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The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools

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...

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Autores principales: Boyd, Andrew D, Li, Jianrong ‘John’, Burton, Mike D, Jonen, Michael, Gardeux, Vincent, Achour, Ikbel, Luo, Roger Q, Zenku, Ilir, Bahroos, Neil, Brown, Stephen B, Vanden Hoek, Terry, Lussier, Yves A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3721160/
https://www.ncbi.nlm.nih.gov/pubmed/23645552
http://dx.doi.org/10.1136/amiajnl-2012-001358
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author Boyd, Andrew D
Li, Jianrong ‘John’
Burton, Mike D
Jonen, Michael
Gardeux, Vincent
Achour, Ikbel
Luo, Roger Q
Zenku, Ilir
Bahroos, Neil
Brown, Stephen B
Vanden Hoek, Terry
Lussier, Yves A
author_facet Boyd, Andrew D
Li, Jianrong ‘John’
Burton, Mike D
Jonen, Michael
Gardeux, Vincent
Achour, Ikbel
Luo, Roger Q
Zenku, Ilir
Bahroos, Neil
Brown, Stephen B
Vanden Hoek, Terry
Lussier, Yves A
author_sort Boyd, Andrew D
collection PubMed
description 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 http://lussierlab.org/transition-to-ICD10CM web portal provides insight in linking onerous diseases to the ICD-10 transition.
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spelling pubmed-37211602013-12-11 The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools Boyd, Andrew D Li, Jianrong ‘John’ Burton, Mike D Jonen, Michael Gardeux, Vincent Achour, Ikbel Luo, Roger Q Zenku, Ilir Bahroos, Neil Brown, Stephen B Vanden Hoek, Terry Lussier, Yves A J Am Med Inform Assoc Focus on Human Factors and System Utilization 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 http://lussierlab.org/transition-to-ICD10CM web portal provides insight in linking onerous diseases to the ICD-10 transition. BMJ Publishing Group 2013-07 2013-05-05 /pmc/articles/PMC3721160/ /pubmed/23645552 http://dx.doi.org/10.1136/amiajnl-2012-001358 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Focus on Human Factors and System Utilization
Boyd, Andrew D
Li, Jianrong ‘John’
Burton, Mike D
Jonen, Michael
Gardeux, Vincent
Achour, Ikbel
Luo, Roger Q
Zenku, Ilir
Bahroos, Neil
Brown, Stephen B
Vanden Hoek, Terry
Lussier, Yves A
The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools
title The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools
title_full The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools
title_fullStr The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools
title_full_unstemmed The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools
title_short The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools
title_sort discriminatory cost of icd-10-cm transition between clinical specialties: metrics, case study, and mitigating tools
topic Focus on Human Factors and System Utilization
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3721160/
https://www.ncbi.nlm.nih.gov/pubmed/23645552
http://dx.doi.org/10.1136/amiajnl-2012-001358
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