Lack of clinical practice guideline to optimize patient care by making an evidence-based decision from reviewing evidence and the benefit-risk assessment of Complementary and Alternative Medicine (CAM) use in patients with diabetes has found worldwide. The purpose of this study is to develop a guideline-based decision algorithm for assessing the benefit-risk of CAM use in diabetes and test the reliability and validity of this algorithm.
Methods:
The Delphi-Analytic Hierarchy Process (AHP) method was used to establish a consensus-based decision algorithm with the following steps: 1) to discuss and vote on each recommendation within the structured consensus process; 2) to rate indicators and criteria to be considered in the benefit-risk assessment of CAM use; 3) to reach consensus on each recommendation and important criteria for the benefit-risk assessment; 4) to build up an efficient mode decision algorithm in optimizing choice of care options on CAM use; and 5) to complete consensus-based CPG for the assessment and management of CAM use in diabetes. We performed a three-round modified Delphi study to prioritize the criteria for assessment and management of CAM use in diabetes and then achieve consensus of panel member’s opinion on guideline-based decision algorithm. A total of 26 experts, including academics, diabetic physicians, diabetic dietitian, and diabetic nurses was anonymously completed the survey. The analytic hierarchy process was undertaken for the data collection and analysis.
Results:
The five domains with 18 criteria regarding the benefit-risk assessment of CAM use in diabetes were identified. The most important domain was the safety of CAM, including side effect, contraindication and medical compliance. Other sequential domains were patient factors, utility factors, medical environment factors, and product factors . The consistency and consensus is acceptable as the principal eigenvalue (λmax= 5.041) was equal to the number of comparisons and both of consistency index (CI= 0.01) and Consistency Ratio (CR= 0.009) were less than 0.1.
Conclusion:
The decision making accuracy of healthcare professionals depend largely on the required systematic consideration of decision criteria and evidence available to inform them; therefore, the effectiveness and comprehensiveness of guideline-based decision algorithm providing support for professionals are extremely helpful in the process of their decision making on CAM use in diabetes management.