Disease Management: What it is and what it could be

There’s a great deal of discussion about “disease management” as a model for improving healthcare quality. Disease management should be:

“… a system of coordinated health care interventions and communications for populations with conditions in which patient self-care efforts are significant.

Disease management:

• Supports the physician or practitioner/patient relationship and plan of care;
• Emphasizes prevention of exacerbations and complications utilizing evidence-based practice guidelines and patient empowerment strategies; and
• Evaluates clinical, humanistic, and economic outcomes on an on-going basis with the goal of improving overall health.

Disease management components include:

• Population identification processes;
• Evidence-based practice guidelines;
• Collaborative practice models to include physician and support-service providers;
• Patient self-management education (may include primary
  prevention, behavior modification programs, and compliance/surveillance);
• Process and outcomes measurement, evaluation, and management;
• Routine reporting/feedback loop (may include communication with patient, physician, health plan and ancillary providers, and practice profiling).
  

Note: Full service disease management programs must include all six components. Programs consisting of fewer components are disease management support services. ”[1]

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:

• 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.

[1] http://www.dmaa.org/definition.html