Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe

IAIMS newsletter

NewsletterThe IAIMS Newsletter (1996-2005) provides valuable information about library activities and resources as well as informative articles related to information technology

The evolution of business analytics : based on case study research

While business analytics is becoming more significant and widely used by companies from increasing industries, for many the concept remains a complex illusion. The field of business analytics is considerably generic and fragmented, leaving managers confused and ultimately inhibited to make valuable decisions. This paper presents an evolutionary depiction of business analytics, using real-world case studies to illustrate a distinct overview that describes where the phenomenon was derived from, where it currently stands, and where it is heading towards. This paper provides eight case studies, representing three different eras: yesterday (1950s to 1990s), today (2000s to 2020s), and tomorrow (2030s to 2050s). Through cross-case analysis we have identified concluding patterns that lay as foundation for the discussion on future development within business analytics. We argue based on our findings that automatization of business processes will most likely continue to increase. AI is expanding in numerous areas, each specializing in a complex task, previously reserved by professionals. However, patterns show that new occupations linked to artificial intelligence will most probably be created. For the training of intelligent systems, data will most likely be requested more than ever. The increasing data will likely cause complications in current data infrastructures, causing the need for stronger networks and systems. The systems will need to process, store, and manage the great amount of various data types in real-time, while maintaining high security. Furthermore, data privacy concerns have become more significant in recent years, although, the case study research indicates that it has not limited corporations access to data. On the contrary, corporations, people, and devices will most likely become even more connected than ever before.nhhma

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic

Improving Access and Mental Health for Youth Through Virtual Models of Care

The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic