1. Frequency of return to stock errors in a community pharmacy running weekly electronic waiting bin reports: An observational study Monica Boomer 1, Mahdieh Fazel 1, Kellie Goodlet 1, Sara Andrus 1, and Allan Bates 2, PharmD. 1 University of Arizona College of Pharmacy and 2 Fry’s Marketplace Background and Introduction Definition of return-to-stock errors Return-to-stock prescription errors are the existence of prescriptions in the will-call bin (i.e. “ready bin” or “waiting bin”) that should not be there, but rather should have been removed and returned to stock. Background Return-to-stock prescriptions cause community retail pharmacy errors and patient dissatisfaction. Any medication that is filled but not picked up within twelve days needs to be returned to stock per insurance requirements. There is an electronic waiting bin report run at Fry's Pharmacy that is processed through Easy-Fill. Often times, the medications are not returned to stock in accordance with the report. This occurs due to various reasons: hectic environment and not following the correct procedure of returning medications to stock. In most instances, a patient tells the pharmacy staff that he/she no longer wants to pick up a certain medication. The medication transaction is then reversed in the computer system, but the pharmacy staff forgets to physically remove the medication from the shelf (will call bin) and return it to stock. Community retail pharmacies have return-to-stock errors that may impact pharmacy inventory, workflow, and patient satisfaction. Despite the presence of electronic systems in place to ensure that prescriptions filled are put back into stock, there are still prescriptions that get missed or forgotten and can cause problems within the health care system. Such problems may include poor patient adherence if patients are not picking up their medications, or patient confusion as to whether they received all the correct medications they ordered (1). In addition, a patient may also receive unintended duplicate therapy if a double fill is not caught by the electronic system. Prior Research The Institute for Medication Safety Practices published “Scanner beep only means the barcode has been scanned.” (2) This is the case in many pharmacies. At Fry’s Pharmacy, the register scanner beep means the prescription was scanned at the point of sale. It does not mean that the prescription scanned is ready or is the correct prescription for that patient. This is a cause of error if return-to-stock medications are not put back, because they could still be sold. Patients frequently abandon prescriptions. The article “Epidemiology of prescriptions abandoned at the pharmacy” found that 10.349,139 prescriptions filled by 5,249,380 patients 3.27% were abandoned (3). In the study “Prescription abandonment: another path to medication nonadherence” they found that overall 17% to 20% of patients do not collect new prescriptions from pharmacies. These abandoned prescriptions have the potential to cause pharmacy errors. Purpose of Project The purpose of this project is to quantify the number and type of return-to-stock prescription errors occurring each day at a Fry’s Marketplace community pharmacy. Additionally, this project gives some measure of the extent to which electronic system can catch return-to-stock errors and which errors are more likely to occur despite these systems being put in place. Objectives Determine the number of incidents that occur daily due to return-to-stock errors (i.e., duplicate therapy, patient requests that remain in the will call bin, and past return date) Determine the impact return-to-stock errors have on patient satisfaction Determine which day(s) of the week had the highest incidence of return-to-stock errors Determine the return-to-stock error that had the highest prevalence Methods Descriptive statistics were employed to determine the incidence of return-to-stock issues within the Fry’s community pharmacy on Tangerine and Thornydale in Tucson, Arizona. Therefore, no intervention was made. Observational data were collected within the pharmacy for three months and the number of incidents per day that occurred due to return-to-stock issues was recorded. Each return-to-stock issue was classified as one of the following: duplicate therapy, patient requested return to stock that remained in the will call bin, and past return date that remained in the will call bin. When each return-to-stock issue was recorded for the specific day, it was also recorded whether or not that issue resulted in patient dissatisfaction. The data collected was separated into the days of the week, type of return-to-stock issue, and whether patient dissatisfaction occurred. The data recorded in this data sheet consisted of tally marks for each incident experienced. Below is the template of the data collection sheet. Data was utilized to determine the incidence of return-to-stock issues on each day of the week (total average calculated per day, sum of every issue type), which type of issue is most prevalent (total calculated per week of each issue type), and whether these issues resulted in patient dissatisfaction (total calculated per day). The average number of return-to-stock issues experienced each day will also be calculated for the data set, which will help compare the incidence and prevalence of these issues on different days of the week. In addition, the percentage of events per day that resulted in patient dissatisfaction was calculated based upon the number of dissatisfactory events recorded that day compared with the number of return-to-stock issues (total of all issue types) recorded that day. This information will help determine the prevalence of patient dissatisfaction due to return-to-stock issues, separated into each day of the week. Data Table 1: Summary of return-to-stock errors made by day and type (percents in each row or column may not equal 100% due to rounding) Table 2: Summary of total event by day and events resulting in patient dissatisfaction Conclusion and Discussion The overall number of return-to-stock error incidents over a 3 month period totaled 143. The return-to-stock error that occurred most frequently was the past return-to-stock date (44%). An overall patient dissatisfaction of 12% occurred within all 3 measured return-to-stock errors. The most return-to-stock errors were observed on Mondays and Fridays with the most patient dissatisfaction occurring on Tuesdays and Fridays. Future studies could benefit from addressing the following questions: Does the report capture all of the prescriptions that are left on the shelf for over 2 weeks? How would running the report daily versus bi-monthly affect the staffs ability to effectively remove all of the flagged prescriptions? How does the company's staffing model affect the technicians ability to find and remove flagged prescriptions given the volume of business and the time allotted to them? Recommendations for Future Studies References 1. Murry, M.D., and J. Harrison. 16 Nov. 2010. Prescription Abandonment: Another Path to Medication Nonadherence. Ann Intern Med. 153(10):680- 681.http://annals.org.ezproxy1.library.arizona.edu/article.aspx?articleid=746457 2. Shrank, W.H. et. al. 16 Nov 2010. The Epidemiology of Prescriptions Abandoned at the Pharmacy. Ann Intern Med. 153(10):633- 640.http://annals.org/article.aspx?articleid=746421 3. 30 June 2011. Scanner Beep only means the barcode has been scanned. ISMP Medication Safety Alert http://www.ismp.org/Newsletters/acutecare/articles/20110630.asp A total of 143 return-to-stock errors were recorded over a 3 month period. Patient requests for return-to-stock and prescriptions kept past the pharmacy’s return to stock date made up the majority of errors and occurred with approximately equal frequency. (See Figure 1.) Double fills made up only a small percentage (15%) of the total return-to-stock errors. 15% of the errors were prescriptions that had been filled twice for the same patient. Errors occurred most frequently on Mondays (25% of all return-to-stock errors) and Fridays (21%). See Table 1 for additional information on the number of errors occurring by day of the week. 12% of the return-to-stock errors resulted in observed patient dissatisfaction. Patient dissatisfaction was observed most frequently on Fridays (dissatisfaction observed with 23% of the return-to-stock errors) and Tuesdays (23%). See Table 2 for additional information on the number of times a return-to-stock error resulted in patient dissatisfaction by day of the week. Results Due to the limited space within the pharmacy and the high volume of customers it was difficult for any group members to be present during data collection. The group had to rely on the pharmacy technicians to collect data and therefore it is likely that some data may have been missed altogether. This quality improvement does not take into account the differences between this Fry s Marketplace pharmacy and other pharmacies. This project lacks generalizability to other grocery store pharmacies, other retail pharmacies, and other Fry’s pharmacies regardless of location as this project is only applicable to Fry's Marketplace located on Tangerine and Thornydale in Tucson Arizona. Statistical significance cannot be determined. For more information, please contact: Sara Andrus: andrus@pharmacy.arizona.eduandrus@pharmacy.arizona.edu Monica Boomer: mboomer@pharmacy.arizona.edumboomer@pharmacy.arizona.edu Mahdieh Fazel: fazelm@pharmacy.arizona.edufazelm@pharmacy.arizona.edu Kellie Goodlet: goodlet@pharmacy.arizona.edugoodlet@pharmacy.arizona.edu Allan Bates: allan.bates@stores.frysfood.comallan.bates@stores.frysfood.com Implications Limitations The results of this project are important in understanding the frequency in which medications are left on the shelf for pick up and the frequency of overall patient dissatisfaction resulting from these return-to-stock error events. It is important to differentiate between a patient not wanting the prescription versus not knowing it is ready and leaving it at the pharmacy for 2 weeks. These data can be used to note return-to-stock procedure failures in order to avoid patient dissatisfaction and help drive patient adherence to ensure patient safety while maintaining pharmacy workflow. Figure 1: Chart showing the percent of each type of return-to-stock error out of the total events (RTS = return-to-stock) Total Events Events Resulting in Patient Dissatisfaction; N (%) Monday351 (3) Tuesday133 (23) Wednesday182 (11) Thursday201 (5) Friday307 (23) Saturday171 (6) Sunday102 (20) All days14317 (12) MondayTuesdayWednesdayThursdayFridaySaturdaySunday Total events; N (%) Double Fill313381221 (15) Patient Requests Return To Stock118510119559 (41) Past Return To Stock Date214107117363 (44) Total events; N (%)35 (25)13 (9)18 (13)20 (14)30 (21)17 (12)10 (7)143 (100) DateMondayTuesdayWednesdayThursdayFridaySaturdaySunday Double Fill Pt. Request Return To Stock Past Return To Stock Date Patient Dissatisfaction Data cont. This was a quality improvement project; therefore, it does not meet the Federal definition of research and Institutional Review Board approval was not required.