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

2. Smart Pump Data Analysis
Why look at smart pump data??
Literature statistics
TJC issued Sentinel Event Alert 42 in 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)

3. 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

4. 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

5. 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%

6. Smart Pump Data Analysis
Trends at WSMC – override by profile

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

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

9. Smart Pump Data Analysis
Trends at WSMC – overrides and reprogramming

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

11. 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

12. 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

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

14. 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), doi: /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: /pts
Murdoch, L., & Cameron, V. (2008). Smart infusion technology: a minimum safety standard for intensive care? British Journal of Nursing, 17(10), doi: /bjon
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:
The Joint Commission. (2008). Sentinel Event Alert, Issue 42: Safely implementing health information and converging technologies. Joint Commission. Retrieved from
The Joint Commission. (2016). National patient safety goals effective January 1, Joint Commission. Retrieved from