To date, only three TAM-related databases have been generated specifically for the study of PACS acceptance. The present study therefore adds to the small knowledge base of TAM-based PACS acceptance studies. Reviews of the TAM in healthcare-related studies (covering a variety of health technologies) show that the basic (original) model usually explains 30-40 % of IT acceptance (behavioral intention to use or behavior regarding new technology), and that its variations/extensions generally explain 40-60 % of physicians’ acceptance of new technologies [22]. The variance explained in the model here (41 %) is consistent with the range expressed in the literature.
Factors influencing user acceptance
All three antecedent constructs—PU, PEU, and change—were found to be statistically significant predictors of IT user acceptance. PU was the most important individual predictor (38 % of variation explained), followed by the change scale (4.5 %) and PEU (3.5 %). In their overview of TAM studies in healthcare, Holden and Karsh [22] discovered 16 studies that had tested the relationship between PU and the outcome variable, all of which were significant. In contrast, 7 out of 13 studies that tested the influence of PEU found it to be significantly related to the outcome variable. The apparent lesser influence of PEU on user IT behavior found for PACS users at KAMC is therefore consistent with existing studies of acceptance of various technologies in healthcare settings. In this context, this finding has been explained in previous studies by the above-average intelligence of physicians and technologists [15].
Specifically regarding PACS technology acceptance, Duyck et al. [6] using the UTAUT model found that PU was a strong determinant of physicians’ and radiologists’ behavioral intention to use PACS (overall model R2 adj. of 33 %, 21 months post-implementation), but PEU was insignificant. Duyck et al. [23] also using UTAUT discovered that PU was the best predictor of acceptance, with PEU also being a significant predictor, and the overall model R2 adj. was 37 % (all PACS-using physicians but not radiologists, 21 months post-implementation). In a related study, Duyck et al. [26] achieved an R2 adj. of 48 % for the UTAUT studying radiologists and technologists. Pare et al. [24] used the Information Systems Success model, which differs from the TAM and its variants in both the suite of independent variables used and in the ultimate dependent variable. However, in their study, 24 months after PACS implementation, PU was a significant influence on “user satisfaction” for clinicians but not for radiologists or technologists, and PEU was significant for radiologists but not for technologists or clinicians. Pynoo et al. [25] used the UTAUT and path analysis (including indirect effects on acceptance via PU and PEU), and discovered that PU influenced physician acceptance at both 4 and 16 months post-implementation, whereas PEU was insignificant at both times (although PEU was found to be important at the actual time of implementation). The multiple correlation coefficient for acceptance was 0.60 at 16 months, meaning about 36 % of the variation in acceptance was explained by the overall model.
When the present findings regarding antecedents of acceptance are also considered, it would appear that PU is much more important than PEU for PACS acceptance. The percentage of variance in user acceptance explained by the various models used in PACS studies (including this investigation) lies in a fairly tight range of 33-48 %. Although this level of explanation is quite reasonable, it seems that there is a ceiling of explanation for PACS acceptance using TAMs (including variants/extensions). Some predictors evidently remain unknown or incompletely quantified given that more than half of the variance in acceptance remains unexplained. The change construct employed in this study showed some promise as a predictor of IT acceptance, and its use could be considered in future studies.
Influence of professional user groups, gender, age, and experience
Duyck et al. [6], using the UTAUT, surveyed the acceptance of a PACS by radiologists and hospital physicians in a Belgian hospital. User acceptance ratings were higher for radiologists than for physicians, apparently because the former group experienced more benefits of the PACS and also had to use PACS more often through the working day. Duyck et al. [26] found that radiologists had higher ratings on PU, PEU, and acceptance than did technologists. However, Pare et al. [24] found similar acceptance ratings between radiologists, clinicians, and technologists. The present results show that there was no overall difference between professional user groups in PACS acceptance levels, although technologists had the lowest level of acceptance out of the five user groups surveyed. Technologists may have lower acceptance ratings as they are involved in PACS in a more limited way than are clinicians and radiologists [24], who additionally use the system for diagnostic and interventional purposes; alternatively, the training/familiarization program used (although extensive) may not have catered to their particular needs as successfully as it did for clinicians and radiologists.
Although various papers have found that age and gender are significant factors in attitudes toward IT in general, the review of Ward et al. [11] specifically on healthcare-related studies found no strong evidence for either an age or gender influence. Duyck et al. [6] found that male users rated PU more highly than did females, but it should be noted that in the UTAUT, gender is treated as a moderating influence and has no direct effect on acceptance. This study found there was no significant difference between men and women in PACS acceptance levels, or any influence of age, supporting the finding of Pare et al. [24].
Some healthcare studies have revealed positive relationships between IT acceptance and the years of experience in computer use [11]. Duyck at al. [23], using the UTAUT, discovered that the length of experience with PACS led to an overall improved attitude toward PACS. At KAMC, the length of experience using the technology had no direct influence on staff acceptance. This may reflect the particular professional groups surveyed, being radiologists and referring physicians in Duyck et al. [23] and additionally including technologists in this study, or it may be due to differences in the training/familiarization programs run at each hospital. The contrasting findings are unlikely to be due to PACS system architecture and features, as the hospitals in the respective studies both use General Electric PACSs. The very recent study of Pynoo et al. [25] found that although there was no main effect of experience on acceptance, it did show interaction effects with PU at 16 months post-implementation.
Overall, the findings in the literature (e.g. [11]) regarding professional grouping, gender, age, and experience with respect to acceptance of both PACSs and other health-related information technologies are mixed, and none of the characteristics appears to be a consistent indicator of users’ acceptance. This may partly reflect the differences between studies in the formulations of models used [15].
Successful PACS adoption
There are many factors that influence whether an IT system, including a PACS, is successfully adopted into a healthcare organization, including organizational (managerial and structural) factors, technological factors, and behavioral factors [3, 30]. User acceptance is a major factor influencing successful PACS adoption, as indicated by previous investigations (e.g., [19, 21, 27, 30]). If the technology is not used, or under-used, or mis-used, then many of the tangible and intangible benefits of PACSs [1, 2, 4, 5] relating to organizational efficiency, financial considerations, and improved patient care may not be fully realized. Resistance to IT among clinicians is well known ([3, 10, 30, 31]), and such resistance has led in too many instances to failed, prolonged, or suboptimal implementation of new systems [10]. Resistance can be traced to various problems, including poor input into managing organizational change, insufficient pre-implementation training, installation issues, and personal-level factors including physicians’ time for adopting new technology, skepticism of the reliability and benefits of new technology, and users’ IT familiarity and ability [3, 10, 15]. PACS users at KAMC benefitted from a long (14-month) period of familiarization and training prior to the “go live” date. It is likely that this was an important facet of enhancing the subsequent levels of staff satisfaction and acceptance of the PACS, and hence was an important part of successful system adoption (e.g., [7]). Ayal and Seidmann [5], in their study of PACS implementation at a hospital in Rochester, New York, found that that physician satisfaction with the PACS service post-implementation was highly correlated with satisfaction with the implementation process, suggesting that sufficient and proper training is critical in increasing the level of users’ acceptance.
The two contrasting case studies of Pare and Trudel [3] exemplify the importance of the role of staff behavior and acceptance in an institution’s successful (or otherwise) adoption of a PACS. In respect of such resistance/acceptance, the findings of this study should be regarded as very encouraging. The overall level of acceptance for PACS users at KAMC is high, as indicated by the high mean values for the model constructs (PU 4.33/5, PEU 4.15/5, and acceptance 3.86/5). Previous studies of PACS acceptance also report positive attitudes from surveyed users. Duyck et al. [6] reported 86 % of responding physicians as giving positive scores (i.e. 4/7 or better) for PU, and 98 % for PACS acceptance. Pynoo et al. [25] recorded mean scores for PU, PEU, and acceptance of 4.70/7, 5.06/7, and 6.29/7, respectively, for physicians. The present study’s mean PU and PEU scores are higher (proportionally) than reported by Pynoo et al., but the acceptance score is lower. The lower acceptance score is probably due to the technologists surveyed here, who reported lower acceptance ratings than other user groups including radiologists and clinicians.
Cultural beliefs and values are considered by some researchers to play a part in the adoption, acceptance, and use of technology [32–34]. Straube et al. [34] refer to technical, organizational, and human constraints in Arab countries concerning IT transfer, which lead to resistance to technology. Based on arguments concerning culture-specific beliefs and values in Arab countries, it might be expected that the surveyed users would exhibit lower levels of PU and acceptance than their western counterparts, and that women would show lower levels than men. Although this study did not specifically test for a cultural influence, the high levels of PU and of user acceptance and the lack of consistent differences across different types of user (e.g., male v female) suggest that acceptance of PACS does not contain a cultural dimension in this case, supporting the result of Baker et al. [35] for knowledge workers in Saudi Arabia. The current finding may reflect the fact that the radiology department staff surveyed comprised a mix of cultures and nationalities, including Americans, Australians, and Europeans, as well as Saudi nationals: the increasing global mobility of healthcare professionals may reduce/remove the influence of host cultural elements in user acceptance of PACSs, as well as that of other health IT systems. The finding may also be due to the PACS being supplied by a multinational vendor (GE), rather than by a local vendor.