Thematic list of projects using linked data relating to Aboriginal and Torres Strait Islander people

This report contains an alphabetical listing and description of past (published since 1991), current and planned data linkage studies relating to Aboriginal and Torres Strait Islander people. The publication provides a brief listing of: the name of the projectthe names of the investigatorsthe date of the studythe jurisdiction where the study is basedthe datasets used in the studythe core issue, or theme, of the studythe method of analysisthe method or algorithms used or intended to be used to derive Indigenous status information, if required. This list should be read in conjunction with the National best practice guidelines for data linkage activities relating to Aboriginal and Torres Strait Islander People and its online attachment, Report on the use of linked data relating to Aboriginal and Torres Strait Islander people. The list was compiled from consultations with jurisdictional departments and researchers who use linked data relating to Aboriginal and Torres Strait Islander Australians and from reports and academic journal articles that describe the analysis of linked data relating to Aboriginal and Torres Strait Islander Australians

How Registries Can Help Performance Measurement Improve Care

Suggests ways to better utilize databases of clinical information to evaluate care processes and outcomes and improve measurements of healthcare quality and costs, comparative clinical effectiveness research, and medical product safety surveillance

Under-reporting of roadcasualties ? phase 1

Although this report was commissioned by the Department for Transport, the findings and recommendations are those of the authors and do not necessarily represent the views of the DfT

Big data and data repurposing – using existing data to answer new questions in vascular dementia research

Introduction: Traditional approaches to clinical research have, as yet, failed to provide effective treatments for vascular dementia (VaD). Novel approaches to collation and synthesis of data may allow for time and cost efficient hypothesis generating and testing. These approaches may have particular utility in helping us understand and treat a complex condition such as VaD. Methods: We present an overview of new uses for existing data to progress VaD research. The overview is the result of consultation with various stakeholders, focused literature review and learning from the group’s experience of successful approaches to data repurposing. In particular, we benefitted from the expert discussion and input of delegates at the 9th International Congress on Vascular Dementia (Ljubljana, 16-18th October 2015). Results: We agreed on key areas that could be of relevance to VaD research: systematic review of existing studies; individual patient level analyses of existing trials and cohorts and linking electronic health record data to other datasets. We illustrated each theme with a case-study of an existing project that has utilised this approach. Conclusions: There are many opportunities for the VaD research community to make better use of existing data. The volume of potentially available data is increasing and the opportunities for using these resources to progress the VaD research agenda are exciting. Of course, these approaches come with inherent limitations and biases, as bigger datasets are not necessarily better datasets and maintaining rigour and critical analysis will be key to optimising data use

Nutrient Estimation from 24-Hour Food Recalls Using Machine Learning and Database Mapping: A Case Study with Lactose.

The Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a free dietary recall system that outputs fewer nutrients than the Nutrition Data System for Research (NDSR). NDSR uses the Nutrition Coordinating Center (NCC) Food and Nutrient Database, both of which require a license. Manual lookup of ASA24 foods into NDSR is time-consuming but currently the only way to acquire NCC-exclusive nutrients. Using lactose as an example, we evaluated machine learning and database matching methods to estimate this NCC-exclusive nutrient from ASA24 reports. ASA24-reported foods were manually looked up into NDSR to obtain lactose estimates and split into training (n = 378) and test (n = 189) datasets. Nine machine learning models were developed to predict lactose from the nutrients common between ASA24 and the NCC database. Database matching algorithms were developed to match NCC foods to an ASA24 food using only nutrients ("Nutrient-Only") or the nutrient and food descriptions ("Nutrient + Text"). For both methods, the lactose values were compared to the manual curation. Among machine learning models, the XGB-Regressor model performed best on held-out test data (R2 = 0.33). For the database matching method, Nutrient + Text matching yielded the best lactose estimates (R2 = 0.76), a vast improvement over the status quo of no estimate. These results suggest that computational methods can successfully estimate an NCC-exclusive nutrient for foods reported in ASA24

Accuracy and completeness of patient pathways – the benefits of national data linkage in Australia

Background - The technical challenges associated with national data linkage, and the extent of cross-border population movements, are explored as part of a pioneering research project. The project involved linking state-based hospital admission records and death registrations across Australia for a national study of hospital related deaths. Methods - The project linked over 44 million morbidity and mortality records from four Australian states between 1st July 1999 and 31st December 2009 using probabilistic methods. The accuracy of the linkage was measured through a comparison with jurisdictional keys sourced from individual states. The extent of cross-border population movement between these states was also assessed. Results - Data matching identified almost twelve million individuals across the four Australian states. The percentage of individuals from one state with records found in another ranged from 3-5 %. Using jurisdictional keys to measure linkage quality, results indicate a high matching efficiency (F measure 97 to 99 %), with linkage processing taking only a matter of days. Conclusions - The results demonstrate the feasibility and accuracy of undertaking cross jurisdictional linkage for national research. The benefits are substantial, particularly in relation to capturing the full complement of records in patient pathways as a result of cross-border population movements. The project identified a sizeable ‘mobile’ population with hospital records in more than one state. Research studies that focus on a single jurisdiction will under-enumerate the extent of hospital usage by individuals in the population. It is important that researchers understand and are aware of the impact of this missing hospital activity on their studies. The project highlights the need for an efficient and accurate data linkage system to support national research across Australia

Record Linkage Techniques: Exploring and developing data matching methods to create national record linkage infrastructure to support population level research

In a world where the growth in digital information and systems continues to expand, researchers have access to unprecedented amounts of data. These large and complex data reservoirs require creative, innovative and scalable tools to unlock the potential of this ‘big data’. Record linkage is a powerful tool in the ‘big data’ arsenal. This thesis demonstrates the value of national record linkage infrastructure and how this has been achieved for the Australian research community

Avoiding disclosure of individually identifiable health information: a literature review

Achieving data and information dissemination without arming anyone is a central task of any entity in charge of collecting data. In this article, the authors examine the literature on data and statistical confidentiality. Rather than comparing the theoretical properties of specific methods, they emphasize the main themes that emerge from the ongoing discussion among scientists regarding how best to achieve the appropriate balance between data protection, data utility, and data dissemination. They cover the literature on de-identification and reidentification methods with emphasis on health care data. The authors also discuss the benefits and limitations for the most common access methods. Although there is abundant theoretical and empirical research, their review reveals lack of consensus on fundamental questions for empirical practice: How to assess disclosure risk, how to choose among disclosure methods, how to assess reidentification risk, and how to measure utility loss.public use files, disclosure avoidance, reidentification, de-identification, data utility

Using linked administrative data for monitoring and evaluating the Family Nurse Partnership in England: A scoping report

This report, commissioned by the FNP National Unit and undertaken by researchers at UCL and the London School of Hygiene and Tropical Medicine, presents a scoping review of how population-based linkage between data from the Family Nurse Partnership (FNP) in England and administrative datasets from other services could be used to generate evidence for commissioning, service evaluation and research. It addresses the methodological considerations, permission pathways and technical challenges of using data from the FNP linked with routinely collected, administrative data from other public services for population-based analyses, at a national and local authority level. Our ambition, when commissioning this work, was to explore whether linking data from FNP with administrative datasets might help provide a richer view about how the FNP intervention is affecting different cohorts of clients and their child after they have graduated. The report suggests that the potential for data linkage to support ongoing evaluation of a wide range of interventions including FNP at a national level is promising and an important area to explore. It makes a significant contribution to understanding the possibilities and constraints for doing this, which include barriers to data linkage at a local level (which we know is crucial for local commissioners) and the significant investment required to realise the potential of this project. We believe this report offers valuable insights other organisations interested in the delivery of evidence based policy may want to pursue