Researchers: Tzahit Simon-Tuval¹, Jacob Moan-Gilad¹

Background: The implementation of next generation sequencing (NGS) in hospitals often involves multiple conflicting managerial viewpoints and constraints.

Objectives: To develop a multi-criteria-based decision tool, which considers clinical, operational and economic criteria for optimal integration of microbial NGS in hospitals.

Method: The study comprised of four stages: I. A systematic literature review; II. Interviews with experts and stakeholders (n=10); III. Structured survey among specialists and directors of microbiology laboratories (n=52). IV. An analytical hierarchy process (AHP)-based survey among similar population (n=17).

Findings: We identified three main operational models for implementing of NGS: Full In-house full outsourcing and a hybrid model in which the sequencing/analysis components alternate between in-house and outsourcing. Eight main criteria and multiple sub-criteria were identified: cost, manpower, laboratory infrastructure, bioinformatics requirements, computational infrastructure, quality control, motivations, and test goal. Manpower, costs and computational requirements were ranked as most influential on the decision. Multivariable models revealed that participants with vast experience were less likely to rank manpower as an influential criterion (p=0.014) and more likely to rank test goal as influential (p=0.110), for in-house sequencing/analysis. For the majority of criteria and most operational models, there was no difference between the rankings of participants with vast experience and others. The AHP method revealed that the most important criteria were manpower (0.410) for the in-house model, and cost (0.465) for outsourcing model.

Conclusions: We comprehensively delineated for the first time, different criteria and sub-criteria for the implementation of microbial NGS in hospitals. Our proposed weights represent the relative importance of criteria and sub-criteria and can guide decision-makers with regard to the feasible implementation of NGS in their organization, ahead of effectively implementing NGS in the clinical routine. Further research should validate the results of our study using real-world decisions to implement the technology.

Research end date: 10/2019