Graduation Year


Document Type




Degree Granting Department

Industrial and Management Systems Engineering

Major Professor

Grisselle Centeno, Ph.D.

Co-Major Professor

Paul McCright, Ph.D.

Committee Member

Kingsley Reeves, Ph.D.

Committee Member

Thomas Sanocki, Ph.D.

Committee Member

Stuart Wilkinson, Ph.D.


Health Safety, Pharmacy Costs, Job Design, Motivation, Pharmacy Regulation


Healthcare costs in the United States continue to grow at an alarming rate. Concerning the cost of medications, there are a number of factors that drive these costs. While personnel costs are not the largest of these, they do contribute a significant portion. The cost of the cognitive component of order processing by pharmacists can range from three dollars to over six dollars per prescription depending on the production throughput of the pharmacist.

Studies at the organization which was the focus of the research, as well as reports in the literature, indicated that work disruption and other environmental factors could impact the rate at which pharmacist process physicians' orders into prescriptions. At the time of this study the collaborating facility was undergoing a re-organization; funding had been allocated to relocate and redesign the outpatient pharmacy. This provided a timely opportunity to examine the effect that changes to the physical plant, with specific attention being given to reducing interruptions to the pharmacists finishing orders, would have on pharmacists' productivity. This was measured in orders processed per hour, before and after the reorganization.

Sixteen months after the pharmacy was moved, supervisors were concerned that the outpatient pharmacy was still not performing at maximum efficiency and workload data was posted, with the intent that this information would motivate those professionals, whose output may have been below the average, to increase their production.

All outpatient prescriptions are maintained in a data base which records, among other items, the pharmacist who processed the order which generated the prescription and the time and date this was done. Data for prescriptions filled before and after each intervention were abstracted from the data base and used to determine production rates before and after the interventions.

There was a small, but statistically significant, decrease of two prescriptions per hour per pharmacist in production following the relocation. Fourteen of the twenty-one pharmacists (66.6%) had decreases in productivity averaging 4.1 prescriptions per hour while seven had an increase averaging 2.2 prescriptions per hour. All but one of the pharmacists who had an increase in productivity after the relocation also had a slight, but statistically insignificant, increase averaging 3.0 prescriptions per hour per pharmacist after the posting of the workload data.

The effect of posting the workload data was not statistically significant even though the study group processed 16,692 more orders working only 221 more hours. Nine of the study pharmacists (42.8%) had decreases in productivity averaging 2.3 prescriptions per hour per person, while the remaining twelve increased production by an average of 2.8 prescriptions per hour per pharmacist.

An analysis of both effects, using ANOVA, indicated that the pharmacist was a significant contributor to the effect in both cases. Only in the analysis of the impact of the relocation was the effect of the intervention significant and that was to decrease productivity.

The net result of this research was that the postulated interventions to increase productivity had no real effect and the motivation of the pharmacists may be the most significant factor. The fact that a third of the study pharmacists had decreases in productivity after both interventions is telling and may indicate problems with job design and motivation.

A further review of production rates and error are indicated with an emphasis on determining if there is an association between error rate and production rate. At this point there are little published data and what is available is either conjecture, as in the case of the North Carolina Board's determination of 150 prescriptions per day being a safe upper limit, to Malone's survey based research determining an average rate of 14.1 prescriptions per hour.