Computer-based patient data which are represented in a coded form have a variety of uses, including direct patient care, statistical reporting, automated decision support, and clinical research. No standard exists whi...
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Computer-based patient data which are represented in a coded form have a variety of uses, including direct patient care, statistical reporting, automated decision support, and clinical research. No standard exists which supports all of these functions. Abstracting coding systems, such as ICD, CPT, DRGs and MeSH fail to provide adequate detail, forcing application developers to create their own coding schemes for systems. Some of these schemes have been put forward as possible standards, but they have not been widely accepted. This paper reviews existing schemes used for abstracting, electronic record systems, and comprehensive coding. It also discusses the remaining impediments to acceptance of standards and the current efforts to overcome them, including SNOMED, the Gabrieli medical Nomenclature, the Read Clinical Codes, GALEN, and the Unified medical Language System (UMLS).
Objective The most important challenge in utilizing medicalrecord codes is the quality of coding data. The present study aims to investigate factors affecting the quality of diagnosis coding from different aspects co...
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Objective The most important challenge in utilizing medicalrecord codes is the quality of coding data. The present study aims to investigate factors affecting the quality of diagnosis coding from different aspects covering different stakeholders in a multi-dimensional approach. Methods First, we used Conventional Content Analysis to maximally gather all effective factors. As such, semi-structured interviews were conducted with medicalrecord coders (N = 32) at the referral hospitals in Mashhad, Iran. Second, 86 hospital staff members from 25 provinces were surveyed using a web-based questionnaire. Finally, a focus group discussion was conducted among coders (N = 18) in different hospitals across the country. Results In general, the barriers to quality of inpatient recordcoding can be classified into three categories: (I) physician-related, (II) coder-related, and (III) managerial, financial and administrative factors. Conclusion A triangulation view (related to coders, physicians as well as managerial, financial and administrative dimensions) could be used to identify the barriers affecting the quality of diagnosis coding data. The results of this study may help policymakers in development and implementation of appropriate strategies and effective interventions to improve the quality of clinical coding.
medical Concept coding (MCD) is a crucial task in biomedical information extraction. Recent advances in neural network modeling have demonstrated its usefulness in the task of natural language processing. Modern frame...
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ISBN:
(纸本)9783319989327;9783319989310
medical Concept coding (MCD) is a crucial task in biomedical information extraction. Recent advances in neural network modeling have demonstrated its usefulness in the task of natural language processing. Modern framework of sequence-to-sequence learning that was initially used for recurrent neural networks has been shown to provide powerful solution to tasks such as Named Entity Recognition or medical Concept coding. We have addressed the identification of clinical concepts within the International Classification of Diseases version 10 (ICD-10) in two benchmark data sets of death certificates provided for the task 1 in the CLEF eHealth shared task 2017. A proposed architecture combines ideas from recurrent neural networks and traditional text retrieval term weighting schemes. We found that our models reach accuracy of 75% and 86% as evaluated by the F-measure on the CepiDc corpus of French texts and on the CDC corpus of English texts, respectfully. The proposed models can be employed for coding electronic medicalrecords with ICD codes including diagnosis and procedure codes.
Background: Many outcome studies capture the presence of mental health, drug and alcohol comorbidities from administrative datasets and medicalrecords. How these sources compare as predictors of patient outcomes has ...
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Background: Many outcome studies capture the presence of mental health, drug and alcohol comorbidities from administrative datasets and medicalrecords. How these sources compare as predictors of patient outcomes has not been determined. The purpose of the present study was to compare mental health, drug and alcohol comorbidities based on ICD-10-AM coding and medicalrecord documentation for predicting longer-term outcomes in injured patients. Methods: A random sample of patients (n = 500) captured by the Victorian State Trauma Registry was selected for the study. Retrospective medicalrecord reviews were conducted to collect data about documented mental health, drug and alcohol comorbidities while ICD-10-AM codes were obtained from routinely collected hospital data. Outcomes at 12-months post-injury were the Glasgow Outcome Scale -Extended (GOS-E), European Quality of Life Five Dimensions (EQ-5D-3L), and return to work. Linear and logistic regression models, adjusted for age and gender, using medicalrecord derived comorbidity and ICD-10-AM were compared using measures of calibration (Hosmer-Lemeshow statistic) and discrimination (C-statistic and R-2). Results: There was no demonstrable difference in predictive performance between the medicalrecord and ICD-10-AM models for predicting the GOS-E, EQ-5D-3L utility sore and EQ-5D-3L mobility, self-care, usual activities and pain/discomfort items. The area under the receiver operating characteristic (AUC) for models using medicalrecord derived comorbidity (AUC 0.68, 95% CI: 0.63, 0.73) was higher than the model using ICD-10-AM data (AUC 0.62, 95% CI: 0.57, 0.67) for predicting the EQ-5D-3L anxiety/depression item. The discrimination of the model for predicting return to work was higher with inclusion of the medicalrecord data (AUC 0.69, 95% CI: 0.63, 0.76) than the ICD-10-AM data (AUC 0.59, 95% CL: 0.52, 0.65). Conclusions: Mental health, drug and alcohol comorbidity information derived from medicalrecord review was
Standard controlled medical vocabularies are typically based on a coding scheme, while medical informatics applications tend to have a more formal conceptual foundation. When such applications attempt to use data code...
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Standard controlled medical vocabularies are typically based on a coding scheme, while medical informatics applications tend to have a more formal conceptual foundation. When such applications attempt to use data coded with standard vocabularies, problems can arise when the standard vocabulary changes over time. A formal taxonomy is presented for describing the semantic changes which can occur in a vocabulary, such as simple addition, refinement, precoordination, disambiguation, redundancy, obsolescence, discovered redundancy, major name changes, minor name changes, code reuse, and changed codes. The taxonomy is described that used to effect change in one concept-based vocabulary (the medical Entities Dictionary), and the utility of the approach is demonstrated by applying it to the changes appearing in the 1994 release of the International Classification of Diseases, Ninth Edition, with Clinical Modifications (ICD-9-CM).
The disorder chapter of Version 3 of the Read codes is a rich source of clinically derived terminology. The file structure has been designed to meet a clinical need to support both enumerated and compositional taxonom...
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The disorder chapter of Version 3 of the Read codes is a rich source of clinically derived terminology. The file structure has been designed to meet a clinical need to support both enumerated and compositional taxonomy, This requirement coupled with the maintenance of multiple classification necessitates a mechanism to identify consistent hierarchical placement and equivalence between concepts. The early work on the semantic definition of the disorder chapter, to support these requirements, is outlined and the attributes that have been found to be important are presented. We also describe different categories of completeness of definition that have been identified, and the scope of those that are likely to remain incompletely characterised.
Computer-based patient data which are represented in a coded form have a variety of uses, including direct patient care, statistical reporting, automated decision support, and clinical research. No standard exists whi...
详细信息
Computer-based patient data which are represented in a coded form have a variety of uses, including direct patient care, statistical reporting, automated decision support, and clinical research. No standard exists which supports all of these functions. Abstracting coding systems, such as ICD, CPT, DRGs and MeSH fail to provide adequate detail, forcing application developers to create their own coding schemes for systems. Some of these schemes have been put forward as possible standards, but they have not been widely accepted. This paper reviews existing schemes used for abstracting, electronic record systems, and comprehensive coding. It also discusses the remaining impediments to acceptance of standards and the current efforts to overcome them, including SNOMED, the Gabrieli medical Nomenclature, the Read Clinical Codes, GALEN, and the Unified medical Language System (UMLS).
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