CoChat
Sign Up
Cited by 139Clinical Reasoning and Diagnostic SkillsEmergency and Acute Care StudiesPatient Safety and Medication Errors

Diagnostic error increases mortality and length of hospital stay in patients presenting through the emergency room

Open access
Hautz, Wolf E., Kämmer, Juliane E., Hautz, Stefanie C., Sauter, Thomas C., Zwaan, Laura, Exadaktylos, Aristomenis K., Birrenbach, Tanja, Maier, Volker +2 more·2019·Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine
DOI 10.1186/s13049-019-0629-zPMC PMC6505221
Open this paper in CoChat — free accountOpen PDF

Abstract

BACKGROUND: Diagnostic errors occur frequently, especially in the emergency room. Estimates about the consequences of diagnostic error vary widely and little is known about the factors predicting error. Our objectives thus was to determine the rate of discrepancy between diagnoses at hospital admission and discharge in patients presenting through the emergency room, the discrepancies' consequences, and factors predicting them. METHODS: Prospective observational clinical study combined with a survey in a University-affiliated tertiary care hospital. Patients' hospital discharge diagnosis was compared with the diagnosis at hospital admittance through the emergency room and classified as similar or discrepant according to a predefined scheme by two independent expert raters. Generalized linear mixed-effects models were used to estimate the effect of diagnostic discrepancy on mortality and length of hospital stay and to determine whether characteristics of patients, diagnosing physicians, and context predicted diagnostic discrepancy. RESULTS: 755 consecutive patients (322 [42.7%] female; mean age 65.14 years) were included. The discharge diagnosis differed substantially from the admittance diagnosis in 12.3% of cases. Diagnostic discrepancy was associated with a longer hospital stay (mean 10.29 vs. 6.90 days; Cohen's d 0.47; 95% confidence interval 0.26 to 0.70; P = 0.002) and increased patient mortality (8 (8.60%) vs. 25(3.78%); OR 2.40; 95% CI 1.05 to 5.5 P = 0.038). A factor available at admittance that predicted diagnostic discrepancy was the diagnosing physician's assessment that the patient presented atypically for the diagnosis assigned (OR 3.04; 95% CI 1.33-6.96; P = 0.009). CONCLUSIONS: Diagnostic discrepancies are a relevant healthcare problem in patients admitted through the emergency room because they occur in every ninth patient and are associated with increased in-hospital mortality. Discrepancies are not readily predictable by fixed patient or physician characteristics; attention should focus on context. TRIAL REGISTRATION: https://bmjopen.bmj.com/content/6/5/e011585.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s13049-019-0629-z

Cites

10 of 10 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Diagnostic suggestions were classified according to procedures described by Hautz et al. and Bastakoti et al.

    “Diagnostic suggestions were classified by the raters as identical, plausible, or diagnostically different, according to the procedures described by Hautz et al. [16] and Bastakoti et al. [17].”

    From Diagnostic performance of Prof. Valmed, ChatGPT-5 Thinking, and OpenEvidence in rheumatology: A comparative evaluation (2026) · cites this paper as Hautz et al. [16]

    In Methods > Measures (page not available), Hautz et al. describe expert raters using a predefined scheme to classify the relationship between admission and discharge diagnoses. Table 1 includes an ‘Identical’ category, but the paper does not describe classifying diagnostic suggestions into the three stated categories—identical, plausible, and diagnostically different. The Bastakoti citation is outside the scope of this verdict. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 59

  1. [1]Balogh EP Miller BT Ball JR Improving diagnosis in health care [internet] 2015 Washington, D.C. National Academies Press 26803862
  2. [2]Leape LL Brennan TA Laird N Lawthers AG Localio AR Barnes BA The nature of adverse events in hospitalized patients. Results of the Harvard medical practice study II N Engl J Med 1991 324 377 384 10.1056/NEJM199102073240605 1824793 · DOI
  3. [3]Thomas EJ Studdert DM Burstin HR Orav EJ Zeena T Williams EJ Incidence and types of adverse events and negligent care in Utah and Colorado Med Care 2000 38 261 271 10.1097/00005650-200003000-00003 10718351 · DOI
  4. [4]Graber M Diagnostic errors in medicine: a case of neglect Jt Comm J Qual Patient Saf 2005 31 106 113 10.1016/S1553-7250(05)31015-4 15791770 · DOI · Paper page
  5. [5]Newman-Toker DE Diagnostic errors—the next frontier for patient safety JAMA. 2009 301 1060 10.1001/jama.2009.249 19278949 PMC12396158 · DOI
  6. [6]Weeks WB Foster T Wallace AE Stalhandske E Tort claims analysis in the veterans health Administration for Quality Improvement J Law Med Ethics 2001 29 335 345 10.1111/j.1748-720X.2001.tb00352.x 12056372 · DOI
  7. [7]Brown TW McCarthy ML Kelen GD Levy F An epidemiologic study of closed emergency department malpractice claims in a national database of physician malpractice insurers Acad Emerg Med Off J Soc Acad Emerg Med 2010 17 553 560 10.1111/j.1553-2712.2010.00729.x 20536812 · DOI
  8. [8]Schaffer AC Jena AB Seabury SA Singh H Chalasani V Kachalia A Rates and characteristics of paid malpractice claims among US physicians by specialty, 1992-2014 JAMA Intern Med 2017 177 710 10.1001/jamainternmed.2017.0311 28346582 PMC5470361 · DOI
  9. [9]Kachalia A Gandhi TK Puopolo AL Yoon C Thomas EJ Griffey R Missed and delayed diagnoses in the emergency department: a study of closed malpractice claims from 4 liability insurers Ann Emerg Med 2007 49 196 205 10.1016/j.annemergmed.2006.06.035 16997424 · DOI
  10. [10]Ilgen JS Humbert AJ Kuhn G Hansen ML Norman GR Eva KW Assessing diagnostic reasoning: a consensus statement summarizing theory, practice, and future needs Acad Emerg Med Off J Soc Acad Emerg Med 2012 19 1454 1461 10.1111/acem.12034 23279251 · DOI
  11. [11]Kämmer Juliane E. Hautz Wolf E. Herzog Stefan M. Kunina-Habenicht Olga Kurvers Ralf H. J. M. The Potential of Collective Intelligence in Emergency Medicine: Pooling Medical Students’ Independent Decisions Improves Diagnostic Performance Medical Decision Making 2017 37 6 715 724 10.1177/0272989X17696998 28355975 · DOI
  12. [12]Makary MA, Daniel M. Medical error—the third leading cause of death in the US. BMJ. 2016:i2139. 10.1136/bmj.i2139. 27143499 · DOI · Paper page
  13. [13]Hautz WE When I say … diagnostic error Med Educ 2018 52 896 897 10.1111/medu.13602 · DOI
  14. [17]Singh H Meyer AND Thomas EJ The frequency of diagnostic errors in outpatient care: estimations from three large observational studies involving US adult populations BMJ Qual Saf 2014 23 727 731 10.1136/bmjqs-2013-002627 24742777 PMC4145460 · DOI · Paper page
  15. [18]Berner ES Graber ML Overconfidence as a cause of diagnostic error in medicine Am J Med 2008 121 S2 23 10.1016/j.amjmed.2008.01.001 18440350 · DOI · Paper page
  16. [19]Wears RL Nemeth CP Replacing hindsight with insight: toward better understanding of diagnostic failures Ann Emerg Med 2007 49 206 209 10.1016/j.annemergmed.2006.08.027 17083994 · DOI
  17. [20]Henriksen K Kaplan H Hindsight bias, outcome knowledge and adaptive learning Qual Saf Health Care 2003 12 Suppl 2 ii46 ii50 14645895 PMC1765779
  18. [21]Caplan RA Posner KL Cheney FW Effect of outcome on physician judgments of appropriateness of care JAMA. 1991 265 1957 1960 10.1001/jama.1991.03460150061024 2008024 · DOI
  19. [22]Norman GR Eva KW Diagnostic error and clinical reasoning Med Educ 2010 44 94 100 10.1111/j.1365-2923.2009.03507.x 20078760 · DOI
  20. [23]Klein JG Five pitfalls in decisions about diagnosis and prescribing BMJ. 2005 330 781 10.1136/bmj.330.7494.781 15802723 PMC555888 · DOI
  21. [25]Redelmeier DA The cognitive psychology of missed diagnoses Ann Intern Med 2005 142 115 120 10.7326/0003-4819-142-2-200501180-00010 15657159 · DOI
  22. [26]Elstein AS Heuristics and biases: selected errors in clinical reasoning Acad Med J Assoc Am Med Coll. 1999 74 791 794 10.1097/00001888-199907000-00012 10429587 · DOI · Paper page
  23. [27]Voytovich AE Rippey RM Suffredini A Premature conclusions in diagnostic reasoning J Med Educ 1985 60 302 307 3981589
  24. [28]Schmidt HG van Gog T CE Schuit S Van den Berge K LA Van Daele P Bueving H Do patients’ disruptive behaviors influence the accuracy of a doctor’s diagnosis? A randomised experiment BMJ Qual Saf 2017 26 19 23 10.1136/bmjqs-2015-004109 26951795 · DOI
  25. [29]Mamede S Van Gog T Schuit SCE Van den Berge K Van Daele PLA Bueving H Why patients’ disruptive behaviors impair diagnostic reasoning: a randomised experiment BMJ Qual Saf 2017 26 13 18 10.1136/bmjqs-2015-005065 26951796 · DOI
  26. [30]Mamede S van Gog T van den Berge K Rikers RM van Saase JL van Guldener C Effect of availability bias and reflective reasoning on diagnostic accuracy among internal medicine residents Jama. 2010 304 1198 1203 10.1001/jama.2010.1276 20841533 · DOI · Paper page
  27. [31]Schmidt HG Mamede S van den Berge K van Gog T van Saase JLCM Rikers RMJP Exposure to media information about a disease can cause doctors to misdiagnose similar-looking clinical cases Acad Med J Assoc Am Med Coll 2014 89 285 291 10.1097/ACM.0000000000000107 24362387 · DOI
  28. [32]Kunina-Habenicht Olga Hautz Wolf E. Knigge Michel Spies Claudia Ahlers Olaf Assessing clinical reasoning (ASCLIRE): Instrument development and validation Advances in Health Sciences Education 2015 20 5 1205 1224 10.1007/s10459-015-9596-y 25725935 · DOI
  29. [33]McLaughlin K Eva KW Norman GR Reexamining our bias against heuristics Adv Health Sci Educ 2014 19 457 464 10.1007/s10459-014-9518-4 24889994 · DOI
  30. [34]Blumenthal-Barby JS Krieger H Cognitive biases and heuristics in medical decision making: a critical review using a systematic search strategy Med Decis Mak Int J Soc Med Decis Mak 2015 35 539 557 10.1177/0272989X14547740 25145577 · DOI
  31. [35]Zwaan L Monteiro S Sherbino J Ilgen J Howey B Norman G Is bias in the eye of the beholder? A vignette study to assess recognition of cognitive biases in clinical case workups BMJ Qual Saf 2017 26 104 110 10.1136/bmjqs-2015-005014 26825476 · DOI
  32. [37]Durning SJ Artino AR Boulet JR Dorrance K van der Vleuten C Schuwirth L The impact of selected contextual factors on experts’ clinical reasoning performance (does context impact clinical reasoning performance in experts?) Adv Health Sci Educ Theory Pract 2012 17 65 79 10.1007/s10459-011-9294-3 21505841 · DOI
  33. [38]Weiss SJ Derlet R Arndahl J Ernst AA Richards J Fernández-Frankelton M Estimating the degree of emergency department overcrowding in academic medical centers: results of the national ED overcrowding study (NEDOCS) Acad Emerg Med 2004 11 38 50 10.1111/j.1553-2712.2004.tb01369.x 14709427 · DOI
  34. [39]Weiss SJ Ernst AA Nick TG Comparison of the National Emergency Department Overcrowding Scale and the emergency department work index for quantifying emergency department crowding Acad Emerg Med 2006 13 513 518 10.1197/j.aem.2005.12.009 16551777 · DOI
  35. [41]Kurmann A Peter M Tschan F Mühlemann K Candinas D Beldi G Adverse effect of noise in the operating theatre on surgical-site infection Br J Surg 2011 98 1021 1025 10.1002/bjs.7496 21618484 · DOI
  36. [42]Nemec M Koller MT Nickel CH Maile S Winterhalder C Karrer C Patients presenting to the emergency department with non-specific complaints: the Basel non-specific complaints (BANC) study Acad Emerg Med Off J Soc Acad Emerg Med 2010 17 284 292 10.1111/j.1553-2712.2009.00658.x 20370761 · DOI
  37. [43]Ruger JP Lewis LM Richter CJ Identifying high-risk patients for triage and resource allocation in the ED Am J Emerg Med 2007 25 794 798 10.1016/j.ajem.2007.01.014 17870484 · DOI
  38. [44]Sauter TC, Capaldo G, Hoffmann M, Birrenbach T, Hautz SC, Kämmer JE, et al. Non-specific complaints at emergency department presentation result in unclear diagnoses and lengthened hospitalization: a prospective observational study. Scand J Trauma Resusc Emerg Med. 2018;26. 10.1186/s13049-018-0526-x. PMC6048907 30012186 · DOI
  39. [45]Artino AR Gehlbach H Durning SJ AM last page: avoiding five common pitfalls of survey design Acad Med J Assoc Am Med Coll. 2011 86 1327 10.1097/ACM.0b013e31822f77cc 21955721 · DOI
  40. [46]Gehlbach H Artino AR Durning S AM last page: survey development guidance for medical education researchers Acad Med J Assoc Am Med Coll. 2010 85 925 10.1097/ACM.0b013e3181dd3e88 20520050 · DOI
  41. [48]Naismith LM Cheung JJH Ringsted C Cavalcanti RB Limitations of subjective cognitive load measures in simulation-based procedural training Med Educ 2015 49 805 814 10.1111/medu.12732 26152492 · DOI
  42. [50]Weber N Brewer N Confidence-accuracy calibration in absolute and relative face recognition judgments J Exp Psychol Appl 2004 10 156 172 10.1037/1076-898X.10.3.156 15462618 · DOI
  43. [51]Charlson ME Pompei P Ales KL MacKenzie CR A new method of classifying prognostic comorbidity in longitudinal studies: development and validation J Chronic Dis 1987 40 373 383 10.1016/0021-9681(87)90171-8 3558716 · DOI · Paper page
  44. [53]Hautz SC Schuler L Kämmer JE Schauber SK Ricklin ME Sauter TC Factors predicting a change in diagnosis in patients hospitalised through the emergency room: a prospective observational study BMJ Open 2016 6 e011585 10.1136/bmjopen-2016-011585 PMC4874162 27169743 · DOI
  45. [56]Rubin DB Inference and missing data Biometrika. 1976 63 581 10.2307/2335739 · DOI
  46. [60]Snijders TAB Bosker RJ Multilevel analysis: an introduction to basic and advanced multilevel modeling. 2nd edition. Los Angeles London New Delhi Singapore 2012 Washington DC Sage
  47. [61]Newman-Toker DE Moy E Valente E Coffey R Hines AL Missed diagnosis of stroke in the emergency department: a cross-sectional analysis of a large population-based sample Diagnosis. 2014 1 155 166 10.1515/dx-2013-0038 28344918 PMC5361750 · DOI
  48. [62]Peng A Rohacek M Ackermann S Ilsemann-Karakoumis J Ghanim L Messmer AS The proportion of correct diagnoses is low in emergency patients with nonspecific complaints presenting to the emergency department Swiss Med Wkly 2015 145 w14121 10.4414/smw.2015.14121 25741894 · DOI
  49. [63]Singh H Giardina TD Meyer AND Forjuoh SN Reis MD Thomas EJ Types and origins of diagnostic errors in primary care settings JAMA Intern Med 2013 173 418 425 10.1001/jamainternmed.2013.2777 23440149 PMC3690001 · DOI · Paper page
  50. [64]Zwaan L de Bruijne M Wagner C Thijs A Smits M van der Wal G Patient record review of the incidence, consequences, and causes of diagnostic adverse events Arch Intern Med 2010 170 1015 1021 10.1001/archinternmed.2010.146 20585065 · DOI
  51. [65]Zwaan L Thijs A Wagner C Timmermans DRM Does inappropriate selectivity in information use relate to diagnostic errors and patient harm? The diagnosis of patients with dyspnea Soc Sci Med 2013 91 32 38 10.1016/j.socscimed.2013.05.001 23849236 · DOI
  52. [66]Kostopoulou O Delaney BC Munro CW Diagnostic difficulty and error in primary care--a systematic review Fam Pract 2008 25 400 413 10.1093/fampra/cmn071 18842618 · DOI · Paper page
  53. [67]Andrews LB Stocking C Krizek T Gottlieb L Krizek C Vargish T An alternative strategy for studying adverse events in medical care Lancet Lond Engl 1997 349 309 313 10.1016/S0140-6736(96)08268-2 9024373 · DOI
  54. [68]Battle RM Pathak D Humble CG Key CR Vanatta PR Hill RB Factors influencing discrepancies between premortem and postmortem diagnoses JAMA. 1987 258 339 344 10.1001/jama.1987.03400030055031 3599326 · DOI
  55. [69]Mattsson B Ertman D Exadaktylos AK Martinolli L Hautz WE Now you see me: a pragmatic cohort study comparing first and final radiological diagnoses in the emergency department BMJ Open 2018 8 e020230 10.1136/bmjopen-2017-020230 29331979 PMC5781021 · DOI
  56. [70]Eva KW On the generality of specificity Med Educ 2003 37 587 588 10.1046/j.1365-2923.2003.01563.x 12834414 · DOI
  57. [71]Eva KW What every teacher needs to know about clinical reasoning Med Educ 2005 39 98 106 10.1111/j.1365-2929.2004.01972.x 15612906 · DOI
  58. [72]Chellis M Olson J Augustine J Hamilton G Evaluation of missed diagnoses for patients admitted from the emergency department Acad Emerg Med 2001 8 125 130 10.1111/j.1553-2712.2001.tb01276.x 11157287 · DOI
  59. [74]Hautz WE Kämmer JE Exadaktylos A Hautz SC How thinking about groups is different from groupthink Med Educ 2017 51 229 10.1111/medu.13137 27859482 · DOI

Cited by

Sorted by citations

Authors
Hautz, W. E., Kämmer, J. E., Hautz, S. C., Sauter, T. C., Zwaan, L., Exadaktylos, A. K., Birrenbach, T., Maier, V., Müller, M., & Schauber, S. K.
Affiliations
  • University of Bern (CH)
  • Max Planck Institute for Human Development (DE)
  • Erasmus MC (NL)
  • University of Oslo (NO)
Corresponding author
Hautz, Wolf E.
ORCID
Venue
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine
Publisher
Springer Science and Business Media LLC
Published
2019-05-08
Volume
27
Issue
1
Pages
54-54
ISSN
1757-7241 (ISSN-L)
DOI
10.1186/s13049-019-0629-z
PMC
PMC6505221
OpenAlex
W2944015619
Cited by
139
References
10
Citations by year
2026: 18 · 2025: 23 · 2024: 19 · 2023: 31 · 2022: 20 · 2021: 17 · 2020: 10 · 2019: 1
FWCI
12.35
Type
journal article
Language
en
Open access
Licence
Locations
  • Scandinavian Journal of Trauma Resuscitation and Emergency Medicine (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, other-oa)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • Bern Open Repository and Information System (University of Bern) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
Funders
  • Mittelbauvereinigung Universität Bern (none)
  • Clinical Trials Unit Inselspital Bern (None)
Topics
  • Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
  • Health Sciences › Medicine › Emergency Medicine › Emergency and Acute Care Studies
  • Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
Keywords
diagnostic errors, emergency department, in-hospital mortality, length of hospital stay, atypical presentation, physician assessment
MeSH terms
Aged, Diagnostic Errors, Emergency Service, Hospital, Female, Follow-Up Studies, Humans, Length of Stay, Male, Middle Aged, Patient Discharge, Prospective Studies, Switzerland, Hospital Mortality

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review