![](bg4.png)
2 MEASURING THE BENEFITS
Setting. Sunderland Royal Hospital is a 1,000 bed
hospital in Northern England. The hospital operates
2 dispensaries, including a smaller discrete out-
patients pharmacy dispensing around 5000 items per
month. Control charts have been widely used by
industry for many years to manage process variation,
but the literature for healthcare in Europe suggests
this method of process control is less widely used.
This paper uses of control charts to look at the
impact on out-patient dispensing errors when robotic
dispensing and skill mix reductions are introduced.
Method. Dispensing errors per month was plotted
on a control chart for 12 months prior and
subsequently to the installation of the first
dispensing robot ( March 09). On installation, staff
was reduced by 1.4wte ( in line with business case).
Skill mix was also adjusted (not in business case) to
meet overall operation needs of the department. All
NHS Hospitals in the UK pay staff on a banding
system that equates all jobs on their value. The
higher the job band, the more highly skilled the post.
The job band and whole time equivalents for staff
were determined, and used as a measure of the
‘quantity of skill’ to run the Outpatient pharmacy.
The monetary value of the ‘skill quantity’ changes is
calculated from the mid-point salary scale.
Results. The change in skill mix was 50% ; (Table.
3). On installing the robot, band 5 technical staff
could be replaced with lower banded dispensing
staff, without adversely affecting the quality of the
dispensing process. This was 16% more efficient
than the business case required.
Discussion. Changes in skill mix equates to an
additional saving on top of staff reduction more than
the business case. Early data from the control chart
suggests de-skilling the dispensary workforce using
robots has a no worse impact on dispensing errors.
However, towards the end of 2009, there was an
increase in dispensing errors. This is where control
charts are useful to monitor the processes, when
dealing with small numbers. There is no EP function
at present in the Out-patient pharmacy, and analysis
of the ‘blip’ was undertaken by looking at the errors
and other factors. An audit of the prescriptions
received was undertaken, revealing that 25% of the
written prescriptions required further clarification by
the pharmacist.
It should be noted that the out-patient dispensary
does not yet have EP, but uses traditional pharmacy
prescriptions. The impact on errors, efficiency and
skill mix apply without any of the EP benefits. A
previous paper (5) listed the different types of
dispensing methods at CHS, and the error rates
associated with them. The same approach has been
taken for looking at errors for in-patient dispensing.
The results to date are shown in figure 2.
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 (e.g. eye drop bottles) to be labelled
by robot.
Significantly, we have found zero errors for the
robot plus EP system combined, based on around
800,00 items per annum. Potentially a huge benefit
in safety. However, dispensing is not risk-free, since
not all items are supplied and labelled from the
robot. Clearly though, the opportunity for errors is
significantly reduced.
Turn Around Time for Prescriptions. Speed of
turnaround time taken from clinical check is nearly
instantaneous, very different from many hospitals.
At busy periods dispensing times can rise to up to 20
to 30 minutes, but this situation tend not to last
beyond about half an hour. Normally dispensing
times can often be up to 4 hours for non-urgent
dispensing. (Beard J. and Wood D 2010). These
authors quotes how be using lean processes they
reduced the dispensing time of the 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 non-EP –
robotic system. The concept of instantaneous
dispensing is not currently part of hospital pharmacy
culture, nor is dispensing triggered from over 36
different points in the hospital.
Dispensing Rate. Whittlesea (7) quotes a Welsh
benchmark of 10 items per person per hour.
Sunderland dispenses a maximum of 360 items per
hour, equating to 36 dispensing staff. The in-patient
pharmacy operates with around 10 dispensary staff.
Sunderland’s robot chute 24 issues 60 % of the
dispensing activity, which is from the ward based
pharmacy staff. Ours is not a directly comparable
situation. However if one takes the figure of 360
items an hour the pharmacy can dispense, it has
therefore a capacity of 57,000 items per month. To
INTEGRATED ELECTRONIC PRESCRIBING AND ROBOTIC PHARMACY DISPENSING - Are there Any Benefits?
379