Objective On July 1, 2012 Australia launched a personally controlled electronic health record (PCEHR) designed around the needs of consumers. Using a distributed model and leveraging key component national eHealth infrastructure, the PCEHR is designed to enable sharing of any health information about a patient with them and any other health practitioner involved in their care to whom the patient allows access. This paper discusses the consumer-facing part of the program. Method Design of the system was through stakeholder consultation and the development of detailed requirements, followed by clinical design assurance. Results Patients are able to access any posted information through a web-accessible 'consumer portal.' Within the portal they are able to assert access controls on all or part of their record. The portal includes areas for consumers to record their own personal information. Discussion The PCEHR has the potential to transform the ability of patients to actively engage in their own healthcare, and to enable the emerging partnership model of health and healthcare in medicine. The ability to access health information traditionally kept within the closed walls of institutions also raises challenges for the profession, both in the language clinicians choose and the ethical issues raised by the changed roles and responsibilities. Conclusions The PCEHR is aimed at connecting all participants and their interventions, and is intended to become a system-wide activity. BACKGROUND AND OBJECTIVE

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BackgroundFragmented care results in poor outcomes for individuals with complexity of need. Person-centred coordinated care (P3C) is perceived to be a potential solution, but an absence of accessible evidence and the lack of a scalable ‘blue print’ mean that services are ‘experimenting’ with new models of care with little guidance and support. This paper presents an approach to the implementation of P3C using collaborative action, providing examples of early developments across this programme of work, the core aim of which is to accelerate the spread and adoption of P3C in United Kingdom primary care settings.MethodsTwo centrally funded United Kingdom organisations (South West Collaboration for Leadership in Applied Health Research and Care and South West Academic Health Science Network) are leading this initiative to narrow the gap between research and practice in this urgent area of improvement through a programme of service change, evaluation and research. Multi-stakeholder engagement and co-design are core to the approach. A whole system measurement framework combines outcomes of importance to patients, practitioners and health organisations. Iterative and multi-level feedback helps to shape service change while collecting practice-based data to generate implementation knowledge for the delivery of P3C. The role of the research team is proving vital to support informed change and challenge organisational practice. The bidirectional flow of knowledge and evidence relies on the transitional positioning of researchers and research organisations.ResultsExtensive engagement and embedded researchers have led to strong collaborations across the region. Practice is beginning to show signs of change and data flow and exchange is taking place. However, working in this way is not without its challenges; progress has been slow in the development of a linked data set to allow us to assess impact innovations from a cost perspective. Trust is vital, takes time to establish and is dependent on the exchange of services and interactions. If collaborative action can foster P3C it will require sustained commitment from both research and practice. This approach is a radical departure from how policy, research and practice traditionally work, but one that we argue is now necessary to deal with the most complex health and social problems.

BackgroundData, particularly ‘big’ data are increasingly being used for research in health. Using data from electronic medical records optimally requires coded data, but not all systems produce coded data.ObjectiveTo design a suitable, accurate method for converting large volumes of narrative diagnoses from Australian general practice records to codify them into SNOMED-CT-AU. Such codification will make them clinically useful for aggregation for population health and research purposes.MethodThe developed method consisted of using natural language processing to automatically code the texts, followed by a manual process to correct codes and subsequent natural language processing re-computation. These steps were repeated for four iterations until 95% of the records were coded. The coded data were then aggregated into classes considered to be useful for population health analytics.ResultsCoding the data effectively covered 95% of the corpus. Problems with the use of SNOMED CT-AU were identified and protocols for creating consistent coding were created. These protocols can be used to guide further development of SNOMED CT-AU (SCT). The coded values will be immensely useful for the development of population health analytics for Australia, and the lessons learnt applicable elsewhere.

SummaryObjectives: Issues related to lack of system usability and potential safety hazards continue to be reported in the health information technology (HIT) literature. Usability engineering methods are increasingly used to ensure improved system usability and they are also beginning to be applied more widely for ensuring the safety of HIT applications. These methods are being used in the design and implementation of many HIT systems. In this paper we describe evidence-based approaches to applying usability engineering methods. Methods: A multi-phased approach to ensuring system usability and safety in healthcare is described. Usability inspection methods are first described including the development of evidence-based safety heuristics for HIT. Laboratory-based usability testing is then conducted under artificial conditions to test if a system has any base level usability problems that need to be corrected. Usability problems that are detected are corrected and then a new phase is initiated where the system is tested under more realistic conditions using clinical simulations. This phase may involve testing the system with simulated patients. Finally, an additional phase may be conducted, involving a naturalistic study of system use under real-world clinical conditions. Results: The methods described have been employed in the analysis of the usability and safety of a wide range of HIT applications, including electronic health record systems, decision support systems and consumer health applications. It has been found that at least usability inspection and usability testing should be applied prior to the widespread release of HIT. However, wherever possible, additional layers of testing involving clinical simulations and a naturalistic evaluation will likely detect usability and safety issues that may not otherwise be detected prior to widespread system release. Conclusion: The framework presented in the paper can be applied in order to develop more usable and safer HIT, based on multiple layers of evidence.