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Appl Clin Inform 2017; 08(01): 80-96
DOI: 10.4338/ACI-2016-10-RA-0164
DOI: 10.4338/ACI-2016-10-RA-0164
Research Article
Development and Feasibility of a Real-Time Clinical Decision Support System for Traumatic Brain Injury Anesthesia Care
FundingThis work was supported by a grant from National Institute of Health [R01 NS072308–05]
Further Information
Correspondence to:
Bala G. Nair, PhD
Department of Anesthesiology and Pain Medicine
University of Washington
BB-1469 Health Sciences Bldg, Mail Box: 356540
1959 NE Pacific Street
Seattle, WA 98195
Phone: (206) 598 4993
Fax: (206) 543–2958
Email: nairbg@uw.edu
Publication History
Received:
06 October 2016
Accepted:
26 January 2016
Publication Date:
20 December 2017 (online)
Summary
Background: Real-time clinical decision support (CDS) integrated with anesthesia information management systems (AIMS) can generate point of care reminders to improve quality of care. Objective: To develop, implement and evaluate a real-time clinical decision support system for anesthetic management of pediatric traumatic brain injury (TBI) patients undergoing urgent neurosurgery.
Methods: We iteratively developed a CDS system for pediatric TBI patients undergoing urgent neurosurgery. The system automatically detects eligible cases and evidence-based key performance indicators (KPIs). Unwanted clinical events trigger and display real-time messages on the AIMS computer screen. Main outcomes were feasibility of detecting eligible cases and KPIs, and user acceptance.
Results: The CDS system was triggered in 22 out of 28 (79%) patients. The sensitivity of detecting continuously sampled KPIs reached 93.8%. For intermittently sampled KPIs, sensitivity and specificity reached 90.9% and 100%, respectively. 88% of providers reported that CDS helped with TBI anesthesia care.
Conclusions: CDS implementation is feasible and acceptable with a high rate of case capture and appropriate generation of alert and guidance messages for TBI anesthesia care.
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Conflict of interest
The authors declare that they have no conflict of interest.
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References
- 1 Vavilala MS, Kernic MA, Wang J, Kannan N, Mink RB, Wainwright MS. et. al. Acute care clinical indicators associated with discharge outcomes in children with severe traumatic brain injury. Crit Care Med 2014; 42 (Suppl. 10) 2258-2266.
- 2 Epstein RH, Dexter F, Patel N. Influencing anesthesia provider behavior using Anesthesia Information Management System data for near real-time alerts and post hoc reports. Anesth Analg 2015; 121 (Suppl. 03) 678-692.
- 3 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 (Suppl. 01) 206-214.
- 4 Nair BG, Horibe M, Newman SF, Wu WY, Schwid HA. Near real-time notification of gaps in cuff blood pressure recordings for improved patient monitoring. J Clin Monit Comput 2013; 27 (Suppl. 03) 265-271.
- 5 Nair BG, Newman SF, Peterson GN, Schwid HA. Smart Anesthesia Manager™ (SAM) –a real-time decision support system for anesthesia care during surgery. IEEE Trans Biomed Eng 2013; 60 (Suppl. 01) 207-210.
- 6 Blum JM, Stentz MJ, Maile MD, Jewell E, Raghavendran K, Engoren M. et. al. Automated alerting and recommendations for the management of patients with preexisting hypoxia and potential acute lung injury: a pilot study. Anesthesiology 2013; 119 (Suppl. 02) 295-302.
- 7 Nair BG, Peterson GN, Newman SF, Wu WY, Kolios-Morris V, Schwid HA. Improving documentation of a beta-blocker quality measure through an anesthesia information management system and real-time notification of documentation errors. Jt Comm J Qual Saf 2012; 38 (Suppl. 06) 283-288.
- 8 Nair BG, Newman SF, Peterson GN, Schwid HA. Automated electronic reminders to improve redosing of antibiotics during surgical cases: comparison of two approaches. Surg Infect 2011; 12 (Suppl. 01) 57-63.
- 9 Chau A, Ehrenfeld JM. Using real-time clinical decision support to improve performance on perioperative quality and process measures. Anesthesiol Clin 2011; 29 (Suppl. 01) 57-69.
- 10 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 (Suppl. 02) 356-363.
- 11 Wanderer JP, Sandberg WS, Ehrenfeld JM. Real-time alerts and reminders using information systems. Anesthesiol Clin 2011; 29 (Suppl. 03) 389-396.
- 12 Schwann NM, Bretz KA, Eid S, Burger T, Fry D, Ackler F. et. al. Point-of-care electronic prompts: an effective means of increasing compliance, demonstrating quality, and improving outcome. Anesth Analg 2011; 113 (Suppl. 04) 869-876.
- 13 Nair BG, Newman SF, Peterson GN, Wu WY, Schwid HA. Feedback mechanisms including real-time electronic alerts to achieve near 100% timely prophylactic antibiotic administration in surgical cases. Anesth Analg 2010; 111 (Suppl. 05) 1293-1300.
- 14 Kochanek PM, Carney N, Adelson PD, Ashwal S, Bell MJ, Bratton S. et. al. Guidelines for the acute medical management of severe traumatic brain injury in infants, children, and adolescents-second edition. Pediatr Crit Care Med 2012; 13 (Suppl. 01) S1-S82.
- 15 Gary K, Enquobahrie A, Ibanez L, Cheng P, Yaniv Z, Cleary K. et. al. Agile methods for open source safety-critical software. Softw Pract Exp 2011; 41 (Suppl. 09) 945-962.
- 16 Kane DW, Hohman MM, Cerami EG, McCormick MW, Kuhlmman KF, Byrd JA. Agile methods in biomedical software development: a multi-site experience report. BMC Bioinformatics 2006; 7: 273.
- 17 Kaplan B. Evaluating informatics applications--clinical decision support systems literature review. Int J Med Inform 2001; 64 (Suppl. 01) 15-37.
- 18 Sailors RM, East TD, Wallce CJ, Carlson DA, Franklin MA, Heermann LK. et al. Testing and validation of computerized decision support systems. Proc AMIA Annu Fall Symp 1996; 234-238.
- 19 Hardcastle N, Benzon HA, Vavilala MS. Update on the 2012 guidelines for the management of pediatric traumatic brain injury –information for the anesthesiologist. Paediatr Anaesth 2014; 24 (Suppl. 07) 703-710.
- 20 Sandberg WS, Sandberg EH, Seim AR, Anupama S, Ehrenfeld JM, Spring SF. et. al. Real-time checking of electronic anesthesia records for documentation errors and automatically text messaging clinicians improves quality of documentation. Anesth Analg 2008; 106 (Suppl. 01) 192-201.
- 21 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 (Suppl. 03) 592-597.
- 22 Sittig DF, Krall MA, Dykstra RH, Russell A, Chin HL. A survey of factors affecting clinician acceptance of clinical decision support. BMC Med Inform Decis Mak 2006; 6: 6.
- 23 Nair BG, Schwid HA. Don‘t blame the messenger. Anesth Analg 2015; 121 (Suppl. 06) 1409-1411.
- 24 Epstein RH, Dexter F, Ehrenfeld JM, Sandberg WS. Implications of event entry latency on anesthesia information management decision support systems. Anesth Analg 2009; 108: 941-947.
- 25 Takla G, Petre JH, Doyle DJ, Horibe M, Gopakumaran B. The problem of artifacts in patient monitor data during surgery: a clinical and methodological review. Anesth Analg 2006; 103 (Suppl. 05) 1196-1204.
Correspondence to:
Bala G. Nair, PhD
Department of Anesthesiology and Pain Medicine
University of Washington
BB-1469 Health Sciences Bldg, Mail Box: 356540
1959 NE Pacific Street
Seattle, WA 98195
Phone: (206) 598 4993
Fax: (206) 543–2958
Email: nairbg@uw.edu
-
References
- 1 Vavilala MS, Kernic MA, Wang J, Kannan N, Mink RB, Wainwright MS. et. al. Acute care clinical indicators associated with discharge outcomes in children with severe traumatic brain injury. Crit Care Med 2014; 42 (Suppl. 10) 2258-2266.
- 2 Epstein RH, Dexter F, Patel N. Influencing anesthesia provider behavior using Anesthesia Information Management System data for near real-time alerts and post hoc reports. Anesth Analg 2015; 121 (Suppl. 03) 678-692.
- 3 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 (Suppl. 01) 206-214.
- 4 Nair BG, Horibe M, Newman SF, Wu WY, Schwid HA. Near real-time notification of gaps in cuff blood pressure recordings for improved patient monitoring. J Clin Monit Comput 2013; 27 (Suppl. 03) 265-271.
- 5 Nair BG, Newman SF, Peterson GN, Schwid HA. Smart Anesthesia Manager™ (SAM) –a real-time decision support system for anesthesia care during surgery. IEEE Trans Biomed Eng 2013; 60 (Suppl. 01) 207-210.
- 6 Blum JM, Stentz MJ, Maile MD, Jewell E, Raghavendran K, Engoren M. et. al. Automated alerting and recommendations for the management of patients with preexisting hypoxia and potential acute lung injury: a pilot study. Anesthesiology 2013; 119 (Suppl. 02) 295-302.
- 7 Nair BG, Peterson GN, Newman SF, Wu WY, Kolios-Morris V, Schwid HA. Improving documentation of a beta-blocker quality measure through an anesthesia information management system and real-time notification of documentation errors. Jt Comm J Qual Saf 2012; 38 (Suppl. 06) 283-288.
- 8 Nair BG, Newman SF, Peterson GN, Schwid HA. Automated electronic reminders to improve redosing of antibiotics during surgical cases: comparison of two approaches. Surg Infect 2011; 12 (Suppl. 01) 57-63.
- 9 Chau A, Ehrenfeld JM. Using real-time clinical decision support to improve performance on perioperative quality and process measures. Anesthesiol Clin 2011; 29 (Suppl. 01) 57-69.
- 10 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 (Suppl. 02) 356-363.
- 11 Wanderer JP, Sandberg WS, Ehrenfeld JM. Real-time alerts and reminders using information systems. Anesthesiol Clin 2011; 29 (Suppl. 03) 389-396.
- 12 Schwann NM, Bretz KA, Eid S, Burger T, Fry D, Ackler F. et. al. Point-of-care electronic prompts: an effective means of increasing compliance, demonstrating quality, and improving outcome. Anesth Analg 2011; 113 (Suppl. 04) 869-876.
- 13 Nair BG, Newman SF, Peterson GN, Wu WY, Schwid HA. Feedback mechanisms including real-time electronic alerts to achieve near 100% timely prophylactic antibiotic administration in surgical cases. Anesth Analg 2010; 111 (Suppl. 05) 1293-1300.
- 14 Kochanek PM, Carney N, Adelson PD, Ashwal S, Bell MJ, Bratton S. et. al. Guidelines for the acute medical management of severe traumatic brain injury in infants, children, and adolescents-second edition. Pediatr Crit Care Med 2012; 13 (Suppl. 01) S1-S82.
- 15 Gary K, Enquobahrie A, Ibanez L, Cheng P, Yaniv Z, Cleary K. et. al. Agile methods for open source safety-critical software. Softw Pract Exp 2011; 41 (Suppl. 09) 945-962.
- 16 Kane DW, Hohman MM, Cerami EG, McCormick MW, Kuhlmman KF, Byrd JA. Agile methods in biomedical software development: a multi-site experience report. BMC Bioinformatics 2006; 7: 273.
- 17 Kaplan B. Evaluating informatics applications--clinical decision support systems literature review. Int J Med Inform 2001; 64 (Suppl. 01) 15-37.
- 18 Sailors RM, East TD, Wallce CJ, Carlson DA, Franklin MA, Heermann LK. et al. Testing and validation of computerized decision support systems. Proc AMIA Annu Fall Symp 1996; 234-238.
- 19 Hardcastle N, Benzon HA, Vavilala MS. Update on the 2012 guidelines for the management of pediatric traumatic brain injury –information for the anesthesiologist. Paediatr Anaesth 2014; 24 (Suppl. 07) 703-710.
- 20 Sandberg WS, Sandberg EH, Seim AR, Anupama S, Ehrenfeld JM, Spring SF. et. al. Real-time checking of electronic anesthesia records for documentation errors and automatically text messaging clinicians improves quality of documentation. Anesth Analg 2008; 106 (Suppl. 01) 192-201.
- 21 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 (Suppl. 03) 592-597.
- 22 Sittig DF, Krall MA, Dykstra RH, Russell A, Chin HL. A survey of factors affecting clinician acceptance of clinical decision support. BMC Med Inform Decis Mak 2006; 6: 6.
- 23 Nair BG, Schwid HA. Don‘t blame the messenger. Anesth Analg 2015; 121 (Suppl. 06) 1409-1411.
- 24 Epstein RH, Dexter F, Ehrenfeld JM, Sandberg WS. Implications of event entry latency on anesthesia information management decision support systems. Anesth Analg 2009; 108: 941-947.
- 25 Takla G, Petre JH, Doyle DJ, Horibe M, Gopakumaran B. The problem of artifacts in patient monitor data during surgery: a clinical and methodological review. Anesth Analg 2006; 103 (Suppl. 05) 1196-1204.