Electronic medical record systems in Saudi Arabia: Knowledge and preferences of healthcare professionals

Background The use of Electronic Medical Record (EMR) systems is increasing internationally, though developing countries, such as Saudi Arabia, have tended to lag behind in the adoption and implementation of EMR systems due to several barriers. The literature shows that the main barriers to EMR in Saudi Arabia are lack of knowledge or experience using EMR systems and staff resistance to using the implemented EMR system. Methods A quantitative methodology was used to examine health personnel knowledge and acceptance of and preference for EMR systems in seven Saudi public hospitals in Jeddah, Makkah and Taif cities. Results Both English literacy and education levels were significantly correlated with computer literacy and EMR literacy. Participants whose first language was not Arabic were more likely to prefer using an EMR system compared to those whose first language was Arabic. Conclusion This study suggests that as computer literacy levels increase, so too do staff preferences for using EMR systems. Thus, it would be beneficial for hospitals to assess English language proficiency and computer literacy levels of staff prior to implementing an EMR system. It is recommended that hospitals need to offer training and targeted educational programs to the potential users of the EMR system. This would help to increase English language proficiency and computer literacy levels of staff as well as staff acceptance of the system.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

A process mining-based investigation of adverse events in care processes

This paper proposes the Clinical Pathway Analysis Method (CPAM) approach that enables the extraction of valuable organisational and medical information on past clinical pathway executions from the event logs of healthcare information systems. The method deals with the complexity of real-world clinical pathways by introducing a perspective-based segmentation of the date-stamped event log. CPAM enables the clinical pathway analyst to effectively and efficiently acquire a profound insight into the clinical pathways. By comparing the specific medical conditions of patients with the factors used for characterising the different clinical pathway variants, the medical expert can identify the best therapeutic option. Process mining-based analytics enables the acquisition of valuable insights into clinical pathways, based on the complete audit traces of previous clinical pathway instances. Additionally, the methodology is suited to assess guideline compliance and analyse adverse events. Finally, the methodology provides support for eliciting tacit knowledge and providing treatment selection assistance.

Developing sustainable banana production systems: a case study from tropical Australia

The north Queensland banana industry is under pressure from government and community expectations to exhibit good environmental stewardship. The industry is situated on the high-rainfall north Queensland coast adjacent to 2 natural icons, the Great Barrier Reef to the east and World Heritage-listed rain forest areas to the west. The main environmental concern is agricultural industry pollutants harming the Great Barrier Reef. In addition to environmental issues the banana industry also suffers financial pressure from declining margins and production loss from tropical cyclones. As part of a broader government strategy to reduce land-based pollutants affecting the Great Barrier Reef, the formation of a pilot banana producers group to address these environmental and economic pressures was facilitated. Using an integrated farming systems approach, we worked collaboratively with these producers to conduct an environmental risk assessment of their businesses and then to develop best management practices (BMP) to address environmental concerns. We also sought input from technical experts to provide increased rigour for the environmental risk assessment and BMP development. The producers' commercial experience ensured new ideas for improved sustainable practices were constantly assessed through their profit-driven 'filter' thus ensuring economic sustainability was also considered. Relying heavily on the producers' knowledge and experience meant the agreed sustainable practices were practical, relevant and financially feasible for the average-sized banana business in the region. Expert input and review also ensured that practices were technically sound. The pilot group producers then implemented and adapted selected key practices on their farms. High priority practices addressed by the producers group included optimizing nitrogen fertilizer management to reduce runoff water nitrification, developing practical ground cover management to reduce soil erosion and improving integrated pest management systems to reduce pesticide use. To facilitate wider banana industry understanding and adoption of the BMP's developed by the pilot group, we conducted field days at the farms of the pilot group members. Information generated by the pilot group has had wider application to Australian horticulture and the process has been subsequently used with the north Queensland sugar industry. Our experiences have shown that integrated farming systems methodologies are useful in addressing complex issues like environmental and economic sustainability. We have also found that individual horticulture businesses need on-going technical support for change to more sustainable practices. One-off interventions have little impact, as farm improvement is usually an on-going incremental process. A key lesson from this project has been the need to develop practical, farm scale economic tools to clarify and demonstrate the financial impact of alternative management practices. Demonstrating continued profitability is critical to encourage widespread industry adoption of environmentally sustainable practices

Development and feasibility testing of an education program to improve knowledge and self-care among Aboriginal and Torres Strait Islander patients with heart failure

Background/Aim There is a 70% higher age-adjusted incidence of heart failure (HF) amongst Aboriginal and Torres Strait Islander people, three times more hospitalisations and twice as many deaths than non-Aboriginal people. There is a need to develop holistic yet individualised approaches in accord with the values of Aboriginal community healthcare to support patient education and self-care. The aim of this study was to re-design an existing HF educational resource (Fluid Watchers-Pacific Rim©) to be culturally safe for Aboriginal and Torres Strait Islander peoples, working in collaboration with the local community, and to conduct feasibility testing. Methods This study was conducted in two phases and utilised a mixed methods approach (qualitative and quantitative). Phase 1 of this study used action research methods to develop a culturally safe electronic resource to be provided to Aboriginal HF patients via a tablet computer. A HF expert panel adapted the existing resource to ensure it was evidence-based and contained appropriate language and images that reflects Aboriginal culture. A stakeholder group (which included Aboriginal workers and HF patients, as well as researchers and clinicians) then reviewed the resources and changes were made accordingly. In Phase 2, the new resource was tested on a sample of Aboriginal HF patients to assess feasibility and acceptability. Patient knowledge, satisfaction and self-care behaviours were measured using a before and after design with validated questionnaires. As this was a pilot test to determine feasibility, no statistical comparisons were made. Results - Phase 1: Throughout the process of resource development, two main themes emerged from the stakeholder consultation. These were the importance of identity, meaning that it was important to ensure that the resource accurately reflected the local community, with the appropriate clothing, skin tone and voice. The resource was adapted to reflect this and of the local community voiced the recordings for the resource. The other theme was comprehension; images were important and all text was converted to the first person and used plain language. - Phase 2: Five Aboriginal participants, mean age 61.6 ± 10.0 years, with NYHA Class III and IV heart failure were enrolled. Participants reported a high level of satisfaction with the resource (83.0%). HF knowledge (percentage of correct responses) increased from 48.0 ± 6.7% to 58.0 ± 9.7%, a 20.8% increase and results of the self-care index indicated that the biggest change was in patient confidence for self-care with a 95% increase in confidence score (46.7 ± 16.0 to 91.1 ± 11.5). Changes in management and maintenance scores varied between9275 patients. Conclusion By working in collaboration with HF experts, Aboriginal researchers and patients, a culturally safe HF resource has been developed for Aboriginal and Torres Strait Islander patients. Engaging Aboriginal researchers, capacity-building, and being responsive to local systems and structures enabled this pilot study to be successfully completed with the Aboriginal community and positive participant feedback demonstrated that the methodology used in this study was appropriate and acceptable; participants were able to engage with willingness and confidence.

Eliciting and encoding expert knowledge on variable selection into classical or Bayesian species distribution models

The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.

Reconfiguring agriculture through the relocation of production systems for water, environment and food security under climate change

The prospect of climate change has revived both fears of food insecurity and its corollary, market opportunities for agricultural production. In Australia, with its long history of state-sponsored agricultural development, there is renewed interest in the agricultural development of tropical and sub-tropical northern regions. Climate projections suggest that there will be less water available to the main irrigation systems of the eastern central and southern regions of Australia, while net rainfall could be sustained or even increase in the northern areas. Hence, there could be more intensive use of northern agricultural areas, with the relocation of some production of economically important commodities such as vegetables, rice and cotton. The problem is that the expansion of cropping in northern Australia has been constrained by agronomic and economic considerations. The present paper examines the economics, at both farm and regional level, of relocating some cotton production from the east-central irrigation areas to the north where there is an existing irrigation scheme together with some industry and individual interest in such relocation. Integrated modelling and expert knowledge are used to examine this example of prospective climate change adaptation. Farm-level simulations show that without adaptation, overall gross margins will decrease under a combination of climate change and reduction in water availability. A dynamic regional Computable General Equilibrium model is used to explore two scenarios of relocating cotton production from south east Queensland, to sugar-dominated areas in northern Queensland. Overall, an increase in real economic output and real income was realized when some cotton production was relocated to sugar cane fallow land/new land. There were, however, large negative effects on regional economies where cotton production displaced sugar cane. It is concluded that even excluding the agronomic uncertainties, which are not examined here, there is unlikely to be significant market-driven relocation of cotton production.

Systems between information and knowledge : In a memory management model of an extended enterprise

The research question of this thesis was how knowledge can be managed with information systems. Information systems can support but not replace knowledge management. Systems can mainly store epistemic organisational knowledge included in content, and process data and information. Certain value can be achieved by adding communication technology to systems. All communication, however, can not be managed. A new layer between communication and manageable information was named as knowformation. Knowledge management literature was surveyed, together with information species from philosophy, physics, communication theory, and information system science. Positivism, post-positivism, and critical theory were studied, but knowformation in extended organisational memory seemed to be socially constructed. A memory management model of an extended enterprise (M3.exe) and knowformation concept were findings from iterative case studies, covering data, information and knowledge management systems. The cases varied from groups towards extended organisation. Systems were investigated, and administrators, users (knowledge workers) and managers interviewed. The model building required alternative sets of data, information and knowledge, instead of using the traditional pyramid. Also the explicit-tacit dichotomy was reconsidered. As human knowledge is the final aim of all data and information in the systems, the distinction between management of information vs. management of people was harmonised. Information systems were classified as the core of organisational memory. The content of the systems is in practice between communication and presentation. Firstly, the epistemic criterion of knowledge is not required neither in the knowledge management literature, nor from the content of the systems. Secondly, systems deal mostly with containers, and the knowledge management literature with applied knowledge. Also the construction of reality based on the system content and communication supports the knowformation concept. Knowformation belongs to memory management model of an extended enterprise (M3.exe) that is divided into horizontal and vertical key dimensions. Vertically, processes deal with content that can be managed, whereas communication can be supported, mainly by infrastructure. Horizontally, the right hand side of the model contains systems, and the left hand side content, which should be independent from each other. A strategy based on the model was defined.

Representation of evidence: An approach to uncertainty handling in knowledge-based systems

Many knowledge based systems (KBS) transform a situation information into an appropriate decision using an in built knowledge base. As the knowledge in real world situation is often uncertain, the degree of truth of a proposition provides a measure of uncertainty in the underlying knowledge. This uncertainty can be evaluated by collecting `evidence' about the truth or falsehood of the proposition from multiple sources. In this paper we propose a simple framework for representing uncertainty in using the notion of an evidence space.