Use of a Computer-Assisted Decision Support (CADS) System in Management of Patients With Type 2 Diabetes (CADS)
Recruitment status was Not yet recruiting
|Study Design:||Allocation: Randomized
Endpoint Classification: Safety/Efficacy Study
Intervention Model: Parallel Assignment
Masking: Open Label
Primary Purpose: Supportive Care
|Official Title:||The Use of a Computer-Assisted Decision Support (CADS) System to Improve Outcomes in Patients With Type 2 Diabetes|
- Improved glycemic control as determined by A1C in a population of patients with inadequately controlled type 2 diabetes mellitus. [ Time Frame: One year ] [ Designated as safety issue: Yes ]The primary purpose of this 12-month, open, "cluster-randomized" trial study is to determine whether the use of a Computer Assisted Decision Support (CADS) System by primary care providers (PCPs) for their patients with type 2 diabetes mellitus (T2DM) changes the quality of care relative to a "usual care" group in terms of objective outcome measures of glycemic control (e.g., A1C, mean blood glucose, frequency of hypoglycemic episodes) and in terms of subjective ratings by patients.
- Blood pressure [ Time Frame: 1 year ] [ Designated as safety issue: No ]Blood pressure (BP) and lipid levels will change over one year in those patients whose health care providers use CADS.
- Lipid levels [ Time Frame: 1 year ] [ Designated as safety issue: No ]This study will determine whether the patients of CADS-enabled providers are more likely to improve specific diabetes-related co-morbidities that contribute to the development of the microvascular and macrovascular complications of diabetes i. Lipid profiles ii. Blood pressure
- Number of major and minor hypoglycemic episodes in the intervention and control groups. [ Time Frame: 1 year ] [ Designated as safety issue: Yes ]The study will determine whether there is a decrease in the number of major and minor hypoglycemic episodesin the patients of CADS-enabled providers compared to patients receiving usual care.
- Satisfaction with treatment and quality of life. [ Time Frame: 1 year ] [ Designated as safety issue: No ]This study will determine whether there is an improved satisfaction with treatment and quality of life for patients with DM based on the results of the Diabetes Treatment Satisfaction Questionnaire (DTSQ).
|Study Start Date:||July 2011|
|Estimated Study Completion Date:||October 2012|
|Estimated Primary Completion Date:||July 2012 (Final data collection date for primary outcome measure)|
Other: Computer Assisted Decision Support
Program to provide recommendations for achieving glycemic control in poorly controlled patients with T2 diabetes.
Diabetes accounts for an enormous fraction of the cost of health care in the United States and presents a major burden on Military Medical Facilities for care of retirees and dependents. There are insufficient endocrinologists and other diabetes specialists to manage all patients with diabetes mellitus (DM) and a significant fraction of these patients have less than optimal control (hemoglobin A1C's [A1Cs] over 7%). Multiple barriers prevent the necessary improvement in glycemic control that would result in savings in lives and costs. The implementation of a telemedicine and web-based approach for patients to send their blood glucose data which, when combined with relevant laboratory, pharmacy, and A1C targets as set individually for each patient by the Primary Care Physician (PCP), triggers a clinical decision support system (DSS) for the providers can be expected to improve quality of care and efficiency of care. The computer assisted decision support (CADS) system has been integrated with the Comprehensive Diabetes Management Program (CDMP), a web-based, multi-platform, interactive patient and provider tool which is currently operative in the Walter Reed Health Care System (WRHCS), Wilford Hall Medical Center (WHMC) at Lackland Air Force Base (AFB), and five community clinics affiliated with the University of Hawaii (UH). This existing infrastructure permits CADS to be tested in a multiple sites that are geographically diverse with diverse patient populations.
This study will test the safety and efficacy of CADS as used by PCPs in a multi-site, ethnically and geographically diverse study in a 12-month, open, prospective, cluster-randomized, controlled clinical trial. The specific aims of the study are to: (1) monitor the impact of the intervention on: a) measures of glycemic control, b) the number of diabetes -related hospitalizations and emergency room visits, c) the control of co-morbidities, hyperlipidemia and hypertension, d) the number of clinic visits, e) the change in the patients' quality of life as a result of the intervention; and (2) evaluate the PCPs' satisfaction with the technology.
We will employ a cluster-randomized, controlled, clinical trial involving 30 PCPs who will each recruit approximately 19 patients from their respective geographic site. After completion of recruitment, PCPs and their patients will be randomly assigned to 1 of 2 "treatment" categories: CADS, or "Usual Care". Input data for use by the CADS system will come from the electronic medical record (laboratory and pharmacy data) and from the PCP who will set goals for each individual patient's glycemic control. Patients will upload blood glucose data through a modem to a password-protected, secure server at least every 2 weeks and receive modification in their treatment regimen at least every three months from their PCP, based in part on the recommendations provided by the CADS system to the PCP. We will compare quantitative outcome measures of glycemic control (the primary outcome is the change in the patient's A1C), blood pressure, and lipid levels from the two treatment groups. In addition, subjective qualitative data from the patients and providers will be obtained.
Please refer to this study by its ClinicalTrials.gov identifier: NCT01382264
|Contact: Robert A. Vigersky, MDemail@example.com|
|United States, District of Columbia|
|Walter Reed Army Medical Center||Not yet recruiting|
|Washington, District of Columbia, United States, 20307|
|Principal Investigator: Robert A Vigersky, MD|