Study: Model helps predict PACS upgrade benefits
The Task-Technology Fit (TTF) model developed by Dale L. Goodhue, PhD, is a valid tool to predict the utilization and perceived net benefits of a PACS upgrade, according to a case study published in the December issue of the Journal of Digital Imaging. The researchers, including Luigi Lepanto, MD, of the University of Montreal, and colleagues also found that utilization alone was not predictive of net benefits.

“Goodhue argues that an information technology must not only be utilized, but must also be a good fit with the task supported in order to have a beneficial impact on performance,” wrote the authors. “The [TTF] model developed by Goodhue sought to study the relationship between information technology and individual performance.”

An 800-bed, university hospital undergoing a PACS upgrade was used for the case study. The hospital’s initial PACS had been in place eight years, and was updated in mid-2009. The authors administered a questionnaire to radiologists, which had 45 respondents, and also conducted interviews with developers involved in the upgrade who were asked to predict impact and TTF.

Results showed that radiologists did not deem the upgrade a success and identified only a moderate fit between the PACS enhancements and their tasks. Developers incorrectly predicted that organization and, to a lesser extent, interpretation would see the most impact from the upgrade, with a neutral impact in the area of analysis. Users, however, perceived a high impact in all three areas: organization, interpetation and analysis.

“The combination of a moderate fit and an underestimation of the potential impact of changes in the PACS likely explain the low score for perceived net benefits,” wrote the authors. “Considering the time and investment a PACS provider can devote to product development, it is noteworthy that the appreciation of users in this study fell well short of that predicted by the developers.”

Lepanto et al noted that previous studies of PACS implementation have been limited to initial implementation, with none focused on a PACS undergoing a significant upgrade. Since experience and familiarity with the existing system will play a role in user response, evaluations of the success of an upgrade will differ from evaluations of initial implementations.

The authors added that different user sub-groups rated the impact of the upgrade differently. Radiologists who interpreted a large number of studies of lesser complexity gave the highest score for impact and the lowest score for perceived net benefit compared with radiologists who interpreted a smaller number of more complex studies. These different reactions led the authors to conclude that it is important to take individual characteristics of users into account.

“In the context of a technology that is rapidly evolving, there needs to be an alignment of what users perceive as a good fit and the functionality developers incorporate into their products,” they wrote.