Skip to main content

Advertisement

SpringerLink
Log in

Decision-Making in the Catheter Laboratory: The Most Important Variable in Successful Outcomes

  • Review Article
  • Published:
Pediatric Cardiology Aims and scope Submit manuscript

Abstract

Increasingly the importance of how and why we make decisions in the medical arena has been questioned. Traditionally the aeronautical and business worlds have shed a light on this complex area of human decision-making. In this review we reflect on what we already know about the complexity of decision-making in addition to directing particular focus on the challenges to decision-making in the high-intensity environment of the pediatric cardiac catheterization laboratory. We propose that the most critical factor in outcomes for children in the catheterization lab may not be technical failures but rather human factors and the lack of preparation and robust shared decision-making process between the catheterization team. Key technical factors involved in the decision-making process include understanding the anatomy, the indications and objective to be achieved, equipment availability, procedural flow, having a back-up plan and post-procedural care plan. Increased awareness, pre-catheterization planning, use of standardized clinical assessment and management plans and artificial intelligence may provide solutions to pitfalls in decision-making. Further research and efforts should be directed towards studying the impact of human factors in the cardiac catheterization laboratory as well as the broader medical environment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Hammond JS, Keeney RL, Raiffa H (1998) The hidden traps in decision making. Harv Bus Rev 76(5):47–58

    CAS  PubMed  Google Scholar 

  2. Tversky A, Kahneman D (1974) Judgment under uncertainty: heuristics and biases. Science 185(4157):1124–1131

    CAS  PubMed  Google Scholar 

  3. Sackett DL, Rosenberg WMC, Gray JAM, Haynes RB, Richardson WS (1996) Evidence based medicine: what it is and what it isn't. BMJ 312(7023):71–72

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Ryan A, Duignan S, Kenny D, McMahon CJ (2018) Decision making in paediatric cardiology. Are we prone to heuristics, biases and traps? Pediatr Cardiol 39(1):160–167

    PubMed  Google Scholar 

  5. Duignan S, Ryan A, O’Keeffe D, Kenny D, McMahon CJ (2018) Prospective analysis of decision making during joint cardiology cardiothoracic conference in treatment of 107 consecutive children with congenital heart disease. Pediatr Cardiol 39(7):1330–1338

    PubMed  Google Scholar 

  6. Global Air Training Ltd (2006) Team resource management instructor manual. Cheshire

  7. Uramatsu M, Fujisawa Y, Mizuno S, Souma T, Komatsubara A, Miki T (2017) Do failures in non-technical skills contribute to fatal medical accidents in Japan? A review of the 2010–2013 national accident reports. BMJ Open 7(2):e013678

    PubMed  PubMed Central  Google Scholar 

  8. Odell M (2011) Human factors and patient safety: changing roles in critical care. Aust Crit Care 24(4):215–217

    PubMed  Google Scholar 

  9. Reader T, Flin R, Lauche K, Cuthbertson BH (2006) Non-technical skills in the intensive care unit. Br J Anaesth 96(5):551–559

    CAS  PubMed  Google Scholar 

  10. Siu J, Maran N, Paterson-Brown S (2016) Observation of behavioural markers of non-technical skills in the operating room and their relationship to intra-operative incidents. Surgeon 14(3):119–128

    PubMed  Google Scholar 

  11. Yule S, Flin R, Paterson-Brown S, Maran N (2006) Non-technical skills for surgeons in the operating room: a review of the literature. Surgery 139(2):140–149

    CAS  PubMed  Google Scholar 

  12. Binenbaum G, Volpe NJ (2006) Ophthalmology resident surgical competency: a national survey. Ophthalmology 113(7):1237–1244

    PubMed  Google Scholar 

  13. Zsambok CE, Klein G (2014) Naturalistic decision making. Psychology Press, New York

    Google Scholar 

  14. Flin R, Youngson G, Yule S (2007) How do surgeons make intraoperative decisions? Qual Saf Health Care 16(3):235–239

    PubMed  PubMed Central  Google Scholar 

  15. Pauley K, Flin R, Yule S, Youngson G (2011) Surgeons’ intraoperative decision making and risk management. Am J Surg 202(4):375–381

    PubMed  Google Scholar 

  16. Pauley K, Flin R, Azuara-Blanco A (2013) Intra-operative decision making by ophthalmic surgeons. Br J Ophthalmol 97(10):1303–1307

    PubMed  Google Scholar 

  17. Abernathy C, Hamm RM (1995) Surgical intuition: what it is and how to get it. Hanley and Belfus, Philadelphia

    Google Scholar 

  18. Kahneman D, Egan P (2011) Thinking, fast and slow, vol 1. Farrar, Straus and Giroux, New York

    Google Scholar 

  19. Ely JW, Graber ML, Croskerry P (2011) Checklists to reduce diagnostic errors. Acad Med 86(3):307–313

    PubMed  Google Scholar 

  20. Mamede S, van Gog T, van den Berge K, van Saase JLCM, Schmidt HG (2014) Why do doctors make mistakes? A study of the role of salient distracting clinical features. Acad Med 89(1):114–120

    PubMed  Google Scholar 

  21. van den Berge K, Mamede S (2013) Cognitive diagnostic error in internal medicine. Eur J Intern Med 24(6):525–529

    PubMed  Google Scholar 

  22. Turk DC, Salovey PE (1988) Reasoning, inference, and judgment in clinical psychology. Free Press, New York

    Google Scholar 

  23. Fischhoff B (1982) Debiasing. In: Kahneman D, Slovic P, Tversky A (eds) Judgment under uncertainty. Cambridge University Press, Cambridge, pp 422–444

    Google Scholar 

  24. Gruppen LD, Margolin J, Wisdom K, Grum CM (1994) Outcome bias and cognitive dissonance in evaluating treatment decisions. Acad Med 69(10 Suppl):S57–S59

    CAS  PubMed  Google Scholar 

  25. Flin R, Patey R, Glavin R, Maran N (2010) Anaesthetists’ non-technical skills. Br J Anaesth 105(1):38–44

    CAS  PubMed  Google Scholar 

  26. Christian CK, Gustafson ML, Roth EM, Sheridan TB, Gandhi TK, Dwyer K et al (2006) A prospective study of patient safety in the operating room. Surgery 139(2):159–173

    PubMed  Google Scholar 

  27. Stevenson KS, Gibson SC, MacDonald D, Hole DJ, Rogers PN, Byrne DS et al (2007) Measurement of process as quality control in the management of acute surgical emergencies. Br J Surg 94(3):376–381

    CAS  PubMed  Google Scholar 

  28. Yule S, Flin R, Paterson-Brown S, Maran N, Rowley D (2006) Development of a rating system for surgeons’ non-technical skills. Med Educ 40(11):1098–1104

    CAS  PubMed  Google Scholar 

  29. Yule S, Flin R, Maran N, Rowley D, Youngson G, Paterson-Brown S (2008) Surgeons’ non-technical skills in the operating room: reliability testing of the notss behavior rating system. World J Surg 32(4):548–556

    PubMed  Google Scholar 

  30. Harvey A, Bandiera G, Nathens AB, LeBlanc VR (2012) Impact of stress on resident performance in simulated trauma scenarios. J Trauma Acute Care Surg 72(2):497–503

    PubMed  Google Scholar 

  31. Müller MP, Hänsel M, Fichtner A, Hardt F, Weber S, Kirschbaum C et al (2009) Excellence in performance and stress reduction during two different full scale simulator training courses: a pilot study. Resuscitation 80(8):919–924

    PubMed  Google Scholar 

  32. Ghazali DA, Ragot S, Breque C, Guechi Y, Boureau-Voultoury A, Petitpas F et al (2016) Randomized controlled trial of multidisciplinary team stress and performance in immersive simulation for management of infant in shock: study protocol. Scand J Trauma Resusc Emerg Med 24:36

    PubMed  PubMed Central  Google Scholar 

  33. Rudarakanchana N, Van Herzeele I, Desender L, Cheshire NJ (2015) Virtual reality simulation for the optimization of endovascular procedures: current perspectives. Vasc Health Risk Manag 11:195–202

    PubMed  PubMed Central  Google Scholar 

  34. Willaert WIM, Aggarwal R, Daruwalla F, Van Herzeele I, Darzi AW, Vermassen FE et al (2012) Simulated procedure rehearsal is more effective than a preoperative generic warm-up for endovascular procedures. Ann Surg 255(6):1184–1189

    PubMed  Google Scholar 

  35. Duignan S, Ryan A, Burns B, Kenny D, McMahon CJ (2018) Complex decision making in the pediatric catheterization laboratory: catheterizer, know thyself and the data. Pediatr Cardiol 39(7):1281–1289

    PubMed  Google Scholar 

  36. Billings CE (1998) Some hopes and concerns regarding medical event-reporting systems: lessons from the NASA aviation safety reporting system. Arch Pathol Lab Med 122(3):214–215

    CAS  PubMed  Google Scholar 

  37. Reason JT (2008) The human contribution: unsafe acts, accidents and heroic recoveries. Ashgate, England

    Google Scholar 

  38. Kohn LT, Corrigan J, Donaldson MS (2000) To err is human: building a safer health system. https://site.ebrary.com/id/10038653. Accessed 15 Nov 2019

  39. Catchpole K, Bell MDD, Johnson S (2008) Safety in anaesthesia: a study of 12,606 reported incidents from the UK national reporting and learning system. Anaesthesia 63(4):340–346

    CAS  PubMed  Google Scholar 

  40. Lee ME (2008) Near misses in cardiac surgery. iUniverse, Bloomington

  41. Somerville J (1997) Near misses and disasters in the treatment of grown-up congenital heart patients. J R Soc Med 90(3):124–127

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Jenkins OF, Morris R, Simpson JM (1997) Australasian perfusion incident survey. Perfusion 12(5):279–288

    CAS  PubMed  Google Scholar 

  43. de Leval MR, François K, Bull C, Brawn W, Spiegelhalter D (1994) Analysis of a cluster of surgical failures: application to a series of neonatal arterial switch operations. J Thorac Cardiovasc Surg 107(3):914–924

    PubMed  Google Scholar 

  44. de Leval MR, Carthey J, Wright DJ, Farewell VT, Reason JT (2000) Human factors and cardiac surgery: a multicenter study. J Thorac Cardiovasc Surg 119(4):661–672

    PubMed  Google Scholar 

  45. Silber JH, Rosenbaum PR, Schwartz JS, Ross RN, Williams SV (1995) Evaluation of the complication rate as a measure of quality of care in coronary artery bypass graft surgery. JAMA 274(4):317–323

    CAS  PubMed  Google Scholar 

  46. Silber JH, Williams SV, Krakauer H, Schwartz JS (1992) Hospital and patient characteristics associated with death after surgery: a study of adverse occurrence and failure to rescue. Med Care 30(7):615–629

    CAS  PubMed  Google Scholar 

  47. Lynn LA (2019) Artificial intelligence systems for complex decision-making in acute care medicine: a review. Patient Saf Surg. https://doi.org/10.1186/s13037-019-0188-2

    Article  PubMed  PubMed Central  Google Scholar 

  48. Nemati S, Holder A, Razmi F, Stanley MD, Clifford GD, Buchman TG (2018) An interpretable machine learning model for accurate prediction of sepsis in the ICU. Crit Care Med 46(4):547–553

    PubMed  PubMed Central  Google Scholar 

  49. Diller G-P, Babu-Narayan S, Li W, Radojevic J, Kempny A, Uebing A et al (2019) Utility of machine learning algorithms in assessing patients with a systemic right ventricle. Eur Heart J Cardiovasc Imaging. https://doi.org/10.1093/ehjci/jey211

    Article  PubMed  PubMed Central  Google Scholar 

  50. Meza JM, Slieker M, Blackstone EH, Mertens L, DeCampli WM, Kirklin JK et al (2018) A novel, data-driven conceptualization for critical left heart obstruction. Comput Method Progr Biomed 165:107–116

    Google Scholar 

  51. Lohr S (2016) IBM is counting on its bet on watson, and paying big money for it. The New York Times. https://www.nytimes.com/2016/10/17/technology/ibm-is-counting-on-its-bet-on-watson-and-paying-big-money-for-it.html. Accessed 15 Nov 2019

  52. Porras D, Brown DW, Rathod R, Friedman K, Gauvreau K, Lock JE et al (2014) Acute outcomes after introduction of a standardized clinical assessment and management plan (SCAMP) for balloon aortic valvuloplastyin congenital aortic stenosis. Congenit Heart Dis 9(4):316–325

    PubMed  Google Scholar 

  53. Boe BA, Zampi JD, Kennedy KF, Jayaram N, Porras D, Foerster SR et al (2017) Acute success of balloon aortic valvuloplasty in the current era: a national cardiovascular data registry study. JACC Cardiovasc Interv 10(17):1717–1726

    PubMed  Google Scholar 

  54. McCrindle BW (1996) Independent predictors of immediate results of percutaneous balloon aortic valvotomy in children Valvuloplasty and angioplasty of congenital anomalies (VACA) registry investigators. Am J Cardiol 77(4):286–293

    CAS  PubMed  Google Scholar 

  55. Kim DW, Raviele AA, Vincent RN (2005) Use of a 3 French system for balloon aortic valvuloplasty in infants. Catheter Cardiovasc Interv 66(2):254–257

    PubMed  Google Scholar 

  56. Magee AG, Nykanen D, McCrindle BW, Wax D, Freedom RM, Benson LN (1997) Balloon dilation of severe aortic stenosis in the neonate: comparison of anterograde and retrograde catheter approaches. J Am Coll Cardiol 30(4):1061–1066

    CAS  PubMed  Google Scholar 

  57. McElhinney DB, Lock JE, Keane JF, Moran AM, Colan SD (2005) Left heart growth, function, and reintervention after balloon aortic valvuloplasty for neonatal aortic stenosis. Circulation 111(4):451–458

    PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Paediatric Cardiology, Children’s Hospital Ireland, Crumlin, Dublin 12, Ireland

    Sophie Duignan, Kevin P. Walsh & Colin J. McMahon

Authors
  1. Sophie Duignan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kevin P. Walsh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Colin J. McMahon
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Colin J. McMahon.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Duignan, S., Walsh, K.P. & McMahon, C.J. Decision-Making in the Catheter Laboratory: The Most Important Variable in Successful Outcomes. Pediatr Cardiol 41, 459–468 (2020). https://doi.org/10.1007/s00246-020-02295-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00246-020-02295-1

Keywords

Search

Navigation