## Introduction ## The objective of this scoping review is to identify the methods used in health technology assessment of precision medicine, and expand on the best practices and recommendations for the application of advanced computing tools such as artificial intelligence or machine learning. A preliminary search of PubMed, PROSPERO and Open Science Framework was conducted and no current or underway systematic reviews or scoping reviews on the topic were identified ## Review question ## What challenges are identified in health technology assessment of advanced computing tools in precision medicine and what recommendations can be derived from previous literature? ## Eligibility criteria ## **Participants:** No inclusion or exclusion criteria for the population **Concept:** Economic evaluation of prognostic and predictive companion diagnostic tools utilized in clinical decision-making **Context:** Challenges, limitations, methodologies, guidelines and recommendations ## Types of sources ## This scoping review will consider both experimental and quasi-experimental study designs including randomized controlled trials, non-randomized controlled trials, before and after studies and interrupted time-series studies. In addition, analytical observational studies including prospective and retrospective cohort studies, case-control studies and analytical cross-sectional studies will be considered for inclusion. This review will also consider descriptive observational study designs including case series, individual case reports and descriptive cross-sectional studies for inclusion. Qualitative studies will also be considered that focus on qualitative data including, but not limited to, designs such as phenomenology, grounded theory, ethnography, qualitative description, action research and feminist research. In addition, systematic reviews that meet the inclusion criteria will also be considered, depending on the research question. Text and opinion papers will also be considered for inclusion in this scoping review. ## Methods ## The search strategy will aim to identify all relevant published studies. An initial limited search of PubMed was conducted to identify relevant articles on the topic. The text words contained in the titles and abstracts of relevant articles, and the index terms used to describe the articles will be used to develop a full search strategy for MEDLINE and Scopus. The reference list of all included sources of evidence will be screened for additional studies (reference tracking). Only studies published in English will be included. Studies published since 01.01.2009 will be included. ## Selection Process ## Following the search, all identified citations will be collated and uploaded into Covidence 2020 and duplicates removed. Titles and abstracts will then be screened by two independent reviewers for assessment against the inclusion criteria for the review. Potentially relevant sources will be retrieved in full and their citation details imported into the Covidence software. The full text of selected citations will be assessed in detail against the inclusion criteria by two independent reviewers. Reasons for exclusion of sources of evidence at full text that do not meet the inclusion criteria will be recorded and reported in the scoping review. Any disagreements that arise between the reviewers at each stage of the selection process will be resolved with an additional reviewer. The results of the search and the study inclusion process will be reported in full in the final scoping review and presented in a Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for scoping review (PRISMA-ScR) flow diagram. ## Data extraction ## Data will be extracted from papers included in the scoping review by two independent reviewers using a data extraction template developed by the reviewers in Covidence. The data extracted will include specific details about the participants, concept, context, study methods and key findings relevant to the review question.