The purpose of this randomized controlled trial (RCT) study is to examine the extent that financial incentives when combined with diabetes evidence-based practices, improve self-management and biometric measures for adult diabetic Medicaid recipients with an HbA1c of ≥ 6.5 at enrollment. The study will also evaluate the cost-effectiveness of the program. Specific Aims: 1. Evaluate whether financial incentives for completing American Diabetes Association (ADA) recommended tests, exams, health education, biometric outcome goals, and vaccinations will improve primary biometric outcomes. 2. Evaluate whether financial incentives for completing ADA recommended tests, exams, health education, biometric outcome goals, and vaccinations will improve diabetes patients' self-management as assessed by Summary of Diabetes Self-Care Activities Measure (SDSCA) and 36-Item Short Form Health Survey (SF36v2). 3. Evaluate the extent to which financial incentives for healthy behaviors reduce the cost of health care utilization.
Diabetes is the seventh leading cause of death in the United States (OECD 2013). It is also known that certain populations are at greater risk for diabetes. In Hawaii, diabetes disproportionally affects Native Hawaiians and Pacific Islanders as they are three times more likely to be diagnosed with diabetes. In addition, in 2010 the U.S. Department of Health and Human Services Office of Minority Health reported that Native Hawaiians/Pacific Islanders in Hawaii were 5.7 times as likely as Caucasians living in Hawaii to die from diabetes(Office of Minority Health, 2010). In order to address the challenges that chronic diseases impose on individuals and the health care system the Centers for Medicare \& Medicaid Services (CMS) is assessing the impact of incentivizing patients to increase self-care and disease management. Previous studies have demonstrated that monetary incentives have been associated with an improvement in behavioral outcomes, most notably when the incentive is received immediately following the targeted behavior (Volpp, K.G., et.al., 2008; Mitchell, M.S., et.al., 2013). Cahill et al. (2008) showed that economic incentives were tied to smoking cessation and led to a decrease in relapse within a year. Our study seeks to build on these findings and determine whether financial incentives may provide a way to improve diabetes self-management. Data: Electronic data (Labs, Outcomes) - January 1st, 2013 through December 31, 2015 Electronic data (Claims) - January 1st, 2011 through December 31, 2015
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
320
This intervention will examine the effects of incentives on improving adult diabetic Medicaid beneficiaries' health outcomes and reducing associated costs through healthy behavior changes in their diabetes self-management. Incentives focus on improving self-management of diabetes, compliance with ADA recommended preventive, treatment and management measures, primary biometric measures of diabetes, and eliminating barriers to a healthy lifestyle
Kaiser Permanente Hawaii
Honolulu, Hawaii, United States
Changes in HbA1c From Baseline to the End of Intervention (December 2015)
Changes in Hemoglobin A1c from baseline to end of study. Change = (End of Intervention score - Baseline score)
Time frame: Baseline to end of intervention - 12 months minimum to 19 months maximum due to rolling enrollment
Changes in Systolic Blood Pressure From Baseline to the End of Intervention (December 2015)
Changes in systolic blood pressure from baseline to end of study. Change = (End of Intervention score - Baseline score)
Time frame: Baseline to end of intervention - 12 months minimum to 19 months maximum due to rolling enrollment
Changes in Diastolic Blood Pressure From Baseline to the End of Intervention (December 2015)
Changes in diastolic blood pressure from baseline to end of study. Change = (End of Intervention score - Baseline score)
Time frame: Baseline to end of intervention - 12 months minimum to 19 months maximum due to rolling enrollment
Changes in Total Cholesterol From Baseline to the End of Intervention (December 2015)
Changes in total cholesterol from baseline to end of study. Change = (End of Intervention score - Baseline score)
Time frame: Baseline to end of intervention - 12 months minimum to 19 months maximum due to rolling enrollment
Changes in Triglycerides From Baseline to the End of Intervention (December 2015)
Changes in triglycerides from baseline to end of study. Change = (End of Intervention score - Baseline score)
Time frame: Baseline to end of intervention - 12 months minimum to 19 months maximum due to rolling enrollment
Changes in LDL From Baseline to the End of Intervention (December 2015)
Changes in LDL from baseline to end of study. Change = (End of Intervention score - Baseline score)
Time frame: Baseline to end of intervention - 12 months minimum to 19 months maximum due to rolling enrollment
Changes in HDL From Baseline to the End of Intervention (December 2015)
Changes in HDL from baseline to end of study. Change = (End of Intervention score - Baseline score)
Time frame: Baseline to end of intervention - 12 months minimum to 19 months maximum due to rolling enrollment
Changes in Health Utilization Cost Before and During Intervention - Amount Paid by Service Providers
Changes of total cost expenditures including emergency room use and hospitalizations in the intervention and control groups before and during intervention.
Time frame: Before intervention (3 years prior to baseline) and during intervention (2 years from baseline to end of intervention)
Change From Baseline to End of Intervention (December 2015) in General Diet Subscale of The Summary of Diabetes Self-Care Activities (SDSCA) Measure
SDSCA is a validated, self-reported measure assessing the average # of days the recommended diabetes self-care activities are performed over the past 7 days in the areas of general diet, specific diet, exercise, blood-glucose testing, and foot care at baseline, mid, and end of intervention. Possible scores range from 0 to 7 days. Change = (End of Intervention Score - Baseline Score)
Time frame: Baseline to end of intervention - 12 months minimum to 19 months maximum due to rolling enrollment
Change From Baseline to End of Intervention (December 2015) in Physical Component Summary Measure of the Short Form (SF-36v2) Health Survey
The SF-36v2 is validated, self reported short-form health survey used to assess changes over time in the well-being of participants. It consists of 2 component summary measures that further summarize 8 health domain scales. The Physical Component Summary (PCS) measure is derived from domain scales of Physical Functioning (10 items), Role-Physical (4 items), Bodily Pain (2 items), and General Health (5 items). Scores of component summary measures and health domain scales range from 0 to 100 with higher scores indicating better outcomes. Norm-based scoring was used so that scores for each health domain scale and component summary measure have a mean of 50 and standard deviation of 10 based on the 2009 U.S. general population. The SF-36v2 was used to assess participants' health and wellbeing at baseline, mid, and endpoint of intervention. Change = (Midpoint Score - Baseline Score)
Time frame: Baseline to end of intervention - 12 months minimum to 19 months maximum due to rolling enrollment
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