The key findings of this study are that because electronic prescribing is integrated, when the doctor prescribes the medicine on the computer, he/she is also in fact writing the label to attach to the medicine. This means the label is always what the doctor requested. Because the label is always accurate to the prescription there can be no transcription error. Drugs can only be stored in the robot by bar code identification. There is a direct electronic link between the medicine, bar code, the item selected on the electronic prescription, and the label that the robot applies. These are the crucial links in deriving safety benefits from technology. To design in these links is to design out potential errors. Once designed, the system works from anywhere in the hospital. This allows 60% of dispensing activity to be triggered outside the pharmacy at Hospital A. Automatic labelling is a critical component of this system.
Another important consideration is avoidance wherever practically possible of part-packs. The robot does not handle these well in the way Hospital A operates the system, so avoidance of part packs is vital. Part packs cannot be entirely eradicated from use (e.g., steroids courses, chemotherapy), but minimising the number out of the robot is important. Once medication has been checked by a pharmacist (usually at ward level at Hospital A) the dispensing becomes nearly instantaneous. The remaining part of the process is to get the medication from pharmacy to the ward. In achieving instantaneous dispensing through the use of integrated electronic prescribing and a robot, the role of the dispensary pharmacist changes. No longer are pharmacists directly in control over the whole dispensing process. It is akin to craftsmen producing goods being replaced by production lines where quality control is through process control, and each individual is responsible for a part of the overall process, not all of it.
The prior use of electronic prescribing at Hospital A for 8 years meant that the integrated medicines management processes were well established. The delivery of products to the wards links in with these processes. Typically, most wards (30 out of 36) receive a medicines management service. Each ward can expect 0.75 WTE pharmacists, and 0.5 WTE technician time per week. Changes in skill-mix in out-patient department equates to an additional saving on top of staff reduction of 16%. Data from the control chart suggest de-skilling the dispensary workforce using robots has no impact on dispensing errors. Towards the end of 2009, there was an increase in dispensing errors, which was in part due to the consequences of the installation programme. This is where control charts proved useful to monitor the processes, especially when dealing with small numbers. A previous paper (Beard and Candlish, 2004) listed the different types of dispensing methods at Hospital A, and the error rates associated with them. Figure 2 shows a spike in errors just after installation. Error analysis showed them to be non-robot errors, i.e. they were picking errors from those shelves of the pharmacy where items cannot go into robots (part packs, round tubs of medicines, or items too small to be labelled by robot). Significantly, we have found zero errors for the robot plus electronic prescribing system combined, based on around 800,000 items per annum. This represents a huge benefit in safety. However, dispensing is not risk-free, since not all items are supplied and labelled from the robot. However, the opportunity for errors is significantly reduced.
The stock figures for 2008–09 represent values pre-robot. The business case required that besides re-deploying 4 staff, inventory value would be reduced by £250,000. This was achieved, but over time, the reduction in the number of weeks that stock is held has fallen by over 2 weeks, representing an additional saving of around £500,000 above the business case requirement. The cost of the robotic programme was around £750,000 over 10 years. This was achieved because the electronic prescribing - robot system allowed continuous reviewing of internal processes to yield better stock control.
Speed of turnaround time taken from the pharmacist’s clinical check is nearly instantaneous. At very busy periods dispensing times can rise to up to 20 to 30 minutes, but this situation tends not to last beyond about half an hour. Normally dispensing times, using traditional methods, can often be up to 4 hours for non-urgent dispensing (Beard and Wood, 2010). These authors quote how, by using lean processes, they reduced the dispensing time of a prescription from 4 hours to around 2 hours (these times include the time it takes a signed prescription to get from ward to pharmacy). This is not untypical of a traditional non-electronic prescribing – robotic system. The concept of instantaneous dispensing is not currently part of hospital pharmacy culture, nor is dispensing triggered from over 30 different points in the hospital.
Whittlesea et al. (2004) quotes a benchmark of 10 items per person per hour. The main Hospital A robot dispenses a maximum of 360 items per hour, equating to 36 dispensing staff. The in-patient pharmacy operates with around 10 dispensary staff. Hospital A’s robot chute 24 issues 60% of the dispensing activity, which is from the ward based pharmacy staff. This is not a directly comparable situation, but the efficiency is apparent.