Home Harbingers of sepsis misdiagnosis among pediatric emergency department patients
Article
Licensed
Unlicensed Requires Authentication

Harbingers of sepsis misdiagnosis among pediatric emergency department patients

  • Jonathan G. Sawicki ORCID logo EMAIL logo , Jessica Graham , Gitte Larsen and Jennifer K. Workman
Published/Copyright: December 12, 2024

Abstract

Objectives

To identify clinical presentations that acted as harbingers for future sepsis hospitalizations in pediatric patients evaluated in the emergency department (ED) using the Symptom Disease Pair Analysis of Diagnostic Error (SPADE) methodology.

Methods

We identified patients in the Pediatric Health Information Systems (PHIS) database admitted for sepsis between January 1, 2004 and December 31, 2023 and limited the study cohort to those patients who had an ED treat-and-release visit in the 30 days prior to admission. Using the look-back approach of the SPADE methodology, we identified the most common clinical presentations at the initial ED visit and used an observed to expected (O:E) analysis to determine which presentations were overrepresented. We then employed a graphical, temporal analysis with a comparison group to identify which overrepresented presentations most likely represented harbingers for future sepsis hospitalization.

Results

We identified 184,157 inpatient admissions for sepsis, of which 15,331 hospitalizations (8.3 %) were preceded by a treat-and-release ED visit in the prior 30 days. Based on the O:E and temporal analyses, the presentations of fever and dehydration were both overrepresented in the study cohort and temporally clustered close to sepsis hospitalization. ED treat-and-release visits for fever or dehydration preceded 1.2 % of all sepsis admissions.

Conclusions

In pediatric patients presenting to the ED, fever and dehydration may represent harbingers for future sepsis hospitalization. The SPADE methodology could be applied to the PHIS database to develop diagnostic performance measures across a wide range of pediatric hospitals.


Corresponding author: Jonathan G. Sawicki, MD, MSCI, Department of Pediatrics, University of Utah School of Medicine, 100 N. Mario Capecchi Drive, Salt Lake City, UT 84113 USA, E-mail:

  1. Research ethics: The local Institutional Review Board deemed the study to be non-human subjects research.

  2. Informed consent: Not applicable.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: The raw data can be obtained on request from the corresponding author.

References

1. Medicine, IO. National academies of sciences E, and medicine. In: Balogh, EP, Miller, BT, Ball, JR, editors. Improving diagnosis in health care. Washington, DC: The National Academies Press; 2015:472 p.Search in Google Scholar

2. Graber, ML. The incidence of diagnostic error in medicine. BMJ Qual Saf 2013;22:ii21–7. https://doi.org/10.1136/bmjqs-2012-001615.Search in Google Scholar PubMed PubMed Central

3. Newman-Toker, DE, Pronovost, PJ. Diagnostic errors–the next Frontier for patient safety. JAMA 2009;301:1060–2. https://doi.org/10.1001/jama.2009.249.Search in Google Scholar PubMed

4. Hoffman, JM, Keeling, NJ, Forrest, CB, Tubbs-Cooley, HL, Moore, E, Oehler, E, et al.. Priorities for pediatric patient safety research. Pediatrics 2019;143. https://doi.org/10.1542/peds.2018-0496.Search in Google Scholar PubMed PubMed Central

5. Marshall, TL, Rinke, ML, Olson, APJ, Brady, PW. Diagnostic error in pediatrics: a narrative review. Pediatrics 2022;149. https://doi.org/10.1542/peds.2020-045948d.Search in Google Scholar

6. Newman-Toker, DE. A unified conceptual model for diagnostic errors: underdiagnosis, overdiagnosis, and misdiagnosis. Diagnosis 2014;1:43–8. https://doi.org/10.1515/dx-2013-0027.Search in Google Scholar PubMed PubMed Central

7. Schiff, GD, Hasan, O, Kim, S, Abrams, R, Cosby, K, Lambert, BL, et al.. Diagnostic error in medicine: analysis of 583 physician-reported errors. Arch Intern Med 2009;169:1881–7. https://doi.org/10.1001/archinternmed.2009.333.Search in Google Scholar PubMed

8. Singh, H.: helping health care organizations to define diagnostic errors as missed opportunities in diagnosis. Joint Comm J Qual Patient Saf 2014;40:99–101. https://doi.org/10.1016/s1553-7250(14)40012-6.Search in Google Scholar PubMed

9. Newman-Toker, DE, Nassery, N, Schaffer, AC, Yu-Moe, CW, Clemens, GD, Wang, Z, et al.. Burden of serious harms from diagnostic error in the USA. BMJ Qual Saf 2024;33:109–20. https://doi.org/10.1136/bmjqs-2021-014130.Search in Google Scholar PubMed PubMed Central

10. Singh, H, Sittig, DF. Advancing the science of measurement of diagnostic errors in healthcare: the Safer Dx framework. BMJ Qual Saf 2015;24:103–10. https://doi.org/10.1136/bmjqs-2014-003675.Search in Google Scholar PubMed PubMed Central

11. Zwaan, L, Singh, H. The challenges in defining and measuring diagnostic error. Diagnosis 2015;2:97–103. https://doi.org/10.1515/dx-2014-0069.Search in Google Scholar PubMed PubMed Central

12. Sawicki, JG, Nystrom, D, Purtell, R, Good, B, Chaulk, D. Diagnostic error in the pediatric hospital: a narrative review. Hosp Pract 2021;49:437–44. https://doi.org/10.1080/21548331.2021.2004040.Search in Google Scholar PubMed PubMed Central

13. Newman-Toker, DE. Where is the “low-hanging fruit” in diagnostic quality and safety? Qual Manag Health Care 2018;27:234–6. https://doi.org/10.1097/qmh.0000000000000184.Search in Google Scholar PubMed

14. Horberg, MA, Nassery, N, Rubenstein, KB, Certa, JM, Shamim, EA, Rothman, R, et al.. Rate of sepsis hospitalizations after misdiagnosis in adult emergency department patients: a look-forward analysis with administrative claims data using symptom-disease pair analysis of diagnostic error (SPADE) methodology in an integrated health system. Diagnosis 2021;8:479–88. https://doi.org/10.1515/dx-2020-0145.Search in Google Scholar PubMed

15. Liberman, AL, Newman-Toker, DE. Symptom-disease pair analysis of diagnostic error (SPADE): a conceptual framework and methodological approach for unearthing misdiagnosis-related harms using big data. BMJ Qual Saf 2018;27:557–66. https://doi.org/10.1136/bmjqs-2017-007032.Search in Google Scholar PubMed PubMed Central

16. Liberman, AL, Wang, Z, Zhu, Y, Hassoon, A, Choi, J, Austin, JM, et al.. Optimizing measurement of misdiagnosis-related harms using symptom-disease pair analysis of diagnostic error (SPADE): comparison groups to maximize SPADE validity. Diagnosis 2023;10:225–34. https://doi.org/10.1515/dx-2022-0130.Search in Google Scholar PubMed PubMed Central

17. Murphy, DR, Meyer, AN, Sittig, DF, Meeks, DW, Thomas, EJ, Singh, H. Application of electronic trigger tools to identify targets for improving diagnostic safety. BMJ Qual Saf 2019;28:151–9. https://doi.org/10.1136/bmjqs-2018-008086.Search in Google Scholar PubMed PubMed Central

18. Nassery, N, Horberg, MA, Rubenstein, KB, Certa, JM, Watson, E, Somasundaram, B, et al.. Antecedent treat-and-release diagnoses prior to sepsis hospitalization among adult emergency department patients: a look-back analysis employing insurance claims data using symptom-disease pair analysis of diagnostic error (SPADE) methodology. Diagnosis 2021;8:469–78. https://doi.org/10.1515/dx-2020-0140.Search in Google Scholar PubMed

19. Prout, AJ, Talisa, VB, Carcillo, JA, Mayr, FB, Angus, DC, Seymour, CW, et al.. Children with chronic disease bear the highest burden of pediatric sepsis. J Pediatr 2018;199:194–9.e1. https://doi.org/10.1016/j.jpeds.2018.03.056.Search in Google Scholar PubMed PubMed Central

20. Prusakowski, MK, Chen, AP. Pediatric sepsis. Emerg Med Clin 2017;35:123–38. https://doi.org/10.1016/j.emc.2016.08.008.Search in Google Scholar PubMed

21. Rudd, KE, Johnson, SC, Agesa, KM, Shackelford, KA, Tsoi, D, Kievlan, DR, et al.. Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the global burden of disease study. Lancet 2020;395:200–11. https://doi.org/10.1016/s0140-6736(19)32989-7.Search in Google Scholar PubMed PubMed Central

22. Sankar, J, Garg, M, Ghimire, JJ, Sankar, MJ, Lodha, R, Kabra, SK. Delayed administration of antibiotics beyond the first hour of recognition is associated with increased mortality rates in children with sepsis/severe sepsis and septic shock. J Pediatr 2021;233:183–90.e3. https://doi.org/10.1016/j.jpeds.2020.12.035.Search in Google Scholar PubMed

23. Schlapbach, LJ, Watson, RS, Sorce, LR, Argent, AC, Menon, K, Hall, MW, et al.. International consensus criteria for pediatric sepsis and septic shock. JAMA 2024;331:665–674. https://doi.org/10.1001/jama.2024.0179.Search in Google Scholar PubMed PubMed Central

24. Seymour, CW, Gesten, F, Prescott, HC, Friedrich, ME, Iwashyna, TJ, Phillips, GS, et al.. Time to treatment and mortality during mandated emergency care for sepsis. N Engl J Med 2017;376:2235–44. https://doi.org/10.1056/nejmoa1703058.Search in Google Scholar PubMed PubMed Central

25. Weiss, SL, Peters, MJ, Alhazzani, W, Agus, MSD, Flori, HR, Inwald, DP, et al.. Surviving sepsis campaign international guidelines for the management of septic shock and sepsis-associated organ dysfunction in children. Pediatr Crit Care Med 2020;21:e52–106. https://doi.org/10.1097/pcc.0000000000002198.Search in Google Scholar PubMed

26. Weiss, SL, Balamuth, F, Hensley, J, Fitzgerald, JC, Bush, J, Nadkarni, VM, et al.. The epidemiology of hospital death following pediatric severe sepsis: when, why, and how children with sepsis die. Pediatr Crit Care Med 2017;18:823–30. https://doi.org/10.1097/pcc.0000000000001222.Search in Google Scholar

27. Rhee, C, Kadri, SS, Danner, RL, Suffredini, AF, Massaro, AF, Kitch, BT, et al.. Diagnosing sepsis is subjective and highly variable: a survey of intensivists using case vignettes. Crit Care 2016;20:89. https://doi.org/10.1186/s13054-016-1266-9.Search in Google Scholar PubMed PubMed Central

28. Cifra, CL, Westlund, E, Ten Eyck, P, Ward, MM, Mohr, NM, Katz, DA. An estimate of missed pediatric sepsis in the emergency department. Diagnosis 2021;8:193–8. https://doi.org/10.1515/dx-2020-0023.Search in Google Scholar PubMed PubMed Central

29. Decourcey, DD, Steil, GM, Wypij, D, Agus, MS. Increasing use of hypertonic saline over mannitol in the treatment of symptomatic cerebral edema in pediatric diabetic ketoacidosis: an 11-year retrospective analysis of mortality. Pediatr Crit Care Med 2013;14:694–700. https://doi.org/10.1097/pcc.0b013e3182975cab.Search in Google Scholar PubMed

30. Mongelluzzo, J, Mohamad, Z, Ten Have, TR, Shah, SS. Corticosteroids and mortality in children with bacterial meningitis. JAMA 2008;299:2048–55. https://doi.org/10.1001/jama.299.17.2048.Search in Google Scholar PubMed

31. Balamuth, F, Weiss, SL, Hall, M, Neuman, MI, Scott, H, Brady, PW, et al.. Identifying pediatric severe sepsis and septic shock: accuracy of diagnosis codes. J Pediatr 2015;167:1295–300.e4. https://doi.org/10.1016/j.jpeds.2015.09.027.Search in Google Scholar PubMed PubMed Central

32. Jolley, RJ, Quan, H, Jetté, N, Sawka, KJ, Diep, L, Goliath, J, et al.. Validation and optimisation of an ICD-10-coded case definition for sepsis using administrative health data. BMJ Open 2015;5:e009487. https://doi.org/10.1136/bmjopen-2015-009487.Search in Google Scholar PubMed PubMed Central

33. Michelson, KA, Buchhalter, LC, Bachur, RG, Mahajan, P, Monuteaux, MC, Finkelstein, JA. Accuracy of automated identification of delayed diagnosis of pediatric appendicitis and sepsis in the ED. Emerg Med J 2019;36:736–40. https://doi.org/10.1136/emermed-2019-208841.Search in Google Scholar PubMed

34. Gill, PJ, Anwar, MR, Thavam, T, Hall, M, Rodean, J, Mahant, S. Pediatric clinical classification system for use in inpatient settings. JAMA Pediatr 2021;175:525–7. https://doi.org/10.1001/jamapediatrics.2020.6007.Search in Google Scholar PubMed PubMed Central

35. Feudtner, C, Feinstein, JA, Zhong, W, Hall, M, Dai, D. Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation. BMC Pediatr 2014;14:199. https://doi.org/10.1186/1471-2431-14-199.Search in Google Scholar PubMed PubMed Central

36. diversitydatakids.org. Child opportunity index 2.0 database. 2023. https://data.diversitydatakids.org/dataset/coi20-child-opportunity-index-2-0-database?_external=True [Accessed 19 May 2024].Search in Google Scholar

37. Vaillancourt, S, Guttmann, A, Li, Q, Chan, IY, Vermeulen, MJ, Schull, MJ. Repeated emergency department visits among children admitted with meningitis or septicemia: a population-based study. Ann Emerg Med 2015;65:625–32.e3. https://doi.org/10.1016/j.annemergmed.2014.10.022.Search in Google Scholar PubMed

38. Michelson, KA, Bachur, RG, Grubenhoff, JA, Cruz, AT, Chaudhari, PP, Reeves, SD, et al.. Outcomes of missed diagnosis of pediatric appendicitis, new-onset diabetic ketoacidosis, and sepsis in five pediatric hospitals. J Emerg Med 2023;65:e9–18. https://doi.org/10.1016/j.jemermed.2023.04.006.Search in Google Scholar PubMed PubMed Central

39. Wears, RL, Nemeth, CP. Replacing hindsight with insight: toward better understanding of diagnostic failures. Ann Emerg Med 2007;49:206–9. https://doi.org/10.1016/j.annemergmed.2006.08.027.Search in Google Scholar PubMed

40. Michelson, KA, Rees, CA, Florin, TA, Bachur, RG. Emergency department volume and delayed diagnosis of serious pediatric conditions. JAMA Pediatr 2024;178:362–8. https://doi.org/10.1001/jamapediatrics.2023.6672.Search in Google Scholar PubMed PubMed Central

41. Scott, HF, Greenwald, EE, Bajaj, L, Deakyne Davies, SJ, Brou, L, Kempe, A. The sensitivity of clinician diagnosis of sepsis in tertiary and community-based emergency settings. J Pediatr 2018;195:220–7.e1. https://doi.org/10.1016/j.jpeds.2017.11.030.Search in Google Scholar PubMed

42. Michelson, KA, Lyons, TW, Bachur, RG, Monuteaux, MC, Finkelstein, JA. Timing and location of emergency department revisits. Pediatrics 2018;141. https://doi.org/10.1542/peds.2017-4087.Search in Google Scholar PubMed


Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/dx-2024-0119).


Received: 2024-07-09
Accepted: 2024-11-04
Published Online: 2024-12-12

© 2024 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Pioneering diagnosis in Asia: advancing clinical reasoning expertise through the lens of 3M
  4. Short Communication
  5. The foundations of the diagnostic error movement: a tribute to Eta Berner, PhD
  6. Reviews
  7. Interventions to improve timely cancer diagnosis: an integrative review
  8. Technical aspects and clinical applications of synthetic MRI: a scoping review
  9. Mini Review
  10. Challenges and barriers for the adoption of personalized medicine in Europe: the case of Oncotype DX Breast Recurrence Score® test
  11. Opinion Papers
  12. Beyond thinking fast and slow: a Bayesian intuitionist model of clinical reasoning in real-world practice
  13. Diagnostic scope: the AI can’t see what the mind doesn’t know
  14. Guidelines and Recommendations
  15. CDC’s Core Elements to promote diagnostic excellence
  16. Original Articles
  17. Trends of diagnostic adverse events in hospital deaths: longitudinal analyses of four retrospective record review studies
  18. The effect of a provisional diagnosis on intern diagnostic reasoning: a mixed methods study
  19. On context specificity and management reasoning: moving beyond diagnosis
  20. Diagnostic errors in patients admitted directly from new outpatient visits
  21. Breaking the guidelines: how financial unawareness fuels guideline deviations and inefficient DVT diagnostics
  22. Harbingers of sepsis misdiagnosis among pediatric emergency department patients
  23. Factors affecting diagnostic difficulties in aseptic meningitis: a retrospective observational study
  24. Prenatal diagnostic errors in hemoglobin Bart’s hydrops fetalis caused by rare genetic interactions of α-thalassemia
  25. Screening fasting glucose before the OGTT: near-patient glucometer- or laboratory-based measurement?
  26. Three-way comparison of different ESR measurement methods and analytical performance assessment of TEST1 automated ESR analyzer
  27. Short Communications
  28. Medical language matters: impact of clinical summary composition on a generative artificial intelligence’s diagnostic accuracy
  29. Impact of meta-memory techniques in generating effective differential diagnoses in a pediatric core clerkship
Downloaded on 24.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/dx-2024-0119/html
Scroll to top button