Back to the Bedside: Developing a Bedside Aid for Concussion and Brain Injury Decisions in the Emergency Department

Edward R Melnick, Kevin Lopez, Erik P Hess, Fuad Abujarad, Cynthia A Brandt, Richard N Shiffman, Lori A Post, Edward R Melnick, Kevin Lopez, Erik P Hess, Fuad Abujarad, Cynthia A Brandt, Richard N Shiffman, Lori A Post

Abstract

Context: Current information-rich electronic health record (EHR) interfaces require large, high-resolution screens running on desktop computers. This interface compromises the provider's already limited time at the bedside by physically separating the patient from the doctor. The case study presented here describes a patient-centered clinical decision support (CDS) design process that aims to bring the physician back to the bedside by integrating a patient decision aid with CDS for shared use by the patient and provider on a touchscreen tablet computer for deciding whether or not to obtain a CT scan for minor head injury in the emergency department, a clinical scenario that could benefit from CDS but has failed previous implementation attempts.

Case description: This case study follows the user-centered design (UCD) approach to build a bedside aid that is useful and usable, and that promotes shared decision-making between patients and their providers using a tablet computer at the bedside. The patient-centered decision support design process focuses on the prototype build using agile software development, but also describes the following: (1) the requirement gathering phase including triangulated qualitative research (focus groups and cognitive task analysis) to understand current challenges, (2) features for patient education, the physician, and shared decision-making, (3) system architecture and technical requirements, and (4) future plans for formative usability testing and field testing.

Lessons learned: We share specific lessons learned and general recommendations from critical insights gained in the patient-centered decision support design process about early stakeholder engagement, EHR integration, external expert feedback, challenges to two users on a single device, project management, and accessibility.

Conclusions: Successful implementation of this tool will require seamless integration into the provider's workflow. This protocol can create an effective interface for shared decision-making and safe resource reduction at the bedside in the austere and dynamic clinical environment of the ED and is generalizable for these purposes in other clinical environments as well.

Keywords: Informatics; Methods; Quality Improvement.

Figures

Figure 1.
Figure 1.
The MCMP Operation Analysis Model
Figure 2.
Figure 2.
Card Allowing Patient to Communicate Their Concerns with the Provider
Figure 3.
Figure 3.
The Provider Sees the Preidentified Patient Concerns and Discusses Them with the Patient
Figure 4.
Figure 4.
The Database Schema, Where the Shared Decision-Making is Reflected in the Database as FinalDecision in the userRisk Relation

References

    1. Simon HA. Designing Organizations for an Information-Rich World. In: Greenberger M, editor. Computers, Communication, and the Public Interest. Baltimore, MD: The Johns Hopkins Press; 1971. pp. 40–1.
    1. Howell WC, Cooke NJ. Training the human information processor: A look at cognitive model. In: Goldstein IL, editor. Training and Development in Work Organizations: Frontiers of Industrial and Organizational Psychology. San Francisco, CA: Jossey-Bass; 1989. pp. 121–82.
    1. O’Malley AS. Tapping the unmet potential of health information technology. The New England journal of medicine. 2011;364(12):1090–1.
    1. Mandl KD, Kohane IS. Escaping the EHR trap--the future of health IT. The New England journal of medicine. 2012;366(24):2240–2.
    1. Melnick ER. An outdated solution. The New York Times. 2014 Jan 21;
    1. May CR, Mair F, Finch T, MacFarlane A, Dowrick C, Treweek S, et al. Development of a theory of implementation and integration: Normalization Process Theory. Implement Sci. 2009;4(29):29.
    1. May C, Finch T, Mair F, Ballini L, Dowrick C, Eccles M, et al. Understanding the implementation of complex interventions in health care: the normalization process model. BMC Health Services Research. 2007;7(1):148.
    1. Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ (Clinical research ed) 2005;330(7494):765. Epub 2005 Mar 14.
    1. Saleem JJ, Patterson ES, Militello L, Render ML, Orshansky G, Asch SM. Exploring barriers and facilitators to the use of computerized clinical reminders. Journal of the American Medical Informatics Association : JAMIA. 2005;12(4):438–47. Epub 2005 Mar 31.
    1. Sittig DF, Wright A, Osheroff JA, Middleton B, Teich JM, Ash JS, et al. Grand challenges in clinical decision support. Journal of Biomedical Informatics. 2008;41(2):387–92. Epub 2007 Sep 21.
    1. Karsh BT. Clinical practice improvement and redesign: how change in workflow can be supported by clinical decision support. Rockville, MD: Agency for Healthcare Research and Quality; 2009 09-0054-EF Contract No.: Report.
    1. Melnick ER, Nielson JA, Finnell JT, Bullard MJ, Cantrill SV, Cochrane DG, et al. Delphi consensus on the feasibility of translating the ACEP clinical policies into computerized clinical decision support. Annals of Emergency Medicine. 2010;56(4):317–20. Epub 2010 Apr 3.
    1. Karsh BT, Weinger MB, Abbott PA, Wears RL. Health information technology: fallacies and sober realities. Journal of the American Medical Informatics Association : JAMIA. 2010;17(6):617–23.
    1. Medicare Payment Advisory Commission. A Data Book: Health Care Spending and the Medicare Program 2011. [January 11, 2012]. Available from: .
    1. Korley FK, Pham JC, Kirsch TD. Use of advanced radiology during visits to US emergency departments for injury-related conditions, 1998–2007. JAMA : the journal of the American Medical Association. 2010;304(13):1465–71.
    1. Stiell IG, Clement CM, Grimshaw J, Brison RJ, Rowe BH, Schull MJ, et al. Implementation of the Canadian C-Spine Rule: prospective 12 centre cluster randomised trial. BMJ (Clinical research ed) 2009;339:b4146. doi: 10.1136/bmj.b4146. Journal Article.
    1. Stiell IG, Clement CM, Grimshaw JM, Brison RJ, Rowe BH, Lee JS, et al. A prospective cluster-randomized trial to implement the Canadian CT Head Rule in emergency departments. CMAJ : Canadian Medical Association journal = journal de l’Association medicale canadienne. 2010;182(14):1527–32. Epub 2010 Aug 23.
    1. Smits M, Dippel DW, Nederkoorn PJ, Dekker HM, Vos PE, Kool DR, et al. Minor head injury: CT-based strategies for management--a cost-effectiveness analysis. Radiology. 2010;254(2):532–40.
    1. Melnick ER, Szlezak CM, Bentley SK, Kotlyar S, Post LA. Overuse of CT for mild traumatic brain injury. The Joint Commission Journal on Quality and Patient Safety. 2012. (Accepted, pending revision).
    1. American College of Emergency Physicians. Five Things Physicians and Patients Should Question 2013. [cited 2014 August 12]. Available from: .
    1. Schuur JD, Carney DP, Lyn ET, Raja AS, Michael JA, Ross NG, et al. A top-five list for emergency medicine: a pilot project to improve the value of emergency care. JAMA internal medicine. 2014;174(4):509–15.
    1. Stacey D, Bennett CL, Barry MJ, Col NF, Eden KB, Holmes-Rovner M, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2011(10):CD001431.
    1. Horng S, Goss FR, Chen RS, Nathanson LA. Prospective pilot study of a tablet computer in an Emergency Department. International journal of medical informatics. 2012;81(5):314–9.
    1. Hartmann B, Benson M, Junger A, Quinzio L, Rohrig R, Fengler B, et al. Computer keyboard and mouse as a reservoir of pathogens in an intensive care unit. Journal of clinical monitoring and computing. 2004;18(1):7–12.
    1. Wilson AP, Hayman S, Folan P, Ostro PT, Birkett A, Batson S, et al. Computer keyboards and the spread of MRSA. The Journal of hospital infection. 2006;62(3):390–2.
    1. Kendrick J. Tablets in the enterprise: Pros and cons. April 13, 2012 [April 9, 2015]. Available from: .
    1. Hirsch EB, Raux BR, Lancaster JW, Mann RL, Leonard SN. Surface microbiology of the iPad tablet computer and the potential to serve as a fomite in both inpatient practice settings as well as outside of the hospital environment. PLoS One. 2014;9(10):e111250.
    1. Horsky J, Gutnik L, Patel VL. Technology for emergency care: cognitive and workflow considerations. (Journal Article)
    1. Saleem JJ, Patterson ES, Militello L, Asch SM, Doebbeling BN, Render ML. Using human factors methods to design a new interface for an electronic medical record. 2007. (Journal Article).
    1. Russ AL, Zillich AJ, McManus MS, Doebbeling BN, Saleem JJ. A human factors investigation of medication alerts: barriers to prescriber decision-making and clinical workflow. AMIA Annu Symp Proc. 2009;2009:548–52. Journal Article.
    1. Levin S, Aronsky D, Hemphill R, Han J, Slagle J, France DJ. Shifting toward balance: measuring the distribution of workload among emergency physician teams. Annals of Emergency Medicine. 2007;50(4):419–23. Epub 2007 Jun 7.
    1. Chisholm CD, Dornfeld AM, Nelson DR, Cordell WH. Work interrupted: a comparison of workplace interruptions in emergency departments and primary care offices. Annals of Emergency Medicine. 2001;38(2):146–51.
    1. Chisholm CD, Collison EK, Nelson DR, Cordell WH. Emergency department workplace interruptions: are emergency physicians “interrupt-driven” and “multitasking”? Academic Emergency Medicine. 2000;7(11):1239–43.
    1. Wears RL. Introduction: The Approach to the Emergency Department Patient. In: Wolfson AB, Harwood-Nuss A, editors. Harwood-Nuss’ clinical practice of emergency medicine. 4th. Philadelphia, PA: Lippincott Williams & Wilkins; 2005.
    1. Faul M, Xu L, Wald MM, Coronado VG. Traumatic brain injury in the United States: emergency department visits, hospitalizations, and deaths. Atlanta, GA: Centers for Disease Control and Prevention, National Center for Injury Prevention and Control; 2010.
    1. Marshall LF, Toole BM, Bowers SA. The National Traumatic Coma Data Bank. Part 2: Patients who talk and deteriorate: implications for treatment. Journal of neurosurgery. 1983;59(2):285–8.
    1. Brenner DJ, Hall EJ. Computed tomography--an increasing source of radiation exposure. The New England journal of medicine. 2007;357(22):2277–84.
    1. Stiell IG, Wells GA, Vandemheen K, Clement C, Lesiuk H, Laupacis A, et al. The Canadian CT Head Rule for patients with minor head injury. Lancet. 2001;357(9266):1391–6.
    1. Smith-Bindman R, Lipson J, Marcus R, Kim KP, Mahesh M, Gould R, et al. Radiation dose associated with common computed tomography examinations and the associated lifetime attributable risk of cancer. Archives of Internal Medicine. 2009;169(22):2078–86.
    1. Stiell IG, Wells GA. Methodologic standards for the development of clinical decision rules in emergency medicine. Annals of Emergency Medicine. 1999;33(4):437–47.
    1. Stiell IG, Clement CM, Rowe BH, Schull MJ, Brison R, Cass D, et al. Comparison of the Canadian CT Head Rule and the New Orleans Criteria in patients with minor head injury. JAMA : the journal of the American Medical Association. 2005;294(12):1511–8.
    1. Smits M, Dippel DW, de Haan GG, Dekker HM, Vos PE, Kool DR, et al. External validation of the Canadian CT Head Rule and the New Orleans Criteria for CT scanning in patients with minor head injury. JAMA. 2005;294(12):1519–25.
    1. Papa L, Stiell IG, Clement CM, Pawlowicz A, Wolfram A, Braga C, et al. Performance of the Canadian CT Head Rule and the New Orleans Criteria for Predicting Any Traumatic Intracranial Injury on Computed Tomography in a United States Level I Trauma Center. Acad Emerg Med. 2012;19(1):2–10.
    1. Stiell IG, Wells GA, Vandemheen K, Laupacis A, Brison R, Eisenhauer MA, et al. Variation in ED use of computed tomography for patients with minor head injury. Annals of Emergency Medicine. 1997;30(1):14–22.
    1. Goldberg L, Lide B, Lowry S, Massett HA, O’Connell T, Preece J, et al. Usability and accessibility in consumer health informatics current trends and future challenges. American journal of preventive medicine. 2011;40(5 Suppl 2):S187–97.
    1. Melnick ER, Shafer K, Rodulfo N, Shi J, Hess EP, Wears RL, et al. Understanding Overuse Of CT For Minor Head Injury In The ED: A Triangulated Qualitative Study. Academic Emergency Medicine. 2015 Dec; [in press]
    1. Curry LA, Nembhard IM, Bradley EH. Qualitative and mixed methods provide unique contributions to outcomes research. Circulation. 2009;119(10):1442–52.
    1. Militello LG. Learning to think like a user: using cognitive task analysis to meet today’s health care design challenges. Biomedical instrumentation & technology / Association for the Advancement of Medical Instrumentation. 1998;32(5):535–40.
    1. Klein GA, Calderwood R, MacGregor D. Critical decision method for eliciting knowledge. Systems, Man and Cybernetics, IEEE Transactions on. 1989;19(3):462–72.
    1. Curran JA, Brehaut J, Patey AM, Osmond M, Stiell I, Grimshaw JM. Understanding the Canadian adult CT head rule trial: use of the theoretical domains framework for process evaluation. Implement Sci. 2013;8:25.
    1. Sheehan B, Nigrovic LE, Dayan PS, Kuppermann N, Ballard DW, Alessandrini E, et al. Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: a sociotechnical analysis. J Biomed Inform. 2013;46(5):905–13.
    1. Probst MA, Kanzaria HK, Schriger DL. A conceptual model of emergency physician decision making for head computed tomography in mild head injury. The American journal of emergency medicine. 2014;32(6):645–50.
    1. Kushniruk AW, Patel VL. Cognitive and usability engineering methods for the evaluation of clinical information systems. Journal of Biomedical Informatics. 2004;37(1):56–76.
    1. Stone D, Jarrett C, Woodroffe E, Minocha S. User Interface Design and Evaluation. San Francisco, CA: Elsevier, Inc; 2005.
    1. Morgan DL. Focus Groups. Annual Review of Sociology. 1996;22(1):129–52.
    1. Weir CR, Nebeker JJ, Hicken BL, Campo R, Drews F, Lebar B. A cognitive task analysis of information management strategies in a computerized provider order entry environment. Journal of the American Medical Informatics Association : JAMIA. 2007;14(1):65–75. Epub 2006 Oct 26.
    1. Nemeth CP, Cook RI, Wears RL. Studying the technical work of emergency care. Annals of Emergency Medicine. 2007;50(4):384–6.
    1. Nemeth CP, Cook RI, Woods DD. The messy details: insights from the study of technical work in health care. IEEE Transactions on Systems, Man and Cybernetics: Part A. 2004;34(6):689–92.
    1. Vicente KJ. Ecological interface design: progress and challenges. Human factors. 2002;44(1):62–78.
    1. Legare F, Ratte S, Gravel K, Graham ID. Barriers and facilitators to implementing shared decision-making in clinical practice: update of a systematic review of health professionals’ perceptions. Patient education and counseling. 2008;73(3):526–35.
    1. Martin RC. Agile software development: principles, patterns, and practices. Prentice Hall PTR; 2003.
    1. Elwyn G, O’Connor A, Stacey D, Volk R, Edwards A, Coulter A, et al. Developing a quality criteria framework for patient decision aids: online international Delphi consensus process. BMJ. 2006;333(7565):417.
    1. Flach JM, Vicente KJ, Tanabe F, Monta K, Rasmussen J. An ecological approach to interface design.. Proceedings of the Human Factors and Ergonomics Society 42nd Annual Meeting; 1998. pp. 295–9.
    1. Lomotan EA, Hoeksema LJ, Edmonds DE, Ramirez-Garnica G, Shiffman RN, Horwitz LI. Evaluating the use of a computerized clinical decision support system for asthma by pediatric pulmonologists. International journal of medical informatics. 2012;81(3):157–65.
    1. Diabetes Medication Choice Decision Aid: Mayo Clinic; 2012 [cited 2014 September 7]. Available from: .
    1. Mann DM, Lin JJ. Increasing efficacy of primary care-based counseling for diabetes prevention: rationale and design of the ADAPT (Avoiding Diabetes Thru Action Plan Targeting) trial. Implement Sci. 2012;7:6.
    1. O’Connor AM. Validation of a decisional conflict scale. Medical decision making : an international journal of the Society for Medical Decision Making. 1995;15(1):25–30.
    1. Elwyn G, Hutchings H, Edwards A, Rapport F, Wensing M, Cheung WY, et al. The OPTION scale: measuring the extent that clinicians involve patients in decision-making tasks. Health expectations : an international journal of public participation in health care and health policy. 2005;8(1):34–42.
    1. Gellert GA, Ramirez R, Webster SL. The rise of the medical scribe industry: implications for the advancement of electronic health records. JAMA. 2015;313(13):1315–6.
    1. Montori VM, Breslin M, Maleska M, Weymiller AJ. Creating a conversation: insights from the development of a decision aid. PLoS Med. 2007;4(8):e233.
    1. Zuger A. With Electronic Medical Records, Doctors Read When They Should Talk. The New York Times. 2015 October 14, 2014.
    1. Ackoff RL. From data to wisdom: Presidential address to ISGSR, June 1988. Journal of applied systems analysis. 1989;16(1):3–9.

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