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The last few years have seen new developments to understand and tackle the significant public health issue posed by chronic kidney disease (CKD). Established renal disease currently consumes 2% of the UK National Health Service budget and predictions are that this figure will increase significantly due to the rising number of people requiring renal replacement therapy fuelled by the ageing population and the diabetes mellitus epidemic. This paper reviews the scale of CKD and discusses the new developments such as staging, referral guidelines and new Department of Health incentives brought about to improve awareness. The importance of Information Technology in assisting the management of renal disease is also outlined. We identify various types of intervention which might be used to do this: feedback in an educational context, the establishment of computerized decision support and enhancement of the patient journey. Many principles may be extended to the management of any chronic disease. While new developments are necessary to improve care, wider implementation is required to be able to see if improved outcomes are achieved. [ABSTRACT FROM AUTHOR]

Background: Privacy, ethics, and data access issues pose significant challenges to the timely delivery of health research. Whilst the fundamental drivers to ensure that data access is ethical and satisfies privacy requirements are similar, they are often dealt with in varying ways by different approval processes., Objective: To achieve a consensus across an international panel of health care and informatics professionals on an integrated set of privacy and ethics principles that could accelerate health data access in data-driven health research projects., Method: A three-round consensus development process was used. In round one, we developed a baseline framework for privacy, ethics, and data access based on a review of existing literature in the health, informatics, and policy domains. This was further developed using a two-round Delphi consensus building process involving 20 experts who were members of the International Medical Informatics Association (IMIA) and European Federation of Medical Informatics (EFMI) Primary Health Care Informatics Working Groups. To achieve consensus we required an extended Delphi process., Results: The first round involved feedback on and development of the baseline framework. This consisted of four components: (1) ethical principles, (2) ethical guidance questions, (3) privacy and data access principles, and (4) privacy and data access guidance questions. Round two developed consensus in key areas of the revised framework, allowing the building of a newly, more detailed and descriptive framework. In the final round panel experts expressed their opinions, either as agreements or disagreements, on the ethics and privacy statements of the framework finding some of the previous round disagreements to be surprising in view of established ethical principles., Conclusion: This study develops a framework for an integrated approach to ethics and privacy. Privacy breech risk should not be considered in isolation but instead balanced by potential ethical benefit.

Background: Primary care delivers patient-centred and coordinated care, which should be quality-assured. Much of family practice now routinely uses computerised medical record (CMR) systems, these systems being linked at varying levels to laboratories and other care providers. CMR systems have the potential to support care., Objective: To achieve a consensus among an international panel of health care professionals and informatics experts about the role of informatics in the delivery of patient-centred, coordinated, and quality-assured care., Method: The consensus building exercise involved 20 individuals, five general practitioners and 15 informatics academics, members of the International Medical Informatics Association Primary Care Informatics Working Group. A thematic analysis of the literature was carried out according to the defined themes., Results: The first round of the analysis developed 27 statements on how the CMR, or any other information system, including paper-based medical records, supports care delivery. Round 2 aimed at achieving a consensus about the statements of round one. Round 3 stated that there was an agreement on informatics principles and structures that should be put in place. However, there was a disagreement about the processes involved in the implementation, and about the clinical interaction with the systems after the implementation., Conclusions: The panel had a strong agreement about the core concepts and structures that should be put in place to support high quality care. However, this agreement evaporated over statements related to implementation. These findings reflect literature and personal experiences: whilst there is consensus about how informatics structures and processes support good quality care, implementation is difficult.

Background: Generally benefits and risks of vaccines can be determined from studies carried out as part of regulatory compliance, followed by surveillance of routine data; however there are some rarer and more long term events that require new methods. Big data generated by increasingly affordable personalised computing, and from pervasive computing devices is rapidly growing and low cost, high volume, cloud computing makes the processing of these data inexpensive., Objective: To describe how big data and related analytical methods might be applied to assess the benefits and risks of vaccines., Method: We reviewed the literature on the use of big data to improve health, applied to generic vaccine use cases, that illustrate benefits and risks of vaccination. We defined a use case as the interaction between a user and an information system to achieve a goal. We used flu vaccination and pre-school childhood immunisation as exemplars., Results: We reviewed three big data use cases relevant to assessing vaccine benefits and risks: (i) Big data processing using crowdsourcing, distributed big data processing, and predictive analytics, (ii) Data integration from heterogeneous big data sources, e.g. the increasing range of devices in the "internet of things", and (iii) Real-time monitoring for the direct monitoring of epidemics as well as vaccine effects via social media and other data sources., Conclusions: Big data raises new ethical dilemmas, though its analysis methods can bring complementary real-time capabilities for monitoring epidemics and assessing vaccine benefit-risk balance.