Smart PUMP DATA Analysis West Shore Medical Center Thomas Kane Ferris State University, June 8, 2016

Smart Pump Data Analysis Why look at smart pump data?? Literature statistics TJC issued Sentinel Event Alert 42 in 2008 re: safety risks utilizing technology including smart pumps 2016 TJC NPSG 3 improving safety of using medications e.g. heparin Dunford, 2014 found 8% of nurses did not know why they used smart pumps or why it was important to patient safety Reston, 2013 found 88.5% of all soft alerts are overridden (direct dose programming), 39% for appropriate modifications (so about 50% not)

Smart Pump Data Analysis How do we commit smart pump errors when overriding?? Murdoch and Cameron, (2008) defined 4 main categories 1.) Multiple of 10 errors 2.) Unit errors e.g. patient weight, drug units or administration units 3.) Calculation errors e.g. omission of patient weight, wrong infusion time 4.) Push button errors

Smart Pump Data Analysis Top drugs in literature overridden (Catlin 2015) Study 1 in order: propofol, vancomycin, hydromorphone Study 2 in order: heparin, propofol, fentanyl

Smart Pump Data Analysis WSMC Data Average infusions per month March 2015 to January 2016 6073 !!! (66,804 total) Number that used the Guardrails safety system 34,844 or 3168 on average per month OVERALL Guardrails compliance = 52%

Smart Pump Data Analysis Trends at WSMC – override by profile

Smart Pump Data Analysis Trends at WSMC – alert by time of day

Smart Pump Data Analysis Trends at WSMC – any alert by top 25 drugs

Smart Pump Data Analysis Trends at WSMC – overrides and reprogramming

Smart Pump Data Analysis Trends at WSMC - top 10 drugs by limit reprogramming

Smart Pump Data Analysis Trends at WSMC CONCLUSIONS Basic hydration accounts for the most alerts Minimal alerts from midnight to 7 am High concern for peds profile overrides Critical care and OB more than 50% override Top 10 drugs with reprogrammed limits of concern

Smart Pump Data Analysis Trends at WSMC Next Steps…….. Suggestions for staff survey Review survey results Plan for staff education AND/OR Modification of libraries

Smart Pump Data Analysis THANK YOU FOR YOUR TIME ?????? QUESTIONS ??????

Smart Pump Data Analysis References Catlin, A., Malloy, W., Arthur, K., Gaston, C., Young, J., Fernando, S., & Fernando, R. (2015). Comparative analytics of infusion pump data across multiple hospital systems. American Journal of Health-System Pharmacy, 72(4), 317-324. doi: 10.2146/ajhp140424 Dunford, B., Perrigino, M., Tucker, S., Gaston, C., Young, J., Vermace, B., ... Berndt, D. (2014). Organizational, cultural, and psychological determinants of smart infusion pump work arounds. Journal of Patient Safety. Advanced online publication. doi: 10.1097/pts.0000000000000137 Murdoch, L., & Cameron, V. (2008). Smart infusion technology: a minimum safety standard for intensive care? British Journal of Nursing, 17(10), 630-636. doi: 10.12968/bjon.2008.17.10.29476 Reston, J. (2013). Chapter 6 smart pumps and other protocols for infusion pumps. Making health care safer II: an updated critical analysis of the evidence for patient safety practices. (No. 211). Rockville, MD: Agency for Healthcare Research and Quality. Retrieved from: http://www.ncbi.nlm.gov/books/NBK133356/ The Joint Commission. (2008). Sentinel Event Alert, Issue 42: Safely implementing health information and converging technologies. Joint Commission. Retrieved from http://www.jointcommission.org/sentinel_event_ The Joint Commission. (2016). National patient safety goals effective January 1, 2016. Joint Commission. Retrieved from http://www.jointcommission.org/assets/1/6/2016