This article describes a flexible model for drug evaluation and selection which may be useful to complement guidelines from the National Institute for Clinical Excellence
The major function of the National Institute for Clinical Excellence (NICE)
is to provide advice on the clinical effectiveness and cost-effectiveness of
both new and existing health technologies, including pharmaceuticals. Indeed,
NICE guidelines may, over the years, grow to constitute the single most influential
factor in drug selection within the National Health Service. More than 30 technologies
a year will be selected (by the Department of Health) for appraisal by the NICE.1
Already a number of pharmaceutical based reviews have been circulated. However,
the accrual of a “complete” set of guidelines will inevitably take
many years to accomplish, particularly if the NICE decides to continue to consult
widely. Yet it is clearly impractical for those involved in drug evaluation
and selection to delay important decision making as was the case with sildenafil.
Health care services may not be able to wait until appropriate NICE guidelines
are published. The NICE will inevitably try using existing drug evaluation tools
in its decision making process. Furthermore, any evaluation requires reassessment
with time. In the case of pharmaceuticals, the need for reassessment may arise
more frequently because of changes such as price, new entrants to the market,
adverse reaction reports, alterations to product licences, improved product
features or significant findings from new studies. For example, interferon beta-1b
has recently obtained an additional product licence for secondary progressive
multiple sclerosis and has provoked a further debate about its role in the treatment
of this disease.
A flexible model for drug evaluation and selection may be useful to complement
NICE guidelines. Such an evaluation model needs to compare current information
for a defined range of drugs and requires to be easily and rapidly updated in
order to keep the evaluation process “live”. Comparative Utilisation
of Resources Evaluation (CURE) is such a model.
The CURE model
The CURE model provides decision makers with an analytical tool to support
evaluations on drug selection. It is straightforward, auditable and flexible.
CURE provides ease of updating to accommodate changes — whether clinical,
economic, or arising from research — in the context in which selection
decisions are being made.
CURE is essentially an augmented
version of the Pharmaceutical Product
Drug Differentiation Evaluation model PPDDEM.2 Like the
PPDDEM, CURE focuses on the way in which products are differentiated from each
other. Examples of pharmaceutical product features which can be differentiated
within the same therapeutic class include efficacy, safety, side effects, patient
compliance, outcome data, duration of effects, NHS price, hospital discount
price, credit terms, product licence, method of delivery, packaging, technical
support, and route of administration. The element which distinguishes CURE from
PPDDEM is the inclusion of the criterion of “climate for change”.
Climate for change
“Climate for change” is a measure of the propensity of a prescriber
or organisation to alter pharmaceutical prescribing practice. Although decision
makers may recognise that patients should be prescribed a new drug according
to an agreed protocol, other relevant factors should also be considered. These
“climate for change” factors can be arbitrarily divided into five
different subsets:
Experience factor The experience factor is the measure of experience which a prescriber has with a specific drug. Clinicians may be concerned about prescribing new drugs or existing drugs with new licence indications. Their knowledge of the product and practical experience in using it to treat their patients may be limited. The effort required to learn about new or complex products and gain practical experience is a factor which should be included in the decision making process. For example, many of the newer biotechnology drugs appear to be largely restricted to the hospital sector. Clinical protocols may assist in improving the knowledge base of prescribers and thus help change prescribing practices.
Organisational readiness The organisational readiness factor is predominantly focused towards hospitals or other similar organisations. Here, health care professionals may require resources and time to plan a change in prescribing practices. Delays in altering prescribing practices may occur, especially if large drug stocks are held and in complex treatment areas where many practitioners or patients are involved, eg, blood glucose testing, renal dialysis solutions, enteral feeds, proton pump inhibitors. Other drugs, used in more simpler, smaller clinical areas may be easier to evaluate. Also, current health service staff shortages only serve to reduce the ability of organisations to initiate evaluations and implement newly agreed protocols.
Patient acceptability Patients get familiar with their treatments
and may feel that changing drug therapy would be a retrograde step, particularly
if the treatment works for them. Should patients change drugs if there is only
limited clinical benefit? Also, many new drugs have been
designed specifically to improve administration or patient compliance. For example,
persuading a patient to change from a regular injection once every two weeks
to three times a day, for reasons of cost-effectiveness, would be difficult
to explain.
Resource benefits The financial benefits of changing all drug treatments may not be the same. The NICE has already been given a number of objectives which could have a significant impact on NHS cash resources. Consideration may need to be given to the value of altering drug treatments, especially in an environment where there are only marginal savings to be gained. The desire for or speed of implementation of a change process could, therefore, be affected by the potential for significant financial benefit.
Switch costs/frequency of review How long should a decision maker
wait for emerging evidence? Drug treatments are often dynamic and may be subjected
to frequent change. New products are launched at regular intervals, product
licences are enhanced and prices are altered with competition. For example,
the new licence indications and prices for some of the latest PPIs on the market
will require constant review to ensure that the NHS prescribes these agents
effectively. How frequently should we change from one brand of a PPI to another,
especially if the modification affects approximately 300,000 patients? Consideration
will be needed to determine the most appropriate time within the life cycle
of a therapeutic area to review and recommend prescribing changes.
Using the CURE model
There are five steps to the CURE model:
1. Select drug for evaluation Select products which require evaluation and the broad clinical parameters or treatment areas in which the drug is to be prescribed.
2. Select product attributes A table of product attributes should be developed which can be used to compare competing or similar drugs. An example for angiotensin II blockers is given (Table 1). Similar drug differentiation tables, which include the product attributes, can perhaps be produced centrally by the NICE or by regional drug information centres. They, in turn, could then distribute copies through local networks to trust, health authority or primary care group drug evaluators. This would centralise workload, especially when updating information, thereby making efficient use of resources. Local decision makers will still be involved in the evaluation process, but not necessarily in the data collection. Alternatively, the attributes of each drug can be selected locally by literature review, or by discussions with clinicians, pharmacists, manufacturers, patients and so on.
| Table 1: A table of product attributes to assist in differentiating competing or similar drugs, in this case angiotensin ii blockers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3. Assign a weighting score to each attribute A weighting score is assigned to each attribute (Table 2) according to its degree of importance in the evaluation process. The more important the attribute, the higher the weighting factor. The total score of all the factors should equal 100 points. This is clearly a crucial judgment for evaluators who must have knowledge of relevant clinical trials, economic factors, etc.
| Table 2: Weighting scores assigned to each of the product attributes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
However, much of these data are available from the summary drug differentiation table (Table 1). The assignments for any given therapeutic category can be made either by a health care professional or by a group of health care professionals involved in the evaluation process. The greater the variety of roles of each health care professional and the size of the group consulted, the greater the opportunity to obtain a consensus view and take any diverse outlook into account. Once a weighting has been established for a set of attributes, they constitute an evaluation template for that therapeutic category. This template can be reused as often as necessary to evaluate and re-evaluate the available products as information about them accumulates or changes. Each template can be recorded as a computer spreadsheet for convenience as an audit record, and also to ensure consistency of approach.
4. Assign individual scores for each drug being assessed Individual scores are now given to the products being evaluated for every attribute described. Again, a detailed analysis of each product (Table 1) should assist as the main data source, although other accessible data sources may be preferred. The relative merits of each product must be in the range specified by the weighting factor: the greater the merit, the higher the score. For example, if the “efficacy” attribute has a weighting factor of 50 and drug A is deemed to be more efficacious than drug B, then A might receive a score of 50 whereas B scores 45 for that specific attribute. If the “side effects” attribute has a weighting factor of 12 and drug A gives rise to hypotension whereas drug B may produce only mild nausea, then the scores might be 2 for A and 9 for B, for that attribute. If the “cost” attribute has a weighting factor of 30, B is the cheapest drug in its class, and A costs twice as much, then B would score 30 and A would score 15. The relative merits of each product and for every attribute are summed and tabulated (Table 2) and converted to a final index score. The higher the score the more preferred the product and the greater the requirement or drive to change prescribing. The final CURE index score can be used alone. However, experience has shown that its purpose is best served by using it to stimulate discussion among drug evaluators before a decision is made.
5. Consider “climate for change” Managing changes in prescribing can often be complex and should require careful thought and planning to ensure a smooth transition. Following completion of all the above phases where the preferred product has been selected, an assessment of “climate for change” should then be considered. Often those who are involved in the drug decision making processes are not involved in implementing the change process. The change process should be discussed at the same time as evaluation of drug treatments; it should not be dealt with separately, because the process may be arduous, may require prudent deliberation and, because of financial constraints, may impact on the final decision.
6. Final decision and further audit A final decision as to the most appropriate place in therapy can now be made using the CURE model. This can be achieved either by an individual or preferably by a group of experts who would consider the data from the two tables. Because products and markets change with time, an agreement could also be reached as to what changes in scoring would trigger a review of the decision and a further audit. In practice the highest-scoring drugs should always be selected but prescribers and organisations may not want to change their prescribing practices too frequently. Benchmarking results between decision making groups can confirm the outcome of the CURE decision. If differences occur, and they inevitably will, then evaluators will be able to consider why and then improve their decision making in the future.
CURE is a tool intended to stimulate discussion or debate by decision makers and may assist in providing a suitable mechanism for producing the decision itself. With experience in the use of the model, evaluators should be able to establish their own differentiating scores on a spreadsheet, which could be applied to almost any therapeutic area. The appropriate value can then be incorporated into a template so that a prescribing decision could be derived automatically from the insertion of individual-product attribute scores. The inclusion of factors which highlight the ability to change prescribing gives CURE an advantage over other evaluation models, such as the SOJA (system for objectified judgment analysis) model,3 which can be criticised for not including a “climate for change” factor. A decision on future prescribing practice can possibly be derived more appropriately from application of the CURE model, as it includes all relevant factors.
Advantages of CURE
One of the principal advantages of the CURE model is the ease with which a range
of products can be evaluated and then re-evaluated in the light of new information.
An updated comparison between products can be achieved quickly in response to
new data in any given therapeutic class — more rapidly perhaps than waiting
for a revised NICE guideline. Results of differential comparisons are auditable
and can be open to external scrutiny, if required. CURE could also highlight,
to any interested party, precisely what are the most important factors in the
decision making process, eg, clinical outcomes data, increased adverse drug
reactions. CURE is systematic and can involve any number or type of health care
professional in the scoring procedure, either within a single organisation or
group of organisations.
CURE can also be used locally by drug and therapeutics or joint formulary committees
thus getting more clinicians involved and committed to the decision. It can
provide a ready source of data which can be benchmarked between different organisations.
Perhaps most importantly, because of the local involvement of health care professionals,
consideration about the “climate for change” can be taken into account
as well. This could lead to an increased level of commitment to the decision
by clinicians and improved medicines management.
CURE thus provides a simple and flexible approach to the evaluation and selection
of pharmaceutical products and has substantial merit in its own right. It can
be more
responsive to the constant flow of developments and could serve as a useful
complement to NICE guidance.
Acknowledgments Thanks to Bunmi Fajemisin (clinical effectiveness pharmacist, Oxford Radcliffe Hospital trust).
Allan Karr is pharmacy business services manager at University College London Hospitals, 140 Hampstead Road, London NW1 2BX