Early cost estimating model for new bioabsorbable orthopedic implant candidates: A theoretical study

An early health technology assessment (HTA) study was performed to assess the need for developing a new bioabsorbable implant for the treatment of specific orthopedic injuries. The Anterior Cruciate Ligament Reconstruction (ACLR) procedure was selected based on the need and potential impact of bioabsorbable implants in the treatment of ACL injuries. The economic model considers the possible health events after an ACLR (failures and other complications such as stiffness and pain). A decision tree approach was used, and several sensitivity analyses were performed using a Monte Carlo simulation. A cost estimating model was applied comparatively for currently available metal and bioabsorbable implants against a potential new bioabsorbable implant with improved performance. A reduction in stiffness and pain symptoms were considered as targets for these new implants performance, with reduced inflammation resulting from the use of materials with appropriate biological and mechanical properties. The current study estimates that, under the assumptions made, the introduction of a new bioabsorbable implant in ACLR surgeries may generate yearly cost savings. The model estimates positive cost-benefits of the new implant when it reduces the probability of failure by more than 30%, or reduces at least 14% the probability of complications of an inflammatory nature. The development of a new bioabsorbable orthopedic implant for ACLR is encouraged by this study identifying the need for new bioabsorbable implants with improved biological and mechanical performance. The results of this early HTA have made it possible to anticipate design needs and objectives for the research and development of new orthopedic bioabsorbable implants

Mobile Technology: The Wave of the Future to Improve Healthcare?

Mobile devices (e.g., smartphones, personal digital assistants, and tablets) are evolving rapidly and growing exponentially in multiple facets around the globe. Specifically, mobile devices can be used as audio and video chat, reference guide, training tool, handoff facilitation, and decision support. Undoubtedly, there are clear advantages of leveraging this technology including automatic updates, portable and unobtrusive access to data, and time savings for documentation allowing clinicians more time for patient care. However, innovative technology brings new yet critical obstacles to overcome (e.g., usability and security). Thus, the current panel is designed to gather leading human factors and medical experts in the fields of clinical care, system design, and human-system interaction to provide their insight and perspective on the following question: What contributions can human factors science and medical experts combine to bring to bear on the development, implementation, and evaluation of mobile-based technology

Organization and Representation of Patient Safety Data: Current Status and Issues around Generalizability and Scalability

Recent reports have identified medical errors as a significant cause of morbidity and mortality among patients. A variety of approaches have been implemented to identify errors and their causes. These approaches include retrospective reporting and investigation of errors and adverse events and prospective analyses for identifying hazardous situations. The above approaches, along with other sources, contribute to data that are used to analyze patient safety risks. A variety of data structures and terminologies have been created to represent the information contained in these sources of patient safety data. Whereas many representations may be well suited to the particular safety application for which they were developed, such application-specific and often organization-specific representations limit the sharability of patient safety data. The result is that aggregation and comparison of safety data across organizations, practice domains, and applications is difficult at best. A common reference data model and a broadly applicable terminology for patient safety data are needed to aggregate safety data at the regional and national level and conduct large-scale studies of patient safety risks and interventions