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BMC Medical Informatics and Decision Making

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Open Access 01-12-2020 | Heart Failure | Research

Lab indicators standardization method for the regional healthcare platform: a case study on heart failure

Authors: Ming Liang, ZhiXing Zhang, JiaYing Zhang, Tong Ruan, Qi Ye, Ping He

Published in: BMC Medical Informatics and Decision Making | Special Issue 14/2020

Abstract

Background

Laboratory indicator test results in electronic health records have been applied to many clinical big data analysis. However, it is quite common that the same laboratory examination item (i.e., lab indicator) is presented using different names in Chinese due to the translation problem and the habit problem of various hospitals, which results in distortion of analysis results.

Methods

A framework with a recall model and a binary classification model is proposed, which could reduce the alignment scale and improve the accuracy of lab indicator normalization. To reduce alignment scale, tf-idf is used for candidate selection. To assure the accuracy of output, we utilize enhanced sequential inference model for binary classification. And active learning is applied with a selection strategy which is proposed for reducing annotation cost.

Results

Since our indicator standardization method mainly focuses on Chinese indicator inconsistency, we perform our experiment on Shanghai Hospital Development Center and select clinical data from 8 hospitals. The method achieves a F1-score 92.08\(\%\) in our final binary classification. As for active learning, the new strategy proposed performs better than random baseline and could outperform the result trained on full data with only 43\(\%\) training data. A case study on heart failure clinic analysis conducted on the sub-dataset collected from SHDC shows that our proposed method is practical in the application with good performance.

Conclusion

This work demonstrates that the structure we proposed can be effectively applied to lab indicator normalization. And active learning is also suitable for this task for cost reduction. Such a method is also valuable in data cleaning, data mining, text extracting and entity alignment.

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Title: Lab indicators standardization method for the regional healthcare platform: a case study on heart failure
Authors: Ming Liang
ZhiXing Zhang
JiaYing Zhang
Tong Ruan
Qi Ye
Ping He
Publication date: 01-12-2020
Publisher: BioMed Central
Keyword: Heart Failure
Published in: BMC Medical Informatics and Decision Making / Issue Special Issue 14/2020
Electronic ISSN: 1472-6947
DOI: https://doi.org/10.1186/s12911-020-01324-6

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Lab indicators standardization method for the regional healthcare platform: a case study on heart failure

Abstract

Background

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

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