Evidence map›Paper›PMID 30474108›Full record

ArticleHealth services research2019

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

John M Austin, Erin M Kirley, Michael A Rosen, Bradford D Winters

Open access · greenAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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 · 2021
    Article
  3. Hospital Climate and Peer Report Intention on Adverse Medical Events: Role of Attribution and Rewards.International journal of environmental research and public health · 2021
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

John M AustinArmstrong Institute for Patient Safety and Quality, Johns Hopkins Medicine, Baltimore, Maryland.ORCID 0000-0002-3061-3540
Erin M KirleyArmstrong Institute for Patient Safety and Quality, Johns Hopkins Medicine, Baltimore, Maryland.
Michael A RosenArmstrong Institute for Patient Safety and Quality, Johns Hopkins Medicine, Baltimore, Maryland.
Bradford D WintersAnesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Johns Hopkins University · US

Funding

AHRQ HHS HHSP233201500020I
6 · The paper itself

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.

Indexed as

AdultAgedDistrict of ColumbiaDocumentationFemaleHospital AdministrationHumansInternational Classification of DiseasesMaleMarylandMiddle AgedPatient HarmPatient SafetySafety ManagementUnited StatesUnited States Agency for Healthcare Research and Qualityadverse eventsmeasurementpatient safety

Identifiers

PMID30474108
PMCPMC6505417
OpenAlexW2902342847

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.