A World Health Organization field trial assessing a proposed ICD-11 framework for classifying patient safety events

Forster, Alan J.; Burnand, Bernard; Drösler, Saskia E.; Gurevich, Yana; Harrison, James Edward; Januel, Jean-Marie; Romano, Patrick S.; Southern, Danielle; Sundararajan, Vijaya; Quan, Hude; Vanderloo, Saskia; Pincus, Harold Alan; Ghali, William A.

doi:10.1093/intqhc/mzx070

Cited by 12 publications

(11 citation statements)

References 5 publications

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“…However, the ICD‐11 Q&S TAG recently completed a small field trial using vignettes to assess the utility of the proposed ICD‐11 framework for classifying patient safety events. They found the proposed ICD‐11 framework enabled classification of the majority of patient safety events; however, similar to our findings, cases for which it was difficult to link a specific intervention or omission in care to the outcome (eg, fall), classifying the cause and/or mode was problematic …”

Section: Discussionsupporting

confidence: 81%

“…They found the proposed ICD-11 framework enabled classification of the majority of patient safety events; however, similar to our findings, cases for which it was difficult to link a specific intervention or omission in care to the outcome (eg, fall), classifying the cause and/or mode was problematic. 23 Other studies that have looked at other administrative data sets, such as ICD-9 and ICD-10, have found mixed results with their ability to identify adverse events. [24][25][26][27] Our analysis comparing QSRS and ICD-10-CM found very similar results to the QSRS/ICD-11 comparison in that there was less than 20 percent agreement between QSRS and ICD-10-CM in capturing the same adverse events in the inpatient hospital setting.…”

Section: Con Clus Ionsmentioning

confidence: 99%

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A comparison of two structured taxonomic strategies in capturing adverse events in U.S. hospitals

Austin

Kirley

Rosen

et al. 2018

Health Services Research

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Objective To compare the Agency for Healthcare Research and Quality's Quality and Safety Review System (QSRS) and the proposed triadic structure for the 11th version of the International Classification of Disease (ICD‐11) in their ability to capture adverse events in U.S. hospitals. Data Sources/Study Setting One thousand patient admissions between 2014 and 2016 from three general, acute care hospitals located in Maryland and Washington D.C. Study Design The admissions chosen for the study were a random sample from all three hospitals. Data Collection/Extraction Methods All 1000 admissions were abstracted through QSRS by one set of Certified Coding Specialists and a different set of coders assigned the draft ICD‐11 codes. Previously assigned ICD‐10‐CM codes for 230 of the admissions were also used. Principal Findings We found less than 20 percent agreement between QSRS and ICD‐11 in identifying the same adverse event. The likelihood of a mismatch between QSRS and ICD‐11 was almost twice that of a match. The findings were similar to the agreement found between QSRS and ICD‐10‐CM in identifying the same adverse event. When coders were provided with a list of potential adverse events, the sensitivity and negative predictive value of ICD‐11 improved. Conclusions While ICD‐11 may offer an efficient way of identifying adverse events, our analysis found that in its draft form, it has a limited ability to capture the same types of events as QSRS. Coders may require additional training on identifying adverse events in the chart if ICD‐11 is going to prove its maximum benefit.

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Section: Discussionsupporting

confidence: 81%

Section: Con Clus Ionsmentioning

confidence: 99%

A comparison of two structured taxonomic strategies in capturing adverse events in U.S. hospitals

Austin

Kirley

Rosen

et al. 2018

Health Services Research

View full text Add to dashboard Cite

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“…These have demonstrated considerable acceptance and understanding among health information stakeholders who are involved in generating current coded health data using ICD-10. The field testing done has revealed that the ICD-11 coding tool is powerful in assisting coders in generating code clusters, guiding post-coordinated selection of relevant extension codes that relate to a stem code clinical concept [ 13 , 14 ].…”

Section: Discussionmentioning

confidence: 99%

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

Drösler

Weber

Chute

2021

BMC Med Inform Decis Mak

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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.

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“…Field testing conducted during the ICD-11 development phase has assessed the utility of the proposed WHO framework for classifying patient safety events. Forster et al found that the ICD-11 framework for healthcare-related adverse events has a high degree of coverage of relevant concepts [ 9 ]. With ICD-11, pilot testing on a wide scope of adverse event concepts has demonstrated comprehensive concept coverage, with most adverse events being readily codable [ 9 ].…”

Section: Discussionmentioning

confidence: 99%

The three-part model for coding causes and mechanisms of healthcare-related adverse events

Southern

Harrison

Romano

et al. 2021

BMC Med Inform Decis Mak

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ICD-11 provides a promising new way to capture healthcare-related harm or injury. In this paper, we elaborate on the framework for describing healthcare-related events where there is a presumed causal link between an event and underlying healthcare-related factors. The three-part model for describing healthcare-related harm or injury in ICD-11 consists of (1) a healthcare-related activity that is the cause of injury or other harm (selected from Chapter 23 of ICD-11); (2) a mode or mechanism of injury or harm, related to the underlying cause (also from Chapter 23 of ICD-11); and (3) the harmful consequences of the event to the patient, selected from any of Chapters 1 through 22 of ICD-11 (most importantly, the injury or harm experienced by the patient). Concepts from these three elements are linked/clustered through postcoordination to reflect the three-part model in a single coded expression. ICD-11 contains many novel features, and the three-part model described here for healthcare-related adverse events is a notable example.

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A World Health Organization field trial assessing a proposed ICD-11 framework for classifying patient safety events

Cited by 12 publications

References 5 publications

A comparison of two structured taxonomic strategies in capturing adverse events in U.S. hospitals

A comparison of two structured taxonomic strategies in capturing adverse events in U.S. hospitals

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

The three-part model for coding causes and mechanisms of healthcare-related adverse events

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