305955
Segmentation of a Medicare Advantage population using the Diabetes Complications Severity Index (DCSI)
To stratify members with Type II Diabetes among a Medicare Advantage population by Diabetes Complications Severity Index (DCSI) and report descriptive differences in health care consumption and clinical outcomes.
METHODS:
We identified a retrospective cohort of individuals with diabetes (n=661,277) that were a part of a Medicare Advantage population during 2012. The cohort was stratified into three groups, Low (0-3), Medium (4-7), and High (8-13) diabetes severity based on DCSI. We reported differences in utilization, outcomes and costs between these three groups.
RESULTS:
The distribution of the population was skewed heavily towards the low severity group (73%), followed by medium (25%) and high (2%). For every point increase in DCSI, on average we observed a 25% increase in inpatient admissions along with a 14% increase in emergency room visits, and a 22% increase in medical costs.
Prevalence of diabetic foot wounds was highest among the high severity group at 29.6% compared to 0.8% and 7.6% among low and medium severity groups. Among the clinical outcome metrics, the percentage of people that had an HBA1c less than 8% was highest among the low severity group at 88% followed by medium and low severity groups with 85% and 79%, respectively.
CONCLUSION:
Segmentation based on DCSI may serve as a useful tool for understanding clinical outcomes and health care consumption for populations with diabetes.
Learning Areas:
Administer health education strategies, interventions and programsAdministration, management, leadership
Advocacy for health and health education
Chronic disease management and prevention
Conduct evaluation related to programs, research, and other areas of practice
Epidemiology
Learning Objectives:
Describe Diabetes Complications Severity Index (DCSI) segmentation framework derived from administrative claims that can be leveraged to study meaningful groupings of the diabetes population and associated differences in clinical outcomes, utilization, and cost.
Keyword(s): Diabetes, Health Care Costs
Qualified on the content I am responsible for because: I worked as a Regional Epidemiologist at KY Department for Public Health and in Infectious Disease branch as the Enteric Disease Epidemiologist for Kentucky. During my tenure as an Epidemiologist, I have been a co-author on Norovirus cluster investigation that was reported in CDC-MMWR. I also have worked with Govt Agency (KIPDA) to secure a Grant for Diabetes Initiatives for Region-VI in Kentucky. At Humana, I primarily work on Analytics describing Diabetes among Humana Members.
Any relevant financial relationships? Yes
| Name of Organization | Clinical/Research Area | Type of relationship |
|---|---|---|
| Humana, Inc. | Diabetes Analytics | Employment (includes retainer) |
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.