Designing a quality health information system: Case study analysis of maternal and child health in Papua New Guinea

Papua New Guinea (PNG) is facing what must seem like an insurmountable challenge to deliver quality healthcare servicesfor women living in both rural and urban areas. Glo bal governing bodies and donor agencies including WHO and UN have indicated that PNG does not have an appropriate health information system. Although there are some systems in place, to date, little research has been conducted on improving or resolving the data integrity and integration issues of the existing health information systems and automating the capture of women and newborns information in PNG. This current research study concentrates on the adoption of eHealth, as an innovative tool to strengthen the health information systems in PNG to meet WHO standards. The research targets maternal and child health focussing on child birth records asan exemplar...

Adopting healthcare big data in Sri Lankan healthcare sector

The concept of big data has already outperformed traditional data management efforts in almost all industries. Other instances it has succeeded in obtaining promising results that provide value from large-scale integration and analysis of heterogeneous data sources for example Genomic and proteomic information. Big data analytics have become increasingly important in describing the data sets and analytical techniques in software applications that are so large and complex due to its significant advantages including better business decisions, cost reduction and delivery of new product and services [1]. In a similar context, the health community has experienced not only more complex and large data content, but also information systems that contain a large number of data sources with interrelated and interconnected data attributes. That have resulted in challenging, and highly dynamic environments leading to creation of big data with its enumerate complexities, for instant sharing of information with the expected security requirements of stakeholders. When comparing big data analysis with other sectors, the health sector is still in its early stages. Key challenges include accommodating the volume, velocity and variety of healthcare data with the current deluge of exponential growth. Given the complexity of big data, it is understood that while data storage and accessibility are technically manageable, the implementation of Information Accountability measures to healthcare big data might be a practical solution in support of information security, privacy and traceability measures. Transparency is one important measure that can demonstrate integrity which is a vital factor in the healthcare service. Clarity about performance expectations is considered to be another Information Accountability measure which is necessary to avoid data ambiguity and controversy about interpretation and finally, liability [2]. According to current studies [3] Electronic Health Records (EHR) are key information resources for big data analysis and is also composed of varied co-created values [3]. Common healthcare information originates from and is used by different actors and groups that facilitate understanding of the relationship for other data sources. Consequently, healthcare services often serve as an integrated service bundle. Although a critical requirement in healthcare services and analytics, it is difficult to find a comprehensive set of guidelines to adopt EHR to fulfil the big data analysis requirements. Therefore as a remedy, this research work focus on a systematic approach containing comprehensive guidelines with the accurate data that must be provided to apply and evaluate big data analysis until the necessary decision making requirements are fulfilled to improve quality of healthcare services. Hence, we believe that this approach would subsequently improve quality of life.

Information accountability and health big data analytics: A consent-based model

With the ever increasing amount of eHealth data available from various eHealth systems and sources, Health Big Data Analytics promises enticing benefits such as enabling the discovery of new treatment options and improved decision making. However, concerns over the privacy of information have hindered the aggregation of this information. To address these concerns, we propose the use of Information Accountability protocols to provide patients with the ability to decide how and when their data can be shared and aggregated for use in big data research. In this paper, we discuss the issues surrounding Health Big Data Analytics and propose a consent-based model to address privacy concerns to aid in achieving the promised benefits of Big Data in eHealth.

Managing and sharing health data through information accountability protocols

Concerns over the security and privacy of patient information are one of the biggest hindrances to sharing health information and the wide adoption of eHealth systems. At present, there are competing requirements between healthcare consumers' (i.e. patients) requirements and healthcare professionals' (HCP) requirements. While consumers want control over their information, healthcare professionals want access to as much information as required in order to make well-informed decisions and provide quality care. In order to balance these requirements, the use of an Information Accountability Framework devised for eHealth systems has been proposed. In this paper, we take a step closer to the adoption of the Information Accountability protocols and demonstrate their functionality through an implementation in FluxMED, a customisable EHR system.

Using mobile technology to motivate adolescents with type 1 diabetes mellitus: A systematic review of recent literature

Introduction Behavioural interventions have been shown to improve outcomes in patients with type 1 diabetes mellitus (T1DM). There are a small number of studies that suggest text-messages (TM), native mobile applications (NMAs), and other mobile tools may be useful platforms for delivering behavioural interventions to adolescents. Aim The aim of this study was to explore, by way of a systematic review of available literature, (a) the outcomes of interventions using mobile technology for youth with T1DM and (b) what mobile technologies, functional design elements and aesthetic design elements have the best evidence to support their use. Methods A search of six online databases returned 196 unique results, of which 13 met the inclusion criteria. Results Four studies were randomised controlled trials (RCTs), and all others prospective cohort studies. TM (10) was the most common intervention technology, while NMAs were used in four studies. The most common outcome measured was HbA1c (9); however, only three studies showed a significant decrease. Similarly, the results reported for other outcome measures were mixed. The studies included in this review suggest that interventions which have data collection and clinician support functionality may be more effective in improving adherence and glycaemic control, but more evidence is needed. Further, the evidence base supporting the use of NMAs in T1DM management for adolescents is weak, with most studies adopting TM as the intervention tool. Overall, the studies lack adequate descriptions of their methodology, and better quality studies are required to inform future intervention design.

Spanish version of the screening Orebro Musculoskeletal Pain Questionnaire: A cross-cultural adaptation and validation

Background Spanish is one of the five most spoken languages in the world. There is currently no published Spanish version of the Örebro Musculoskeletal Pain Questionnaire (OMPQ). The aim of the present study is to describe the process of translating the OMPQ into Spanish and to perform an analysis of reliability, internal structure, internal consistency and concurrent criterion-related validity. Methods Design: Translation and psychometric testing. Procedure: Two independent translators translated the OMPQ into Spanish. From both translations a consensus version was achieved. A backward translation was made to verify and resolve any semantic or conceptual problems. A total of 104 patients (67 men/37 women) with a mean age of 53.48 (±11.63), suffering from chronic musculoskeletal disorders, twice completed a Spanish version of the OMPQ. Statistical analysis was performed to evaluate the reliability, the internal structure, internal consistency and concurrent criterion-related validity with reference to the gold standard questionnaire SF-12v2. Results All variables except “Coping” showed a rate above 0.85 on reliability. The internal structure calculation through exploratory factor analysis indicated that 75.2% of the variance can be explained with six components with an eigenvalue higher than 1 and 52.1% with only three components higher than 10% of variance explained. In the concurrent criterion-related validity, several significant correlations were seen close to 0.6, exceeding that value in the correlation between general health and total value of the OMPQ. Conclusions The Spanish version of the screening questionnaire OMPQ can be used to identify Spanish patients with musculoskeletal pain at risk of developing a chronic disability.

Differences in L1 linguistic attention control between monolinguals and bilinguals

Relational elements of language (e.g. spatial prepositions) act to direct attention to aspects of an incoming message. The listener or reader must be able to use these elements to focus and refocus attention on the mental representation being constructed. Research has shown that this type of attention control is specific to language and can be distinguished from attention control for non-relational (semantic or content) elements. Twenty-two monolinguals (18–30 years) and nineteen bilinguals (18–30 years) completed two conditions of an alternating-runs task-switching paradigm in their first language. The relational condition involved processing spatial prepositions, and the non-relational condition involved processing concrete nouns and adjectives. Overall, monolinguals had significantly larger shift costs (i.e. greater attention control burden) in the relational condition than the non-relational condition, whereas bilinguals performed similarly in both conditions. This suggests that proficiency in a second language has a positive impact on linguistic attention control in one's native language.

Response to: Electronic health records and healthcare identifiers : legislation discussion paper

Public submission # 029 to a Australian federal parliamentary committee considering proposed legislative changes to the Commonwealth's Healthcare Identifiers Act 2010 and the Personally Controlled Electronic Health Records Act 2012.

Submission to: Strategic Review of Health and Medical Research (Australia) otherwise known as the McKeon Review

Public submission # 247 to the McKeon Review. The submission addresses the terms of reference on: How can we optimise translation of health and medical research into better health and wellbeing? (Terms of Reference 4, 8, 9, 10 and 11)