Biotechnology ; Diffusion of Innovation ; Humans ; Inventions

Diffusion of Innovation ; Humans ; Medical Oncology ; Neurology ; methods

PURPOSE: The purpose of this study is to explore factors which influence adoption, implementation and continued use of tele-healthcare systems. METHODS: Qualitative research was conducted by in-depth interviews with 17 professionals from various fields of organizations involved in developing and implementing tele-healthcare systems. Data were analysed thematically, using a conceptual model of diffusion of innovations. RESULTS: The system users were reacted positively to the 3 attributes out of 9 which decided the adoption of innovation. In addition, it is required to redesign the tele-health care system simpler and easier so that the system users can access to the system much more easily regardless of space and time limitations. From the design stage on an individual level, it is necessary to conduct detailed needs analysis and listen to users who are at the center of innovation diffusion. On an organizational level, it is necessary to actively prepare for possible problems during system implementation, educate the users and build communication channels continuously. CONCLUSION: This study has identified the factors affecting the innovation of tele-health care systems and contributed to the understanding of the operation of tele-health care systems by the diffusion of innovation theory in community health posts.
Delivery of Health Care ; Diffusion of Innovation* ; Diffusion* ; Qualitative Research ; Telemedicine

No abstract available.
Diffusion of Innovation ; Humans ; Learning Curve ; *Orthopedic Procedures/adverse effects

OBJECTIVES: The purpose of this study is to identify the role of individual innovation to demographic variables for determining IT adoption behaviors. This study also examines the effect of individual innovation on IT adoption behaviors across IT types. METHODS: To verify the invariant effect of individual innovativeness, two groups of persons working in the health care field were surveyed. The first study subject group was radiologists and their adoption of e-purchasing the second group was emergency rescue crews and their adoption of GPS. RESULTS: Adopter categories in innovations (ACI) as the measurement of individual innovation were a significant variable in both studies. Innovative adopters were more likely to use new IT tools than the majority of early adopters, and the early majority was more likely to adopt IT than the laggards. After merging the two data sets into one for testing the role of IT types as a moderator, the significance of ACI did not change, compared to the two separate analyses. In the merged data set, innovative adopters were 2.34 times more likely to be adopters than the early majority. The early majority was 2.32 times more likely to be adopters than laggards. Moreover, there were no moderating effects of IT types. Thus, there were no reversed adoption rates according to levels of ACI and demographic variables. CONCLUSIONS: ACI has invariant effects on IT adoption behaviors regardless of IT types and demographic differences. To implement a new innovation, understanding individual innovativeness will provide more sophisticated implementation strategies for health care organizations and appropriate education programs for their employees.
Adoption ; Delivery of Health Care ; Diffusion of Innovation ; Emergencies ; Humans

The increasing complexity of healthcare is accelerating the rate of specialisation in medicine, which in turn aggravates the fragmentation of care in hospitals. The hospitalist movement advocates for the return of generalist physicians to the hospital to provide general and more holistic medical care to inpatients. This can be seen as an adaptive response to care fragmentation. Starting in the mid-1990s in North America, where the impact of healthcare complexity and fragmentation has been most widely felt, the hospital movement has gained strength and spread across the continent rapidly. This paper examines the phenomenon of the hospitalist movement in the United States, Canada and Singapore. The conclusion is that variants of the hospital movement may emerge in different parts of the world as healthcare systems adapt to common global trends that drive the increasing complexity of healthcare.
Australia ; Diffusion of Innovation ; Hospitalists ; trends ; Hospitals ; Singapore ; United States

OBJECTIVES: This study was conducted to evaluate the adoption behavior of a newly developed Electronic Medical Record (EMR)-based information system (IS) at three public hospitals in Korea with a focus on doctors and nurses. METHODS: User satisfaction scores from four performance layers were analyzed before and two times after the newly develop system was introduced to evaluate the adoption process of the IS with Rogers' diffusion theory. RESULTS: The 'intention to use' scores, the most important indicator for determining whether or not to adopt the IS in Rogers' confirmation stage for doctors, were very high in the third survey (4.21). In addition, the scores for 'reduced medication errors', which is the key indicator for evaluating the success of the IS, increased in the third survey for both doctors and nurses. The factors influencing 'intention to use' with a high odds ratio (>1.5) were the 'frequency of attendance of user training sessions', 'mandatory use of system', 'reduced medication errors', and 'reduced medical record documentation time' for both doctors and nurses. CONCLUSIONS: These findings show that the new EMR-based IS was well accepted by doctors. Both doctors and nurses also positively considered the effects of the new IS on their clinical environments.
Diffusion of Innovation ; Diffusion* ; Electronic Health Records* ; Hospitals, Public* ; Information Systems* ; Korea ; Medical Records ; Odds Ratio

OBJECTIVES: Electronic detailing (e-detailing), the use of electronic devices to facilitate sales presentations to physicians, has been adopted and expanded in the pharmaceutical industry. To maximize the potential outcome of e-detailing, it is important to understand medical representatives (MRs)' behavior and attitude to e-detailing. This study investigates how information technology devices such as laptop computers and tablet PCs are utilized in pharmaceutical marketing, and it analyzes the factors influencing MRs' intention to use devices. METHODS: This study has adopted and modified the theory of Roger's diffusion of innovation model and the technology acceptance model. To test the model empirically, a questionnaire survey was conducted with 221 MRs who were working in three multinational or eleven domestic pharmaceutical companies in Korea. RESULTS: Overall, 28% and 35% of MRs experienced using laptop computers and tablet PCs in pharmaceutical marketing, respectively. However, the rates were different across different groups of MRs, categorized by age, education level, position, and career. The results showed that MRs' intention to use information technology devices was significantly influenced by perceived usefulness in general. Perceived ease of use, organizational and individual innovativeness, and several MR characteristics were also found to have significant impacts. CONCLUSIONS: This study provides timely information about e-detailing devices to marketing managers and policy makers in the pharmaceutical industry for successful marketing strategy development by understanding the needs of MRs' intention to use information technology. Further in-depth study should be conducted to understand obstacles and limitations and to improve the strategies for better marketing tools.
Administrative Personnel ; Commerce ; Diffusion of Innovation ; Drug Industry ; Education ; Humans ; Intention* ; Korea ; Marketing*

OBJECTIVES: We assessed the public acceptance of a health information exchange (HIE) and examined factors that influenced the acceptance and associations among constructs of the Technology Acceptance Model (TAM). METHODS: We collected data from a survey of 1,000 individuals in Korea, which was administered through a structured questionnaire. We assessed the validity and reliability of the survey instrument with exploratory factor analysis and Cronbach's alpha coefficients. We computed descriptive statistics to assess the acceptance and performed regression analyses with a structural equation model to estimate the magnitude and significance of influences among constructs of TAM. RESULTS: Eighty-seven percent of the respondents were willing to use the technology, and the average level of agreement with the need for the technology was 4.16 on a 5-point Likert scale. The perception of ease of use of the technology significantly influenced perceptions of usefulness and attitudes about the need for HIE. Perceptions of usefulness influenced attitude and behavioral intention to use HIE, and attitude influenced intention. Age showed a wide range of influences throughout the model, and experience with offline-based information exchange and health status also showed noteworthy influences. CONCLUSIONS: The public acceptance of HIE was high, and influences posited by TAM were mostly confirmed by the study results. The study findings indicated a need for an education and communication strategy tailored by population age, health status, and prior experience with offline-based exchange to gain public buy-in for a successful introduction of the technology.
Diffusion of Innovation ; Education ; Health Information Exchange* ; Intention ; Korea* ; Public Opinion ; Reproducibility of Results ; Surveys and Questionnaires

BACKGROUND: eHealth in the Philippines is poised to take off but adoption of eHealth applications in the country's public health sector is limited in scale.

OBJECTIVE: This paper examines the context and status of eHealth policy in the Philippines. The aim is to lay out the domains of policy issues that should be addressed for the successful implementation of eHealth in the Philippines.

METHODS: The themes and issues of policies on eHealth cited by Khoja, Durrani, Nayani and Fahim (2012) were used to describe and analyze the status of eHealth policy context in the Philippines. These are: (1) networked care, (2) interjurisdictional practice, (3) diffusion of eHealth/digital divide, (4) eHealth integration with existing systems, (5) response to new initiatives, (6) goal-setting for eHealth policy, (7) evaluation and research, (8) investment, and (9) ethics in eHealth. Documents and policies in the form of enacted laws, memoranda, implementing rules and regulations were retrieved and reviewed to answer whether or not policy themes and issues are addressed currently.

RESULTS AND CONCLUSION: Current policies in the status quo do not adequately address the issues that enable effective implementation of eHealth in the Philippines. While preconditions for eHealth to flourish such as strategic frameworks for ICT and eHealth have been established, they are inadequate in addressing licensing, diffusion of innovation, handling innovation, evaluation and research, and investment.