Automated ICD Coding of Primary Diagnosis Based on Machine Learning

National Center for Cardiovascular Diseases

Status: Unknown

Conditions: Cardiovascular Diseases

Treatments: Other: No intervention

Study type: Observational

Funder types: Other

Identifiers

NCT04817423

2021-1425

Details and patient eligibility

About

This study aims to develop and validate machine learning model in ICD-10 coding of primary diagnosis related to cardiovascular diseases in Chinese corpus.

Full description

The accuracy and productivity of ICD coding has always been a concern of clinical practice. Errors of ICD codes may result in claim denials and missed revenue. However, ICD coding process is complex, time-consuming and error-prone. More experienced coders are in need, but there is an increasing lack of supply. Automated ICD coding has potential to facilitate clinical coders for improved efficiency and quality. Model performance of related studies is still far below coders and both the accuracy and interpretability need to be improved in great demand. Besides, studies in Chinese corpus are not sufficient.

In this study, the investigators will implement automated ICD coding study based on inpatient' data collected from electronic medical records from Fuwai Hospital, the world's largest medical center for cardiovascular disease. Feature engineering and machine learning methods will be used to develop classification models with good performance, interpretability and practicability for ICD codes of primary diagnosis.

Enrollment: 74,880 estimated patients

Sex: All

Volunteers: No Healthy Volunteers

Inclusion criteria

• Admissions in Fuwai Hospital, from January 1, 2019, to December 31, 2020

Exclusion criteria

• Admissions stayed in nephrology department, Fuwai Hospital

Trial design

74,880 participants in 1 patient group

Model training and test group

Description:

Data set will be split into training group and test group, where training group will be used for model building, and test group for subsequent evaluation and verification.

Treatment:

Other: No intervention