The Myotubular/centronuclear myopathy (MTM/CNM) patient registry is an international, patient-reported, disease-specific registry. It was established in March 2013 to facilitate and accelerate translational and clinical research through the identification of information and participants. Registrations are accepted from patients, parents/guardians of patients, female carriers of X-linked myotubular myopathy (XLMTM), and from family members who wish to register deceased patients. After initial registration, online consents must be completed before access is given to the rest of the questionnaires including clinical information. Patients' genetic and/or muscle biopsy reports can be uploaded if available. As of February 22nd, 2017. 188 participants have registered from 27 countries, and 145 have consented (122 patients and 23 XLMTM female carriers). Out of 122 patients, 98 patients reported to be diagnosed as MTM (64 males, 2 females) or CNM (19 males, 11 females) both pathologically and genetically. Genetic mutations were identified in myotubularin gene (MTM1) (n = 62), dynamin-2 gene (n = 15), ryanodine receptor-1 gene (n = 3), bridging integrator-1/amphiphysin-2 gene (n = 2), or titin gene (n = 1). The median deceased age among 18 patients with MTM1 was 2.5 years old. We observed that clinical features were varied among female carriers as well as patients having some mutation in the same gene. The registry contains a significant amount of data from diverse and growing cohorts of MTM/CNM patients, and provides a means of accessing and analyzing a cross-sectional snapshot of the international patient population. It can help to identify and recruit patients into all aspects of clinical research, and aims to assist and support a collaborative effort between clinicians, researchers and patient groups to increase our understanding of these conditions and enhance trial readiness in the patient population.

Rare genetic lipid disorders comprise all the monogenic disorders of lipoprotein metabolism with the exception of heterozygous familial hypercholesterolaemia (FH). The creation and maintenance of patient registries is critical for disease monitoring, improving clinical best practice, facilitating research and enabling the development of novel therapeutics, but very few disease-specific rare genetic lipid disorder registries currently exist. Our aim was to design, develop and deploy a web-based patient registry for rare genetic lipid disorders. The Rare Genetic Lipid Disorders Registry is based on the FH Australasia Network (FHAN) Registry, which has been operating since 2015. The Rare Genetic Lipid Disorders Registry was deployed utilising the open-source Rare Disease Registry Framework (RDRF), which enables the efficient customisation and sustainable deployment of web-based registries. The Registry has been designed to capture longitudinal data on 13 rare genetic lipid disorders, with the ability to add more if required in the future. Recruitment of volunteers into the Registry is currently through the Royal Perth Hospital Lipid Disorders Clinic in Western Australia. Although in essence a clinic-based patient registry, the web-based design allows for expansion and distribution across Australia and beyond. Data collated by the Registry may ultimately improve the diagnosis, management and treatment of these conditions.

Background: Rare genetic lipid disorders comprise all the monogenic disorders of lipoprotein metabolism with the exception of heterozygous familial hypercholesterolaemia (FH). Disease registries are critical resources for disease monitoring, improving clinical best practice, facilitating research and enabling the development of novel therapeutics, but very few disease-specific rare genetic lipid disorder registries currently exist. Our aim was to design, develop and deploy a web-based registry for rare genetic lipid disorders.

Background: Angelman syndrome (AS) is a rare neurodevelopmental disorder affecting 1 in 15 000 to 1 in 24 000 individuals. The condition results in severe delays in development and expressive language and motor impairments. The Global Angelman Syndrome Registry was developed by families to facilitate longitudinal studies to advance research and therapeutics. This study describes preliminary clinical and behavioural outcomes. Methods: Caregivers completed the Sleep Disturbance Scale for Children (SDSC; N = 161) and a 29‐item behavioural scale developed for Angelman Syndrome (N = 184). Relationships between seizure and gastroesophageal history, and behaviour and sleep were explored. Results: A history of seizures was associated with higher levels of excessive somnolence (Mann–Whitney U = 2733.000, p = .028, d = .336), and greater incidences of spontaneous laughter/smiling (Mann–Whitney U = 3709.000, p = .009, d = .406), behaviour dysregulation (Mann–Whitney U = 3,550.000, p = .039, d = .318), and repetitive behaviours (Mann–Whitney U = 3566.000, p = .042, d = .305). A history of gastroesophageal reflux in infancy was associated with spontaneous laughter/smiling (Mann–Whitney U = 2973.500, p = .016, d = .377). Individuals with severe gastroesophageal reflux had higher levels of disordered breathing in sleep compared to individuals with mild cases (Kruskal–Wallis = 9.924, p = .007, d = .796). Medical treatment of gastroesophageal reflux was associated with higher levels of self‐injury (Mann–Whitney U = 913.000, p = .044, d = .388) and repetitive behaviours (Mann–Whitney U = 1003.000, p = .031, d = .454). Spontaneous laughter/smiling, anxiety and repetitive behaviours were associated with sleep disorders (Spearman's r range = .055–.361). Conclusions: Repetitive behaviours, spontaneous laughter and self‐injury may represent seizure activity or efforts to communicate discomfort associated with gastroesophageal reflux. Excessive somnolence may be a side effect of seizure activity or anti‐epileptics, while disordered breathing may occur in sleep due to reflux.

Aims: The aim of the Continuous Improvement in Care (CIC) Cancer research program is to explain variations in health outcomes, which at present cannot be understood with conventional health outcome measures. To achieve this, the project is collecting data reflecting not just the disease process but results of procedures, processes, structures, and systems in the continuum from prevention, diagnosis, treatment, survivorship to end of life care. Method: Data from both the clinical and patient perspective will be measured. The project will utilise an extensive platform of data and evaluate how best to implement the system within both the public and private sector for a range of cancer types including colorectal. The International Consortium for Health Outcomes Measurement (ICHOM) standard sets of outcomes measures will be used with the addition of data and outcomes relevant to WA patients. Ongoing clinical data will be collected by clinicians. Wherever possible data will be extracted electronically from other data systems, securely transferred and then data items mapped to automatically populate the relevant dataset field within the ‘Site System’. Patient reported outcome measures (PROMs) will be collected at designated time points by either the clinician in consultation with the participant or the participant will complete these via a web‐based ‘PROMS Platform’ using a computer, tablet, or mobile telephone. The PROMs dataset will be transferred to the ‘Site System’. De‐identified data will be regularly transferred to the ‘CIC Cancer Research Database’ for evaluation and feedback to the hospital sites as part of a quality improvement cycle. Results: Mapping is underway for colorectal cancer services at SJoG Midland and RPH. Process enablers and barriers will be discussed. Conclusion: This pilot will inform the model for data capture in four other cancers – lung, breast, prostate and ovarian.

Familial Hypercholesterolemia (FH) is the most common and serious monogenic disorder of lipoprotein metabolism that leads to premature coronary heart disease. There are over 65,000 people estimated to have FH in Australia, but many remain undiagnosed. Patients with FH are often under-treated, but with early detection, cascade family testing and adequate treatment, patient outcomes can improve. Patient registries are key tools for providing new information on FH and enhancing care worldwide. The development and design of the FH Australasia Network Registry is a crucial component in the comprehensive model of care for FH, which aims to provide a standardized, high-quality and cost-effective system of care that is likely to have the highest impact on patient outcomes. Informed by stakeholder engagement, the FH Australasia Network Registry was collaboratively developed by government, patient and clinical networks and research groups. The open-source, web-based Rare Disease Registry Framework was the architecture chosen for this registry owing to its open-source standards, modular design, interoperability, scalability and security features; all these are key components required to meet the ever changing clinical demands across regions. This paper provides a high level blueprint for other countries and jurisdictions to help inform and map out the critical features of an FH registry to meet their particular health system needs.

Clinical decisions rely on expert knowledge that draws on quality patient phenotypic and physiological data. In this regard, systems that can support patient-centric care are essential. Patient registries are a key component of patient-centre care and can come in many forms such as disease-specific, recruitment, clinical, contact, post market and surveillance. There are, however, a number of significant challenges to overcome in order to maximise the utility of these information management systems to facilitate improved patient-centred care. Registries need to be harmonised regionally, nationally and internationally. However, the majority are implemented as standalone systems without consideration for data standards or system interoperability. Hence the task of harmonisation can become daunting. Fortunately, there are strategies to address this. In this paper, a disease registry framework is outlined that enables efficient deployment of national and international registries that can be modified dynamically as registry requirements evolve. This framework provides a basis for the development and implementation of data standards and enables patients to seamlessly belong to multiple registries. Other significant advances include the ability for registry curators to create and manage registries themselves without the need to contract software developers, and the concept of a registry description language for ease of registry template sharing.

BACKGROUND:Information management systems are essential to capture data be it for public health and human disease, sustainable agriculture, or plant and animal biosecurity. In public health, the term patient registry is often used to describe information management systems that are used to record and track phenotypic data of patients. Appropriate design, implementation and deployment of patient registries enables rapid decision making and ongoing data mining ultimately leading to improved patient outcomes. A major bottleneck encountered is the static nature of these registries. That is, software developers are required to work with stakeholders to determine requirements, design the system, implement the required data fields and functionality for each patient registry. Additionally, software developer time is required for ongoing maintenance and customisation. It is desirable to deploy a sophisticated registry framework that can allow scientists and registry curators possessing standard computing skills to dynamically construct a complete patient registry from scratch and customise it for their specific needs with little or no need to engage a software developer at any stage.RESULTS:This paper introduces our second generation open source registry framework which builds on our previous rare disease registry framework (RDRF). This second generation RDRF is a new approach as it empowers registry administrators to construct one or more patient registries without software developer effort. New data elements for a diverse range of phenotypic and genotypic measurements can be defined at any time. Defined data elements can then be utilised in any of the created registries. Fine grained, multi-level user and workgroup access can be applied to each data element to ensure appropriate access and data privacy. We introduce the concept of derived data elements to assist the data element standards communities on how they might be best categorised.CONCLUSIONS:We introduce the second generation RDRF that enables the user-driven dynamic creation of patient registries. We believe this second generation RDRF is a novel approach to patient registry design, implementation and deployment and a significant advance on existing registry systems.