A review of information privacy laws and standards for secure digital ecosystems

© 2018 authors. Information privacy is mainly concerned with the protection of personally identifiable information. Information privacy is an arduous task, in particular, in the context of complex adaptive and multi-party heterogeneous digital ecosystems. There is a need to identify and understand the relevant privacy laws and standards for designing the secure digital ecosystems. This paper presents the results of our information privacy research in digital ecosystems through the lens of local and international privacy regulations and standards. A qualitative research method was applied to review a set of identified privacy laws across the four layers of digital ecosystem. The evaluation criteria has been applied to evaluate the applicability and coverage of the selected seven information privacy laws to people, process, information and technology layers of the digital ecosystems. The research results indicate that information privacy is a critical phenomenon; however, it is not adequately addressed in the context of end-to-end digital ecosystems. It is recommended that a multi-layered privacy by design approach is required by reviewing and mapping information privacy laws and standards to design the secure digital ecosystems

Mentoring for mental health: a mixed-method study of the benefits of formal mentoring programmes in the English police force

Recent research suggests that mentors can enhance their mentees' mental health. Yet little is known about the effect of mentoring on the anxieties of the mentors themselves. We hypothesise that mentoring programmes can have a positive impact on both mentees' and mentors' mental health. In a multi-method longitudinal study, we explore empirically the effect of a formal mentoring programme in the English police force on senior police officers' levels of anxiety. In the first step of our study, we conducted a field experiment. This experiment yielded preliminary results that suggest mentors may experience marginally lower levels of anxiety and feel as if their job is more meaningful when they participate in the mentoring programme. As a second step, we qualitatively investigated the subjective experience of the participants to explain and substantiate our findings. We found that mentoring relationships provide a unique context for mentors to discuss and normalise their concerns, to share ideas for managing anxieties, and to find more meaning in their work. We discuss our findings in terms of mentoring theory and consider their practical implications for improving mental health in the workplace

A multi-level analysis of risky streets and neighbourhoods for dissident republican violence in belfast

This paper uses graph theoretical measures to analyse the relationship between street network usage, as well as other street-and area-level factors, and dissident Republican violence in Belfast. A multi-level statistical model is used. Specifically, we employ an observation-level random-effects (OLRE) Poisson regression and use variables at the street and area levels. Streetand area-level characteristics simultaneously influence where violent incidents occur. For every 10% change in the betweenness value of a street segment, the segment is expected to experience 1.32 times as many incidents. Police stations (IRR: 22.05), protestant churches (IRR: 6.19) and commercial premises (IRR: 1.44) on each street segment were also all found to significantly increase the expected number of attacks. At the small-area level, for every 10% change in the number of Catholic residents, the number of incidents is expected to be 4.45 times as many. The results indicate that along with other factors, the street network plays a role in shaping terrorist target selection. Streets that are more connected and more likely to be traversed will experience more incidents than those that are not. This has important practical implications for the policing of political violence in Northern Ireland generally and for shaping specific targeted interventions

Closing the sea surface mixed layer temperature budget from in situ observations alone: Operation Advection during BoBBLE

Sea surface temperature (SST) is a fundamental driver of tropical weather systems such as monsoon rainfall and tropical cyclones. However, understanding of the factors that control SST variability is lacking, especially during the monsoons when in situ observations are sparse. Here we use a ground-breaking observational approach to determine the controls on the SST variability in the southern Bay of Bengal. We achieve this through the first full closure of the ocean mixed layer energy budget derived entirely from in situ observations during the Bay of Bengal Boundary Layer Experiment (BoBBLE). Locally measured horizontal advection and entrainment contribute more significantly than expected to SST evolution and thus oceanic variability during the observation period. These processes are poorly resolved by state-of-the-art climate models, which may contribute to poor representation of monsoon rainfall variability. The novel techniques presented here provide a blueprint for future observational experiments to quantify the mixed layer heat budget on longer time scales and to evaluate these processes in models

Developing an Integrated ISO 27701 and GDPR based Information Privacy Compliance Requirements Model

The protection of information assets requires interdisciplinary approach and cross-functional capabilities. In recent times, information security and privacy compliance continue to be a complicated task due to increasing regulatory restrictions, changing legislations and public awareness. The newly published information security and privacy standard ISO/IEC 27701:2019 provides support for organisations looking to put in place systems to support compliance with global data privacy requirements. However, there is little known about how does this standard map to other regulatory requirements in different jurisdictions specifically the globally relevant General Data Protection Regulation (GDPR). Hence, this research aims to answer an important research question: whether and how the ISO/IEC 27701:2019 framework represents an opportunity for the GDPR compliance? This research provides a review and mapping of ISO/IEC 27701:2019 and GDPR by using an integrated requirement engineering model as a kernel theory. The results of this research will assist organisations contemplating to meet their compliance needs. It will also help academics and practitioners interested in integrating the ISO/IEC 27701:2019 and GDPR for developing relevant compliance frameworks and tools

Development of risk prediction models to predict urine culture growth for adults with suspected urinary tract infection in the emergency department: protocol for an electronic health record study from a single UK university hospital

Background: Urinary tract infection (UTI) is a leading cause of hospital admissions and is diagnosed based on urinary symptoms and microbiological cultures. Due to lags in the availability of culture results of up to 72 h, and the limitations of routine diagnostics, many patients with suspected UTI are started on antibiotic treatment unnecessarily. Predictive models based on routinely collected clinical information may help clinicians to rule out a diagnosis of bacterial UTI in low-risk patients shortly after hospital admission, providing additional evidence to guide antibiotic treatment decisions. / Methods: Using electronic hospital records from Queen Elizabeth Hospital Birmingham (QEHB) collected between 2011 and 2017, we aim to develop a series of models that estimate the probability of bacterial UTI at presentation in the emergency department (ED) among individuals with suspected UTI syndromes. Predictions will be made during ED attendance and at different time points after hospital admission to assess whether predictive performance may be improved over time as more information becomes available about patient status. All models will be externally validated for expected future performance using QEHB data from 2018/2019. / Discussion: Risk prediction models using electronic health records offer a new approach to improve antibiotic prescribing decisions, integrating clinical and demographic data with test results to stratify patients according to their probability of bacterial infection. Used in conjunction with expert opinion, they may help clinicians to identify patients that benefit the most from early antibiotic cessation

Feasibility study of hospital antimicrobial stewardship analytics using electronic health records

Background: Hospital antimicrobial stewardship (AMS) programmes are multidisciplinary initiatives to optimise the use of antimicrobials. Most hospitals depend on time-consuming manual audits to monitor clinicians’ prescribing. But much of the information needed could be sourced from electronic health records (EHRs). Objectives: To develop an informatics methodology to analyse characteristics of hospital AMS practice using routine electronic prescribing and laboratory records. Methods: Feasibility study using electronic prescribing, laboratory and clinical coding records from adult patients admitted to six specialties at Queen Elizabeth Hospital, Birmingham, UK (September 2017–August 2018). The study involved: (1) a review of antimicrobial stewardship standards of care; (2) their translation into concepts measurable from commonly available EHRs; (3) pilot application in an EHR cohort study (n=61,679 admissions). Results: We developed data modelling methods to characterise the use of antimicrobials (antimicrobial therapy episode linkage methods, therapy table, therapy changes). Prescriptions were linked into antimicrobial therapy episodes (mean 2.4 prescriptions/episode; mean length of therapy of 5.8 days) enabling production of several actionable findings. For example, 22% of therapy episodes for low-severity community acquired pneumonia were congruent with prescribing guidelines, with a tendency to use antibiotics with a broader spectrum. Analysis of therapy changes revealed a delay in switching from intravenous to oral therapy by an average 3.6 days [95% CI: 3.4; 3.7]. Performance of microbial cultures prior to treatment initiation occurred in just 22% of antibacterial prescriptions. The proposed methods enabled fine-grained monitoring of AMS practice all the way down to specialties, wards, and individual clinical teams by case mix, enabling more meaningful peer comparison. Conclusions: It is feasible to use hospital EHRs to construct rapid, meaningful measures of prescribing quality with potential to support quality improvement interventions (audit/feedback to prescribers), engagement with front-line clinicians on optimising prescribing, and AMS impact evaluation studies

Roles of Education and IQ in Cognitive Reserve in Parkinson's Disease-Mild Cognitive Impairment.

Background/aimsThe role of cognitive reserve in Parkinson's disease (PD)-mild cognitive impairment (MCI) is incompletely understood.MethodsThe relationships between PD-MCI, years of education, and estimated premorbid IQ were examined in 119 consecutive non-demented PD patients using logistic regression models.ResultsHigher education and IQ were associated with reduced odds of PD-MCI in univariate analysis. In multivariable analysis, a higher IQ was associated with a significantly decreased odds of PD-MCI, but education was not.ConclusionThe association of higher IQ and decreased odds of PD-MCI supports a role for cognitive reserve in PD, but further studies are needed to clarify the interaction of IQ and education and the impact of other contributors such as employment and hobbies