Automated Triage in Digital Primary Care : Assessing the Potential of Using Multi-Criteria Decision-Making Models

Abstract: The increasing global deficit of healthcare resources makes efficiency improvements in the healthcare industry a complete necessity to assure safe and available healthcare for everyone. Digitalization is expected to play a fundamental role in this transition and digital primary healthcare providers have in recent years developed into a substantial part of the Swedishprimary care sector. Several of those have built solutions for automated triage, where the role of a triage officer in traditional primary care is replaced by an automated process, in which an triage algorithm directly refers the patient to the appropriate level of care. Despite the rise of digital healthcare providers and automated primary care triage systems in particular, research on the implications of automating the triage process in primary healthcare is scarce. This study aims to assess the potential of using MCDM models for automated triage in digital primary care, by conducting a single case study at one of the leading digital healthcare providers. The study is separated into two phases. In phase one, interviews are conducted to qualitatively determine what set of factors to include in an automated MCDM triage model.In phase two, the resulting model is simulated to evaluate the performance compared to the traditional triage model in which all patient journeys start with an initial nurse meeting. The study shows that an automated MCDM triage model can improve cost efficiency in terms of clinician salary costs and productivity in terms of fewer consultations per patient, compared to the traditional triage model. However, the traditional triage model is shown to be more efficient in terms of only utilizing doctor resources for patients in absolute need of doctor care.