Digitalization in MedTech: Understanding the Impact on Total Knee Arthroplasty - Max Lorenz; Patrick Reinhard; Thomas Spring (Universität St.Gallen, School of Medicine, Lehrstuhl für Management im Gesundheitswesen, 2021)
Digital Technologies (DTs) in healthcare are of growing relevance for different actors along the patient journey. This paper breaks down the complex landscape of digitalization by focusing on the Total Knee Arthroplasty (TKA). It aims to identify today's technologies and the most promising future trend, assessing the impact on the respective stakeholders. To answer these questions, a structured literature review (SLR) was conducted combining the search term digital AND knee AND replacement with journey OR value OR trend. This resulted in 39 peer-reviewed articles for in-depth analysis. In addition, a qualitative assessment was carried out based on 27 semi-structured interviews (SSI) with six stakeholder groups (patients, surgeons, physiotherapists, industry experts, insurance representatives, regulators) along the patients' TKA journey. The SLR revealed five clusters (3D Printing, Big Data, Wearables, Virtual Healthcare, Robotics) as most recurrent DTs within TKA. The SSIs confirmed that all five clusters are relevant and recognised today. Big Data is considered by the stakeholders to be the most promising DT in the future because of its power to interconnect the other technologies and thereby improve health outcomes. Among the different stakeholder groups, the effect of DTs on their individual roles were perceived differently. Regulatory hurdles and cost-benefit uncertainties were determined to be the most prominent obstacles on the establishment of DTs. Improvements in patient outcomes is the principal gain from utilizing DTs throughout the patient journey. However, the benefits of switching to DTs require convincing scientific evidence to promote acceptance by all stakeholders in a value-based healthcare system.
Keywords: I10; I11; I19; 650; Digital Technologies; Value-Based Healthcare; TKA; Knee Replacement; Big Data; Patient Journey