Diabetes Clinical Trial
Official title:
Personalized Decision Support for Older Patients With Diabetes
The purpose of this study is to determine the impact of web-based personalized decision
support on:
1. Patient awareness of treatment goal options and ability to articulate their goals of
diabetes care.
2. Provider awareness of patients' clinical status (e.g. life expectancy) and treatment
preferences.
3. Individualization of care plans in accordance with geriatric diabetes guidelines.
In 2003, the first geriatric diabetes care guidelines were published that encouraged older
patients and their providers to consider less intensive glucose control goals (HbA1C <8%)
among frail, older patients with limited life expectancy, while continuing to pursue
intensive glucose control (HbA1C <7%) among relatively healthy older patients. The
guidelines also emphasized the importance of cardiovascular prevention, encouraged routine
screening for geriatric syndromes that can influence treatment decisions (i.e., polypharmacy
and falls), and advised providers to acknowledge patients' preferences when making treatment
decisions.
These guidelines represent a conceptual advance in the care of older diabetes patients;
however, there has been little effort to implement and evaluate these recommendations in a
practice setting. This may be partially due to the fact that many of the recommendations are
difficult to carry out in busy clinical practices without sophisticated decision support
tools. Determining whether an older patient will benefit from intensive glucose control is a
complex cognitive task requiring simultaneous consideration of multiple, sometimes
contradictory, clinical criteria (e.g. advanced duration of diabetes and limited life
expectancy). Completing this task accurately may only be possible with computer simulation
models.
Along with this barrier to implementing care guidelines, there is also no consensus on how
to elicit patient preferences in the setting of chronic disease management or how to account
for these views in the decision-making process. To overcome these challenges, we developed a
web-based Geriatric Diabetes Decision Aid (GDDA) which combines a decision analytic model of
diabetes complications with the latest prognostic tools from geriatrics.
This personalized decision support tool will encourage the individualization of diabetes
care among older patients by educating patients on diabetes, delivering prognostic
information to providers, providing personalized data on the risks and benefits of diabetes
care to patients and providers, and eliciting the treatment preferences of patients. In this
proposed set of studies, we developed the GDDA with the input of patients and providers and
assessed its impact through individual interviews.
The findings from this series of studies will be important for establishing the feasibility
of using the GDDA in practice, and providing estimates of the intervention's effect on
processes of care for power calculations for a future large scale randomized controlled
trial. This pilot randomized controlled trial will be one of the first trials to formally
examine new care recommendations for the growing population of older patients living with
diabetes.
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Allocation: Randomized, Intervention Model: Parallel Assignment, Masking: Single Blind (Subject)
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