Skip to main content

Advertisement

SpringerLink
Log in

Intraoperative blood glucose management: impact of a real-time decision support system on adherence to institutional protocol

  • Original Research
  • Published:
Journal of Clinical Monitoring and Computing Aims and scope Submit manuscript

Abstract

Poor perioperative glycemic management can lead to negative surgical outcome. Improved compliance to glucose control protocol could lead to better glucose management. An Anesthesia Information Management System based decision support system—Smart Anesthesia Manager™ (SAM) was used to generate real-time reminders to the anesthesia providers to closely adhere to our institutional glucose management protocol. Compliance to hourly glucose measurements and correct insulin dose adjustments was compared for the baseline period (12 months) without SAM and the intervention period (12 months) with SAM decision support. Additionally, glucose management parameters were compared for the baseline and intervention periods. A total of 1587 cases during baseline and 1997 cases during intervention met the criteria for glucose management (diabetic patients or non-diabetic patients with glucose level >140 mg/dL). Among the intervention cases anesthesia providers chose to use SAM reminders 48.7 % of the time primarily for patients who had diabetes, higher HbA1C or body mass index, while disabling the system for the remaining cases. Compliance to hourly glucose measurement and correct insulin doses increased significantly during the intervention period when compared with the baseline (from 52.6 to 71.2 % and from 13.5 to 24.4 %, respectively). In spite of improved compliance to institutional protocol, the mean glucose levels and other glycemic management parameters did not show significant improvement with SAM reminders. Real-time electronic reminders improved intraoperative compliance to institutional glucose management protocol though glycemic parameters did not improve even when there was greater compliance to the protocol.

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

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Sebranek JJ, Lugli AK, Coursin DB. Glycaemic control in the perioperative period. Br J Anaesth. 2013;111(Suppl 1):i18–34. doi:10.1093/bja/aet381.

    Article  CAS  PubMed  Google Scholar 

  2. Kadoi Y. Blood glucose control in the perioperative period. Minerva Anestesiol. 2012;78:574–95.

    CAS  PubMed  Google Scholar 

  3. Duncan AE. Hyperglycemia and perioperative glucose management. Curr Pharm Des. 2012;18:6195–203. doi:10.2174/138161212803832236.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Maerz LL, Akhtar S. Perioperative glycemic management in 2011: paradigm shifts. Curr Opin Crit Care. 2011;17:370–5. doi:10.1097/MCC.0b013e328348beb7.

    PubMed  Google Scholar 

  5. Akhtar S, Barash PG, Inzucchi SE. Scientific principles and clinical implications of perioperative glucose regulation and control. Anesth Analg. 2010;110:478–97. doi:10.1213/ANE.0b013e3181c6be63.

    Article  PubMed  Google Scholar 

  6. Frisch A, Chandra P, Smiley D, Peng L, Rizzo M, Gatcliffe C, Hudson M, Mendoza J, Johnson R, Lin E, Umpierrez GE. Prevalence and clinical outcome of hyperglycemia in the perioperative period in noncardiac surgery. Diabetes Care. 2010;33:1783–8. doi:10.2337/dc10-0304.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Lipshutz AK, Gropper MA. Perioperative glycemic control: an evidence-based review. Anesthesiology. 2009;110:408–21. doi:10.1097/ALN.0b013e3181948a80.

    PubMed  Google Scholar 

  8. Bilotta F, Rosa G. Glycemia management in critical care patients. World J Diabetes. 2012;3:130–4. doi:10.4239/wjd.v3.i7.130.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Jacobi J, Bircher N, Krinsley J, Agus M, Braithwaite SS, Deutschman C, Freire AX, Geehan D, Kohl B, Nasraway SA, Rigby M, Sands K, Schallom L, Taylor B, Umpierrez G, Mazuski J, Schunemann H. Guidelines for the use of an insulin infusion for the management of hyperglycemia in critically ill patients. Crit Care Med. 2012;40:3251–76. doi:10.1097/CCM.0b013e3182653269.

    Article  PubMed  Google Scholar 

  10. Atkins JH, Smith DS. A review of perioperative glucose control in the neurosurgical population. J Diabetes Sci Technol. 2009;3:1352–64. doi:10.1177/193229680900300615.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Kwon S, Thompson R, Dellinger P, Yanez D, Farrohki E, Flum D. Importance of perioperative glycemic control in general surgery: a report from the surgical care and outcomes assessment program. Ann Surg. 2013;257:8–14. doi:10.1097/SLA.0b013e31827b6bbc.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Duncan AE, Abd-Elsayed A, Maheshwari A, Xu M, Soltesz E, Koch CG. Role of intraoperative and postoperative blood glucose concentrations in predicting outcomes after cardiac surgery. Anesthesiology. 2010;112:860–71. doi:10.1097/ALN.0b013e3181d3d4b4.

    Article  PubMed  Google Scholar 

  13. Ramos M, Khalpey Z, Lipsitz S, Steinberg J, Panizales MT, Zinner M, Rogers SO. Relationship of perioperative hyperglycemia and postoperative infections in patients who undergo general and vascular surgery. Ann Surg. 2008;248:585–91. doi:10.1097/SLA.0b013e31818990d1.

    PubMed  Google Scholar 

  14. McGirt MJ, Woodworth GF, Brooke BS, Coon AL, Jain S, Buck D, Huang J, Clatterbuck RE, Tamargo RJ, Perler BA. Hyperglycemia independently increases the risk of perioperative stroke, myocardial infarction, and death after carotid endarterectomy. Neurosurgery. 2006; 58:1066–73; discussion 1066–73. doi: 10.1227/01.NEU.0000215887.59922.36.

  15. Ouattara A, Lecomte P, Le Manach Y, Landi M, Jacqueminet S, Platonov I, Bonnet N, Riou B, Coriat P. Poor intraoperative blood glucose control is associated with a worsened hospital outcome after cardiac surgery in diabetic patients. Anesthesiology. 2005;103:687–94.

    Article  CAS  PubMed  Google Scholar 

  16. Doenst T, Wijeysundera D, Karkouti K, Zechner C, Maganti M, Rao V, Borger MA. Hyperglycemia during cardiopulmonary bypass is an independent risk factor for mortality in patients undergoing cardiac surgery. J Thorac Cardiovasc Surg. 2005;130:1144. doi:10.1016/j.jtcvs.2005.05.049.

    Article  PubMed  Google Scholar 

  17. van den Berghe G, Wouters P, Weekers F, Verwaest C, Bruyninckx F, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P, Bouillon R. Intensive insulin therapy in critically ill patients. N Engl J Med. 2001;345:1359–67. doi:10.1056/NEJMoa011300.

    Article  PubMed  Google Scholar 

  18. Gandhi GY, Nuttall GA, Abel MD, Mullany CJ, Schaff HV, O’Brien PC, Johnson MG, Williams AR, Cutshall SM, Mundy LM, Rizza RA, McMahon MM. Intensive intraoperative insulin therapy versus conventional glucose management during cardiac surgery: a randomized trial. Ann Intern Med. 2007;146:233–43. doi:10.7326/0003-4819-146-4-200702200-00002.

    Article  PubMed  Google Scholar 

  19. Studer C, Sankou W, Penfornis A, Pili-Floury S, Puyraveau M, Cordier A, Etievent JP, Samain E. Efficacy and safety of an insulin infusion protocol during and after cardiac surgery. Diabetes Metab. 2010;36:71–8. doi:10.1016/j.diabet.2009.05.008.

    Article  CAS  PubMed  Google Scholar 

  20. Rea RS, Donihi AC, Bobeck M, Herout P, McKaveney TP, Kane-Gill SL, Korytkowski MT. Implementing an intravenous insulin infusion protocol in the intensive care unit. Am J Health Syst Pharm. 2007;64:385–95. doi:10.2146/ajhp060014.

    Article  PubMed  Google Scholar 

  21. Kelly JL, Hirsch IB, Furnary AP. Implementing an intravenous insulin protocol in your practice: practical advice to overcome clinical, administrative, and financial barriers. Semin Thorac Cardiovasc Surg. 2006;18:346–58. doi:10.1053/j.semtcvs.2006.06.004.

    Article  PubMed  Google Scholar 

  22. Juneja R, Roudebush CP, Nasraway SA, Golas AA, Jacobi J, Carroll J, Nelson D, Abad VJ, Flanders SJ. Computerized intensive insulin dosing can mitigate hypoglycemia and achieve tight glycemic control when glucose measurement is performed frequently and on time. Crit Care. 2009;13:R163. doi:10.1186/cc8129.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Hoekstra M, Vogelzang M, Verbitsky E, Nijsten MW. Health technology assessment review: computerized glucose regulation in the intensive care unit—how to create artificial control. Crit Care. 2009;13:223. doi:10.1186/cc8023.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Nair BG, Horibe M, Newman SF, Wu WY, Peterson GN, Schwid HA. Anesthesia information management system-based near real-time decision support to manage intraoperative hypotension and hypertension. Anesth Analg. 2014;118:206–14. doi:10.1213/ANE.0000000000000027.

    Article  CAS  PubMed  Google Scholar 

  25. Nair BG, Horibe M, Newman S, Wu W, Schwid HA. Near real-time notification of gaps in cuff blood pressure recordings for improved patient monitoring. J Clin Monit Comput. 2013;27:265–71. doi:10.1007/s10877-012-9425-2.

    Article  PubMed  Google Scholar 

  26. Nair BG, Peterson GN, Neradilek MB, Newman SF, Huang EY, Schwid HA. Reducing wastage of inhalation anesthetics using real-time decision support to notify of excessive fresh gas flow. Anesthesiology. 2013;118:874–84. doi:10.1097/ALN.0b013e3182829de0.

    Article  CAS  PubMed  Google Scholar 

  27. Nair BG, Newman SF, Peterson GN, Schwid HA. Smart anesthesia manager (TM) (SAM)-a real-time decision support system for anesthesia care during surgery. IEEE Trans Biomed Eng. 2013;60:207–10. doi:10.1109/TBME.2012.2205384.

    Article  PubMed  Google Scholar 

  28. Nair BG, Peterson GN, Newman S, Wu W, Kolios-Morris V, Schwid HA. Improved documentation of β-blocker quality measure through anesthesia information management system and real-time notification of documentation errors. Jt Comm J Qual Saf. 2012;38:283–8.

    Google Scholar 

  29. Nair BG, Newman S, Peterson GN, Schwid HA. Automated electronic reminders to improve redosing of antibiotics during surgical cases: comparison of two approaches. Surg Infect. 2011;12:57–63. doi:10.1089/sur.2010.047.

    Article  Google Scholar 

  30. Nair BG, Newman S, Peterson GN, Wu W, Schwid HA. Feedback mechanisms including real-time electronic alerts to achieve near 100 % timely prophylactic antibiotic administration in surgical cases. Anesth Analg. 2010;111:1293–300. doi:10.1213/ANE.0b013e3181f46d89.

    Article  PubMed  Google Scholar 

  31. Chau A, Ehrenfeld JM. Using real time clinical decision support to improve performance on perioperative quality and process measures. Anesthesiol Clin. 2011;29:57–69. doi:10.1016/j.anclin.2010.11.002.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Ehrenfeld JM, Epstein RH, Bader S, Kheterpal S, Sandberg WS. Automatic notifications mediated by anesthesia information management systems reduce the frequency of prolonged gaps in blood pressure documentation. Anesth Analg. 2011;113:356–63. doi:10.1213/ANE.0b013e31820d95e7.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Wanderer JP, Sandberg WS, Ehrenfeld JM. Real-Time alerts and reminders using information systems. Anesthesiol Clin. 2011;29:389–96. doi:10.1016/j.anclin.2011.05.003.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Sandberg WS, Sandberg EH, Seim AR, Anupama S, Ehrenfeld JM, Spring SF, Walsh JL. Real-time checking of electronic anesthesia records for documentation errors and automatically text messaging clinicians improves quality of documentation. Anesth Analg. 2008;106:192–201. doi:10.1213/01.ane.0000289640.38523.bc.

    Article  PubMed  Google Scholar 

  35. Kheterpal S, Gupta R, Blum JM, Tremper KK, O’Reilly M, Kazanjian PE. Electronic reminders improve procedure documentation compliance and professional fee reimbursement. Anesth Analg. 2008;104:592–7. doi:10.1213/01.ane.0000255707.98268.96.

    Article  Google Scholar 

  36. Thompson BT, Orme JF, Zheng H, Luckett PM, Truwit JD, Willson DF, Duncan Hite R, Brower RG, Bernard GR, Curley MA, Steingrub JS, Sorenson DK, Sward K, Hirshberg E, Morris AH. multicenter validation of a computer-based clinical decision support tool for glucose control in adult and pediatric intensive care units. J Diabetes Sci Technol. 2008;2:357–68. doi:10.1177/193229680800200304.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Saager L, Collins GL, Burnside B, Tymkew H, Zhang L, Jacobsohn E, Avidan M. A randomized study in diabetic patients undergoing cardiac surgery comparing computer-guided glucose management with a standard sliding scale protocol. J Cardiothorac Vasc Anesthe. 2008;22:377–82. doi:10.1053/j.jvca.2007.09.013.

    Article  Google Scholar 

  38. Boord JB, Sharifi M, Greevy RA, Griffin MR, Lee VK, Webb TA, May ME, Waitman LR, May AK, Miller RA. Computer-based insulin infusion protocol improves glycemia control over manual protocol. J Am Med Inform Assoc. 2007;14:278–87. doi:10.1197/jamia.M2292.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Rood E, Bosman RJ, van der Spoel JI, Tayor P, Zandstra DF. Use of a Computerized Guideline for Glucose Regulation in the Intensive Care Unit Improved Both Guideline Adherence and Glucose Regulation. J Am Med Inform Assoc. 2005;12:172–80. doi:10.1197/jamia.M1598.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Terajima K, Ogawa R. What is the optimal dose of glucose administration during minor surgery under sevoflurane anesthesia? J Anesth. 2000;14:14–8.

    Article  CAS  PubMed  Google Scholar 

  41. Horibe M, Nair BG, Yurina G, Neradilek MB, Rozet I. A novel computerized fading memory algorithm for glycemic control in postoperative surgical patients. Anesth Analg. 2012;115:580–7. doi:10.1213/ANE.0b013e318259ee31.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This research was supported by the Patient Safety Innovation Program (PSIP) of the University of Washington, Seattle, WA. Additional funding was obtained from University of Washington Medical Center to install point of care glucose meter cradles. University of Washington Medical Center Lab Medicine, Surgical Services and Clinical Engineering departments assisted with the purchase and installation of point of care glucose meter docking stations in the operating rooms. Dr. Nayak Polissar of The-Mountain-Whisper-Light Statistics provided critical review of the statistical methods. Dr. Irl.B.Hirsch reports grants from Sanofi USA, grants from Halozyme, personal fees from Roche Diagnostics, and personal fees from Abbott Diabetes Care outside of the submitted work. None of the other authors have any financial disclosure to report.

Conflict of interest

The authors declare that they have no conflict of interest.

Author information

Authors and Affiliations

  1. Department of Anesthesiology and Pain Medicine, University of Washington, BB-1469 Health Sciences Bldg, 1959 NE Pacific Street, Mail Box: 356540, Seattle, WA, 98195, USA

    Bala G. Nair, Mayumi Horibe, Shu-Fang Newman & Gail Van Norman

  2. School of Medicine, University of Washington, Seattle, WA, USA

    Katherine Grunzweig

  3. Department of Anesthesiology, Virginia Commonwealth University, Richmond, VA, USA

    Gene N. Peterson

  4. The-Mountain-Whisper-Light Statistics, Seattle, WA, USA

    Moni B. Neradilek

  5. Department of Anesthesiology and Perioperative Care, University of California, Irvine, CA, USA

    Howard A. Schwid

  6. Division of Metabolism, Department of Medicine, University of Washington, Seattle, WA, USA

    Wei Hao & Irl B. Hirsch

  7. Division of General Surgery, Department of Surgery, University of Washington, Seattle, WA, USA

    E. Patchen Dellinger

Authors
  1. Bala G. Nair
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Katherine Grunzweig
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gene N. Peterson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mayumi Horibe
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Moni B. Neradilek
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shu-Fang Newman
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Gail Van Norman
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Howard A. Schwid
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Wei Hao
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Irl B. Hirsch
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. E. Patchen Dellinger
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bala G. Nair.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nair, B.G., Grunzweig, K., Peterson, G.N. et al. Intraoperative blood glucose management: impact of a real-time decision support system on adherence to institutional protocol. J Clin Monit Comput 30, 301–312 (2016). https://doi.org/10.1007/s10877-015-9718-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10877-015-9718-3

Keywords

Search

Navigation