Positive Deviance in Health Care: Beware of Pseudo-Equifinality

  • David C. Aron
  • Brigid Wilson
  • Chin-Lin Tseng
  • Orysya Soroka
  • Leonard M. Pogach


Objective Identification of best practices constitutes an important strategy for organizational improvement. We compared different criteria (different measurement thresholds, different comparators, and performance consistency over time) on identification of high-performing facilities, especially positive deviants.

Methods The design was serial cross-sectional, using yearly VHA administrative data (2009–2013). Our primary outcome measure was facility-level rate of HbA1c overtreatment of diabetes in patients at risk for hypoglycemia. Outlier status was assessed by three methods.

Results From 2009 to 2013, the rate of overtreatment overall based on a threshold of 6.5% decreased from 28.6% in 2009 to 22.7% in 2013; the rate of undertreatment increased from 7 to 10.3%. Fourteen facilities were identified in the lowest decile of overtreatment. Undertreatment rates among these facilities were compared to the mean overall undertreatment rate; several facilities identified as positive deviants based on overtreatment rates had exceptionally high rates of undertreatment.

Conclusion Because two facilities may arrive at the same results via very different pathways, it is important to consider that a best practice may actually reflect a separate worst practice.



Funding. The work was supported by grants from the Veterans Health Administration (VHA) Health Services Research & Development Service and its Quality Enhancement Research Initiative (QUERI) to Dr. Aron (SCE 12-181), to Dr. Pogach (RRP-12-492), and to Dr. Tseng (IIR 11-077).

Disclaimer. The opinions expressed are solely those of the authors and do not represent the views of the Department of Veterans Affairs.


  1. 1.
    Bretschneider S, Marc-Aurele Jr F, Wu J. “Best practices” research: a methodological guide for the perplexed. J Public Adm Res Theory 2005;15:307–23.CrossRefGoogle Scholar
  2. 2.
    Guzman G, Fitzgerald JA, Fulop L, et al. How best practices are copied, transferred, or translated between health care facilities: a conceptual framework. Health Care Manag Rev. 2015;40:193–202.CrossRefGoogle Scholar
  3. 3.
    Maggs-Rapport F. ‘Best research practice’: in pursuit of methodological rigour. J Adv Nurs. 2001;35:373–83.CrossRefGoogle Scholar
  4. 4.
    Mold J, Gregory M. Best practices research. Fam Med. 2003;35:131–4.PubMedGoogle Scholar
  5. 5.
    A systematic review of outliers detection techniques in medical data: preliminary study. 11 Jan 26; Rome, Italy: HEALTHINF 2011, 2011.Google Scholar
  6. 6.
    Hodge V, Austin J. A survey of outlier detection methodologies. Artif Intell Rev. 2004;22:85–126.CrossRefGoogle Scholar
  7. 7.
    Shahian DM, Normand SL. What is a performance outlier? BMJ Qual Saf. 2015;24:95–9.CrossRefGoogle Scholar
  8. 8.
    Baxter R, Kellar I, Taylor N, Lawton R. How is the positive deviance approach applied within healthcare organizations? A systematic review of methods used. BMC Health Serv Res. 2014;14 Suppl 2:7.CrossRefGoogle Scholar
  9. 9.
    Bradley EH, Curry LA, Ramanadhan S, Rowe L, Nembhard IM, Krumholz HM. Research in action: using positive deviance to improve quality of health care. Implement Sci. 2009;4:25.CrossRefGoogle Scholar
  10. 10.
    Gabbay RA, Friedberg MW, Miller-Day M, Cronholm PF, Adelman A, Schneider EC. A positive deviance approach to understanding key features to improving diabetes care in the medical home. Ann Fam Med. 2013;11 Suppl 1:S99–107.CrossRefGoogle Scholar
  11. 11.
    Krumholz HM, Curry LA, Bradley EH. Survival after acute myocardial infarction (SAMI) study: the design and implementation of a positive deviance study. Am Heart J. 2011;162:981–7.CrossRefGoogle Scholar
  12. 12.
    Lawton R, Taylor N, Clay-Williams R, Braithwaite J. Positive deviance: a different approach to achieving patient safety. BMJ Qual Saf. 2014;23:880–3.CrossRefGoogle Scholar
  13. 13.
    Luft HS. Data and methods to facilitate delivery system reform: harnessing collective intelligence to learn from positive deviance. Health Serv Res. 2010;45:1570–80.CrossRefGoogle Scholar
  14. 14.
    Setiawan M, Sadiq S. A methodology for improving business process performance through positive deviance. Int J Inf Syst Model Des. 2013;4:1–22.CrossRefGoogle Scholar
  15. 15.
    Singhal A, Greiner K. Using the Positive Deviance approach to reduce hospital-acquired infections at the Veterans Administration Healthcare System in Pittsburgh. In: Suchman A, Sluyter D, Williamson P, editors. Leading change in healthcare: transforming organizations using complexity, positive psychology, and relationship-centered care. New York: Radcliffe Publishing; 2011. p. 177–209.Google Scholar
  16. 16.
    Marsh G. Are follow-up consultations at medical outpatient departments futile? BMJ 1982;284:1176–7.CrossRefGoogle Scholar
  17. 17.
    Sternin J. Practice positive deviance for extraordinary social and organizational change. In: The change champion’s field guide: strategies and tools for leading change in your organization. Hoboken, NJ: Wiley; 2013. p. 20–37.Google Scholar
  18. 18.
    Zeitlin M, Ghassemi H, Mansour M. Positive deviance in child nutrition - with emphasis on psychosocial and behavioural aspects and implications for development. New York: United Nations University Press; 1991.Google Scholar
  19. 19.
    Selby L. Public health project taps into superstar patients’ expertise. (2017). Accessed 5 Jan 2017.
  20. 20.
    Mainemelis C. Stealing fire: creative deviance in the evolution of new ideas. Acad Manag Rev. 2010;35:558–78.CrossRefGoogle Scholar
  21. 21.
    Spreitzer G, Sonenshein S. Positive deviance and extraordinary organizing. In: Cameron K, Dutton J, editors. Positive organizational scholarship: foundations of a new discipline. Oakland, CA: Berrett-Koehler Publishers; 2003. p. 207–24.Google Scholar
  22. 22.
    Spreitzer G, Sonenshein S. Toward the construct definition of positive deviance. Am Behav Sci. 2004;47:828–47.CrossRefGoogle Scholar
  23. 23.
    Vadera A, Pratt M, Mishra P. Constructive deviance in organizations: integrating and moving forward. J Manag. 2013;39:1221–76.Google Scholar
  24. 24.
    Warren D. Constructive and destructive deviance in organizations. Acad Manag Rev. 2003;28:622–32.Google Scholar
  25. 25.
    Lindberg C, Clancy TR. Positive deviance: an elegant solution to a complex problem. J Nurs Adm. 2010;40:150–3.CrossRefGoogle Scholar
  26. 26.
    Spindler M, Wagenheim G. Positive deviance: sparks that ignite systems change. Chall Organ Soc. 2015;4:647–9.Google Scholar
  27. 27.
    Richardson KA, Mathieson G, Cilliers P. The theory and practice of complexity science: epistemological considerations for military operational analysis. SysteMexico 2000;1:25–66.Google Scholar
  28. 28.
    Richardson KA. Complex systems thinking and its implications for policy analysis. In: Handbook of decision making. Boca Raton, FL: CRC Press; 2007. p. 189–122.Google Scholar
  29. 29.
    Pascale R, Sternin J, Sternin M. The power of positive deviance: how unlikely innovators solve the world’s toughest problems. Boston, MA: Harvard Business Press; 2010.Google Scholar
  30. 30.
    Tseng CL, Soroka O, Maney M, Aron DC, Pogach LM. Assessing potential glycemic overtreatment in persons at hypoglycemic risk. JAMA Intern Med. 2013;174:259–68.CrossRefGoogle Scholar
  31. 31.
    Bilimoria KY, Cohen ME, Merkow RP, et al. Comparison of outlier identification methods in hospital surgical quality improvement programs. J Gastrointest Surg. 2010;14:1600–7.CrossRefGoogle Scholar
  32. 32.
    Mull HJ, Chen Q, O’Brien WJ, et al. Comparing 2 methods of assessing 30-day readmissions: what is the impact on hospital profiling in the veterans health administration? Med Care 2013;51:589–96.CrossRefGoogle Scholar
  33. 33.
    Rothberg MB, Morsi E, Benjamin EM, Pekow PS, Lindenauer PK. Choosing the best hospital: the limitations of public quality reporting. Health Aff. (Millwood) 2008;27:1680–7.CrossRefGoogle Scholar
  34. 34.
    Paddock SM, Adams JL, Hoces dlG. Better-than-average and worse-than-average hospitals may not significantly differ from average hospitals: an analysis of Medicare Hospital Compare ratings. BMJ Qual Saf. 2015;24:128–34.CrossRefGoogle Scholar
  35. 35.
    Aron DC. Quality indicators and performance measures in diabetes care. Curr Diab Rep. 2014;14:472.CrossRefGoogle Scholar
  36. 36.
    National action plan for adverse drug event prevention. Washington, DC: U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion; 2014. Accessed 5 Jan 2017.
  37. 37.
    Trucil D. AGS unveils revised list of topics to talk about with older adults as part of choosing wisely®campaign. Accessed 5 Jan 2017.
  38. 38.
    Duckworth W, Abraira C, Moritz T, Reda D, Emanuele N, et al. Glucose control and vascular complications in veterans with type 2 diabetes. N Engl J Med. 2009;360:129–39.CrossRefGoogle Scholar
  39. 39.
    Miller ME, Bonds DE, Gerstein HC, et al. The effects of baseline characteristics, glycaemia treatment approach, and glycated haemoglobin concentration on the risk of severe hypoglycaemia: post hoc epidemiological analysis of the ACCORD study. BMJ 2010;340:b5444.CrossRefGoogle Scholar
  40. 40.
    Inzucchi SE, Bergenstal RM, Buse JB, et al. Management of hyperglycaemia in type 2 diabetes: a patient-centered approach. Position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia 2012;55:1577–96.CrossRefGoogle Scholar
  41. 41.
    Ismail-Beigi F, Moghissi ES, Tiktin M, Hirsch IB, Inzucchi SE, Genuth S. Individualizing glycemic targets in type 2 diabetes mellitus: implications of recent clinical trials. Ann Intern Med 2011;154:554–9.CrossRefGoogle Scholar
  42. 42.
    Montori V, Fernandez-Balsells M. Glycemic control in type 2 diabetes: time for an evidence-based about-face? Ann Intern Med. 2009;150:803–8.CrossRefGoogle Scholar
  43. 43.
    Pogach L, Aron D. Balancing hypoglycemia and glycemic control: a public health approach for insulin safety. JAMA 2010;303:2076–7.CrossRefGoogle Scholar
  44. 44.
    Pogach LM, Tiwari A, Maney M, Rajan M, Miller DR, Aron D. Should mitigating comorbidities be considered in assessing healthcare plan performance in achieving optimal glycemic control? Am J Manag Care 2007;13:133–40.PubMedGoogle Scholar
  45. 45.
    Kapsali M. Equifinality in project management exploring causal complexity in projects. Syst Res Behav Sci. 2013;30:2–14.CrossRefGoogle Scholar
  46. 46.
    Ragin CC, Shulman D, Weinberg A, Gran B. Complexity, generality, and qualitative comparative analysis. Field Methods 2003;15:323–40.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • David C. Aron
    • 1
    • 2
  • Brigid Wilson
    • 3
  • Chin-Lin Tseng
    • 4
    • 5
  • Orysya Soroka
    • 6
  • Leonard M. Pogach
    • 4
    • 5
  1. 1.Department of Veterans AffairsLouis Stokes Cleveland VA Medical CenterClevelandUSA
  2. 2.Case Western Reserve University School of MedicineClevelandUSA
  3. 3.Department of Veterans AffairsLouis Stokes Cleveland VA Medical CenterClevelandUSA
  4. 4.Department of Veterans Affairs, New Jersey Healthcare SystemEast OrangeUSA
  5. 5.Department of Biostatistics, School of Public HealthRutgers UniversityPiscatawayUSA
  6. 6.Department of Veterans Affairs, New Jersey Healthcare SystemEast OrangeUSA

Personalised recommendations