Novel Representation of Clinical Information in the ICU

Summary

The introduction of electronic medical records (EMR) and computerized physician order entry (CPOE) into the intensive care unit (ICU) is transforming the way health care providers currently work. The challenge facing developers of EMR’s is to create products which add value to systems of health care delivery. As EMR’s become more prevalent, the potential impact they have on the quality and safety, both negative and positive, will be amplified. In this paper we outline the key barriers to effective use of EMR and describe the methodology, using a worked example of the output. AWARE (Ambient Warning and Response Evaluation), is a physician led, electronic-environment enhancement program in an academic, tertiary care institution’s ICU. The development process is focused on reducing information overload, improving efficiency and eliminating medical error in the ICU.

Citation: Pickering BW, Herasevich V, Ahmed A, Gajic O. Novel representation of clinical information in the ICU – developing user interfaces which reduce information overload. Appl Clin Inf 2010; 1: 116–131 http://dx.doi.org/10.4338/ACI-2009-12-CR-0027

Keywords

Safety - medical error - ICU - ambient intelligence - EMR - NASA-TLX

 

• References

• 1 Angus DC, Barnato AE, Linde-Zwirble WT, Weissfeld LA, Watson RS, Rickert T, Rubenfeld GD. Use of intensive care at the end of life in the United States: an epidemiologic study. Crit Care Med 2004; 32 (Suppl. 03) 638-643.
• 2 Donchin Y, Gopher D, Olin M, Badihi Y, Biesky M, Sprung CL, Pizov R, Cotev S. A look into the nature and causes of human errors in the intensive care unit. Crit Care Med 1995; 23 (Suppl. 02) 294-300.
• 3 Bracco D, Favre JB, Bissonnette B, Wasserfallen JB, Revelly JP, Ravussin P, Chiolero R. Human errors in a multidisciplinary intensive care unit: a 1-year prospective study. Intensive Care Med 2001; 27 (Suppl. 01) 137-145.
• 4 Samaras GM, Horst RL. A systems engineering perspective on the human-centered design of health information systems. Journal of Biomedical Informatics 2005; 38 (Suppl. 01) 61-74.
• 5 Manor-Shulman O, Beyene J, Frndova H, Parshuram CS. Quantifying the volume of documented clinical information in critical illness. J Crit Care 2008; 23 (Suppl. 02) 245-250.
• 6 Kumar A, Roberts D, Wood KE, Light B, Parrillo JE, Sharma S, Suppes R, Feinstein D, Zanotti S, Taiberg L. et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Critical care medicine 2006; 34 (Suppl. 06) 1589-1596.
• 7 Mack EH, Wheeler DS, Embi PJ. Clinical decision support systems in the pediatric intensive care unit. Pediatr Crit Care Med 2009; 10 (Suppl. 01) 23-28.
• 8 Adhikari N, Lapinsky SE. Medical informatics in the intensive care unit: overview of technology assessment. J Crit Care 2003; 18 (Suppl. 01) 41-47.
• 9 Gagnon MP, Legare F, Labrecque M, Fremont P, Pluye P, Gagnon J, Car J, Pagliari C, Desmartis M, Turcot L. et al. Interventions for promoting information and communication technologies adoption in healthcare professionals. Cochrane Database Syst Rev 2009 (Suppl. 01) CD006093.
• 10 Herasevich V, Gajic O. Medical Informatics Improves Quality of Care in the Intensive Care Unit. ICU Management 2007; 1: 30-31.
• 11 Herasevich V, Yilmaz M, Khan H, Chute CG, Gajic O. Rule base system for identification of patients with specific critical care syndromes: The “sniffer” for acute lung injury. AMIA 2007 Symposium Proceedings 2007; 972.
• 12 Li M, Pickering BW, Smith VD, Hadzikadic M, Gajic O, Herasevich V. Medical informatics: an essential tool for health sciences research in acute care. Bosnian journal of basic medical sciences 2009; 9 (Suppl. 01) 34-39.
• 13 Pakhomov S, Weston SA, Jacobsen SJ, Chute CG, Meverden R, Roger VL. Electronic medical records for clinical research: application to the identification of heart failure. Am J Manag Care 2007; 13 6 Part 1 281-288.
• 14 Herasevich V, Pickering BW, Dong Y, Peters SG, Gajic O. Informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness. Mayo Clin Proc 2010; 85: 247-254.
• 15 Zhang J. Human-centered computing in health information systems: Part 1: Analysis and design. Journal of Biomedical Informatics 2005; 38 (Suppl. 01) 1-3.
• 16 Zhang J. Human-centered computing in health information systems: Part 2: Evaluation. Journal of Biomedical Informatics 2005; 38 (Suppl. 03) 173-175.
• 17 Pickering BW. et al. Identification of data points which contribute to ICU medical decision making. Critical Care Medicine 2008; 36 12[Suppl.] A83.
• 18 Ash JS, Berg M, Coiera E. Some unintended consequences of information technology in health care: The nature of patient care information system-related errors. J Am Med Inform Assoc 2004; 11 (Suppl. 02) 104-112.
• 19 Sittig DF, Ash JS, Zhang J, Osheroff JA, Shabot MM. Lessons from “Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system”. Pediatrics 2006; 118 (Suppl. 02) 797-801.
• 20 Han YY, Carcillo JA, Venkataraman ST, Clark RS, Watson RS, Nguyen TC, Bayir H, Orr RA. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics 2005; 116 (Suppl. 06) 1506-1512.
• 21 Wachter SB, Johnson K, Albert R, Syroid N, Drews F, Westenskow D. The evaluation of a pulmonary display to detect adverse respiratory events using high resolution human simulator. J Am Med Inform Assoc 2006; 13 (Suppl. 06) 635-642.
• 22 Saleem JJ, Patterson ES, Militello L, Anders S, Falciglia M, Wissman JA, Roth EM, Asch SM. Impact of clinical reminder redesign on learnability, efficiency, usability, and workload for ambulatory clinic nurses. J Am Med Inform Assoc 2007; 14 (Suppl. 05) 632-640.
• 23 Pickering BW, Hurley K, Marsh B. Identification of patient information corruption in the intensive care unit: using a scoring tool to direct quality improvements in handover. Crit Care Med 2009; 37 (Suppl. 11) 2905-2912.