Background: Scanners are becoming widespread in Prosthetics and Orthotics, replacing plaster casting in the manufacture of some types of devices. P&O shape capture must be accurate and reliable, so the device is comfortable and reproducible between clinicians/sessions. Objectives: To map knowledge on measuring accuracy and reliability of spatial data produced from 3D scanners. Methods: The study design was a scoping review using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Studies published in or after 2010 in English with a full-text available that analyse either the accuracy/validity or reliability of human 3D scanning data within a P&O context. Sources were obtained from Pubmed, CINAHL, Scopus, Cochrane Library, Web of Science, and AMed databases on 25th March. Results: The search identified 115 studies of which 9 were included (7 experimental [4 prosthetic, 3 orthotic], 1 systematic review, 1 literature review). 7 analysed both reliability and accuracy/validity and 2 analysed reliability. High heterogeneity amongst studies’ methods, techniques, and equipment. Conclusion: Methods, techniques, and equipment used to measure accuracy/validity and reliability varied greatly though more so in the measurement of accuracy/validity. Within the studies, researchers called for more research on standardisation of measurement methods and techniques.

Background: Disruptive technology describes technology that is significantly more advanced than previous iterations, such as: 3D printing, genetic manipulation, stem cell research, innovative surgical procedures, and computer-based charting software. These technologies often require extensive overhauls to implement into older systems and must overcome many difficult financial and societal complications before they can be widely used. In a field like healthcare that makes frequent advancements, these difficulties can mean that the technology will not be utilized to its full potential or implemented at all. Objective: To determine the inhibiting factors that prevent disruptive technology from being implemented in conventional healthcare. Methods: Peer reviewed articles were gathered from Cumulative Index to Nursing and Allied Health Literature (CINAHL), Educational Resources Information Center (ERIC), Elton B. Stephens Co. Host (Ebsco Host), Medical Literature On-line (Medline), and Psychological Information Database (PsychINFO). Articles were included if written in English and focusing on technology that was or is difficult to implement. Results: Research suggests that the primary reason disruptive technology is not implemented sooner is the cost versus benefit ratio. Those technologies with extremely high benefits that greatly improve efficiency, safety, or expense are integrated relatively quickly, especially if their cost is reasonable. Secondary reasons for difficulty with integration include ethical dilemmas, extreme complexity, technical limitations, maintenance, security, and fallibility. Conclusion: Research indicates that a decrease in production cost and selling price along with removing any issues that may depreciate the technology will provide better incentives for healthcare systems to integrate disruptive technologies on a wider scale.