(Photography: Jim Shive Illustration: Paul A. Belci)
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Measurement of workload is a complex, multifaceted area and an important but difficult subject. In reviews of measurement
methods, radiotherapy workload is de scribed as being "poorly represented" by the use of simple parameters, as they do not
contain any measure of treatment complexity.1,2 In the specialties of oncology and hematology, recruitment figures are the main focus of performance management, with little
consideration given to study complexity, phase, and status of subject. Yet, these are key factors when considering workload
and study complexity.3
There is very little published on clinical research workload measurement, complexity, and capacity. The only comprehensive
study, which was undertaken in Canada, expressed the need to be able to estimate specific costs and resources associated with
clinical trials as the main reason for the study.3,4 The study measured trial activity throughout the study process and identified sponsor and study phase as important factors
to consider when estimating cost and resource use, but it did not result in a complexity scoring tool.
Within the UK, some work on trial complexity and parameters for scoring were presented at a recent conference.5 The components used included the areas of screening, randomization, treatment, pharmacovilgilance, samples and questionnaires,
and tumor assessment and treatment. An interesting inclusion was that of patient group. In other studies, work activity over a certain number of days has been measured to try and determine research related costs.6,7 In other areas, instigation of monthly workload reporting has occurred, including the recording of number of queries and
safety reports submitted in an attempt to quantify workload. An attempt to define the number of patients and trials that could
be dealt with by nurses and data managers depending on complexity has been made; the conclusion being that it allowed more
effective planning and flexibility to meet the changing demands of clinical research.
The Complexity Scoring Tool Broken Down by Section and Category
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Related work has also been undertaken by the European Organization for Research and Treatment of Cancer (EORTC) Clinical Research
Coordinators Group. This is work in progress that is looking at the development of a workload measurement instrument by initially
doing workload analysis to determine the staff requirements for a set of tasks by reviewing the processes, frequency, and
time required. The group has echoed the sections developed within this tool (i.e., set up, recruitment, and follow up) by
reviewing planning, implementation, data collection, and closure (see Table 1). Further collaborate work is planned with this
group.
Therefore, although there is very little literature and work in progress, attempts have been and are being made in this important
area.
Piloting studies
If a complexity scoring tool enables units to demonstrate the complexity and components of the work they undertake, then it
can also act as a valuable communication tool both within and outside the organization. The tool the author used in a pilot
study was developed over a year with a research team and in collaboration with research colleagues.
The tool was designed to score studies according to complexity across five categories. Each study was initially allocated
a predicted category according to its requirements to allow comparison. Once developed, the complexity tool was piloted by
volunteers throughout the UK, who were asked to review face validity, reliability, and repeatability by undertaking three
different exercises.
The tool was developed in response to problems and requirements related to clinical research management at a cancer center
within a Clinical Trials Unit in the UK that organizes predominantly multicentered research studies coordinated elsewhere—the
majority of which are Phase I to III. The pilot tool was reviewed by research teams based mainly in NHS Trusts within England
and Wales; all but one of the participants worked within the specialities of oncology and hematology.
In terms of participants, from the 36 pilot packs sent out to people who had expressed an interest in piloting the tool, 18
(50%) completed the face validity exercise, 14 (39%) completed pilot tools for the reliability exercise, and eight (22%) completed
pilot tools for the repeatability exercise.
