Evidence map›Paper›PMID 40526380›Full record

ArticleJAMA network open2025

Potential Diagnostic Error for Emergency Conditions, Mortality, and Healthy Days at Home.

Michelle P Lin, Ryan C Burke, Amber K Sabbatini, Ellen Latsko, Jonathan A Edlow, E John Orav, Laura G Burke

Abstract read
In one paragraph

Article in JAMA network open, 2025. 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
  3. Review
  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

7 authors.

Michelle P LinDepartment of Emergency Medicine, Stanford University, Palo Alto, California.
Ryan C BurkeDepartment of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
Amber K SabbatiniDepartment of Emergency Medicine, University of Washington, Seattle.
Ellen LatskoDepartment of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Jonathan A EdlowDepartment of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
E John OravDivision of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Laura G BurkeDepartment of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.

Funding

Observation Stays and Readmissions for Older Adults: Implications for Medicare PoliciesR01AG063759 · NIA · UNIVERSITY OF WASHINGTON · PI SABBATINI, AMBER KATHLEEN · 2020 to 2023
$1.4M
PROAACT- Admin SupplementK23HL143042 · NHLBI · STANFORD UNIVERSITY · PI LIN, MICHELLE P · 2019 to 2023
$1.0M
A National Analysis of Observation Care Among Medicare Beneficiaries with Alzheimer's Disease and Related DementiasR56AG075017 · NIA · BETH ISRAEL DEACONESS MEDICAL CENTER · PI BURKE, LAURA G · 2022 to 2022
$779k
AHRQ HHS R01 HS029781NHLBI NIH HHS K23 HL143042NIA NIH HHS R01 AG063759NIA NIH HHS R56 AG075017
6 · The paper itself

Abstract

Importance: There is limited evidence regarding the frequency of diagnostic errors and outcomes associated with them in emergency care in the US. Objective: To examine rates of potential diagnostic errors and associated clinical outcomes among Medicare beneficiaries with emergency hospitalizations. Design, Setting, and Participants: This cohort study examined a national sample of fee-for-service Medicare beneficiaries aged 65 years or older with emergency hospitalizations for 10 high-risk conditions from 2016 to 2019. Data were analyzed from December 20, 2022, to April 16, 2025. Exposure: Potential diagnostic errors in the emergency department (ED). Main Outcome and Measures: The percentage of hospitalizations with an ED discharge (potential diagnostic error) in the preceding 9 days was calculated. From this observed ED visit rate, an adjusted rate of potential diagnostic errors was calculated by subtracting the rate of background ED discharges among a comparison cohort of beneficiaries with similar baseline risk. To examine the association between potential diagnostic error and outcomes, multivariable linear regression models were specified for the outcomes: 30-day mortality and healthy days at home (HDAH). Potential diagnostic error was the exposure, and the models were adjusted for diagnosis, patient demographics, and chronic conditions. Results: Among 302 837 emergency hospitalizations, 13 550 (4.5%) were preceded by an ED discharge (ie, potential diagnostic error) within 9 days. For the comparison group with similar baseline risk, 1.2% (95% CI, 1.2%-1.3%) had an ED discharge in a random 9-day period. After accounting for this background use, the adjusted potential diagnostic error rate was 3.2% (95% CI, 3.1%-3.3%) for all conditions in aggregate but ranged from 2.1% (95% CI, 1.9%-2.4%) for spontaneous intracranial hemorrhage to 15.6% (95% CI, 11.9%-19.3%) for spinal abscess. Having a potential diagnostic error was associated with higher adjusted 30-day mortality for emergency admissions (15.7% vs 14.9%; point absolute difference, 0.8 percentage points, 95% CI, 0.2 to 1.4 percentage points; P = .007) as well as fewer 30-day HDAH (13.5 days vs 15.0 days; difference, -1.4 days; 95% CI, -1.6 to -1.3 days; P < .001), although associations varied among conditions. Conclusions and Relevance: In this cohort study of Medicare beneficiaries aged 65 years and older with emergency hospitalizations, the adjusted potential diagnostic error rate was modest overall but varied by condition. Potential diagnostic errors were associated with worse outcomes for emergency conditions overall, with associations again varying among individual conditions.

Indexed as

Diagnostic ErrorsEmergency Service, HospitalHospitalizationAgedAged, 80 and overCohort StudiesFemaleHumansMaleMedicareUnited States

Identifiers

PMID40526380
PMCPMC12175027

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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.