In 2018, Health Dialog launched a program focused on increasing medication adherence across a large Medicare Part D population. Machine-learning AI analytics (which incorporated prescription claims, condition information, social determinants of health, and other available data sets) were used to stratify the population. In addition, telephonic coaching was used to identify barriers to adherence and establish a personalized care plan to support intrinsic motivation and help patients overcome these barriers. This case study discusses the results of the program in its first nine months.
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Our Care Pathways analytics identify members earlier and help deliver comprehensive clinical interventions. We analyzed c data by condition stage and population size to determine increase in savings.
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