Future Trends in the Use of Computer

Future Trends in the Use of Computer Technology in Surgery

The rapid levels of innovation occurring in the field of Computer Assisted Surgery (CAS) are leading to significantly greater levels of accuracy, patient care success, and lower costs of outpatient surgery treatment programs for hospitals and care centers. The intent of this paper is to analyze the future direction of CAS and its implications on the quality of healthcare and its associated costs. At a strategic level, the pace of innovation in CAS-based image processing and surgical navigation continues to accelerate with forecasts showing an adoption rate over 35% or more per year through 2015 (Bohn, Korb, Burgert, 2008).

Computer-Assisted Surgery Analysis and Predictions

The combined areas of image analysis and image processing, surgical navigation, pre- and post-operation planning, 3D imagery of organs and orthopedics, and the growth of computer-assisted radiology all are revolutionizing how computing technology is used in surgery today. There also continues to be the development of patient- and treatment-based taxonomies that define optimal cure levels by patient condition (Bohn, Korb, Burgert, 2008). These taxonomies are the system of record that unifies the diverse series of computing technologies together. Within the next ten years, the scope and extent of integration to these taxonomies or systems of record will dictate the economies of surgery and medical care globally (Vendruscolo, Martelli, 2001). The system of record will also be more graphically oriented that in the past, storing visual imagery of the patient, including time series analytics and measures of their progress on key aspects of treatment programs as well (Bohn, Korb, Burgert, 2008). In essence this first innovation in CAS will be the catalyst that propels all others, as this system of record will be critical for unifying data models, serving as the basis of analytics and continued data mining to determine the best possible cure or treatment programs for patients.

The area where CAS will experience the most disruptive levels of innovation however is in translating the 3D imagery into orthopedic replacements, including joints and bones (Deshmukh, Kuthe, Chaware, Vaibhav, Ingole, 2011). 3D modeling, driven through stereo-lithography, has for decades been able to create a plastic or polymer model of any item defined through vector-based coordinates using computer-assisted design (CAD) technology (Rigelsford, 2003). Using the 3D modeling techniques in CAS-based systems available now and in the future, physician teams will be able to create replacement bones and joints within hours, streamlining surgery and reducing hospital operating costs as well. All of these factors will also be driven by a continual series of improvements in 3D modeling of complex bone structures and their related prerequisites and dependencies throughout a patients' skeletal structure (Dobbe, Du Pre, Kloen, Blankevoort, Streekstra, 2011). These advances will also make it possible to complete total knee arthroplasty within a single session, also saving thousands of dollars in incremental costs while also alleviating pain to the patient (La Palombara, Fadda, Martelli, Marcacci, 1997). All of these areas combined are considered part of the rapid prototyping technology base that is also beginning to show the potential for creating hear values and cardiovascular devise as well (Singare, Lian, Wang, Wang, Liu, Li, Lu, 2009). The use of rapid prototyping will also be predicated on how effectively the data sets, collections of data in the systems of record, and associated taxonomies used for accessing and storing them are used (Bohn, Korb, Burgert, 2008). All of these factors taken together will define the growth trajectory of CAS in the short- and long-term.