Here are some ideas for conducting comparative effectiveness research
Here are some ideas for conducting comparative effectiveness research
Think in terms of comparing treatments
Comparative effectiveness research (CER) grants will be distributed by three federal agencies, including the Agency for Healthcare Research and Quality (AHRQ), the National Institutes of Health, and the Secretary of Health and Human Services.
Clinical trial sites and research institutions interested in pursuing these grants may consider conducting CER in one of these different ways:
1. Conduct a CT that answers a question about a population and a particular treatment.
"This is the most obvious comparative effectiveness study," says Mark S. Roberts, MD, MPP, president of the Society for Medical Decision-Making and a professor of medicine, health policy, and management and industrial engineering at the University of Pittsburgh School of Medicine in Pittsburgh, PA. Roberts also is chief of the section of decision sciences and clinical systems modeling in the department of medicine at the University of Pittsburgh.
"You do the trial that answers questions about drugs and the population you care about," he says. "It's expensive to do a huge trial with 14 arms, but that's the simplest way."
2. Use statistical techniques and meta-analysis techniques.
Through the use of resourceful statistical techniques and meta-analysis, investigators could combine data from multiple trials and sources, including those that compared treatment A versus treatment B and treatment A versus placebo, Roberts suggests.
"You can use a number of techniques, adjusting for a difference in populations, and sometimes you can obtain information from the fact that patient populations are a little different across these studies," he says.
Meta-analyses might highlight variability in studies and outcomes, he adds.
3. Conduct observational studies using large databases.
Investigators can collect information from claims data, insurance data, and other large databases, Roberts says.
"Since you haven't randomized people, you never really know whether or not the results are confounded by some hidden thing you don't know about, because medical decisions are made for various reasons," he notes.
For instance, an observational study that looked at heart disease patients might find that more people who received pulmonary artery catheters in the emergency department die than those who didn't, he says.
But this observation could be because people who are given catheters are more likely to die because this population is sicker, Roberts adds.
"The advantages of observational data is that they give you examples of things in real populations that randomized trials can't give you because of the conditions under which people are treated," he says.
4. Use decision models and cost-effectiveness analysis.
Decision models and cost-effectiveness analysis help clinicians make treatment decisions, Roberts says.
This kind of research would look at how to combine data and put the information into a systematic, analytic structure to combine information from multiple sources, he says.
"We as a society believe costs are an outcome, just like everything else, and we think decisions are enhanced by taking costs into account," Roberts says. "Patients can do a good job of this, but they normally don't have to."
Comparative effectiveness research (CER) grants will be distributed by three federal agencies, including the Agency for Healthcare Research and Quality (AHRQ), the National Institutes of Health, and the Secretary of Health and Human Services.Subscribe Now for Access
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