A Rasch model analysis of technology usage in Minnesota hospitals

User acceptance factors of hospital information systems and related technologies: Systematic review

This study reviews the literature on the most important acceptance factors associated with Hospital Information Systems (HIS) and related technologies based on user groups' perspectives (medical staff, hospital management, administrative personnel, patient, medical student, and IT staff), which can assist researchers and hospital management to develop suitable acceptance models to improve the quality of HIS. We conducted searches in online databases with large repositories of academic studies, written in English and fully accessible by the authors. The articles being reviewed are related to health information technology (HIT), clinical information systems (CIS), HIS, electronic medical records (EMR), telemedicine or telehealth, picture archiving and communication systems (PACS), radio frequency identification (RFID), and computerized physician order entry (CPOE), where the use of most of those applications and technologies is highly integrated. A predefined string was used to extract 1,005 articles, and the results were reviewed and checked. The results of this study found 15 user acceptance factors related to HIS and related technologies that were frequently identified by a minimum of five previous studies. These factors were related to individual, technological, and organizational factors. In addition, HIS and related technologies' user acceptance factors in each user group describe different results.

Acceptance model of a Hospital Information System

PURPOSE

The purpose of this study is to develop a model of Hospital Information System (HIS) user acceptance focusing on human, technological, and organizational characteristics for supporting government eHealth programs. This model was then tested to see which hospital type in Indonesia would benefit from the model to resolve problems related to HIS user acceptance.

METHOD

This study used qualitative and quantitative approaches with case studies at four privately owned hospitals and three government-owned hospitals, which are general hospitals in Indonesia. The respondents involved in this study are low-level and mid-level hospital management officers, doctors, nurses, and administrative staff who work at medical record, inpatient, outpatient, emergency, pharmacy, and information technology units. Data was processed using Structural Equation Modeling (SEM) and AMOS 21.0.

RESULTS

The study concludes that non-technological factors, such as human characteristics (i.e. compatibility, information security expectancy, and self-efficacy), and organizational characteristics (i.e. management support, facilitating conditions, and user involvement) which have level of significance of p<0.05, significantly influenced users' opinions of both the ease of use and the benefits of the HIS. This study found that different factors may affect the acceptance of each user in each type of hospital regarding the use of HIS. Finally, this model is best suited for government-owned hospitals.

CONCLUSIONS

Based on the results of this study, hospital management and IT developers should have more understanding on the non-technological factors to better plan for HIS implementation. Support from management is critical to the sustainability of HIS implementation to ensure HIS is easy to use and provides benefits to the users as well as hospitals. Finally, this study could assist hospital management and IT developers, as well as researchers, to understand the obstacles faced by hospitals in implementing HIS.

Rasch validation of the SF-36 for assessing the health status of Korean older adults

[Purpose] To verify, using Rasch analysis, the applicability of the 36-Item Short Form Health Survey (SF-36) to elderly Koreans, as this instrument would be useful for determining elderly individuals’ overall performance and providing them with health information. [Subjects and Methods] The SF-36 was administered to a sample of 510 individuals aged over 60 living in the Seoul and Gyeonggi areas of South Korea. When testing for goodness-of-fit, we considered items with infit and outfit indexes of over 1.30 or less than 0.70 to be incongruent. SF-36 factors that contained over three items, including physical functioning, role limitations (physical and emotional), mental health, vitality, and general health, were analyzed. Each factor was examined through step calibration of the response categories in the probability curve. [Results] The response categories were found to be appropriate because the adjustment values of each factor increased. We found five items in physical functioning, two items in role limitation–emotion, one item in mental health, and one item in general health to be incongruent; all items in the role limitation–physical and vitality factors were congruent. [Conclusion] We conclude that the SF-36 could be revised to more accurately measure the health status of elderly Koreans.

Healthcare technologies, quality improvement programs and hospital organizational culture in Canadian hospitals

Background

Healthcare technology and quality improvement programs have been identified as a means to influence healthcare costs and healthcare quality in Canada. This study seeks to identify whether the ability to implement healthcare technology by a hospital was related to usage of quality improvement programs within the hospital and whether the culture within a hospital plays a role in the adoption of quality improvement programs.

Methods

A cross-sectional study of Canadian hospitals was conducted in 2010. The sample consisted of hospital administrators that were selected by provincial review boards. The questionnaire consisted of 3 sections: 20 healthcare technology items, 16 quality improvement program items and 63 culture items.

Results

Rasch model analysis revealed that a hierarchy existed among the healthcare technologies based upon the difficulty of implementation. The results also showed a significant relationship existed between the ability to implement healthcare technologies and the number of quality improvement programs adopted. In addition, culture within a hospital served a mediating role in quality improvement programs adoption.

Conclusions

Healthcare technologies each have different levels of difficulty. As a consequence, hospitals need to understand their current level of capability before selecting a particular technology in order to assess the level of resources needed. Further the usage of quality improvement programs is related to the ability to implement technology and the culture within a hospital.