ArticleHealth services research2019
A comparison of two structured taxonomic strategies in capturing adverse events in U.S. hospitals.
Article in Health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 3 citations in OpenAlex.
- Documentation of Drug-Related Problems with ICD-11: Application of the New WHO Code-Set to Clinical Routine Data.Journal of clinical medicine · 2022Article
- Feasibility of replacing the ICD-10-CM with the ICD-11 for morbidity coding: A content analysis.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Hospital Climate and Peer Report Intention on Adverse Medical Events: Role of Attribution and Rewards.International journal of environmental research and public health · 2021Article
- A comparison of two structured taxonomic strategies in capturing adverse events in U.S. hospitals.Health services research · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
objectiveTo 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
settingOne thousand patient admissions between 2014 and 2016 from three general, acute care hospitals located in Maryland and Washington D.C. STUDY
designThe admissions chosen for the study were a random sample from all three hospitals. DATA COLLECTION/EXTRACTION
methodsAll 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
findingsWe 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.
conclusionsWhile 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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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.