Adoption of network and plan-do-check-action in the international classification of disease 10 coding

BACKGROUND with the widespread application of computer network systems in the medical field,the plan-do-check-action(PDCA)and the international classification of diseases tenth edition(ICD-10)coding system have also achieved favorable results in clinical medical record management.However,research on their combined application is relatively lacking.Objective:it was to explore the impact of network systems and PDCA management mode on ICD-10 encoding.Material and Method:a retrospective collection of 768 discharged medical records from the Medical Record Management Department of Meishan People’s Hospital was conducted.They were divided into a control group(n=232)and an observation group(n=536)based on whether the PDCA management mode was implemented.The two sets of coding accuracy,time spent,case completion rate,satisfaction,and other indicators were compared.AIM To study the adoption of network and PDCA in the ICD-10.METHODS A retrospective collection of 768 discharged medical records from the Medical Record Management Department of Meishan People’s Hospital was conducted.They were divided into a control group(n=232)and an observation group(n=536)based on whether the PDCA management mode was implemented.The two sets of coding accuracy,time spent,case completion rate,satisfaction,and other indicators were compared.RESULTS In the 3,6,12,18,and 24 months of PDCA cycle management mode,the coding accuracy and medical record completion rate were higher,and the coding time was lower in the observation group as against the controls(P<0.05).The satisfaction of coders(80.22%vs 53.45%)and patients(84.89%vs 51.72%)in the observation group was markedly higher as against the controls(P<0.05).CONCLUSION The combination of computer networks and PDCA can improve the accuracy,efficiency,completion rate,and satisfaction of ICD-10 coding.

A survey of automated International Classification of Diseases coding:development,challenges,and applications

The International Classification of Diseases(ICD)is an international standard and tool for epidemiological in-vestigation,health management,and clinical diagnosis with a fundamental role in intelligent medical care.The assignment of ICD codes to health-related documents has become a focus of academic research,and numerous studies have developed the process of ICD coding from manual to automated work.In this survey,we review the developmental history of this task in recent decades in depth,from the rules-based stage,through the traditional machine learning stage,to the neural-network-based stage.Various methods have been introduced to solve this problem by using different techniques,and we report a performance comparison of different methods on the pub-licly available Medical Information Mart for Intensive Care dataset.Next,we summarize four major challenges of this task:(1)the large label space,(2)the unbalanced label distribution,(3)the long text of documents,and(4)the interpretability of coding.Various solutions that have been proposed to solve these problems are analyzed.Further,we discuss the applications of ICD coding,from mortality statistics to payments based on disease-related groups and hospital performance management.In addition,we discuss different ways of considering and evaluat-ing this task,and how it has been transformed into a learnable problem.We also provide details of the commonly used datasets.Overall,this survey aims to provide a reference and possible prospective directions for follow-up research work.