Ignorance, experimentation, redundancy or active management? Organizational approaches to mobile information and communication technology [MICT] integration with existing Hospital IT

The use of mobile ICT (MICT) is said to increase the efficiency of healthcare work practices. Due to the variety of different devices and contexts of use, however, a wide range of patterns of MICT adoption and use are possible. This paper presents a typology of such patterns and considers their effectiveness in supporting clinical work practices. Conclusions are drawn on the role of Information Systems management in this respect. The typology draws on data collected from 13 sites in 9 hospitals in four countries (Portugal, US, UK and Singapore) during the course of one year. A mixed methodology was adopted using questionnaires, log file data, interviews and observation We found four main patterns of MICT adoption: organizations which a) were unaware of MICT use by clinicians; b) were piloting MICT use in specific clinical scenarios; c) were using MICT to add a mobile capacity to the existing network, and d) were using MICT as part of a coherent IT strategy. It was found that careful matching of MICT to existing IT resources and ongoing local work practices was necessary to achieve effective support of clinical work practices. Those institutions where a more pro-active strategy towards MICT use seemed to gain more from the technology with less risk, greater data use, and higher levels of technology awareness. © 2008 IEEE

Moving beyond the machines: The concept of "MICT device at hand" and "mobility in practice"

Mobile Information and Communication Technologies (MICTs) are widely promoted as increasing the efficiency of work practices in healthcare. There are a number of different types of mobile computing devices available, however, that provide users with differing potential capabilities and these may be used in a wide range of different work settings with varying characteristics. Mobile computers are intimately related with moves towards nomadic computing but can equally be seen as a way of achieving ubiquitous computing. As these devices are incapable of autonomous and intelligent movement, however, their mobility remains dependent on their "carrier"-user. This places an emphasis on the human-computer interface as the benefits from the use of MICTs, is likely to depend on the appropriate matching of device characteristics and work settings. From a socio-technical perspective, however, device characteristics may be context dependent, so it is important to focus on the device "at hand", that is in the process of use The analysis of case studies detailing the use of different MICT devices by doctors in different hospital settings indicates that while some MICT devices are viewed as helpful tools for work; others prove problematic as their characteristics in practice diverge from technical expectations. We therefore advance two concepts, "mobility in practice" and "MICT at hand", to serve as ways to move beyond looking at mobile computers just in terms of their technical specification towards a view of entities-in-use, which, we suggest, offers a more productive perspective for both academics and practitioners. © 2007 IEEE

What's so different about mobile information communication technologies (MICTs) for clinical work practices? A review of selected pilot studies

This article seeks to highlight some distinctive issues involved in the use of mobile information and communication technologies (MICTs) in the healthcare context. A three-layered framework for analysing cases of MICT-in-use is developed from the literature and employed to analyse evidence from a number of healthcare MICT pilot studies. These indicate that MICTs create new implementation challenges, and that developers and implementers appear to pay little attention to the particular workflow modalities of mobility and their relationship with the type of MICT. In terms of effects on clinical work practices, MICTs seemed to make access to information easier but not necessarily faster. Better integration of MICTs with other hospital systems and use of wireless networks were seen as necessary to achieve greater uptake. Areas for further research that might support the implementation of MICTs in healthcare are identified. Copyright © 2005 SAGE Publications

What explains doctors' usage of Mobile Information and Communication Technologies? A comparison of US and Portuguese hospitals.

Doctors, either as a result of individual initiative or departmental policy, may use a number of different mobile computers. The relationship between device ownership/provision and usage is, however, rarely discussed. This paper therefore presents survey data (N=267) on mobile computer ownership and use by doctors in two Portuguese and two US hospitals, considering both devices owned by individuals and those supplied by the hospital. The results show that ownership is not clearly related to either usage pattern or frequency of use. Providing handheld computers also did not lead to higher number of users, higher frequency of use or significant differences in tasks carried out. Nevertheless, doctors owning handhelds alone or in combination with laptops used them more frequently than those using laptops alone. Differences in usage pattern proportions rather than demographics were a better indication of differences in usage frequencies and the tasks for which MICT devices were being used

Temporal and spatial organization of doctors' computer usage in a UK hospital department

This paper describes the use of an application accessible via distributed desktop computing and wireless mobile devices in a specialist department of a UK acute hospital. Data (application logs, in-depth interviews, and ethnographic observation) were simultaneously collected to study doctors' work via this application, when and where they accessed different areas of it, and from what computing devices. These show that the application is widely used, but in significantly different ways over time and space. For example, physicians and surgeons differ in how they use the application and in their choice of mobile or desktop computing. Consultants and junior doctors in the same teams also seem to access different sources of patient information, at different times, and from different locations. Mobile technology was used almost exclusively during the morning by groups of clinicians, predominantly for ward rounds. © 2005 Taylor & Francis

Sistema Manchester: tempo empregado na classificação de risco e prioridade para atendimento em uma emergência

RESUMO Objetivo Avaliar o tempo que antecede e o tempo empregado na classificação de risco, na prioridade para atendimento e no destino dos pacientes 24 horas após a admissão em uma Emergência. Métodos Coorte retrospectiva que incluiu adultos classificados pelo Sistema Manchester de Classificação de Risco na maior Emergência do sul do país em 2012. Os dados foram disponibilizados em forma de planilha eletrônica e analisados de acordo com suas características e distribuição. Resultados Dos 139.556 atendimentos, metade dos pacientes chegou à classificação no tempo preconizado (7; IQR: 2 – 20 minutos), sendo classificados em dois (IQR: 1 – 3) minutos. As classificações de menor prioridade e as altas hospitalares (88,4%) foram mais frequentes que hospitalizações (11,4%) e óbitos (0,2%). Conclusão O tempo envolvido em atividades que antecedem o primeiro atendimento médico permaneceu dentro do preconizado. A proporção de classificações de menor prioridade e as altas, 24 horas após a classificação, foram elevadas

Predictive validity of the Manchester Triage System: evaluation of outcomes of patients admitted to an emergency department Validez predictiva del Protocolo de Clasificación de Riesgo de Manchester: evaluación de la evolución de los pacientes admitidos en un pronto atendimiento Validade preditiva do Protocolo de Classificação de Risco de Manchester: avaliação da evolução dos pacientes admitidos em um pronto atendimento

OBJECTIVE: to assess the predictive validity of the Manchester Triage System implemented in a municipal hospital in Belo Horizonte, MG, Brazil. METHOD: cohort prospective and analytical study. The sample of 300 patients was stratified by color groups. The outcome measured was the scores, obtained by patients in each classification group in the Therapeutic Intervention Scoring System - 28, 24 hours after admission to the emergency department. RESULTS: A total of 172 (57%) patients were men and the average age of all patients was 57.3 years old. The median score concerning the severity of their conditions was 6.5 points in the yellow group, 11.5 in the orange group, and 22 points in the red group. Statistically significant differences were found among the three groups (p<0.001). CONCLUSION: the data confirm that the conditions of patients within the color groups progressed at different levels of severity.<br>OBJETIVO: evaluar la validez predictiva del protocolo de clasificación de riesgo de Manchester implantado en un hospital municipal de Belo Horizonte, Minas Gerais. MÉTODO: estudio de cohorte prospectivo y analítico. La muestra estratificada por colores de la clasificación fue de 300 pacientes. El final evaluado fue la puntuación por el Therapeutic Intervention Scoring System - 28, lograda por los pacientes en cada grupo de clasificación después de 24 horas de la admisión en el servicio de urgencia. RESULTADOS: entre los pacientes, 172 eran hombres (57%); la media de edad de los pacientes evaluados fue de 57,3 años. La mediana de puntuación del índice de gravedad en el grupo amarillo fue 6,5 puntos; en el grupo naranja, 11,5 puntos y, en el grupo rojo, 22 puntos, habiendo diferencia estadística significante entre los tres grupos (p<0,001). CONCLUSIÓN: los datos refuerzan que los pacientes evolucionan con niveles de gravedad diferentes entre los grupos de colores de clasificación.<br>OBJETIVO: avaliar a validade preditiva do protocolo de classificação de risco de Manchester, implantado em um hospital municipal de Belo Horizonte, Minas Gerais. MÉTODO: trata-se de estudo de coorte prospectivo e analítico A amostra estratificada por cores da classificação foi de 300 pacientes. O desfecho avaliado foi a pontuação pelo Therapeutic Intervention Scoring System - 28, obtida pelos pacientes em cada grupo de classificação, após 24 horas da admissão no serviço de urgência. RESULTADOS: entre os pacientes, 172 eram homens (57%) e a média de idade dos pacientes avaliados foi de 57,3 anos. A mediana de pontuação do índice de gravidade no grupo amarelo foi de 6,5 pontos; no grupo laranja, 11,5 pontos e, no grupo vermelho, 22 pontos, havendo diferença estatística significante entre os três grupos (p<0,001). CONCLUSÃO: os dados reforçam que os pacientes evoluem com níveis de gravidade diferentes entre os grupos de cores de classificação