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Hude Quan - One of the best experts on this subject based on the ideXlab platform.
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systematic review and assessment of validated case definitions for depression in administrative data
BMC Psychiatry, 2014Co-Authors: Hude Quan, Nathalie Jette, Cynthia A Beck, Kirsten M Fiest, Christine St Germainesmith, Amy Metcalfe, Scott B PattenAbstract:Administrative data are increasingly used to conduct research on depression and inform health services and health policy. Depression surveillance using administrative data is an alternative to surveys, which can be more resource-intensive. The objectives of this study were to: (1) systematically review the literature on validated case definitions to identify depression using International Classification of Disease and Related Health Problems (ICD) codes in administrative data and (2) identify individuals with and without depression in administrative data and develop an enhanced case definition to identify persons with depression in ICD-coded hospital data. (1) Systematic review: We identified validation studies using ICD codes to indicate depression in administrative data up to January 2013. (2) Validation: All depression case definitions from the literature and an additional three ICD-9-CM and three ICD-10 enhanced definitions were tested in an inpatient database. The diagnostic accuracy of all case definitions was calculated [sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV)]. (1) Systematic review: Of 2,014 abstracts identified, 36 underwent full-text review and three met eligibility criteria. These depression studies used ICD-9 and ICD-10 case definitions. (2) Validation: 4,008 randomly selected medical charts were reviewed to assess the performance of new and previously published depression-related ICD case definitions. All newly tested case definitions resulted in Sp >99%, PPV >89% and NPV >91%. Sensitivities were low (28-35%), but higher than for case definitions identified in the literature (1.1-29.6%). Validating ICD-coded data for depression is important due to variation in coding practices across jurisdictions. The most suitable case definitions for detecting depression in administrative data vary depending on the context. For surveillance purposes, the most inclusive ICD-9 & ICD-10 case definitions resulted in PPVs of 89.7% and 89.5%, respectively. In cases where diagnostic certainty is required, the least inclusive ICD-9 and −10 case definitions are recommended, resulting in PPVs of 92.0% and 91.1%. All proposed case definitions resulted in suboptimal levels of sensitivity (ranging from 28.9%-35.6%). The addition of outpatient data (such as pharmacy records) for depression surveillance is recommended and should result in improved measures of validity.
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the development evolution and modifications of icd 10 challenges to the international comparability of morbidity data
Medical Care, 2010Co-Authors: Nathalie Jette, Hude Quan, Vijaya Sundararajan, Saskia E. Drösler, Lori Moskal, Brenda R Hemmelgarn, Christina Maass, Wansa Paoin, Song Gao, Robert JakobAbstract:Background:The United States is about to make a major nationwide transition from ICD-9-CM coding of hospital discharges to ICD-10-CM, a country-specific modification of the World Health Organization's ICD-10. As this transition occurs, the WHO is already in the midst of developing ICD-11. Given this
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assessing validity of icd 9 cm and icd 10 administrative data in recording clinical conditions in a unique dually coded database
Health Services Research, 2008Co-Authors: Hude Quan, Duncan L Saunders, Gerry A Parsons, Carolyn Nilsson, Arif Alibhai, William A GhaliAbstract:The World Health Organization adopted the first version of the International Classification of Diseases (ICD) in 1900 to internationally monitor and compare mortality statistics and causes of death. Since then, the classification has been revised periodically to accommodate new knowledge of disease and health. The sixth revision, published in 1949, was more radical than the previous five revisions because this edition made it possible to record information from patient charts to compile morbidity statistics. Subsequent revisions were made in 1958 (7th Edition), in 1968 (8th Edition), and in 1979 (9th Edition). The United States modified ICD-9 by specifying many categories and extending coding rubrics to describe the clinical picture in more detail. These modifications resulted in the publication of ICD-9 Clinical Modification (ICD-9-CM) in 1979 for coding diagnoses in patient charts (Commission on Professional and Hospital Activities 1986). The latest version, ICD-10, was introduced in 1992 (World Health Organization 1992). The major differences between the ICD-10 and ICD-9-CM coding systems are: (1) the tabular list in ICD-10 has 21 categories of disease compared with 19 categories in ICD-9-CM and the category of diseases of the nervous system and sense organs in ICD-9-CM is divided into three categories in ICD-10, including diseases of the nervous system, diseases of the eye and adnexa, and diseases of the ear and mastoid process; and (2) the codes in ICD-10 are alphanumeric while codes in ICD-9-CM are numeric. Each code in ICD-10 starts with a letter (i.e., A–Z), followed by two numeric digits, a decimal, and a digit (e.g., acute bronchiolitis due to respiratory syncytial virus is J21.0). In contrast, codes in ICD-9-CM begin with three digit numbers (i.e., 001–999), that are followed by a decimal and up to two digits (e.g., acute bronchiolitis due to respiratory syncytial virus is 466.11). Canada, Australia, Germany, and other countries have enhanced ICD-10 by adding more specific codes and released country-specific ICD-10 versions, such as ICD-10-Canada (ICD-10-CA; Canadian Institute for Health Information 2003). However, ICD-10-CA has maintained its comparability with ICD-10. The basic ICD-10 structure, scope, content, and definition of existing codes are not altered in ICD-10-CA. This means that none of the ICD-10 codes are relocated or deleted. ICD-10-CA mainly extends code character levels, from third and fourth levels of ICD-10 to fourth, fifth, or sixth character levels (e.g., from I15.0 for renovascular hypertension to I15.00 for benign renovascular hypertension and I15.01 for malignant renovascular hypertension). A few additions of third- and fourth-level codes were also included in ICD-10-CA in a manner consistent with the existing classification. All of these additional codes are indicated with red maple leaf symbols in ICD-10-CA coding manuals. To continuously study the health care system and investigate or monitor population health status with ICD-10 data, it is imperative to assess errors that could occur in the process of creating administrative data due to the introduction of the new coding system, ICD-10. We conducted this study to evaluate the validity of ICD-10 administrative hospital discharge data and to determine whether there were improvements in the validity compared with the validity of ICD-9-CM data. To achieve this aim, we reviewed randomly selected charts coded using ICD-10 at four Canadian teaching hospitals, determined the presence or absence of recorded conditions, and then separately recoded the same charts using ICD-9-CM. Then we assessed the agreement between originally coded ICD-10 administrative and chart review data, and the recoded ICD-9-CM administrative data and chart review data for recording the same conditions. This permitted us to compare the accuracy of ICD-10 data relative to the chart review data, with the accuracy of ICD-9-CM data relative to the chart review data for these conditions.
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an administrative data merging solution for dealing with missing data in a clinical registry adaptation from icd 9 to icd 10
BMC Medical Research Methodology, 2008Co-Authors: Danielle A. Southern, Hude Quan, Min Gao, Karin H Humphries, Colleen M Norris, Fiona M Shrive, Diane P Galbraith, Merril L KnudtsonAbstract:We have previously described a method for dealing with missing data in a prospective cardiac registry initiative. The method involves merging registry data to corresponding ICD-9-CM administrative data to fill in missing data 'holes'. Here, we describe the process of translating our data merging solution to ICD-10, and then validating its performance. A multi-step translation process was undertaken to produce an ICD-10 algorithm, and merging was then implemented to produce complete datasets for 1995–2001 based on the ICD-9-CM coding algorithm, and for 2002–2005 based on the ICD-10 algorithm. We used cardiac registry data for patients undergoing cardiac catheterization in fiscal years 1995–2005. The corresponding administrative data records were coded in ICD-9-CM for 1995–2001 and in ICD-10 for 2002–2005. The resulting datasets were then evaluated for their ability to predict death at one year. The prevalence of the individual clinical risk factors increased gradually across years. There was, however, no evidence of either an abrupt drop or rise in prevalence of any of the risk factors. The performance of the new data merging model was comparable to that of our previously reported methodology: c-statistic = 0.788 (95% CI 0.775, 0.802) for the ICD-10 model versus c-statistic = 0.784 (95% CI 0.780, 0.790) for the ICD-9-CM model. The two models also exhibited similar goodness-of-fit. The ICD-10 implementation of our data merging method performs as well as the previously-validated ICD-9-CM method. Such methodological research is an essential prerequisite for research with administrative data now that most health systems are transitioning to ICD-10.
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identifying priorities in methodological research using icd 9 cm and icd 10 administrative data report from an international consortium
BMC Health Services Research, 2006Co-Authors: Hude Quan, Carolyn De Coster, Alan Finlayson, Min Gao, Patricia Halfon, Karin H Humphries, Helen Johansen, Lisa M Lix, Jean Christophe LuthiAbstract:Background Health administrative data are frequently used for health services and population health research. Comparative research using these data has been facilitated by the use of a standard system for coding diagnoses, the International Classification of Diseases (ICD). Research using the data must deal with data quality and validity limitations which arise because the data are not created for research purposes. This paper presents a list of high-priority methodological areas for researchers using health administrative data.
William A Ghali - One of the best experts on this subject based on the ideXlab platform.
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assessing validity of icd 9 cm and icd 10 administrative data in recording clinical conditions in a unique dually coded database
Health Services Research, 2008Co-Authors: Hude Quan, Duncan L Saunders, Gerry A Parsons, Carolyn Nilsson, Arif Alibhai, William A GhaliAbstract:The World Health Organization adopted the first version of the International Classification of Diseases (ICD) in 1900 to internationally monitor and compare mortality statistics and causes of death. Since then, the classification has been revised periodically to accommodate new knowledge of disease and health. The sixth revision, published in 1949, was more radical than the previous five revisions because this edition made it possible to record information from patient charts to compile morbidity statistics. Subsequent revisions were made in 1958 (7th Edition), in 1968 (8th Edition), and in 1979 (9th Edition). The United States modified ICD-9 by specifying many categories and extending coding rubrics to describe the clinical picture in more detail. These modifications resulted in the publication of ICD-9 Clinical Modification (ICD-9-CM) in 1979 for coding diagnoses in patient charts (Commission on Professional and Hospital Activities 1986). The latest version, ICD-10, was introduced in 1992 (World Health Organization 1992). The major differences between the ICD-10 and ICD-9-CM coding systems are: (1) the tabular list in ICD-10 has 21 categories of disease compared with 19 categories in ICD-9-CM and the category of diseases of the nervous system and sense organs in ICD-9-CM is divided into three categories in ICD-10, including diseases of the nervous system, diseases of the eye and adnexa, and diseases of the ear and mastoid process; and (2) the codes in ICD-10 are alphanumeric while codes in ICD-9-CM are numeric. Each code in ICD-10 starts with a letter (i.e., A–Z), followed by two numeric digits, a decimal, and a digit (e.g., acute bronchiolitis due to respiratory syncytial virus is J21.0). In contrast, codes in ICD-9-CM begin with three digit numbers (i.e., 001–999), that are followed by a decimal and up to two digits (e.g., acute bronchiolitis due to respiratory syncytial virus is 466.11). Canada, Australia, Germany, and other countries have enhanced ICD-10 by adding more specific codes and released country-specific ICD-10 versions, such as ICD-10-Canada (ICD-10-CA; Canadian Institute for Health Information 2003). However, ICD-10-CA has maintained its comparability with ICD-10. The basic ICD-10 structure, scope, content, and definition of existing codes are not altered in ICD-10-CA. This means that none of the ICD-10 codes are relocated or deleted. ICD-10-CA mainly extends code character levels, from third and fourth levels of ICD-10 to fourth, fifth, or sixth character levels (e.g., from I15.0 for renovascular hypertension to I15.00 for benign renovascular hypertension and I15.01 for malignant renovascular hypertension). A few additions of third- and fourth-level codes were also included in ICD-10-CA in a manner consistent with the existing classification. All of these additional codes are indicated with red maple leaf symbols in ICD-10-CA coding manuals. To continuously study the health care system and investigate or monitor population health status with ICD-10 data, it is imperative to assess errors that could occur in the process of creating administrative data due to the introduction of the new coding system, ICD-10. We conducted this study to evaluate the validity of ICD-10 administrative hospital discharge data and to determine whether there were improvements in the validity compared with the validity of ICD-9-CM data. To achieve this aim, we reviewed randomly selected charts coded using ICD-10 at four Canadian teaching hospitals, determined the presence or absence of recorded conditions, and then separately recoded the same charts using ICD-9-CM. Then we assessed the agreement between originally coded ICD-10 administrative and chart review data, and the recoded ICD-9-CM administrative data and chart review data for recording the same conditions. This permitted us to compare the accuracy of ICD-10 data relative to the chart review data, with the accuracy of ICD-9-CM data relative to the chart review data for these conditions.
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coding algorithms for defining comorbidities in icd 9 cm and icd 10 administrative data
Medical Care, 2005Co-Authors: Hude Quan, Vijaya Sundararajan, Bernard Burnand, Patricia Halfon, Jean Christophe Luthi, Andrew Fong, Duncan L Saunders, Cynthia A Beck, Thomas E Feasby, William A GhaliAbstract:Objectives:Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define C
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new icd 10 version of the charlson comorbidity index predicted in hospital mortality
Journal of Clinical Epidemiology, 2004Co-Authors: Vijaya Sundararajan, Hude Quan, Toni Henderson, Catherine Perry, Amanda Muggivan, William A GhaliAbstract:Abstract Background and objective The ICD-9-CM adaptation of the Charlson comorbidity score has been a valuable resource for health services researchers. With the transition into ICD-10 coding worldwide, an ICD-10 version of the Deyo adaptation was developed and validated using population-based hospital data from Victoria, Australia. Methods The algorithm was translated from ICD-9-CM into ICD-10-AM (Australian modification) in a multistep process. After a mapping algorithm was used to develop an initial translation, these codes were manually examined by the coding experts and a general physician for face validity. Because the ICD-10 system is country specific, our goal was to keep many of the translated code at the three-digit level for generalizability of the new index. Results There appears to be little difference in the distribution of the Charlson Index score between the two versions. A strong association between increasing index scores and mortality exists: the area under the ROC curve is 0.865 for the last year using the ICD-9-CM version and remains high, at 0.855, for the ICD-10 version. Conclusion This work represents the first rigorous adaptation of the Charlson comorbidity index for use with ICD-10 data. In comparison with a well-established ICD-9-CM coding algorithm, it yields closely similar prevalence and prognosis information by comorbidity category.
Andrew D Boyd - One of the best experts on this subject based on the ideXlab platform.
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the challenges of pediatrics cohort discovery in the age of the transition to international classification of disease version 10 clinial modification icd 10 cm
Pediatrics, 2018Co-Authors: Sangeetha Muralidharan, Rachel N Caskey, Andrew D BoydAbstract:Background: The Centers for Medicare and Medicaid Services (CMS) mandated transition to International Classification of Diseases 10th Revision (ICD-10-CM) on October 1, 2015. This transition provided an increase in the number of codes, proving a greater clinical detail for diagnostic codes in the area of Pediatrics. The transition however leads to a miscommunication of definitions when translating from ICD-10-CM to ICD-9-CM for studies using retrospective data. This study evaluates the transition. Methods: A search for ICD-9-CM codes was conducted by analyzing journal articles from Pediatrics that utilized ICD-9-CM codes for research purposes over a 26-month period from August 2012 to November 2014. Thirty articles were found …
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the discriminatory cost of icd 10 cm transition between clinical specialties metrics case study and mitigating tools
Journal of the American Medical Informatics Association, 2013Co-Authors: Andrew D Boyd, Michael D Burton, Michael Jonen, Vincent Gardeux, Ikbel Achour, Roger Q Luo, Ilir ZenkuAbstract:Objective Applying the science of networks to quantify the discriminatory impact of the ICD-9-CM to ICD-10-CM transition between clinical specialties. Materials and Methods Datasets were the Center for Medicaid and Medicare Services ICD-9-CM to ICD-10-CM mapping files, general equivalence mappings, and statewide Medicaid emergency department billing. Diagnoses were represented as nodes and their mappings as directional relationships. The complex network was synthesized as an aggregate of simpler motifs and tabulation per clinical specialty. Results We identified five mapping motif categories: identity, class-to-subclass, subclass-to-class, convoluted, and no mapping. Convoluted mappings indicate that multiple ICD-9-CM and ICD-10-CM codes share complex, entangled, and non-reciprocal mappings. The proportions of convoluted diagnoses mappings (36% overall) range from 5% (hematology) to 60% (obstetrics and injuries). In a case study of 24 008 patient visits in 217 emergency departments, 27% of the costs are associated with convoluted diagnoses, with ‘abdominal pain’ and ‘gastroenteritis’ accounting for approximately 3.5%. Discussion Previous qualitative studies report that administrators and clinicians are likely to be challenged in understanding and managing their practice because of the ICD-10-CM transition. We substantiate the complexity of this transition with a thorough quantitative summary per clinical specialty, a case study, and the tools to apply this methodology easily to any clinical practice in the form of a web portal and analytic tables. Conclusions Post-transition, successful management of frequent diseases with convoluted mapping network patterns is critical. The web portal provides insight in linking onerous diseases to the ICD-10 transition.
Brecht Claerhout - One of the best experts on this subject based on the ideXlab platform.
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icd 10 cm extension with icd 9 diagnosis codes to support integrated access to clinical legacy data
International Journal of Medical Informatics, 2019Co-Authors: G Hernandezibarburu, Raul Alonsocalvo, David Perezrey, E Alonsooset, K De Schepper, Laura Meloni, Brecht ClaerhoutAbstract:Abstract Introduction ICD is currently the most widely used terminology to code diagnosis and procedures. The transition from ICD-9-CM to ICD-10-CM became effective on October 1, 2015 in US and many other countries. Projects that use this codification for research purposes, requires advanced methods to exploit data with both versions of ICD. Although the General Equivalence Mappings (GEMs), provided by the Centers for Medicare and Medicaid Services, might help to overcome these challenges, their direct use as translation mappings is not possible, mostly due to the further specificity of ICD-10-CM concepts. Objective We propose a methodology to generate an extended version of ICD-10-CM with selected ICD-9-CM diagnosis codes. Methods The extension was generated using the GEMs relations between concepts of both terminologies and the hierarchical relations of ICD-10-CM. Results This extended ICD-10-CM, together with modifications to the mapping of ICD-9-CM concepts that were not inserted, allows the generation of an improved translation of legacy data, raising the number of 1-to-1 correspondences by +13.81%. Conclusion The extended ICD-10-CM enables the accurate integration of ICD-9-CM and ICD-10-CM diagnosis data into a single terminology. With such analysis of data possible without having to specify both ICD-9-CM and ICD-10-CM separately for each query.
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icd 10 pcs extension with icd 9 procedure codes to support integrated access to clinical legacy data
International Journal of Medical Informatics, 2019Co-Authors: G Hernandezibarburu, Raul Alonsocalvo, David Perezrey, E Alonsooset, Brecht Claerhout, D Voets, Christina Mueller, N V CustodixAbstract:Since the creation of The International Classification of Diseases (ICD), new versions have been released to keep updated with the current medical knowledge. Migrations of Electronic Health Records (EHR) from ICD-9 to ICD-10-PCS as clinical procedure codification system, has been a significant challenge and involved large resources. In addition, it created new barriers for integrated access to legacy medical procedure data (frequently ICD-9 coded) with current data (frequently ICD-10-PCS coded). This work proposes a solution based on extending ICD-10-PCS with a subgroup of ICD-9-CM concepts to facilitate such integrated access. The General Equivalence Mappings (GEMs) has been used as foundation to set the terminology relations of these inserted concepts in ICD-10-PCS hierarchy, but due to the existence of 1-to-many mappings, advanced rules are required to seamlessly integrate both terminologies. With the generation of rules based on GEMs relationships, 2014 ICD-9 concepts were included within the ICD-10-PCS hierarchy. For the rest of the concepts, a new method is also proposed to increase 1-to-1 mappings. As results, with the suggested approach, the percentage of ICD-9-CM procedure concepts that can be mapped accurately (avoiding mappings to a large number of concepts) rise from 11.56% to 69.01% of ICD-9-Proc, through the extended ICD-10-PCS hierarchy.
G Hernandezibarburu - One of the best experts on this subject based on the ideXlab platform.
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icd 10 cm extension with icd 9 diagnosis codes to support integrated access to clinical legacy data
International Journal of Medical Informatics, 2019Co-Authors: G Hernandezibarburu, Raul Alonsocalvo, David Perezrey, E Alonsooset, K De Schepper, Laura Meloni, Brecht ClaerhoutAbstract:Abstract Introduction ICD is currently the most widely used terminology to code diagnosis and procedures. The transition from ICD-9-CM to ICD-10-CM became effective on October 1, 2015 in US and many other countries. Projects that use this codification for research purposes, requires advanced methods to exploit data with both versions of ICD. Although the General Equivalence Mappings (GEMs), provided by the Centers for Medicare and Medicaid Services, might help to overcome these challenges, their direct use as translation mappings is not possible, mostly due to the further specificity of ICD-10-CM concepts. Objective We propose a methodology to generate an extended version of ICD-10-CM with selected ICD-9-CM diagnosis codes. Methods The extension was generated using the GEMs relations between concepts of both terminologies and the hierarchical relations of ICD-10-CM. Results This extended ICD-10-CM, together with modifications to the mapping of ICD-9-CM concepts that were not inserted, allows the generation of an improved translation of legacy data, raising the number of 1-to-1 correspondences by +13.81%. Conclusion The extended ICD-10-CM enables the accurate integration of ICD-9-CM and ICD-10-CM diagnosis data into a single terminology. With such analysis of data possible without having to specify both ICD-9-CM and ICD-10-CM separately for each query.
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icd 10 pcs extension with icd 9 procedure codes to support integrated access to clinical legacy data
International Journal of Medical Informatics, 2019Co-Authors: G Hernandezibarburu, Raul Alonsocalvo, David Perezrey, E Alonsooset, Brecht Claerhout, D Voets, Christina Mueller, N V CustodixAbstract:Since the creation of The International Classification of Diseases (ICD), new versions have been released to keep updated with the current medical knowledge. Migrations of Electronic Health Records (EHR) from ICD-9 to ICD-10-PCS as clinical procedure codification system, has been a significant challenge and involved large resources. In addition, it created new barriers for integrated access to legacy medical procedure data (frequently ICD-9 coded) with current data (frequently ICD-10-PCS coded). This work proposes a solution based on extending ICD-10-PCS with a subgroup of ICD-9-CM concepts to facilitate such integrated access. The General Equivalence Mappings (GEMs) has been used as foundation to set the terminology relations of these inserted concepts in ICD-10-PCS hierarchy, but due to the existence of 1-to-many mappings, advanced rules are required to seamlessly integrate both terminologies. With the generation of rules based on GEMs relationships, 2014 ICD-9 concepts were included within the ICD-10-PCS hierarchy. For the rest of the concepts, a new method is also proposed to increase 1-to-1 mappings. As results, with the suggested approach, the percentage of ICD-9-CM procedure concepts that can be mapped accurately (avoiding mappings to a large number of concepts) rise from 11.56% to 69.01% of ICD-9-Proc, through the extended ICD-10-PCS hierarchy.
