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Assessing the Revised Safer Dx Instrument® in the understanding of ambulatory system design changes for type 1 diabetes and autism spectrum disorder in pediatrics

  • Patrick W. Brady EMAIL logo , Richard M. Ruddy , Jennifer Ehrhardt , Sarah D. Corathers , Eric S. Kirkendall and Kathleen E. Walsh
Published/Copyright: March 25, 2024
Diagnosis
From the journal Diagnosis Volume 11 Issue 3

Abstract

Objectives

We sought within an ambulatory safety study to understand if the Revised Safer Dx instrument may be helpful in identification of diagnostic missed opportunities in care of children with type 1 diabetes (T1D) and autism spectrum disorder (ASD).

Methods

We reviewed two months of emergency department (ED) encounters for all patients at our tertiary care site with T1D and a sample of such encounters for patients with ASD over a 15-month period, and their pre-visit communication methods to better understand opportunities to improve diagnosis. We applied the Revised Safer Dx instrument to each diagnostic journey. We chose potentially preventable ED visits for hyperglycemia, diabetic ketoacidosis, and behavioral crises, and reviewed electronic health record data over the prior three months related to the illness that resulted in the ED visit.

Results

We identified 63 T1D and 27 ASD ED visits. Using the Revised Safer Dx instrument, we did not identify any potentially missed opportunities to improve diagnosis in T1D. We found two potential missed opportunities (Safer Dx overall score of 5) in ASD, related to potential for ambulatory medical management to be improved. Over this period, 40 % of T1D and 52 % of ASD patients used communication prior to the ED visit.

Conclusions

Using the Revised Safer Dx instrument, we uncommonly identified missed opportunities to improve diagnosis in patients who presented to the ED with potentially preventable complications of their chronic diseases. Future researchers should consider prospectively collected data as well as development or adaptation of tools like the Safer Dx.

Keywords: diagnostic error; communication; ambulatory care
Corresponding author: Patrick W. Brady, MD, MSc, Professor of Pediatrics University of Cincinnati College of Medicine, Division of Hospital Medicine, Cincinnati Children’s Hospital, 3333 Burnet Avenue, Cincinnati, OH 45229-1899, USA, E-mail:
Patrick Brady and Richard Ruddy contributed equally to this work and share first authorship.

Funding source: Agency for Healthcare Research and Quality

Award Identifier / Grant number: R18HS026644

Acknowledgments

We would like to thank Samira Ahmed for her assistance with this manuscript.

  1. Research ethics: The local Institutional Review Board deemed the study exempt from review.

  2. Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.

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

  4. Competing interests: The authors state no conflicts of interests to disclose.

  5. Research funding: This work was funded by a Patient Safety Learning Lab grant from the Agency for Healthcare Research and Quality (AHRQ R18HS026644).

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

References

1. No place like home: advancing the safety of care in the home. Boston: Institute for Healthcare Improvement; 2018: 83 p. Available from: ihi.org.Search in Google Scholar

2. Balogh, E, Miller, BT, Ball, J, Institute of Medicine (U.S), Committee on Diagnostic Error in Health Care. Improving diagnosis in health care. Washington, DC: The National Academies Press; 2015, vol xxvii:444 p.10.17226/21794Search in Google Scholar PubMed

3. Graber, ML, Rusz, D, Jones, ML, Farm-Franks, D, Jones, B, Cyr Gluck, J, et al.. The new diagnostic team. Diagnosis 2017;4:225–38. https://doi.org/10.1515/dx-2017-0022.Search in Google Scholar PubMed

4. Ely, JW, Graber, ML. Preventing diagnostic errors in primary care. Am Fam Physician 2016;94:426–32.Search in Google Scholar

5. Singh, H, Meyer, AN, Thomas, EJ. The frequency of diagnostic errors in outpatient care: estimations from three large observational studies involving US adult populations. BMJ Qual Saf 2014;23:727–31. https://doi.org/10.1136/bmjqs-2013-002627.Search in Google Scholar PubMed PubMed Central

6. Stille, CJ, Primack, WA, McLaughlin, TJ, Wasserman, RC. Parents as information intermediaries between primary care and specialty physicians. Pediatrics 2007;120:1238–46. https://doi.org/10.1542/peds.2007-1112.Search in Google Scholar PubMed

7. Stille, CJ, McLaughlin, TJ, Primack, WA, Mazor, KM, Wasserman, RC. Determinants and impact of generalist-specialist communication about pediatric outpatient referrals. Pediatrics 2006;118:1341–9. https://doi.org/10.1542/peds.2005-3010.Search in Google Scholar PubMed

8. Huibers, L, Smits, M, Renaud, V, Giesen, P, Wensing, M. Safety of telephone triage in out-of-hours care: a systematic review. Scand J Prim Health Care 2011;29:198–209. https://doi.org/10.3109/02813432.2011.629150.Search in Google Scholar PubMed PubMed Central

9. Craig, ME, Codner, E, Mahmud, FH, Marcovecchio, ML, DiMeglio, LA, Priyambada, L, et al.. ISPAD clinical practice consensus guidelines 2022: editorial. Pediatr Diabetes 2022;23:1157–9. https://doi.org/10.1111/pedi.13441.Search in Google Scholar PubMed PubMed Central

10. American Diabetes Association Professional Practice Committee. Standards of care in diabetes – 2024. Arlington, Virginia: American Diabetes Association; 2024.Search in Google Scholar

11. Al-Mutairi, A, Meyer, AN, Thomas, EJ, Etchegaray, JM, Roy, KM, Davalos, MC, et al.. Accuracy of the Safer Dx instrument to identify diagnostic errors in primary care. J Gen Intern Med 2016;31:602–8. https://doi.org/10.1007/s11606-016-3601-x.Search in Google Scholar PubMed PubMed Central

12. Singh, H, Khanna, A, Spitzmueller, C, Meyer, AND. Recommendations for using the Revised Safer Dx Instrument to help measure and improve diagnostic safety. Diagnosis 2019;6:315–23. https://doi.org/10.1515/dx-2019-0012.Search in Google Scholar PubMed

13. 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

14. Singh, H, Weingart, SN. Diagnostic errors in ambulatory care: dimensions and preventive strategies. Adv Health Sci Educ 2009;14 Suppl 1:57–61. https://doi.org/10.1007/s10459-009-9177-z.Search in Google Scholar PubMed PubMed Central

15. Hand, BN, Boan, AD, Bradley, CC, Charles, JM, Carpenter, LA. Ambulatory care sensitive admissions in individuals with autism spectrum disorder, intellectual disability, and population controls. Autism Res 2019;12:295–302. https://doi.org/10.1002/aur.2050.Search in Google Scholar PubMed

16. Kalb, LG, Stuart, EA, Vasa, RA. Characteristics of psychiatric emergency department use among privately insured adolescents with autism spectrum disorder. Autism 2019;23:566–73. https://doi.org/10.1177/1362361317749951.Search in Google Scholar PubMed

17. Trief, PM, Cibula, D, Rodriguez, E, Akel, B, Weinstock, RS. Incorrect insulin administration: a problem that warrants attention. Clin Diabetes 2016;34:25–33. https://doi.org/10.2337/diaclin.34.1.25.Search in Google Scholar PubMed PubMed Central

18. Wijngaarde, RO, Hein, I, Daams, J, Van Goudoever, JB, Ubbink, DT. Chronically ill children’s participation and health outcomes in shared decision-making: a scoping review. Eur J Pediatr 2021;180:2345–57. https://doi.org/10.1007/s00431-021-04055-6.Search in Google Scholar PubMed PubMed Central

Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/dx-2023-0166).

Received: 2023-11-15
Accepted: 2024-02-27
Published Online: 2024-03-25

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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  24. Letters to the Editor
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  26. The dilemma of epilepsy diagnosis in Pakistan
  27. The Japanese universal health insurance system in the context of diagnostic equity
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https://doi.org/10.1515/dx-2023-0166
Keywords for this article
diagnostic error; communication; ambulatory care

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. The growing threat of hijacked journals
  4. Review
  5. Effects of SNAPPS in clinical reasoning teaching: a systematic review with meta-analysis of randomized controlled trials
  6. Mini Review
  7. Diagnostic value of D-dimer in differentiating multisystem inflammatory syndrome in Children (MIS-C) from Kawasaki disease: systematic literature review and meta-analysis
  8. Opinion Papers
  9. Masquerade of authority: hijacked journals are gaining more credibility than original ones
  10. FRAMED: a framework facilitating insight problem solving
  11. Algorithms in medical decision-making and in everyday life: what’s the difference?
  12. Original Articles
  13. Computerized diagnostic decision support systems – a comparative performance study of Isabel Pro vs. ChatGPT4
  14. Comparative analysis of diagnostic accuracy in endodontic assessments: dental students vs. artificial intelligence
  15. Assessing the Revised Safer Dx Instrument® in the understanding of ambulatory system design changes for type 1 diabetes and autism spectrum disorder in pediatrics
  16. The Big Three diagnostic errors through reflections of Japanese internists
  17. SASAN: ground truth for the effective segmentation and classification of skin cancer using biopsy images
  18. Computable phenotype for diagnostic error: developing the data schema for application of symptom-disease pair analysis of diagnostic error (SPADE)
  19. Development of a disease-based hospital-level diagnostic intensity index
  20. HbA1c and fasting plasma glucose levels are equally related to incident cardiovascular risk in a high CVD risk population without known diabetes
  21. Short Communications
  22. Can ChatGPT-4 evaluate whether a differential diagnosis list contains the correct diagnosis as accurately as a physician?
  23. Analysis of thicknesses of blood collection needle by scanning electron microscopy reveals wide heterogeneity
  24. Letters to the Editor
  25. For any disease a human can imagine, ChatGPT can generate a fake report
  26. The dilemma of epilepsy diagnosis in Pakistan
  27. The Japanese universal health insurance system in the context of diagnostic equity
  28. Case Report – Lessons in Clinical Reasoning
  29. Lessons in clinical reasoning – pitfalls, myths, and pearls: a case of tarsal tunnel syndrome caused by an intraneural ganglion cyst
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