Preferences of diabetes patients and physicians: A feasibility study to identify the key indicators for appraisal of health care values

Abstract

BackgroundEvidence-based medicine, the Institute of Medicine (IOM) and the German Institute for Quality and Efficiency in Health Care (IQWiG), support the inclusion of patients' preferences in health care decisions. In fact there are not many trials which include an assessment of patient's preferences. The aim of this study is to demonstrate that preferences of physicians and of patients can be assessed and that this information may be helpful for medical decision making.MethodOne of the established methods for assessment of preferences is the conjoint analysis. Conjoint analysis, in combination with a computer assisted telephone interview (CATI), was used to collect data from 827 diabetes patients and 60 physicians, which describe the preferences expressed as levels of four factors in the management and outcome of the disease. The first factor described the main treatment effect (reduction of elevated HbA1c, improved well-being, absence of side effects, and no limitations of daily life). The second factor described the effect on the body weight (gain, no change, reduction). The third factor analyzed the mode of application (linked to meals or flexible application). The fourth factor addressed the type of product (original brand or generic product). Utility values were scaled and normalized in a way that the sum of utility points across all levels is equal to the number of attributes (factors) times 100.ResultsThe preference weights confirm that the reduction of body weight is at least as important for patients - especially obese patients - and physicians as the reduction of an elevated HbA1c. Original products were preferred by patients while general practitioners preferred generic products.ConclusionUsing the example of diabetes, the difference between patients' and physicians' preferences can be assessed. The use of a conjoint analysis in combination with CATI seems to be an effective approach for generation of data which are needed for policy and medical decision making in health care.

Effect of pill burden on dosing preferences, willingness to pay, and likely adherence among patients with type 2 diabetes

“…A few recently published studies examined patients’ preferences for attributes of oral antihyperglycemic agents21,32,33 using DCEs; however, we are aware of only one study that examined both patient preferences and the impact of treatment attributes on likely adherence 21. Similarly to this study, Hauber et al21 employed a DCE comprising attributes related to glucose control, side effects, and treatment-related risks and used a similar follow-up question to elicit patients’ ratings of the impact of treatment attributes on likely adherence.…”

Clinical Factors and the Decision to Transfuse Chronic Dialysis Patients

“…Conjoint analysis has been used in evaluating clinical decision-making in depression (31), rheumatology (32), spinal surgery (33), diabetes management (34), and interhospital transport of critically ill patients (35,36). Recently, conjoint analysis was used to understand patient preferences for HIV medications (37).…”

Preferences for medication attributes among patients with type 2 diabetes mellitus in the UK

“…Several approaches have been used previously to evaluate preferences associated with medication attributes including several studies of patients with T2DM [9][10][11][12][13][14][15]. One common way of assessing preferences is conjoint analysis (CA), an approach which posits that 'humans evaluate the overall desirability of a complex product based on a function of the value of its separate (yet conjoined) parts' [16].…”