ICD-11 extension codes support detailed clinical abstraction and comprehensive classification

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

The new International Classification of Diseases—11th revision (ICD-11) succeeds ICD-10. In the three decades since ICD-10 was released, demands for detailed information on the clinical history of a morbid patient have increased.

Methods

ICD-11 has now implemented an addendum chapter X called “Extension Codes”. This chapter contains numerous codes containing information on concepts including disease stage, severity, histopathology, medicaments, and anatomical details. When linked to a stem code representing a clinical state, the extension codes add significant detail and allow for multidimensional coding.

Results

This paper discusses the purposes and uses of extension codes and presents three examples of how extension codes can be used in coding clinical detail.

Conclusion

ICD-11 with its extension codes implemented has the potential to improve precision and evidence based health care worldwide.

Related collections

Most cited references 6

Record: found
Abstract: found
Article: not found

Risk factors for retained instruments and sponges after surgery.

Atul A Gawande, David Studdert, E. Orav … (2003)

Risk factors for medical errors remain poorly understood. We performed a case-control study of retained foreign bodies in surgical patients in order to identify risk factors for this type of error. We reviewed the medical records associated with all claims or incident reports of a retained surgical sponge or instrument filed between 1985 and 2001 with a large malpractice insurer representing one third of the physicians in Massachusetts. For each case, we identified an average of four randomly selected controls who underwent the same type of operation during the same six-month period. Our study included 54 patients with a total of 61 retained foreign bodies (of which 69 percent were sponges and 31 percent instruments) and 235 control patients. Thirty-seven of the patients with retained foreign bodies (69 percent) required reoperation, and one died. Patients with retained foreign bodies were more likely than controls to have had emergency surgery (33 percent vs. 7 percent, P<0.001) or an unexpected change in surgical procedure (34 percent vs. 9 percent, P<0.001). Patients with retained foreign bodies also had a higher mean body-mass index and were less likely to have had counts of sponges and instruments performed. In multivariate analysis, factors associated with a significantly increased risk of retention of a foreign body were emergency surgery (risk ratio, 8.8 [95 percent confidence interval, 2.4 to 31.9]), unplanned change in the operation (risk ratio, 4.1 [95 percent confidence interval, 1.4 to 12.4]), and body-mass index (risk ratio for each one-unit increment, 1.1 [95 percent confidence interval, 1.0 to 1.2]). The risk of retention of a foreign body after surgery significantly increases in emergencies, with unplanned changes in procedure, and with higher body-mass index. Case--control analysis of medical-malpractice claims may identify and quantify risk factors for specific types of errors. Copyright 2003 Massachusetts Medical Society

0 comments Cited 169 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Toward a science of learning systems: a research agenda for the high-functioning Learning Health System

Charles Friedman, Joshua Rubin, Jeffrey Brown … (2014)

Objective The capability to share data, and harness its potential to generate knowledge rapidly and inform decisions, can have transformative effects that improve health. The infrastructure to achieve this goal at scale—marrying technology, process, and policy—is commonly referred to as the Learning Health System (LHS). Achieving an LHS raises numerous scientific challenges. Materials and methods The National Science Foundation convened an invitational workshop to identify the fundamental scientific and engineering research challenges to achieving a national-scale LHS. The workshop was planned by a 12-member committee and ultimately engaged 45 prominent researchers spanning multiple disciplines over 2 days in Washington, DC on 11–12 April 2013. Results The workshop participants collectively identified 106 research questions organized around four system-level requirements that a high-functioning LHS must satisfy. The workshop participants also identified a new cross-disciplinary integrative science of cyber-social ecosystems that will be required to address these challenges. Conclusions The intellectual merit and potential broad impacts of the innovations that will be driven by investments in an LHS are of great potential significance. The specific research questions that emerged from the workshop, alongside the potential for diverse communities to assemble to address them through a ‘new science of learning systems’, create an important agenda for informatics and related disciplines.

0 comments Cited 129 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

The new International Classification of Diseases 11th edition: a comparative analysis with ICD-10 and ICD-10-CM.

Kin Fung, Julia Zhe Xu, Olivier Bodenreider (2020)

To study the newly adopted International Classification of Diseases 11th revision (ICD-11) and compare it to the International Classification of Diseases 10th revision (ICD-10) and International Classification of Diseases 10th revision-Clinical Modification (ICD-10-CM).

0 comments Cited 19 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Saskia E. Drösler:

ORCID: http://orcid.org/0000-0003-4160-6976

saskia.droesler@hs-niederrhein.de

Stefanie Weber: stefanie.weber@bfarm.de

Christopher G. Chute: chute@jhu.edu

Journal

Journal ID (nlm-ta): BMC Med Inform Decis Mak

Journal ID (iso-abbrev): BMC Med Inform Decis Mak

Title: BMC Medical Informatics and Decision Making

Publisher: BioMed Central (London )

ISSN (Electronic): 1472-6947

Publication date (Electronic): 9 November 2021

Publication date PMC-release: 9 November 2021

Publication date Collection: 2021

Volume: 21

Issue : Suppl 6 Issue sponsor : Work for the series of articles has been undertaken by the WHO-fic (World Health Organization Family of International Classifications) Network. Funding from the Canadian Institutes for Health Information (CIHR) and the Agency for Healthcare Research and Quality (grant number 5R13HS020543-02) supported aspects of this work and activities of several of the authors. The articles have undergone the journal's standard peer review process for supplements. The Supplement Editors declare that they have no competing interests.

Electronic Location Identifier: 278

Affiliations

[1 ]GRID grid.440943.e, ISNI 0000 0000 9422 7759, Faculty of Health Care, , Niederrhein University of Applied Sciences, ; Reinarzstr 49, 47805 Krefeld, Germany

[2 ]GRID grid.414802.b, ISNI 0000 0000 9599 0422, Federal Institute for Drugs and Medical Devices, ; Kurt-Georg-Kiesinger-Allee 3, 53175 Bonn, Germany

[3 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Schools of Medicine, Public Health, and Nursing, , Johns Hopkins University, ; 2024 E Monument St, Suite 1-200, Baltimore, MD 21287 USA

Author information

Saskia E. Drösler http://orcid.org/0000-0003-4160-6976

Article

Publisher ID: 1635

DOI: 10.1186/s12911-021-01635-2

PMC ID: 8577174

PubMed ID: 34753461

SO-VID: e797a717-a89a-4329-ac8f-ea2afc8f52df

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 14 September 2021

Date accepted : 21 September 2021

Custom metadata

ScienceOpen disciplines: Bioinformatics & Computational biology

Keywords: classification,international classification of diseases,icd11,extension codes

Data availability:

ScienceOpen disciplines: Bioinformatics & Computational biology

Keywords: classification, international classification of diseases, icd11, extension codes

ICD-11 extension codes support detailed clinical abstraction and comprehensive classification

Read this article at

Abstract

Background

Methods

Results

Conclusion

Related collections

Genetoberfest

Most cited references 6

Risk factors for retained instruments and sponges after surgery.

Toward a science of learning systems: a research agenda for the high-functioning Learning Health System

The new International Classification of Diseases 11th edition: a comparative analysis with ICD-10 and ICD-10-CM.

Author and article information

Contributors

Journal

Affiliations

Author information

Article

History

Categories

Custom metadata

Comments

Comment on this article

Similar content 88

Cited by 10

Most referenced authors 124