Advertisement

Cognition, Technology & Work

, Volume 13, Issue 2, pp 151–158 | Cite as

Making sense of diseases in medication reconciliation

  • Geva Vashitz
  • Mark E. Nunnally
  • Yuval Bitan
  • Yisrael Parmet
  • Michael F. O’Connor
  • Richard I. Cook
Original Research

Abstract

Patients are most at risk during transitions in care across settings and providers. The communication and reconciliation of an accurate medication list throughout the care continuum are essential in the reduction in transition-related adverse drug events. Most current research focuses on the outcomes of reconciliation interventions, yet not on the clinician’s perspective. We aimed to explore clinicians’ cognitive processes and heuristics of making sense of patients’ disease histories. We used the affinity diagram method to simulate real-life medication reconciliation with 24 clinicians. The participants were given paper cards with diseases and medications representing a real case from an anesthesiology department. The task was to sort the cards in a set that made sense to the clinician. The experiment was video-recorded, and the data were analyzed using a quantitative spatial analysis technique. Levene’s test for equality of variance showed that 79% of the 24 participants arranged the diseases along a straight line (p < 0.001). With only few exceptions, the diseases were arranged along the line in a fixed order, from cardiac conditions to depression (Friedman’s χ2(44) = 291.9, p < 0.001). We learn from this study that although clinicians employ a variety of coping strategies while reconciling patients’ medical histories, there are common reconciliation strategies. Understanding heuristics and the mental models clinicians have for the reconciliation process may help to develop and implement methods and tools to promote safety research and practice.

Keywords

Medication reconciliation Medical expertise Medical cognition Diagnostic reasoning Patient safety Card-sorting Affinity diagram 

Notes

Acknowledgments

This work was kindly supported in part by a Fulbright doctoral dissertation research scholarship to Geva Vashitz. We would like to thank Christine Jette, MD and Annette Martini, MD, for their help in the experiment construction.

References

  1. Agrawal A (2009) Medication errors: prevention using information technology systems. Br J Clin Pharmacol 67(6):681–686CrossRefGoogle Scholar
  2. Boockvar KS, Carlson LaCorte H, Giambanco V, Fridman B, Siu A (2006) Medication reconciliation for reducing drug-discrepancy adverse events. Am J Geriatr Pharmacother 4(3):236–243CrossRefGoogle Scholar
  3. Brady AM, Malone AM, Fleming S (2009) A literature review of the individual and systems factors that contribute to medication errors in nursing practice. J Nurs Manag 17(6):679–697CrossRefGoogle Scholar
  4. Budnitz DS, Pollock DA, Weidenbach KN, Mendelsohn AB, Schroeder TJ, Annest JL (2006) National surveillance of emergency department visits for outpatient adverse drug events. JAMA 296(15):1858–1866CrossRefGoogle Scholar
  5. Clay BJ, Halasyamani L, Stucky ER, Greenwald JL, Williams MV (2008) Results of a medication reconciliation survey from the 2006 society of hospital medicine national meeting. J Hosp Med 3(6):465–472CrossRefGoogle Scholar
  6. Coffey M, Cornish P, Koonthanam T, Etchells E, Matlow A (2009) Implementation of admission medication reconciliation at two academic health sciences centres: challenges and success factors. Healthc Q 12 Spec No Patient:102–109Google Scholar
  7. Cornish PL, Knowles SR, Marchesano R, Tam V, Shadowitz S, Juurlink DN et al (2005) Unintended medication discrepancies at the time of hospital admission. Arch Intern Med 165(4):424–429CrossRefGoogle Scholar
  8. Coxon APM (1999) Sorting data: collection and analysis. Sage, Thousand OakszbMATHGoogle Scholar
  9. Frei P, Huber LC, Simon RW, Bonani M, Luscher TF (2009) Insufficient medication documentation at hospital admission of cardiac patients: a challenge for medication reconciliation. J Cardiovasc Pharmacol 54(6):497–501CrossRefGoogle Scholar
  10. Gandara E, Moniz T, Ungar J, Lee J, Chan-Macrae M, O’Malley T et al (2009) Communication and information deficits in patients discharged to rehabilitation facilities: an evaluation of five acute care hospitals. J Hosp Med 4(8):E28–E33CrossRefGoogle Scholar
  11. Hayes BD, Donovan JL, Smith BS, Hartman CA (2007) Pharmacist-conducted medication reconciliation in an emergency department. Am J Health Syst Pharm 64(16):1720–1723CrossRefGoogle Scholar
  12. JCAHO (2005) Joint commission on accreditation of healthcare organizations (JCAHO). 2005 hospital national patient safety goals. http://www.jointcommission.org/PatientSafety/NationalPatientSafetyGoals/05_hap_npsgs.htm. Accessed 12 Apr 2010
  13. Jylha V, Saranto K (2008) Electronic documentation in medication reconciliation—a challenge for health care professionals. Appl Nurs Res 21(4):237–239CrossRefGoogle Scholar
  14. Kramer JS, Hopkins PJ, Rosendale JC, Garrelts JC, Hale LS, Nester TM et al (2007) Implementation of an electronic system for medication reconciliation. Am J Health Syst Pharm 64(4):404–422. doi: 10.2146/ajhp060506 CrossRefGoogle Scholar
  15. Kushniruk AW, Patel VL, Marley AA (1998) Small worlds and medical expertise: implications for medical cognition and knowledge engineering. Int J Med Inform 49(3):255–271CrossRefGoogle Scholar
  16. Lin L, Isla R, Doniz K, Harkness H, Vicente KJ, Doyle DJ (1998) Applying human factors to the design of medical equipment: patient-controlled analgesia. J Clin Monit Comput 14(4):253–263CrossRefGoogle Scholar
  17. Luck J, Peabody JW, Lewis BL (2006) An automated scoring algorithm for computerized clinical vignettes: evaluating physician performance against explicit quality criteria. Int J Med Inform 75(10–11):701–707CrossRefGoogle Scholar
  18. Manning DM, O’Meara JG, Williams AR, Rahman A, Myhre D, Tammel KJ et al (2007) 3D: a tool for medication discharge education. Qual Saf Health Care 16(1):71–76CrossRefGoogle Scholar
  19. Miller SL, Miller S, Balon J, Helling TS (2008) Medication reconciliation in a rural trauma population. Ann Emerg Med 52(5):483–491CrossRefGoogle Scholar
  20. Nemeth CP (2004) Human factors methods for design: making systems human-centered. (pp. 142–145). CRC Press, Boca RatonCrossRefGoogle Scholar
  21. Patel VL, Groen CJ, Patel YC (1997) Cognitive aspects of clinical performance during patient workup: the role of medical expertise. Adv Health Sci Educ Theory Pract 2(2):95–114CrossRefGoogle Scholar
  22. Patel VL, Kaufman DR, Arocha JF (2002) Emerging paradigms of cognition in medical decision-making. J Biomed Inform 35(1):52–75CrossRefGoogle Scholar
  23. Peabody JW, Luck J, Glassman P, Dresselhaus TR, Lee M (2000) Comparison of vignettes, standardized patients, and chart abstraction: a prospective validation study of 3 methods for measuring quality. JAMA 283(13):1715–1722CrossRefGoogle Scholar
  24. Pippins JR, Gandhi TK, Hamann C, Ndumele CD, Labonville SA, Diedrichsen EK et al (2008) Classifying and predicting errors of inpatient medication reconciliation. J Gen Intern Med 23(9):1414–1422CrossRefGoogle Scholar
  25. Poon EG, Blumenfeld B, Hamann C, Turchin A, Graydon-Baker E, McCarthy PC et al (2006) Design and implementation of an application and associated services to support interdisciplinary medication reconciliation efforts at an integrated healthcare delivery network. J Am Med Inform Assoc 13(6):581–592. doi: 10.1197/jamia.M2142 CrossRefGoogle Scholar
  26. Pronovost P, Weast B, Schwarz M, Wyskiel RM, Prow D, Milanovich SN et al (2003) Medication reconciliation: a practical tool to reduce the risk of medication errors. J Crit Care 18(4):201–205CrossRefGoogle Scholar
  27. Round A (2001) Introduction to clinical reasoning. J Eval Clin Pract 7(2):109–117CrossRefGoogle Scholar
  28. Sarter NB, Mumaw RJ, Wickens CD (2007) Pilots’ monitoring strategies and performance on automated flight decks: an empirical study combining behavioral and eye-tracking data. Hum Factors 49(3):347–357CrossRefGoogle Scholar
  29. Schnipper JL, Hamann C, Ndumele CD, Liang CL, Carty MG, Karson AS et al (2009) Effect of an electronic medication reconciliation application and process redesign on potential adverse drug events: a cluster-randomized trial. Arch Intern Med 169(8):771–780CrossRefGoogle Scholar
  30. Thomas RP, Dougherty MR, Sprenger AM, Harbison JI (2008) Diagnostic hypothesis generation and human judgment. Psychol Rev 115(1):155–185. doi: 10.1037/0033-295X.115.1.155 CrossRefGoogle Scholar
  31. Turchin A, Hamann C, Schnipper JL, Graydon-Baker E, Millar SG, McCarthy PC et al (2008) Evaluation of an inpatient computerized medication reconciliation system. J Am Med Inform Assoc 15(4):449–452. doi: 10.1197/jamia.M2561 CrossRefGoogle Scholar
  32. Veloski J, Tai S, Evans AS, Nash DB (2005) Clinical vignette-based surveys: a tool for assessing physician practice variation. Am J Med Qual 20(3):151–157CrossRefGoogle Scholar
  33. Vickrey BG, Samuels MA, Ropper AH (2010) How neurologists think: a cognitive psychology perspective on missed diagnoses. Ann Neurol 67(4):425–433. doi: 10.1002/ana.21907 CrossRefGoogle Scholar
  34. Walker PC, Bernstein SJ, Jones JN, Piersma J, Kim HW, Regal RE et al (2009) Impact of a pharmacist-facilitated hospital discharge program: a quasi-experimental study. Arch Intern Med 169(21):2003–2010CrossRefGoogle Scholar
  35. Weingart SN, Cleary A, Seger A, Eng TK, Saadeh M, Gross A et al (2007) Medication reconciliation in ambulatory oncology. Jt Comm J Qual Patient Saf 33(12):750–757Google Scholar
  36. Wong JD, Bajcar JM, Wong GG, Alibhai SM, Huh JH, Cesta A et al (2008) Medication reconciliation at hospital discharge: evaluating discrepancies. Ann Pharmacother 42(10):1373–1379Google Scholar
  37. Woods DD (1993) Process-tracing methods for the study of cognition outside of the experimental psychology laboratory. Decision making in action: models and methods. Ablex Publishing, Westport, pp 228–251Google Scholar

Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  • Geva Vashitz
    • 1
  • Mark E. Nunnally
    • 2
  • Yuval Bitan
    • 2
  • Yisrael Parmet
    • 1
  • Michael F. O’Connor
    • 2
  • Richard I. Cook
    • 2
  1. 1.Department of Industrial Engineering and ManagementBen-Gurion University of the NegevBeer-ShevaIsrael
  2. 2.Cognitive Technologies Laboratory, Department of Anesthesia and Critical CareUniversity of Chicago HospitalsChicagoUSA

Personalised recommendations