Evidence map›Paper›PMID 37018487›Full record

ArticleDiagnosis (Berlin, Germany)2023

Optimizing measurement of misdiagnosis-related harms using symptom-disease pair analysis of diagnostic error (SPADE): comparison groups to maximize SPADE validity.

Ava L Liberman, Zheyu Wang, Yuxin Zhu, Ahmed Hassoon, Justin Choi, J Matthew Austin, Michelle C Johansen, David E Newman-Toker

Abstract read
In one paragraph

Article in Diagnosis (Berlin, Germany), 2023. 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
–field-weighted citation impact
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.

  1. Article
  2. Article
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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

8 authors.

Ava L LibermanClinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology, Weill Cornell Medicine, Bronx, USA.ORCID https://orcid.org/0000-0003-0184-6035
Zheyu WangDivision of Biostatistics and Bioinformatics, The Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center, Baltimore, USA.
Yuxin ZhuDivision of Biostatistics and Bioinformatics, The Johns Hopkins University School of Medicine, Sidney Kimmel Comprehensive Cancer Center, Baltimore, USA.
Ahmed HassoonDepartments of Biostatistics, The Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
Justin ChoiDepartment of Internal Medicine, Weill Cornell Medicine, NY, USA.
J Matthew AustinDepartment of Anesthesia and Critical Care Medicine and the Armstrong Institute Center for Diagnostic Excellence, The Johns Hopkins University School of Medicine, Baltimore, USA.
Michelle C JohansenDepartment of Neurology and the Armstrong Institute Center for Diagnostic Excellence, The Johns Hopkins University School of Medicine, Baltimore, USA.
David E Newman-TokerDepartment of Neurology and the Armstrong Institute Center for Diagnostic Excellence, The Johns Hopkins University School of Medicine, Baltimore, USA.

Funding

Statistical Models of Alzheimer's Disease Pathological CascadeR01AG068002 · NIA · JOHNS HOPKINS UNIVERSITY · PI WANG, ZHEYU · 2020 to 2023
$1.6M
Towards a National Diagnostic Excellence Dashboard - Partnering with Stakeholders to Construct Evidence-Based Operational Measures of Misdiagnosis-Related HarmsR01HS027614 · AHRQ · JOHNS HOPKINS UNIVERSITY · PI NEWMAN-TOKER, DAVID · 2020 to 2023
$1.5M
Defining the role of Atrial Cardiopathy and Subclinical Cardiac Disease in Acute Ischemic Stroke: Critical Life Event SupplementK23NS112459 · NINDS · JOHNS HOPKINS UNIVERSITY · PI JOHANSEN, MICHELLE C. · 2020 to 2024
$1.0M
The Misdiagnosis of Cerebrovascular Disease in Emergent Headache EvaluationsK23NS107643 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI LIBERMAN, AVA L · 2018 to 2022
$997k
Determinants of Alzheimer's Disease in Atrial Fibrillation apart from Stroke: The NOMINATE StudyR21NS126967 · NINDS · JOHNS HOPKINS UNIVERSITY · PI JOHANSEN, MICHELLE C. · 2022 to 2023
$466k
AHRQ HHS R01 HS027614NIA NIH HHS R01 AG068002NINDS NIH HHS K23 NS107643NINDS NIH HHS K23 NS112459NINDS NIH HHS R21 NS126967
6 · The paper itself

Abstract

Diagnostic errors in medicine represent a significant public health problem but continue to be challenging to measure accurately, reliably, and efficiently. The recently developed Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) approach measures misdiagnosis related harms using electronic health records or administrative claims data. The approach is clinically valid, methodologically sound, statistically robust, and operationally viable without the requirement for manual chart review. This paper clarifies aspects of the SPADE analysis to assure that researchers apply this method to yield valid results with a particular emphasis on defining appropriate comparator groups and analytical strategies for balancing differences between these groups. We discuss four distinct types of comparators (intra-group and inter-group for both look-back and look-forward analyses), detailing the rationale for choosing one over the other and inferences that can be drawn from these comparative analyses. Our aim is that these additional analytical practices will improve the validity of SPADE and related approaches to quantify diagnostic error in medicine.

Indexed as

Electronic Health RecordsMedicineDiagnostic ErrorsHumansdelayed diagnosisdiagnostic errorsmissed diagnosisoutcome assessment, health carequality improvementstroke

Identifiers

PMID37018487
PMCPMC10659025

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Registered trials

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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.