Background: The GDPR was implemented to build an overarching framework for personal data protection across the EU/EEA. Linkage of data directly collected from cohort participants, potentially serving as a prominent tool for health research, must respect data protection rules and privacy rights. Our objective was to investigate law possibilities of linking cohort data of minors with routinely collected education and health data comparing EU/EEA member states. Methods: A legal comparative analysis and scoping review was conducted of openly accessible published laws and regulations in EUR-Lex and national law databases on GDPR\'s implementation in Portugal, Finland, Norway, and the Netherlands and its connected national regulations purposing record linkage for health research that have been implemented up until April 30, 2021. Results: The GDPR does not ensure total uniformity in data protection legislation across member states offering flexibility for national legislation. Exceptions to process personal data, e.g., public interest and scientific research, must be laid down in EU/EEA or national law. Differences in national interpretation caused obstacles in cross-national research and record linkage: Portugal requires written consent and ethical approval; Finland allows linkage mostly without consent through the national Social and Health Data Permit Authority; Norway when based on regional ethics committee\'s approval and adequate information technology safeguarding confidentiality; the Netherlands mainly bases linkage on the opt-out system and Data Protection Impact Assessment. Conclusions: Though the GDPR is the most important legal framework, national legislation execution matters most when linking cohort data with routinely collected health and education data. As national interpretation varies, legal intervention balancing individual right to informational self-determination and public good is gravely needed for health research. More harmonization across EU/EEA could be helpful but should not be detrimental in those member states which already opened a leeway for registries and research for the public good without explicit consent.

Homelessness is a complex societal and public health challenge. Limited information exists about the population-level health and social care-related predictors and consequences of persons with lived experience of homelessness (PEH). Studies that focus on population subgroups or ad hoc questionnaires to gather data are of relatively limited generalisability to whole-population health surveillance and planning. The aim of this study was to find and synthesise information about the risk factors for, and consequences of, experiencing homelessness in whole-population studies that used routine administrative data.
We performed a systematic search using EMBASE, MEDLINE, the Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and PsycINFO research databases for English-language studies published from inception until February 2023 that reported analyses of administrative data about homelessness and health and social care-related predictors and consequences. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
Of the 1224 articles reviewed, 30 publications met the inclusion criteria. The included studies examined a wide range of topic areas, and the homelessness definitions used in each varied considerably. Studies were categorised into several topic areas: Mortality, morbidity and COVID-19; health care usage and hospital re-admission; care home admission and shelter stay; and other (e.g. employment, crime victimisation). The studies reported that that the physical and mental health of people who experience homelessness was worse than that of the general population. Homeless individuals were more likely to have higher risk of hospitalisation, more likely to use emergency departments, have higher mortality rates and were at greater risk of needing intensive care or of dying from COVID-19 compared with general population. Additionally, homeless individuals were more likely to be incarcerated or unemployed. The effects were strongest for those who experienced being homeless as a child compared to those who experienced being homeless later on in life.
This is the first systematic review of whole-population observational studies that used administrative data to identify causes and consequences associated with individuals who are experiencing homelessness. While the scientific literature provides evidence on some of the possible risk factors associated with being homeless, research into this research topic has been limited and gaps still remain. There is a need for more standardised best practice approaches to understand better the causes and consequences associated with being homeless.

There are public health concerns about an increased risk of mortality after release from prison. The objectives of this scoping review were to investigate, map and summarise evidence from record linkage studies about drug-related deaths among former adult prisoners.
MEDLINE, EMBASE, PsychINFO and Web of Science were searched for studies (January 2011- September 2021) using keywords/index headings. Two authors independently screened all titles and abstracts using inclusion and exclusion criteria and subsequently screened full publications. Discrepancies were discussed with a third author. One author extracted data from all included publications using a data charting form. A second author independently extracted data from approximately one-third of the publications. Data were entered into Microsoft Excel sheets and cleaned for analysis. Standardised mortality ratios (SMRs) were pooled (where possible) using a random-effects DerSimonian-Laird model in STATA.
A total of 3680 publications were screened by title and abstract, and 109 publications were fully screened; 45 publications were included. The pooled drug-related SMR was 27.07 (95%CI 13.32- 55.02; I 2 = 93.99%) for the first two weeks (4 studies), 10.17 (95%CI 3.74-27.66; I 2 = 83.83%) for the first 3-4 weeks (3 studies) and 15.58 (95%CI 7.05-34.40; I 2 = 97.99%) for the first 1 year after release (3 studies) and 6.99 (95%CI 4.13-11.83; I 2 = 99.14%) for any time after release (5 studies). However, the estimates varied markedly between studies. There was considerable heterogeneity in terms of study design, study size, location, methodology and findings. Only four studies reported the use of a quality assessment checklist/technique.
This scoping review found an increased risk of drug-related death after release from prison, particularly during the first two weeks after release, though drug-related mortality risk remained elevated for the first year among former prisoners. Evidence synthesis was limited as only a small number of studies were suitable for pooled analyses for SMRs due to inconsistencies in study design and methodology.

Objectives: The potential for using routinely collected data for medical research in China remains unclear. We sought to conduct a scoping review to systematically characterise nation-wide routinely collected datasets in China that may be of value for clinical research. Methods: We searched public databases and the websites of government agencies, and non-government organizations. We included nation-wide routinely collected databases related to communicable diseases, non-communicable diseases, injuries, and maternal and child health. Database characteristics, including disease area, data custodianship, data volume, frequency of update and accessibility were extracted and summarised. Results: There were 70 databases identified, of which 46 related to communicable diseases, 20 to non-communicable diseases, 1 to injury and 3 to maternal and child health. The data volume varied from below 1000 to over 100,000 records. Over half (64%) of the databases were accessible for medical research mostly comprising communicable diseases. Conclusion: There are large quantities of routinely collected data in China. Challenges to using such data in medical research remain with various accessibility. The potential of routinely collected data may also be applicable to other low- and middle-income countries.

Our study aimed to identify the common themes, knowledge gaps and to evaluate the quality of data linkage research on diabetes in Australia.
This systematic review was developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (the PRISMA Statement). Six biomedical databases and the Australian Population Health Research Network (PHRN) website were searched. A narrative synthesis was conducted to comprehensively identify the common themes and knowledge gaps. The guidelines for studies involving data linkage were used to appraise methodological quality of included studies.
After screening and hand-searching, 118 studies were included in the final analysis. Data linkage publications confirmed negative health outcomes in people with diabetes, reported risk factors for diabetes and its complications, and found an inverse association between primary care use and hospitalization. Linked data were used to validate data sources and diabetes instruments. There were limited publications investigating healthcare expenditure and adverse drug reactions (ADRs) in people with diabetes. Regarding methodological assessment, important information about the linkage performed was under-reported in included studies.
In the future, more up to date data linkage research addressing costs of diabetes and its complications in a contemporary Australian setting, as well as research assessing ADRs of recently approved antidiabetic medications, are required.

There is increasing interest in automatically identifying advertisements related to sex trafficking in online review sites. The main challenge is to identify the changing patterns in text reviews that are used to indicate illegal businesses. This work describes a novel means of identifying illegal business advertisements using natural language processing and machine learning. The method relies on building a training set of reviews of known illegal businesses. This training data is created by integrating a small high precision set of known illegal businesses (Rubmaps) with a large collection of online reviews from a general purpose review site (Yelp). Standard natural language pre-processing techniques are then applied to the text reviews and converted into a bag-of-words model with Term frequency-inverse document weighting. The resulting Document-Term matrix is used to train a classifier and then to identify suspicious activity from the remaining reviews. This approach therefore leverages a high-precision, low-recall dataset to identify relevant instances from the large low-precision, high-recall dataset. The approach was evaluated on a collection of 456,050 reviews from the Yelp online forum with a variety of machine learning algorithms and different number of text features. The method achieved a f1-score of 0.77 with a random forests classifier. The number of text features could also be reduced from 1,473 to 447 for a compact classifier with only a small drop in accuracy.

Family health history is a well-established risk factor for many health conditions but the systematic collection of health histories, particularly for multiple generations and multiple family members, can be challenging. Routinely-collected electronic databases in a select number of sites worldwide offer a powerful tool to conduct multigenerational health research for entire populations. At these sites, administrative and healthcare records are used to construct familial relationships and objectively-measured health histories. We review and synthesize published literature to compare the attributes of routinely-collected, linked databases for three European sites (Denmark, Norway, Sweden) and three non-European sites (Canadian province of Manitoba, Taiwan, Australian state of Western Australia) with the capability to conduct population-based multigenerational health research. Our review found that European sites primarily identified family structures using population registries, whereas non-European sites used health insurance registries (Manitoba and Taiwan) or linked data from multiple sources (Western Australia). Information on familial status was reported to be available as early as 1947 (Sweden); Taiwan had the fewest years of data available (1995 onwards). All centres reported near complete coverage of familial relationships for their population catchment regions. Challenges in working with these data include differentiating biological and legal relationships, establishing accurate familial linkages over time, and accurately identifying health conditions. This review provides important insights about the benefits and challenges of using routinely-collected, population-based linked databases for conducting population-based multigenerational health research, and identifies opportunities for future research within and across the data-intensive environments at these six sites.

There has long been debate about the extent to which mental disorders contribute to suicide. We aimed to examine the evidence on the contribution of mental disorders to suicide among record linkage studies.
We performed a systematic search using eight major health databases for English-language studies published between 1 January 2000 and 11 June 2018 that linked collected data on mental disorders and suicide. We then conducted a meta-analysis to assess risk of suicide conferred by mental disorders.
Our search identified 20 articles representing 13 unique studies. The pooled rate ratio (RR) was 13.2 (95% CI 8.6-20.3) for psychotic disorders, 12.3 (95% CI 8.9-17.1) for mood disorders, 8.1 (95% CI 4.6-14.2) for personality disorders, 4.4 (95% CI 2.9-6.8) for substance use disorders, and 4.1 (95% CI 2.4-6.9) for anxiety disorders in the general population. The overall pooled RR for these mental disorders was 7.5 (95% CI 6.6-8.6). The population attributable risk of mental disorders was up to 21%.
The overall heterogeneity between studies was very high.
Our findings underline the important role of mental disorders in suicide. This suggests that ongoing efforts are required to improve access to and quality of mental health care to prevent suicide by people with mental disorders.

The purpose of this paper is to review the major sources of data on mortality, morbidity and health in Europe and in other developed regions in order to examine their potential for analysing mortality and morbidity levels and trends. The review is primarily focused on routinely collected information covering a whole country. No attempt is made to draw up an inventory of sources by country; the paper deals instead with the pros and cons of each source for mortality and morbidity studies in demography. While each source considered separately can already yield useful, though partial, results, record linkage among data sources can significantly improve the analysis. Record linkage can also lead to the detection of possible causal associations that could eventually be confirmed. More generally, Big Data can reveal changing mortality and morbidity trends and patterns that could lead to preventive measures being taken rather than more costly curative ones.