Thesis
Factors Influencing Indonesian Doctors’ Perception toward Next Generation Genomic Sequencing For Precision Medicine In Oncology
Background. Next Generation Sequencing (NGS) is a technology that possesses tremendous
potential in advancing precision medicine in oncology. However, in Indonesia, the progress of
its integration remains hampered. This research is conducted with the hope of providing
exploratory research for the general NGS maturity in Indonesia, its current level of
implementation, and future challenges from the perspective of Indonesian doctors as a major
stakeholder on the issue. Methods. This research is a mixed-method research that utilizes
quantitative statistical analysis to support qualitative interviews. Indonesian doctors were
interviewed regarding NGS in Indonesia and were then given Likert Scale questionnaires based
on the interview results and existing literature. The resulting Likert scores are then analysed
quantitatively in a model based on the Technology Acceptance Model for a more holistic view.
Results. From 25 doctors interviewed and 30 Likert Scale questionnaires, it was found that the
major factors influencing doctors’ perception of NGS in Indonesia are Knowledge, Price,
Availability, Support Structure, and Duration. These five factors can be further grouped into
Knowledge, Price, Status Quo Insufficiency, and Status Quo Efficacy. Path coefficient analysis
of the model shows no significant correlation between the constructs, however individual
Likert scale score analysis and qualitative analysis of the interview shows the Status Quo to be
sufficient, the Status Quo not efficacious, doctors perceived themselves to be knowledgeable
of NGS, Price to be an issue, and overall positive perception of NGS in Indonesia. Conclusion.
The current Status Quo of NGS implementation in Indonesia is sufficient but not ideal, with
several issues on matters of Knowledge, Price, Availability, Support Structure, and Duration.
Despite these issues, however, most doctors perceive NGS positively, seeing the inherent value
of NGS for precision medicine in Oncology.
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