The Cloud-Enabled Architecture of the Clinical Data Repository in Poland

In this article, the authors, using information-systems modeling techniques, and considering current national legal regulations, present the cloud-enabled architecture of a clinical data repository. The patient’s medical record is an important carrier of information necessary for accurate diagnosis and selection of the correct treatment process. Therefore, it is not surprising that since the beginning of the development of computer technologies, databases have been built to enable the management of a patient’s medical records. These systems were most-often deployed locally at individual healthcare units, which carried certain limitations both in terms of the security and availability of the stored information, and the possibility of exchanging it with other clinics. However, recent developments in the standardization of medical information exchange in Poland, together with the revolution in cloud computing, have opened up completely new perspectives for clinical-data-repository implementations helping to make them far more sustainable. Although, the practical aspects of implementing clinical-documentation repositories are studied both in forums of European countries and also around the world; so far, no similar research was conducted with respect to Poland. This study tries to fill that gap by proposing a flexible multi-variant cloud-enabled architecture of the system providing the services of a clinical-data repository. The goal of the work was to propose such a system architecture that allows having a system that is either cloud-agnostic, that uses specifically selected cloud services, or that is even deployable locally. Thanks to the use of cloud computing services, the implemented system is characterized by high availability, scalability, and the possibility of exchanging data between medical institutions, which enables the improvement in the quality of medical processes for the whole Polish population.

The C-BIG Repository: an Institution-Level Open Science Platform

In January 2016, the Montreal Neurological Institute-Hospital (The Neuro) declared itself an Open Science organization. This vision extends beyond efforts by individual scientists seeking to release individual datasets, software tools, or building platforms that provide for the free dissemination of such information. It involves multiple stakeholders and an infrastructure that considers governance, ethics, computational resourcing, physical design, workflows, training, education, and intra-institutional reporting structures. The C-BIG repository was built in response as The Neuro’s institutional biospecimen and clinical data repository, and collects biospecimens as well as clinical, imaging, and genetic data from patients with neurological disease and healthy controls. It is aimed at helping scientific investigators, in both academia and industry, advance our understanding of neurological diseases and accelerate the development of treatments. As many neurological diseases are quite rare, they present several challenges to researchers due to their small patient populations. Overcoming these challenges required the aggregation of datasets from various projects and locations. The C-BIG repository achieves this goal and stands as a scalable working model for institutions to collect, track, curate, archive, and disseminate multimodal data from patients. In November 2020, a Registered Access layer was made available to the wider research community at https://cbigr-open.loris.ca, and in May 2021 fully open data will be released to complement the Registered Access data. This article outlines many of the aspects of The Neuro’s transition to Open Science by describing the data to be released, C-BIG’s full capabilities, and the design aspects that were implemented for effective data sharing.

openEHR is FAIR-Enabling by Design

The FAIR Principles are a set of recommendations that aim to underpin knowledge discovery and integration by making the research outcomes Findable, Accessible, Interoperable and Reusable. These guidelines encourage the accurate recording and exchange of structured data, coupled with contextual information about their creation, expressed in domain-specific standards and machine readable formats. This paper analyses the potential support to FAIRness of the openEHR e-health standard, by theoretically assessing the compliance with each of the 15 FAIR principles of a hypothetical Clinical Data Repository (CDR) developed according to the openEHR specifications. Our study highlights how the openEHR approach, thanks to its computable semantics-oriented design, is inherently FAIR-enabling and is a promising implementation strategy for creating FAIR-compliant CDRs.

MON-601 Obesity Pharmacotherapy Is Effective in the United States Veterans Affairs Patient Population: A Local and Virtual Cohort Study

Background: Overweight and obesity are major health burdens, and the military veteran population may be disproportionately affected. Multiple new pharmacologic agents and combinations have been approved by the FDA for use in medical weight management. Using deidentified records from our local interdisciplinary weight management clinic and a national clinical data repository, we assessed obesity pharmacotherapy use and its real-world effectiveness for weight loss and improvement of comorbid metabolic parameters in this vulnerable population. Methods: During the initial year of the local weight management clinic, we found over 50 records with monthly followup of lifestyle intervention augmented by obesity pharmacotherapy. In the national clinical data repository, we identified over 2 million records for unique individuals prescribed bupropion-naltrexone, liraglutide, lorcaserin, orlistat, or phentermine-topiramate, and metformin considered as a control prescription. We selected records with detailed documentation of weight trends from 1 year before to 1 year after first prescription date for further analysis. Results: The most commonly prescribed medications in our local weight management clinic were metformin, liraglutide, orlistat, and combination phentermine/topiramate. On average, we observed −4.0 ± 2.1 kg weight loss over the initial 6-month intervention in records that completed at least 3 visits within this period. In the national database, over 800,000 records for an obesity or control metformin prescription provided adequate weight documentation to compare weight slopes during the year before and after the prescription start date. Records for metformin prescriptions showed −0.04 ± 0.008 kg/week difference in weight slope over one year before versus after the prescription start date. The greatest difference in weight slope was seen with phentermine-topiramate (−0.13 ± 0.03 kg/week), followed by lorcaserin, liraglutide, bupropion-naltrexone, and orlistat. Conclusions: Our data suggests that veterans with obesity experience weight loss at 1 year follow-up when engaged with our interdisciplinary weight management clinic. Nationally, veterans with obesity experience modest weight loss when prescribed pharmacotherapy. Taken together, our two data sources provide complementary perspectives to help guide obesity pharmacotherapy in veterans with obesity.

Identification of Microchip Implantation Events for Dogs and Cats in the VetCompass Australia Database

In Australia, compulsory microchipping legislation requires that animals are microchipped before sale or prior to 3 months in the Australian Capital Territory, New South Wales, Queensland and Victoria, and by 6 months in Western Australia and Tasmania. Describing the implementation of microchipping in animals allows the data guardians to identify individual animals presenting to differing veterinary practices over their lifetimes, and to evaluate compliance with legislation. VetCompass Australia (VCA) collates electronic patient records from primary care veterinary practices into a database for epidemiological studies. VCA is the largest companion animal clinical data repository of its kind in Australia, and is therefore the ideal resource to analyse microchip data as a permanent unique identifier of an animal. The current study examined the free-text ‘examination record’ field in the electronic patient records of 1000 randomly selected dogs and cats in the VCA database. This field may allow identification of the date of microchip implantation, enabling comparison with other date fields in the database, such as date of birth. The study revealed that the median age at implantation for dogs presented as individual patients, rather than among litters, was 74.4 days, significantly lower than for cats (127.0 days, p = 0.003). Further exploration into reasons for later microchipping in cats may be useful in aligning common practice with legislative requirements.