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Measuring and Reducing Adverse Drug Events Associated with High Risk Medications in Acute Care

Kathy Crea, Pharm.D., BCPS, Tom Sherrin, M.S., FASHP, Richard Snow, D.O., M.P.H., Dave Morehead, M.D.

 

OhioHealth
Columbus, Ohio

 

Purpose

While medication errors and their prevention have been a focus in previous years, recent efforts have focused on events that cause harm to patients, such as adverse drug events (ADEs). ADEs are common, with more than 770,000 people injured as a result of drug therapy in hospitals each year. Aiming to identify a subset of ADEs consistently, we modified the ADE trigger tool used by Resar and colleagues. We used this tool to identify opportunities for decreasing adverse drug events and measure the success of improvement efforts.

Description of the Program

Previous studies have used a list of 24 triggers to identify and facilitate review of charts to identify potential adverse events in hospitalized patients. This project focused on three classes of high risk medications and their seven associated triggers:

  • Anticoagulants (PTT > 100, INR > 5, or administration of vitamin K),
  • Narcotics and sedatives (administration of naloxone or flumazenil), and
  • Insulin (serum glucose < 50 mg/dL or administration of 50% dextrose injection).

Each of eight hospitals collected baseline data for three months during which time all occurrences of these seven triggers prompted a chart review to determine whether a related adverse event had occurred. From these baseline data, each facility chose one high risk class of medications as a focus for improvement over the following 12-month period. A goal of a 10% reduction was set, and this medication safety indicator was placed on the OhioHealth “Balanced Scorecard.” This step ensured accountability for success with the project.

Experience with the Program

Some of the interventions to reduce adverse events included implementation of an anticoagulation dosing and monitoring service for inpatients, elimination of range orders, failure modes and effects analysis of the process for administering insulin, and development of standardized physician order forms and treatment algorithms. The project heightened awareness of the medical staff, as well as the hospital staff, throughout the system. It helped change the culture regarding the way we look at adverse drug events in each facility, from the highest level administrators to the health care staff on patient-care units.

After 11 months of data collection, results have shown a reduction in ADEs in the selected medication classes from an average rate of 61.3 adverse events/month across the system to 34.0 adverse events/month, which represents a 45% relative reduction. The estimated cost impact of decreasing adverse events within just one class of high risk medications per hospital over a one-year period is approximately $1.5 million across the system. This was derived from the estimated post-event hospital attributable to a preventable ADE of $4700 per admission in 1997, which is likely higher in 2004.

Conclusion

The use of a modified trigger tool provided a consistent method of identifying patients receiving high-risk medications who have potentially experienced an adverse drug event for further chart review. Providing a stable metric, accountability, and process comparison at OhioHealth facilitated a 45% relative reduction in ADEs within a selected high-risk medication class in eight Ohio hospitals.

Selected References

  1. Reducing and preventing adverse drug events to decrease hospital costs. Research in Action, Issue 1. AHRQ publication no. 010020. Rockville, MD: Agency for Healthcare Research and Quality; March 2001. www.ahrq.gov/qual/aderia/aderia.htm (accessed 2004 Oct 18).
  2. Rozich RD, Haraden CR, Resar RK. Adverse drug event trigger tool: a practical methodology for measuring medication related harm. Qual Saf Health Care. 2003; 12:194-200.
  3. Jha AK, Kuperman GJ, Teich JM et al. Identifying adverse drug events: development of a computer-based monitor and comparison with chart review and stimulated voluntary reporting. J Am Med Inform Assoc. 1998; 3:305-14.
  4. Classen DC, Pestotnik SL, Evans RS et al. Computerized surveillance of adverse drug events in hospital patients. JAMA. 1991; 266:2847-51. [Erratum, JAMA. 1992; 267:1922.]
  5. Bates DW. Using information technology to screen for adverse drug events. Am J Health Syst Pharm. 2002; 59:2317-9.