed to analyze the effects of these rates on care outcomes.

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The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 15%
Student > Master 7 15%
Other 6 13%
Researcher 4 8%
Student > Postgraduate 4 8%
Other 8 17%
Unknown 12 25%
Readers by discipline Count As %
Computer Science 9 19%
Medicine and Dentistry 7 15%
Engineering 4 8%
Business, Management and Accounting 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Other 7 15%
Unknown 17 35%