Outcomes on Implementation of Electronic Medication Administration Records and CPOE

1. Outcomes on Implementation of Electronic Medication Administration Records and CPOE Alan Chan, MD Internal Medicine-Pediatrics

2. Mentors • Michael Huke, Pharm D. • Melissa Gabriel, Pharm.D., BCPS • Jeff Hackman, MD – Emergency Dept.

3. Disclaimer • I was working on the CDC Universal Data Collection project for hemophilia and other blood disorders for adult and pediatrics. • A couple months ago, the project was shelved due to funding cuts and delays. • I’m not sure if I should blame the federal budget cuts… • Full statistical analysis is not completed.

4. Background • Something big happened at the end of August 2010! • Cerner GO-Live/Q6 for the CPOE (or Computer Physician Order entry) !!! • This will be referred to as the “start date”.

5. The Institute of Medicine • In 1999 article, notes 44,000 to 98,000 deaths due to medical errors. • To what extent these are directly related are debatable. • Computer physician order entry is one of the benchmarks for patient safety. • Defined by Leapfrog Group along with ICU staffing, High risk treatments/procedures, and Safe Practices Score • Also part of HITECH Act of 2009. • http://www.leapfroggroup.org/for_consumers/hospitals_asked_what accessed 4/1/2011

6. University HealthSystem Consortium (UHC) • Consists of 113 academic medical centers and affialiated hospitals – 90% of nations non-profits academic medical centers • Patient Safety Net (PSN) is a real time, Web-based event reporting system. • At Truman Medical Center (TMC), events can be logged into the system by any health care provider. • https://www.uhc.edu/11851.htm accessed 4/1/2011

7. Objective • We believe that the initiation of the CPOE and electronic medication administration record (eMAR) would decrease total errors. • What new errors might be introduced? • Few studies exist to track these changes.

8. Methods • Search on PubMed limited to past 5 years, English print journals, and Humans. • Terms included “electronic medical records and patient safety” for 228 results and “Adverse drug events computer physician order “ with 51 results. • Some immediate references and citations to these results were used, which could include older articles. • http://www.ncbi.nlm.nih.gov accessed 4/1/2011

9. Methods (cont) • TMC – all areas (inpatient, outpatient, ER, BH) • CPOE system – Powerchart; Cerner • A retrospective review of PSN results were used – these are self reported. • Time frame of 1, 3, and 6 months pre and post implementation were used. • A random sampling of 1 and 3 month windows were done to ensure similar number of reports.

10. Variables • Looked at ALL medications errors (med errors) • Sub groups of wrong medication and incorrect medication list separately and also together. • Looked at Adverse Drug Reactions (ADR), but not medication errors. • In these Med errors, looked at the type of outcome, whether it created an “Unsafe, No Harm, or Harmful Event”.

11. Medication errors – 9 types • Dose omission • Extra dose given • Wrong medication • Prescription/refill delay • Medication list was incorrect • Monitoring error (includes contraindications) • Unauthorized drug • Inadequate pain management • Other

12. Harm Score or Category of Events • Unsafe conditions (A) • Event, but no Harm • B1 – near miss from chance • B2 – near miss because of recovery efforts • C – reached patient (pt), but no harm • D – reached pt, and required additional monitoring to prevent harm • Event, but Harm • E – pt temporary harm, and required treatment • F – pt temporary harm, and required more hospitalization • G – permanent harm • H – harm and required intervention to sustain life like ICU transfer • Death (I) – one case, but unique circumstance. • Undetermined (X) - no cases

13. Results – 1 month window PRE = before “start date”; POST = after “start date”; ARR% is the Absolute risk reduction; RRR % is the relative risk reduction

14. Results – 3 month window

15. Results – 6 month window

16. Results… • A few single months were checked before and after “start date”, and the overall results number of reported events are similar • The overall number of reports have been increasing over the past few years, so difficult to access much before the “start date”. • Overall, all types of errors are lower. **

17. Results – Harm score These are number of medication errors

18. More errors? • Why more Unsafe errors? • More wrong med errors (from 5 to 10) • New type of error – delay in getting med • A contraindication was displayed and noted • Other types • Why More Harmful errors? • Actually less “Omission errors” • More wrong med errors (from 5 to 7) • Other types • The “other types” may be mislabeled**.

19. Discussion • User generated reports, although members of the PSN team here review reports as they are generated in real-time. • Some other reports may not have been correctly classified. • New unintended consequences – one study at a tertiary pediatric center actually noted increased mortality. • Might affect time sensitive therapies like critical care settings. • Han YY, Carcillo JA, Venkataraman ST, et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system

20. Next steps • Review 1 year data • Evaluate whether this represents a fair sample of the cases. • Review the “other category” to make sure properly labeled cases • Look at ADR and mortality, latter difficult to evaluate with this.

21. Notable thoughts. • It takes time for providers to adopt • Pharmacy centralizes many medications • Providers may spend more time away from bedside • Physician workload will increase, but uncertain amount • Is this trade off worth the better documentation and e-paper trail? • More order set would decrease “click through” time • Delays in opening electronic charts during heavy work times • Self reported events and ADR may not correlate with true rate.

22. Other thoughts • One study at a pediatric hospital saw overall decrease in hospital wide mortality with CPOE and electronic nursing documentation. • Studies at ICU areas show decrease in risk of medication errors, but no significant reduction in ADR or mortality. • Many studies have not been fully powered to detect the small number of ADR or mortality though. • We can look at 1 year data from “start date”.

23. References • http://www.leapfroggroup.org/for_consumers/hospitals_asked_what accessed 4/1/2011 • Han YY, Carcillo JA, Venkataraman ST, et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system [published correction appears in Pediatrics. 2006;117(2):594]. Pediatrics. 2005;116(6):1506–1512. • Van Rosse F, Maat B, Carin MA, et al. The Effect of CPOE on Medication Prescription Errors and Clinical Outcome in Pediatric and Intensive Care: A Systemic Review. Pediatrics. 2009; 123(4): 1184-1190. • Sittig DF, Ash JS, Zhang J, et al. Lessons From "Unexpected Increased Mortality After Implementation of a Commercially Sold Computerized Physician Order Entry System“. Pediatrics. 2006; 118; 797-801. • Longhurst CA, Parast L, Sandbord CI, et al. Decrease in Hospital-wide Mortality Rate After • Implementation of a Commercially Sold Computerized Physician Order Entry System. Pediatrics. 2010; 126: 14-21. • Kaushal R, Shojania KG, Bates DW. Effects of Computerized Physician Order Entry and Clinical Decision Support Systems on Medication Safety. Arch Intern Med. 2003; 163: 1409-1416. • http://www.cpoe.org/ From Oregon Health and Sciences University. Accessed 4/1/2011