Modeling the Longitudinality of User Acceptance of Technology with an Evidence-Adaptive Clinical Decision Support System

This paper presents multiple innovations associated with an electronic health record system developed to support evidence-based medicine practice, and highlights a new construct, based on the technology acceptance model, to explain end users’ acceptance of this technology through a lens of continuous behavioral adaptation and change. We show that this new conceptualization of technology acceptance reveals a richer level of detail of the developmental course whereby individuals adjust their behavior gradually to assimilate technology use. We also show that traditional models such as technology acceptance model (TAM) are not capable of delineating this longitudinal behavioral development process. Our TAM-derived analysis provides lens through which we summarize the significance of this project to research and practice. We show that our application is an excellent exemplar of the “end-to-end” IS design realization process; it has drawn upon multiple disciplines to formulate and solve challenges in medical knowledge engineering, just-in-time provisioning of computerized decision-support advice, diffusion of innovation and individual users’ technology acceptance, usability of human-machine interfaces in healthcare, and sociotechnical issues associated with integrating IT applications into a patient care delivery environment

Physician’s Usage Of Mobile Clinical Applications In A Community Hospital: A Longitudinal Analysis Of Adoption Behavior

It is widely believed that mobile clinical information systems can facilitate patient care, increase treatment capacity, reduce healthcare costs, and improve efficiency. Yet, there is limited research to substantiate these claims in healthcare delivery settings, partly due to lack of widespread adoption and use. This study summarizes our results on the adoption and usage trends in a community hospital which deployed several mobile clinical applications for daily patient care. We analyze twenty-two months of usage data to understand trends in physicians’ adoption and use of specific mobile applications. Applying a novel, semi-parametric, group-based, statistical methodology, we obtain developmental trajectories depicting how usage evolves from initial ‘trial’ adoption to long-term institutionalization. We examine this longitudinal developmental pattern to understand how users can be clustered and profiled, and provide insights indicating that the potential impact of social influence needs to be further explored to develop new approaches to facilitate adoption

Understanding Physicians' Adoption Of Electronic Medical Records: Healthcare Technology Self-Efficacy, Service Level And Risk Perspectives

Most developed countries across the globe are deploying electronic medical record (EMR) as one of the most important initiatives in their healthcare policy. EMR can not only reduce the problems associated with managing paper medical records but also improve the accuracy of medical decisions made by physicians and increase the safety of patients. Considering that physicians are the primary users of EMR, their willingness to use EMR is a critical success factor for EMR implementation in a hospital. This study aims to extend an individual-level information technology adoption model by incorporating three additional variables to investigate whether the individual characteristics of a physician affect EMR adoption. A field survey is conducted with a total of 217 physicians from 15 different academic medical centers and metropolitan hospitals for six weeks. Then, the Structural Equation Modeling (SEM) analysis results indicate that perceived service level is an important antecedent of perceived usefulness. Healthcare technology self-efficacy, perceived risk, and perceived service level are also important antecedents of perceived ease of use. This study is concluded with implications for academics, hospital managers, governments, and medical information service providers

Sistem Pendukung Keputusan Pemilihan Tempat Nongkrong dengan Metode Analytical Hierarchy Process

Pada zaman sekarang ini tempat Nongkrong dapat dijumpai dimana-mana. Tanpa memandang usia atau kalangan apapun dan di manapun.  Tak bisa dipungkiri bahwa  seiring  berjalannya waktu tempat Nongkrong akan terus berkembang sesuai kebutuhan pasar. Dilihat dari manfaatnya tempat Nongkrong ini sebenarnya hanyalah tempat untuk berkomunikasi baik mengobrol ataupun bersenda gurau kesesama teman, dan keluarga. Dengan berbagai macam tempat nongkrong yang ada di era ini membuat para USAha bisnis bisa menarik perhatian orang banyak terutama kaum milenial. Banyaknya tempat nongkrong saat ini,  membuat penelitian  ini  mengambil  sample  empat jenis tempat nongkrong yang diminati para kaum milenial  saat ini dan berdasarkan data market share di Indonesia, keputusan terlihat bahwa bobot prioritas tertinggi yaitu The Clave dengan nilai 0,335 atau 33%, maka dapat disimpulkan bahwa responden condong memilih The Clave sebagai Tempat Nongkrong Kaum Millenial terbaik dari segi menu, harga, fasilitas dan Fotogenik. Disusul dengan D&C dengan nilai 0,286 atau 29%, lalu Warung Upnormal dengan nilai 0.241 atau 24% dan terakhir adalah Es Bidadari dengan nilai 0.138 atau 14%.Penelitian ini dibuat dengan menggunakan metode Analytical Hierarchy Process (AHP). Dengan menggunakan metode AHP diharapkan dapat membantu pemilihan tempat nongkrong yang banyak diminati oleh kaum milenial dan layak serta harga yang terjangkau

Using an Extended Technology Acceptance Model to Uncover Variables Influencing Physicians’ Use Of EHR in Jordan: Insights from Alberta, Canada

Adoption rates for electronic health records (EHR) remain low in developing nations, even though health information technologies undoubtedly enhance the quality of service delivery and healthcare institutions’ overall efficiency. In this research, researchers employed a technology acceptance integrated model to analyze what factors are most important in encouraging physicians in Jordan to adopt EHR. This framework was created after a thorough review of the relevant literature and with input from physicians in Alberta, Canada, a province with an openly disclosed high rate of electronic health record adoption. To achieve its aim, the present study used a quantitative correlational research strategy. Data were acquired from a convenient sample size of 413 web-based survey participants recruited from the target population of physicians practicing in the public and private healthcare sectors in Jordan. The study’s hypotheses were tested with structural equation modeling. Physicians’ behavioral intentions were shown to be strongly predicted by factors including perceived usefulness, perceived ease of use, perceived ’privacy and security,’ financial incentives, and self-efficacy, which collectively accounted for 57.8% of the total variance in behavioral intention. Perceived usefulness had the highest influence on intentions, followed by self-efficacy, perceived ”privacy and security,” and perceived ease of use, with financial incentives having the smallest impact on intentions. Accordingly, healthcare practitioners must consider these variables while developing and validating interpretations about HER adoption. This study concludes with several implications for healthcare directors, policymakers, and providers of health information systems, in addition to suggestions for future research areas

From Design Principles to Impacts: A Theoretical Framework and Research Agenda

In this paper, we integrate three streams of research in information systems (i.e., IS success, technology adoption, and human-centered design principles) to extend our understanding of technology use. We present a theoretical framework that incorporates the core ideas from these three streams of research. We leverage the proposed framework to present propositions that could guide future work. Specifically, the propositions we develop relate system-design principles to use and net benefits (i.e., job performance and job satisfaction) and rich use to job performance. We further suggest several broad potential future research directions

Electronic Health Record Implementation Strategies for Decreasing Healthcare Costs

Some managers of primary care provider (PCP) facilities lack the strategies to implement electronic health records (EHRs), which could decrease healthcare costs and enhance the efficiency and quality of healthcare that patients receive. The purpose of this single-case study was to explore the strategies PCP managers used to implement EHRs to decrease healthcare costs. The population consisted of 5 primary care managers with responsibility for the administration, oversight, and direct working knowledge of EHRs in Central Florida. The conceptual framework was the technology acceptance model. Data were collected from semistructured face-to-face interviews and the review of company documents, including training logs, activity records, and cost information. Methodological triangulation was used to validate the creditability and interpretation of the data in transcribing themes. Three themes emerged from the analysis of study data: implementation of EHRs, costs of implementing EHRs, and perceived usefulness of EHRs. Participants indicated that the implementation of EHRs depended on motivation, financial cost, and the usefulness of EHRs relating to training that reflected user-friendliness. The implications of this study for social change include the potential to lower the cost and improve the efficiency of healthcare for patients. The use of EHR systems could enhance the quality of care delivered to patients through improved accessibility, elimination of duplicative tests, and retrieval of accurate patient information. The use of EHRs can lead to a comprehensive preventative healthcare system resulting in a healthier environment

Critical Factors of Adopting Enterprise Application Integration Technology: An Empirical Study on Larger Hospitals

As hospitals extend their service scope, they adopt more information systems. These systems are implemented in different timelines and the interfaces of databases become varied. Frequently, the exchange of information between various systems requires additional coordination or even manual input for unifying data. To embrace automation, the solution is to adopt enterprise application integration (EAI) technology, the middleware, to convert data from among various information systems to enable an efficient flow of data in the hospital. In this paper, we discuss and verify the impact factors on the integration levels of EAI by surveying larger hospitals above the regional level in Taiwan and testing a proposed research model. The findings of this study show that information technology infrastructure, hospital size, external pressure, internal pressure, and external support significantly affect the EAI level

Sensor-as-a-Service: Convergence of Sensor Analytic Point Solutions (SNAPS) and Pay-A-Penny-Per-Use (PAPPU) Paradigm as a Catalyst for Democratization of Healthcare in Underserved Communities

In this manuscript, we discuss relevant socioeconomic factors for developing and implementing sensor analytic point solutions (SNAPS) as point-of-care tools to serve impoverished communities. The distinct economic, environmental, cultural, and ethical paradigms that affect economically disadvantaged users add complexity to the process of technology development and deployment beyond the science and engineering issues. We begin by contextualizing the environmental burden of disease in select low-income regions around the world, including environmental hazards at work, home, and the broader community environment, where SNAPS may be helpful in the prevention and mitigation of human exposure to harmful biological vectors and chemical agents. We offer examples of SNAPS designed for economically disadvantaged users, specifically for supporting decision-making in cases of tuberculosis (TB) infection and mercury exposure. We follow-up by discussing the economic challenges that are involved in the phased implementation of diagnostic tools in low-income markets and describe a micropayment-based systems-as-a-service approach (pay-a-penny-per-use—PAPPU), which may be catalytic for the adoption of low-end, low-margin, low-research, and the development SNAPS. Finally, we provide some insights into the social and ethical considerations for the assimilation of SNAPS to improve health outcomes in marginalized communities

Acceptance and use predictors of open data technologies: Drawing upon the unified theory of acceptance and use of technology

AbstractPolicy-makers expect that open data will be accepted and used more and more, resulting in a range of benefits including transparency, participation and innovation. The ability to use open data partly depends on the availability of open data technologies. However, the actual use of open data technologies has shown mixed results, and there is a paucity of research on the predictors affecting the acceptance and use of open data technologies. A better understanding of these predictors can help policy-makers to determine which policy instruments they can use to increase the acceptance and use of open data technologies. A modified model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) is used to empirically determine predictors influencing the acceptance and use of open data technologies. The results show that the predictors performance expectancy, effort expectancy, social influence, facilitating conditions and voluntariness of use together account for 45% of the variability in people's behavioral intention to use open data technologies. Except for facilitating conditions, all these predictors significantly influence behavioral intention. Our analysis of the predictors that influence the acceptance and use of open data technologies can be used to stimulate the use of open data technologies. The findings suggest that policy-makers should increase the acceptance and use of open data technologies by showing the benefits of open data use, by creating awareness of users that they already use open data, by developing social strategies to encourage people to stimulate each other to use open data, by integrating open data use in daily activities, and by decreasing the effort necessary to use open data technologies