EMPLOYERS AND MCOs realize that effective DM programs can cut costs and improve outcomes, but it isn't easy to determine which
programs are truly effective. The Disease Management Association of America (DMAA) recently released a consensus paper, "Principles
for Assessing Disease Management Outcomes," which clarifies this important subject.
A steering committee convened by the DMAA Quality and Research Committee has been working on the project since February. Its
goal: a consensus statement that would bring the DM community closer together and inform people about good study designs and
the best ways to conduct robust DM evaluations.
"The incorporation of valid study designs in the day-to-day business of disease management is a critical step necessary to
confirm the value of DM in achieving favorable outcomes for populations with chronic disease," they write. "[This step will]
further improve the delivery of DM services ... and meaningfully advance the delivery of healthcare services through the reporting
and dissemination of interventions that are proved to reduce the burden of disease."
Readers should take away three main points from this paper, says Karen Fitzner, PhD, DMAA Director of Research and Program
Development, who served as staff support to the committee: Control group: Robust studies should include a control group; ideally, this would be achieved through a prospective, randomized controlled
trial. However, that isn't always possible. To date, relatively few DM studies have used a randomized design. As the next
option, a study that compares pre-intervention outcomes with post-intervention outcomes is acceptable as long as there is
a parallel "control" group or reference group that receives no intervention.
Equivalence: To reduce potential biases between the control and intervention groups, they should be as similar as possible in everything
except the intervention that's under study. For example, the time frame should be the same, and the program and benefit structure
should be the same. If there are known differences in severity of disease or baseline utilization between the two populations,
try to correct for these differences.
Population-based DM comes to fee-for-service
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Transparency: All the details of study design and execution should be clearly described, so the reader can fully understand what you did.
The study should not be in "research speak," Fitzner says. "It should be in clear layman's language and should comprehensively
describe the study population, the intervention, the time frame, sponsorship, and who the researchers were. The intervention
should be described in sufficient detail to facilitate comparison with other programs."
However, DM studies are done for many reasons, Fitzner notes. "Some studies aren't done as formal research studies, or to
inform potential buyers. They may be done for purely internal reasons. In those cases we feel study designers should use their
own best judgment on how to apply these principles, in terms of their own purposes and needs."
"The principles enunciated in the DMAA paper are sound," says Al Lewis, executive director of the Disease Management Purchasing
Consortium (DMPC). "They provide the jumping-off point for our DMPC Savings Certification Program, which turns these principles
into a specific prescriptive measurement system."
The DMPC program is comparable to the accreditation programs offered by the National Committee for Quality Assurance, but
with a much narrower focus. Lewis describes it as an effort "to draw a 'bright line' between those measurements which are
valid and those which are not."
The committee's goal in writing "Principles for Assessing Disease Management Outcomes" was to develop a preferred approach,
not a mandated or standardized approach for DM program evaluation.
Ariel Linden, DrPH, MS, president of the Linden Consulting Group in Hillsboro, Ore., who served on the Scientific Advisory
Board that supported the committee's work, routinely recommends using more than one approach.
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