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.

Traditional Medicine Diagnostic Codes in ICD-11 and Alternative Diagnostic Classifications in the Mainstream Healthcare

In 2018,the 11^(th) Edition of the International Classification of Diseases(ICD-11)defined a diagnostic code list for standard traditional medicine(TM)conditions.The codes improve patient safety by providing more comprehensive and accurate medical records for hospitals in the Western Pacific Region.In these facilities,TM is often a standard of care for those populations.In several mainstream media sources,writers are circumventing evidence-based peer-reviewed medical literature by unduly influencing public opinion and,in this case,against the new ICD-11 codes.The dangers imposed by the transgression of popular writing onto the discipline of peer-reviewed works are present since best practices in medical record-keeping will fail without the inclusion of TM in the ICD-11 codes.Such failures directly affect the health of the patients and policymakers in regions where TM and conventional medicine are combined.This article investigates the boundaries between substantial evidence and popular opinion.In this era where media is used to manipulate evidence,the reader’s use of sound judgment and critical thought are thwarted.This article also challenges three controversial themes in pop literature,including the threat to endangered species,increased patient risk,and contaminants in the TM.These themes are made without evidence and are,in fact,of flawed logic.There is no reason to assume that improved medical record-keeping and knowledge of patient cases increase risks.

Operational definitions and measurement of externalizing behavior problems:An integrative review including research models and clinical diagnostic systems

Measurement of externalizing disorders such as antisocial disorders,attentiondeficit/hyperactivity disorder or borderline disorder have relevant implications for the daily lives of people with these disorders.While the Diagnostic and Statistical Manual of Mental Disorders(DSM)and the International Classification of Diseases(ICD)have provided the diagnostic framework for decades,recent dimensional frameworks question the categorical approach of psychopathology,inherent in traditional nosotaxies.Tests and instruments develop under the DSM or ICD framework preferentially adopt this categorical approach,providing diagnostic labels.In contrast,dimensional measurement instruments provide an individualized profile for the domains that comprise the externalizing spectrum,but are less widely used in practice.Current paper aims to review the operational definitions of externalizing disorders defined under these different frameworks,revise the different measurement alternatives existing,and provide an integrative operational definition.First,an analysis of the operational definition of externalizing disorders among the DSM/ICD diagnostic systems and the recent Hierarchical Taxonomy of Psychopathology(HiTOP)model is carried out.Then,in order to analyze the coverage of operational definitions found,a description of measurement instruments among each conceptualization is provided.Three phases in the development of the ICD and DSM diagnosis systems can be observed with direct implications for measurement.ICD and DSM versions have progressively introduced systematicity,providing more detailed descriptions of diagnostic criteria and categories that ease the measurement instrument development.However,it is questioned whether the DSM/ICD systems adequately modelize externalizing disorders,and therefore their measurement.More recent theoretical approaches,such as the HiTOP model seek to overcome some of the criticism raised towards the classification systems.Nevertheless,several issues concerning this model raise mesasurement challenges.A revision of the instruments underneath each approach shows incomplete coverage of externalizing disorders among the existing instruments.Efforts to bring nosotaxies together with other theoretical models of psychopathology and personality are still needed.The integrative operational definition of externalizing disorders provided may help to gather clinical practice and research.

Representation of Specific Diagnosis for Low Back Pain Using the 11^(th) Revision of International Classification of Diseases and Related Health Problems: Perspectives of Conventional Medicine and Traditional Medicine

Background:The 11th revision of the International Classification of Diseases and Related Health Problems(ICD-11)was released on June 18,2018,by the World Health Organization and will come into effect on January 1,2022.Apart from the chapters on the classification of diseases in the conventional medicine(CM),a new chapter,traditional medicine(TM)conditions–Module 1,was added.Low back pain(LBP)is one of the common reasons for the physician visits.The classification codes for LBP in the ICD-11 are vital to documenting accurate clinical diagnoses.Methods:The qualitative case study method was adopted.The secondary use data for 100 patients were randomly selected using the ICD-11 online interface to find the classification codes for both the CM section and the TM Conditions–Module 1(TM1)section for LBP diagnosis.Results:Of the 27 codes obtained from the CM section,six codes were not relevant to LBP,whereas the other 21 codes represented diagnoses of LBP and its related diseases or syndromes.In the TM1 section,six codes for different patterns and disorders represented the diagnoses for LBP from the TM perspective.Conclusion:This study indicates that specific diagnoses of LBP can be represented by the combination of CM classification codes and TM1 classification codes in the ICD-11;the CM codes represent specific and accurate clinical diagnoses for LBP,whereas the TM1 codes add more accuracy to the diagnoses of different patterns from the TM perspective.

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.

Impact of hospital type on risk-adjusted,traffic-related 30-day mortality:a population-based registry study

Background:Traffic incidents are still a major contributor to hospital admissions and trauma-related mortality.The aim of this nationwide study was to examine risk-adjusted traffic injury mortality to determine whether hospital type was an independent survival factor.Methods:Data on all patients admitted to Swedish hospitals with traffic-related injuries,based on International Classification of Diseases codes,between 2001 and 2011 were extracted from the Swedish inpatient and cause of death registries.Using the binary outcome measure of death or survival,data were analysed using logistic regression,adjusting for age,sex,comorbidity,severity of injury and hospital type.The severity of injury was established using the International Classification of Diseases Injury Severity Score(ICISS).Results:The final study population consisted of 152,693 hospital admissions.Young individuals(0–25 years of age)were overrepresented,accounting for 41%of traffic-related injuries.Men were overrepresented in all age categories.Fatalities at university hospitals had the lowest mean(SD)ICISS 0.68(0.19).Regional and county hospitals had mean ICISS 0.75(0.15)and 0.77(0.15),respectively,for fatal traffic incidents.The crude overall mortality in the study population was 1193,with a mean ICISS 0.72(0.17).Fatalities at university hospitals had the lowest mean ICISS 0.68(0.19).Regional and county hospitals had mean ICISS 0.75(0.15)and 0.77(0.15),respectively,for fatal traffic incidents.When regional and county hospitals were merged into one group and its risk-adjusted mortality compared with university hospitals,no significant difference was found.A comparison between hospital groups with the most severely injured patients(ICISS0.85)also did not show a significant difference(odds ratio,1.13;95%confidence interval,0.97–1.32).Conclusions:This study shows that,in Sweden,the type of hospital does not influence risk adjusted traffic related mortality,where the most severely injured patients are transported to the university hospitals and centralization of treatment is common.