There’s a great deal of discussion about “disease management” as a model for improving healthcare quality. Disease management should be: Disease management components include: Note: Full service disease management programs must include all six components. Programs consisting of fewer components are disease management support services. ”
“… a system of coordinated health care interventions and communications for populations with conditions in which patient self-care efforts are significant.
prevention, behavior modification programs, and compliance/surveillance);
According to this definition, many disease management practices are actually providing support services only; there are few full service disease management programs in operation today.
Nevertheless, this is an excellent definition, and it is quite comprehensive. It suffers from several crucial gaps, however, which is endemic of American healthcare today:
Disease management components include:
Note: Full service disease management programs must include all six components. Programs consisting of fewer components are disease management support services. ”
- It doesn’t include personalized care, which means generic guidelines are used instead of developing guidelines tailored to a person’s particular needs and preferences. This means that with disease management every person with a particular illness (diagnosis) receives the same basic treatment, even though no two people are exactly alike. It’s like a sledgehammer approach to care, rather than a precise scalpel-like approach. For example, might a HemoglobanA1c of 7.5 be perfectly OK for some Type 2 diabetics, and for others 6.5 is too high, even though they have the same blood pressure and cholesterol readings, because other factors are having a affect? Since evidence-based guidelines change as new evidence is discovered, there needs to be much more research focusing on the differences between people with the same diagnosis, which disease management doesn’t address.
- It doesn’t stress the importance of practitioner-researcher collaborative networks facilitate the development and evolution of evidence-based guidelines by, for example, including patient data and lessons learned from everyday practice, and by having clinicians offer ideas for research. This also addresses the need to complement administrative (claims) data with comprehensive encounter (clinical) data.
- Nor does it address the health information technology gap, which must be bridged in order to support effective disease management programs. For example, more advanced software tools for decision-support, care-execution management, data management and sharing, and public health protection are needed.
- And it doesn’t stress the importance of supporting research on complementary and alternative medicine/interventions, which are not currently considered part of conventional healthcare.