Measuring aggregated clinical IT is important in order to analyze the effect of IT on hospital outcomes. Because hospitals produce multiple products using multiple IT systems, it is necessary to measure clinical IT systems accurately and aggregately. This study used HIMSS data to create a CITA score after using FA to measure the degree of clinical IT use. This study found that most hospitals were adopting a basic system, such as a laboratory and pharmacy information system, and a few were installing CPOE and PACS, or an advanced one. This study result indirectly suggests an important implication for future studies. Evaluating the level of clinical IT use of healthcare organizations may be better evaluated by determining whether or not they had an advanced clinical IT system, such as COPE or PACS.
The study results also show that some clinical IT systems had similar characteristics. LIS, OC/R, PIS, RIS, and SIS could be grouped into one type of system with common characteristics and CPOE and PACS in another. This study got the result of four groups, although it could be less than or more than four groups. It is necessary to study further how these four groups differ from each other and how they affect health outcome or organizational performance differently.
An interesting finding is that IT systems in each level are adopted consecutively. This finding is exactly in line with several theoretical arguments [20
]. Theoretical argument says that there are early adopters and laggards to the advanced technologies. Depending on hospital characteristics, some would adopt CPOE or PACS early, and others would not.
This study also found that the level of clinical IT adoption differs in degree by hospital characteristics. Teaching status, ownership such as profit versus non-profit status, and bed-size of hospitals were closely related to clinical IT adoption status measured with a proxy variable of CITA score. Teaching hospitals, not-for-profit hospitals, and hospitals with large bed-size had higher clinical IT adoption levels, which is consistent with the findings many other studies [2
The study is limited in generalizability. First, it is a cross sectional study. Therefore, we need to be cautious when applying this CITA score to a different year. Second, only acute care hospitals were sampled. Thus, the CITA score may vary if other hospitals (i.e., long-term care and critical access hospitals) were included. Third, an arbitrary weight was attributed in each category. Therefore, the CITA score will be different with different weight. However, for comparison, we need ordinal scores which rank hospitals by score. Even though we applied various weights, similar results were obtained in score order.
Overall, this paper suggests that different IT systems have different adoption patterns. Therefore, aggregated IT systems should be used to explain technology acquisition and utilization in hospitals.