Large datasets in paediatric oncology are inherently rare. Therefore, it is paramount to fully exploit all available data, which are distributed over several resources, including biomaterials, images, clinical trials, and registries. With privacy-preserving record linkage (PPRL), personalised or pseudonymised datasets can be merged, without disclosing the patients\' identities. Although PPRL is implemented in various settings, use case descriptions are currently fragmented and incomplete. The present paper provides a comprehensive overview of current and future use cases for PPRL in paediatric oncology. We analysed the literature, projects, and trial protocols, identified use cases along a hypothetical patient journey, and discussed use cases with paediatric oncology experts. To structure PPRL use cases, we defined six key dimensions: distributed personalised records, pseudonymisation, distributed pseudonymised records, record linkage, linked data, and data analysis. Selected use cases were described (a) per dimension and (b) on a multi-dimensional level. While focusing on paediatric oncology, most aspects are also applicable to other (particularly rare) diseases. We conclude that PPRL is a key concept in paediatric oncology. Therefore, PPRL strategies should already be considered when starting research projects, to avoid distributed data silos, to maximise the knowledge derived from collected data, and, ultimately, to improve outcomes for children with cancer.

OBJECTIVE: To describe the use of privacy preserving linkage methods operationally in Australia, and to present insights and key learnings from their implementation.
METHODS: Privacy preserving record linkage (PPRL) utilising Bloom filters provides a unique practical mechanism that allows linkage to occur without the release of personally identifiable information (PII), while still ensuring high accuracy.
RESULTS: The methodology has received wide uptake within Australia, with four state linkage units with privacy preserving capability. It has enabled access to general practice and private pathology data amongst other, both much sought after datasets previous inaccessible for linkage.
CONCLUSIONS: The Australian experience suggests privacy preserving linkage is a practical solution for improving data access for policy, planning and population health research. It is hoped interest in this methodology internationally continues to grow.

BACKGROUND: The incidence of pediatric-onset inflammatory bowel disease (IBD) and the costs of caring for individuals with IBD are both increasing. We calculated the direct healthcare costs of pediatric IBD in the first year after diagnosis and developed a model to predict children who would have high costs (top 25th percentile).
METHODS: Using data from the Canadian Children IBD Network inception cohort (≤16 years of age, diagnosed between 2013 and 2019) deterministically linked to health administrative data from Ontario, Canada, we estimated direct healthcare and medication costs accrued between 31 and 365 days after diagnosis. Candidate predictors included age at diagnosis, sex, rural/urban residence location, distance to pediatric center, neighborhood income quintile, IBD type, initial therapy, disease activity, diagnostic delay, health services utilization or surgery around diagnosis, regular primary care provider, and receipt of mental health care. Logistic regression with stepwise elimination was used for model building; 5-fold nested cross-validation optimized and improved model accuracy while limiting overfitting.
RESULTS: The mean cost among 487 children with IBD was CA$15 168 ± 15 305. Initial treatment (anti-tumor necrosis factor therapy, aminosalicylates, or systemic steroids), having a mental health care encounter, undergoing surgery, emergency department visit at diagnosis, sex, and age were predictors of increased costs, while having a regular primary care provider was a predictor of decreased costs. The C-statistic for our model was 0.71.
CONCLUSIONS: The cost of caring for children with IBD in the first year after diagnosis is immense and can be predicted based on characteristics at diagnosis. Efforts that mitigate rising costs without compromising quality of care are needed.
Cost of caring for children with IBD is high—CA$15 168 between 31 and 365 days from diagnosis in 487 Canadian children. Predictors of high costs included anti-tumor necrosis factor therapy and mental health care, with lower costs in those with a primary-care provider.

BACKGROUND: Nine in every thousand children born in the United Kingdom have congenital heart disease, and 250,000 adults are living with the condition. This study aims to investigate the associations between congenital heart disease and educational outcomes among school-aged children in Scotland.
METHODS: Routine health and education databases were linked to produce a cohort of all singleton children born in Scotland and attending a local authority run primary, secondary, or special school in Scotland at some point between 2009 and 2013. Children with congenital heart disease within this cohort were compared with children unaffected by congenital conditions. Outcomes investigated were special educational need (SEN), absenteeism, exclusion, academic attainment, and unemployment. All analyses were adjusted for sociodemographic and maternity confounders. Absenteeism was investigated as a mediating factor in the associations with attainment and unemployment.
RESULTS: Of the 715,850 children, 6,295 (0.9%) had congenital heart disease and 4,412 (6.1%) had isolated congenital heart disease. Congenital heart disease and isolated congenital heart disease were both significantly associated with subsequent special educational need (OR 3.45, 95% CI 3.26-3.65, p < 0.001 and OR 1.98, 95% CI 1.84-2.13, p < 0.001 respectively), absenteeism (IRR 1.13, 95% CI 1.10-1.16, p < 0.001 and IRR 1.10, 95% CI 1.06-1.13, p < 0.001 respectively), and low academic attainment (OR 1.69, 95% CI 1.39-2.07, p < 0.001 and OR 1.35, 95% CI 1.07-1.69, p = 0.011 respectively). Neither congenital heart disease nor isolated congenital heart disease were associated with school exclusion. Only congenital heart disease (OR 1.21, 95% CI 1.03-1.42, p = 0.022) but not isolated congenital heart disease was associated with unemployment. When days absent were included in the analyses investigating attainment and unemployment, the conclusions were not altered.
CONCLUSIONS: Children with congenital heart disease have greater special educational need, lower school attendance, attain lower examination grades and have greater unemployment compared to peers. In addition to healthcare support, affected children need educational support to avoid additional impact on their long-term wellbeing.

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UNASSIGNED: To achieve scientific goals, researchers often require integration of data from a primary electronic health record (EHR) system and one or more ancillary EHR systems used during the same patient care encounter. Although studies have demonstrated approaches for linking patient identity records across different EHR systems, little is known about linking patient encounter records across primary and ancillary EHR systems.
UNASSIGNED: We compared a patients-first approach versus an encounters-first approach for linking patient encounter records across multiple EHR systems.
UNASSIGNED: We conducted a retrospective observational study of 348,904 patients with 533,283 encounters from 2010 to 2020 across our institution\'s primary EHR system and an ancillary EHR system used in perioperative settings. For the patients-first approach and the encounters-first approach, we measured the number of patient and encounter links created as well as runtime.
UNASSIGNED: While the patients-first approach linked 43% of patients and 49% of encounters, the encounters-first approach linked 98% of patients and 100% of encounters. The encounters-first approach was 20 times faster than the patients-first approach for linking patients and 33% slower for linking encounters.
UNASSIGNED: Findings suggest that common patient and encounter identifiers shared among EHR systems via automated interfaces may be clinically useful but not \"research-ready\" and thus require an encounters-first linkage approach to enable secondary use for scientific purposes. Based on our search, this study is among the first to demonstrate approaches for linking patient encounters across multiple EHR systems. Enterprise data warehouse for research efforts elsewhere may benefit from an encounters-first approach.

Variation in availability, format, and standardization of patient attributes across health care organizations impacts patient-matching performance. We report on the changing nature of patient-matching features available from 2010-2020 across diverse care settings. We asked 38 health care provider organizations about their current patient attribute data-collection practices. All sites collected name, date of birth (DOB), address, and phone number. Name, DOB, current address, social security number (SSN), sex, and phone number were most commonly used for cross-provider patient matching. Electronic health record queries for a subset of 20 participating sites revealed that DOB, first name, last name, city, and postal codes were highly available (>90%) across health care organizations and time. SSN declined slightly in the last years of the study period. Birth sex, gender identity, language, country full name, country abbreviation, health insurance number, ethnicity, cell phone number, email address, and weight increased over 50% from 2010 to 2020. Understanding the wide variation in available patient attributes across care settings in the United States can guide selection and standardization efforts for improved patient matching in the United States.

BACKGROUND: The global prevalence of diabetes is similar in men and women; however, there is conflicting evidence regarding sex differences in diabetes-related complications. The aim of this study was to investigate sex differences in incident microvascular and macrovascular complications among adults with diabetes.
METHODS: This prospective cohort study linked data from the 45 and Up Study, Australia, to administrative health records. The study sample included 25 713 individuals (57% men), aged ≥45 years, with diabetes at baseline. Incident cardiovascular disease (CVD), eye, lower limb, and kidney complications were determined using hospitalisation data and claims for medical services. Multivariable Cox proportional hazards models were used to assess the association between sex and incident complications.
RESULTS: Age-adjusted incidence rates per 1000 person years for CVD, eye, lower limb, and kidney complications were 37, 52, 21, and 32, respectively. Men had a greater risk of CVD (adjusted hazard ratio (aHR) 1.51, 95% CI 1.43 to 1.59), lower limb (aHR 1.47, 95% CI 1.38 to 1.57), and kidney complications (aHR 1.55, 95% CI 1.47 to 1.64) than women, and a greater risk of diabetic retinopathy (aHR 1.14, 95% CI 1.03 to 1.26). Over 10 years, 44%, 57%, 25%, and 35% of men experienced a CVD, eye, lower limb, or kidney complication, respectively, compared with 31%, 61%, 18%, and 25% of women. Diabetes duration (<10 years vs ≥10 years) had no substantial effect on sex differences in complications.
CONCLUSIONS: Men with diabetes are at greater risk of complications, irrespective of diabetes duration. High rates of complications in both sexes highlight the importance of targeted complication screening and prevention strategies from diagnosis.

BACKGROUND: Growing up with parental alcohol use disorder (AUD) is a risk factor for psychiatric disorders. This study investigated the risk of mood disorders and of anxiety disorders in the adult children of parents with AUD, adjusted for sociodemographic factors.
METHODS: Individual-level register data on the total population were linked to follow children of parents with AUD from 1973 to 2018 to assess their risk of mood disorders and of anxiety disorders. AUD, mood disorders and anxiety disorders were defined with International Statistical Classification of Diseases and Related Health Problems codes from the National Patient Register. HRs of outcomes were calculated with Cox regression. Model 1 was adjusted for the child\'s sex, parental education and death of a parent. Model 2 was adjusted for those factors and parental diagnosis of mood or anxiety disorder.
RESULTS: Those with ≥1 parent with AUD (99 723 of 2 421 479 children) had a higher risk of mood disorder and of anxiety disorder than those whose parents did not have AUD (HR mood 2.32, 95% CI 2.26 to 2.39; HR anxiety 2.66, 95% CI 2.60 to 2.72). The risk remained elevated after adjustment for sociodemographic factors and parental psychiatric diagnosis (HR mood 1.67, 95% CI 1.63 to 1.72; HR anxiety 1.74, 95% CI 1.69 to 1.78). The highest risks were associated with AUD in both parents, followed by AUD in mothers and then in fathers.
CONCLUSIONS: Adult children of parents with AUD have a raised risk of mood and anxiety disorders even after adjustment for sociodemographic factors and parental mood or anxiety disorder. These population-level findings can inform future policies and interventions.

UNASSIGNED: The potential for secondary use of health data to improve healthcare is currently not fully exploited. Health data is largely kept in isolated data silos and key infrastructure to aggregate these silos into standardized bodies of knowledge is underdeveloped. We describe the development, implementation, and evaluation of a federated infrastructure to facilitate versatile secondary use of health data based on Health Data Space nodes.
UNASSIGNED: Our proposed nodes are self-contained units that digest data through an extract-transform-load framework that pseudonymizes and links data with privacy-preserving record linkage and harmonizes into a common data model (OMOP CDM). To support collaborative analyses a multi-level feature store is also implemented. A feasibility experiment was conducted to test the infrastructures potential for machine learning operations and deployment of other apps (e.g., visualization). Nodes can be operated in a network at different levels of sharing according to the level of trust within the network.
UNASSIGNED: In a proof-of-concept study, a privacy-preserving registry for heart failure patients has been implemented as a real-world showcase for Health Data Space nodes at the highest trust level, linking multiple data sources including (a) electronical medical records from hospitals, (b) patient data from a telemonitoring system, and (c) data from Austria\'s national register of deaths. The registry is deployed at the tirol kliniken, a hospital carrier in the Austrian state of Tyrol, and currently includes 5,004 patients, with over 2.9 million measurements, over 574,000 observations, more than 63,000 clinical free text notes, and in total over 5.2 million data points. Data curation and harmonization processes are executed semi-automatically at each individual node according to data sharing policies to ensure data sovereignty, scalability, and privacy. As a feasibility test, a natural language processing model for classification of clinical notes was deployed and tested.
UNASSIGNED: The presented Health Data Space node infrastructure has proven to be practicable in a real-world implementation in a live and productive registry for heart failure. The present work was inspired by the European Health Data Space initiative and its spirit to interconnect health data silos for versatile secondary use of health data.