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The testing of healthcare interventions is evolving
The British pioneer clinical epidemiologist
Archie Cochrane defined three concepts related to testing healthcare
interventions.1 Efficacy is the extent to which an
intervention does more good than harm under ideal circumstances ("Can
it work?"). Effectiveness assesses whether an intervention does more
good than harm when provided under usual circumstances of healthcare
practice ("Does it work in practice?"). Efficiency measures the
effect of an intervention in relation to the resources it consumes
("Is it worth it?"). Trials of efficacy and effectiveness have also
been described as explanatory and management trials,
respectively,2 and efficiency trials are more often called
cost effectiveness or cost benefit studies.
Almost all clinical trials assess efficacy. Such trials typically
select patients who are carefully diagnosed; are at highest risk of
adverse outcomes from the disease in question; lack other serious
illnesses; and are most likely to follow and respond to the treatment
of interest. This treatment will be prescribed by doctors who are most
likely to follow a careful protocol; the comparison will be a placebo,
not the current best alternative therapy; and participants will receive
special attention from staff who supplement or replace those employed
in usual clinical settings. The results of such trials are very useful:
if the intervention doesn't work under such ideal conditions it surely
won't work under usual conditions. Most treatments don't survive this
stage of testing, and it makes good sense to sequence the testing of all interventions through this efficacy stage.
Even if an intervention works astonishingly well in a "Can it
work?" study, it may not work well in usual care. Effectiveness in
the community depends not only on efficacy but also on diagnostic accuracy, provider compliance, patient adherence, and the coverage of
health services.3 Misdiagnosis can result in the wrong
people getting or not getting the treatment. Providers often fail to prescribe or administer the treatment properly. Patients typically take
less than half of prescribed treatments. "High tech," expensive, or
new interventions are usually not available in all communities in the
developed countries or to most communities in the rest of the world. To
paraphrase Muir Gray, what works well at the Sloan Kettering (a high
tech cancer centre) may not work very well in Kettering (a small UK community).
The study by Llewellyn-Jones et al in this issue of the BMJ
reveals many of these problems (p 676).4 In attempting to
provide an intervention to help general practitioners to detect and
care for depressed elderly people in residential care, the authors found little evidence that general practitioners improved their prescribing habits. Many patients refused to participate or dropped out
after entry to the study. The result was a barely detectable benefit,
even among those patients who stuck with the programme. Even then, the
small benefit was at the expense of additional resources Alas, there are more troubles here. Though this study was
intended to be "community based," this desired state was
compromised by the difficulty of recruiting doctors and patients and
keeping those recruited engaged. In the end, the study doesn't inform us about whether the community's mental health was improved. Sadly, the multiple barriers to doing health services research and
implementing innovative health services are why so few investigators
try to do effectiveness studies. And even if they succeed, healthcare managers, planners, and politicians will want to know more than "Does
it work?": they will want to know "Is it worth it?" But don't despair. We're simply going through an evolutionary phase
in testing interventions. Since the end of the second world war we've
learned to walk, with randomised trials that assess efficacy. Trials
such as the one by Llewellyn-Jones et al show that we're just now
learning to run We need more effectiveness studies to sort the fool's gold from the
true gold and efficiency studies to tell us if the price of extraction
is a bargain. Fortunately, many governments around the world are aware
of the need for more and better research into health services and are
providing funds for training and research development. One hopes that
they will not lose heart or patience: we're going in the right
direction, but trial and error are needed, along with investment in
methodological research to get effectiveness and efficiency studies right.
McMaster University Health Sciences Center, Hamilton, Ontario
L8N 3Z5, Canada
that is, the
investigators and their educational programme.
in
comparison with use of the resources for other needs.
with community trials that tackle difficult challenges
in research design and implementation that can undermine the
feasibility of a study or prejudice the interpretation of its findings.
Issues of economic analysis also are being resolved, so that questions
of efficiency can be better addressed. This progress will seem slow to
researchers caught up in it and to all of us waiting for the answers,
but in the history of the world we're heading for success at a
blistering pace. Our progress is fuelled by efficacy studies and by
researchers and governments intent on reaping the benefits they promise.
| 1. | Cochrane AL. Effectiveness and efficiency: random reflection on health services. London: Nuffield Provincial Hospitals Trust , 1972. |
| 2. | Sackett DL, Gent M. Controversies in counting and attributing events in clinical trials. N Engl J Med 1979; 301: 1410-1412[Medline]. |
| 3. | Bennett K, Tugwell P, Sackett D, Haynes B. Relative risks, benefits, and costs of intervention. In: Warren KS, Mahmoud AAF, eds. Tropical and geographic medicine. 2nd ed. New York: McGraw-Hill, 1990:205-228. |
| 4. |
Llewellyn-Jones RH, Baikie KA, Smithers H, Cohen J, Snowdon J, Tennant CC.
Multifaceted shared care intervention for late life depression in residential care: randomised controlled trial.
BMJ
1999;
319:
676-682 |
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