Pharmacogenomics holds promise as a critical component of precision medicine. Yet, the use of pharmacogenomics in routine clinical care is minimal, partly due to the lack of efficient and effective use of existing evidence. This paper describes the design, development, implementation and evaluation of a knowledge-based system that fulfills three critical features: a) providing clinically relevant evidence, b) applying an evidence-based approach, and c) using semantically computable formalism, to facilitate efficient evidence assessment to support timely decisions on adoption of pharmacogenomics in clinical care. To illustrate functionality, the system was piloted in the context of clopidogrel and warfarin pharmacogenomics. In contrast to existing pharmacogenomics knowledge bases, the developed system is the first to exploit the expressivity and reasoning power of logic-based representation formalism to enable unambiguous expression and automatic retrieval of pharmacogenomics evidence to support systematic review with meta-analysis.
Abstract Background Pharmacogenomics (PGx) was one of the first genomics applications to hold promise in precision medicine. The cost-effectiveness of PGx has been estimated for many disease states, with the strongest evidence supporting the use of PGx-guided testing to inform prescribing for cardiovascular diseases. Most studies do not consider the presentation of test results in clinical workflow using a clinical decision support (CDS) system. We previously developed a cost model that found that implementation costs of a PGx-CDS system may constitute a non-trivial proportion of the cost of a PGx program. We recently extended that model to include clinical and cost-effectiveness outcomes, using clopidogrel and warfarin as prototypes. In contrast to CDS that occurs at the level of the individual patient, our approach delivers “administrative decision support”, which can help leaders make informed decisions about the programmatic costs of PGx-CDS implementation. In this manuscript, we describe our efforts to develop an interactive version of our model and host it on a publicly available, interactive web platform. We built the web application of the PhaRmacogEnomics ClInical Support Economic Value (PRECISE-Value) model using shiny/shinydashboard packages in the R software environment. We incorporated user defined, customizable input values expected to differ between health-systems: population size, age/race distribution, number of patients tested, and information technology costs. Dynamic, user manipulation of these values reveals the designated outcomes of adverse drug events and deaths averted, costs, and an incremental cost-effectiveness ratio. Summary and detail tabs, a data dictionary and a cost-effectiveness primer are provided. Six PGx decision makers tested and provided feedback on our web application. Results Users suggested the application is easy to use and accomplishes the stated goals of presenting useful information for decision-makers. Given the prevalence of PGx test panels, all panel members expressed the desire to add additional drug-gene pairs and further tailor inputs by health-system-specific parameters. Conclusions Our interactive, web-based application of our prototype model of the cost-effectiveness of implementing a PGx-CDS system for clopidogrel and warfarin was deemed useful by an expert panel for informing decision makers as they consider the value of implementing a CDS program based on PGx test results.
Background and ObjectiveAdvanced analytic methods for synthesizing evidence about complex interventions continue to be developed. In this paper, we emphasize that the specific research question posed in the review should be used as a guide for choosing the appropriate analytic method.MethodsWe present advanced analytic approaches that address four common questions that guide reviews of complex interventions: (1) How effective is the intervention? (2) For whom does the intervention work and in what contexts? (3) What happens when the intervention is implemented? and (4) What decisions are possible given the results of the synthesis?ConclusionThe analytic approaches presented in this paper are particularly useful when each primary study differs in components, mechanisms of action, context, implementation, timing, and many other domains.
