BACKGROUND: Medical terminologies and code systems, which play a vital role in the health domain, are rarely static but undergo changes as knowledge and terminology evolves. This includes addition, deletion and relabeling of terms, and, if terms are organized hierarchically, changing their position. Tracking these changes may become important if one uses multiple versions of the same terminology and interoperability is desired.
METHODS: We propose a new method for automatic change tracking between terminology versions. It consists of a declarative import pipeline, which translates source terminologies into a common data model. We then use semantic and lexical change detection algorithms. They produce an ontology-based representation of terminology changes, which can be queried using semantic query languages.
RESULTS: The method proves accurate in detecting additions, deletions, relocations and renaming of terms. In cases where inter-version term mapping information is provided by the publisher, we were able to highly enhance the ability to differentiate between simple additions/deletions and refinements/consolidation of terms.
CONCLUSIONS: The method proves effective for semi-automatic change handling if term refinements and consolidation are relevant and for automatic change detection if additional mapping information is available.

UNASSIGNED: Acute kidney injury (AKI) is easily missed and underdiagnosed in routine clinical care. Timely AKI management is important to decrease morbidity and mortality risks. We recently implemented an AKI e-alert at the University Medical Center Utrecht, comparing plasma creatinine concentrations with historical creatinine baselines, thereby identifying patients with AKI. This alert is limited to data from tertiary care, and primary care data can increase diagnostic accuracy for AKI. We assessed the added value of linking primary care data to tertiary care data, in terms of timely diagnosis or excluding AKI.
UNASSIGNED: With plasma creatinine tests for 84,984 emergency department (ED) visits, we applied the Kidney Disease Improving Global Outcome guidelines in both tertiary care-only data and linked data and compared AKI cases.
UNASSIGNED: Using linked data, the presence of AKI could be evaluated in an additional 7886 ED visits. Sex- and age-stratified analyses identified the largest added value for women (an increase of 4095 possible diagnoses) and patients ≥60 years (an increase of 5190 possible diagnoses). We observed 398 additional visits where AKI was diagnosed, as well as 185 cases where AKI could be excluded. We observed no overall decrease in time between baseline and AKI diagnosis (28.4 days vs. 28.0 days). For cases where AKI was diagnosed in both data sets, we observed a decrease of 2.8 days after linkage, indicating a timelier diagnosis of AKI.
UNASSIGNED: Combining primary and tertiary care data improves AKI diagnostic accuracy in routine clinical care and enables timelier AKI diagnosis.

Occupational motor vehicle (OMV) crashes are a leading cause of occupation-related injury and fatality in the United States. Statewide crash databases provide a good source for identifying crashes involving large commercial vehicles but are less optimal for identifying OMV crashes involving light or medium vehicles. This has led to an underestimation of OMV crash counts across states and an incomplete picture of the magnitude of the problem. The goal of this study was to develop and pilot a systematic process for identifying OMV crashes in light and medium vehicles using both state crash and health-related surveillance databases. A two-fold process was developed that included: 1) a machine learning approach for mining crash narratives and 2) a deterministic data linkage effort with crash state data and workers compensation (WC) claims records and emergency medical service (EMS) data, independently. Overall, the combined process identified 5,302 OMV crashes in light and medium vehicles within one year\'s worth of crash data. Findings suggest the inclusion of multi-method approaches and multiple data sources can be implemented and used to improve OMV crash surveillance in the United States.

BACKGROUND: The Medicines Intelligence (MedIntel) Data Platform is an anonymised linked data resource designed to generate real-world evidence on prescribed medicine use, effectiveness, safety, costs and cost-effectiveness in Australia.
RESULTS: The platform comprises Medicare-eligible people who are ≥18 years and residing in New South Wales (NSW), Australia, any time during 2005-2020, with linked administrative data on dispensed prescription medicines (Pharmaceutical Benefits Scheme), health service use (Medicare Benefits Schedule), emergency department visits (NSW Emergency Department Data Collection), hospitalisations (NSW Admitted Patient Data Collection) plus death (National Death Index) and cancer registrations (NSW Cancer Registry). Data are currently available to 2022, with approval to update the cohort and data collections annually. The platform includes 7.4 million unique people across all years, covering 36.9% of the Australian adult population; the overall population increased from 4.8 M in 2005 to 6.0 M in 2020. As of 1 January 2019 (the last pre-pandemic year), the cohort had a mean age of 48.7 years (51.1% female), with most people (4.4 M, 74.7%) residing in a major city. In 2019, 4.4 M people (73.3%) were dispensed a medicine, 1.2 M (20.5%) were hospitalised, 5.3 M (89.4%) had a GP or specialist appointment, and 54 003 people died. Anti-infectives were the most prevalent medicines dispensed to the cohort in 2019 (43.1%), followed by nervous system (32.2%) and cardiovascular system medicines (30.2%).
CONCLUSIONS: The MedIntel Data Platform creates opportunities for national and international research collaborations and enables us to address contemporary clinically- and policy-relevant research questions about quality use of medicines and health outcomes in Australia and globally.

Care home residents are vulnerable to severe outcomes from infections such as COVID-19 and influenza. However, measures to control outbreaks, such as care home closures to visitors and new admissions, have a detrimental impact on their quality of life. Many infections and outbreaks could be prevented but the first step is to measure them reliably. This is challenging in care homes due to the lack of data and research infrastructure. During the pandemic, the VIVALDI study measured COVID-19 infections in residents and staff by partnering with care providers and using routinely collected data. This study aims to establish sentinel surveillance and a research database to enable observational and future interventional studies in care homes. The project has been co-produced with care providers, staff, residents, relatives, and researchers. The study (October 2023 to March 2025) will explore the feasibility of establishing a network of 500-1500 care homes for older adults in England that is underpinned by a linked data platform. No data will be collected from staff. The cohort will be created by regularly extracting resident identifiers from Digital Social Care Records (DSCR), followed by pseudonymisation and linkage to routinely collected datasets. Following extensive consultation, we decided not to seek informed consent from residents for data collection, but they can \'opt out\' of the study. Our goal is to be inclusive, and it is challenging to give every resident the opportunity to \'opt in\' due to cognitive impairment and the requirement for consultees. The project, and all requests to use the data will be overseen by relatives, residents, staff, and care providers. The study has been approved by the Health Research Authority Confidentiality Advisory Group (23/CAG/0134&0135) and the South-West Frenchay Research Ethics Committee (23/SW/0105). It is funded by the UK Health Security Agency.
Infections like flu or COVID-19 are common in care homes and infected residents can become seriously unwell. When infections spread, the measures that are often used to stop outbreaks, like care home closures to visitors and new admissions, can have a detrimental impact on residents. The first step to solving this problem is being able to measure how often infections and outbreaks happen, and how this varies across care homes. This is currently difficult because there are no systems to collect data from care home residents. During the COVID-19 pandemic, care homes worked with researchers and Government to deliver a research study called VIVALDI which measured COVID-19 infections in residents and staff and monitored what happened to them. This pilot study builds on what we learned in the pandemic and aims to reduce the impact of common infections on residents. We will set up a network of 500-1500 care homes for older adults in England that are interested in research. By collecting limited data (NHS numbers) from residents in these homes and linking to other datasets already held in the secure NHS environment, we can measure the extent of infections in residents. We are not collecting data from staff, and any residents in the datasets cannot be identified. We will also create an anonymous database (names, dates of birth, NHS numbers removed), which researchers can use to find new ways to prevent infection in care homes. This will be stored securely by the research team. If the project is successful, and residents and relatives support it, we hope this approach can be used permanently to monitor infections in care homes. The study has been designed in partnership with care providers, experienced care staff, policymakers, academics, and residents and their relatives, who will also oversee the study and all research outputs.

BACKGROUND: There is insufficient evidence of how accurately hypertension is reported on death certificates, which are the primary evidence of causes of death. This study assesses the accuracy of reporting of hypertension on death certificates of decedents in Australia who previously had their blood pressure measured.
METHODS: Blood pressure data from the 2014-15 and 2017-18 National Health Surveys were linked to death registration data from July 2015-December 2021 (average 3.3 years from survey to death). The percentage of decedents with hypertension reported on the death certificate was calculated according to blood pressure level and previous diagnosis of hypertension.
RESULTS: Hypertension was reported on the death certificate of 20.2% (95% confidence interval 12.1-28.3%) of decedents who had very high to severe blood pressure (160/100 mmHg and above), 14.5% (10.3-18.8%) who had high blood pressure (140/90 mmHg to less than 160/100 mmHg), 14.1% (10.8%-17.4%) who had normal to high blood pressure (less than 140/90 mmHg) and who took hypertension medication, and 17.8% (13.6-22.0%) who had been diagnosed with hypertension. Where the decedent had very high to severe blood pressure, hypertension was reported for 27.9% (14.1-41.8%) of deaths if they had been diagnosed with hypertension and 21.7% (9.6-33.7%) where another cardiovascular disease was reported on the death certificate.
CONCLUSIONS: Hypertension mortality in Australia is only reported for a minority of deaths of people with high or very high to severe blood pressure; this is also found for those with a prior diagnosis of hypertension.

Assessing the risk of cancer among people living with HIV (PLHIV) in the current era of antiretroviral therapy (ART) is crucial, given their increased susceptibility to many types of cancer and prolonged survival due to ART exposure. Our study aims to compare the association between HIV infection and specific cancer sites in Rwanda. Population-based cancer registry data were used to identify cancer cases in both PLHIV and HIV-negative persons. A probabilistic record linkage approach between the HIV and cancer registries was used to supplement HIV status ascertainment in the cancer registry. Associations between HIV infection and different cancer types were evaluated using unconditional logistic regression models. We performed several sensitivity analyses to assess the robustness of our findings and to evaluate the potential impact of different assumptions on our results. From 2007 to 2018, the cancer registry recorded 17,679 cases, of which 7% were diagnosed among PLHIV. We found significant associations between HIV infection and Kaposi\'s Sarcoma (KS) (adjusted odds ratio [OR]: 29.1, 95% CI: 23.2-36.6), non-Hodgkin lymphoma (NHL) (1.6, 1.3-2.0), Hodgkin lymphoma (HL) (1.6, 1.1-2.4), cervical (2.3, 2.0-2.7), vulvar (4.0, 2.5-6.5), penile (3.0, 2.0-4.5), and eye cancers (2.2, 1.6-3.0). Men living with HIV had a higher risk of anal cancer (3.1, 1.0-9.5) than men without HIV, but women living with HIV did not have higher risk than women without HIV (1.0, 0.2-4.3). Our study found that in an era of expanded ART coverage in Rwanda, HIV is associated with a broad range of cancers, particularly those linked to viral infections.

BACKGROUND: Primary care plays a central role in most, if not all, health care systems including the care of vulnerable populations such as people who have been incarcerated. Studies linking incarceration records to health care data can improve understanding about health care access following release from prison. This review maps evidence from data-linkage studies about primary care use after prison release.
METHODS: The framework by Arksey and O\'Malley and guidance by the Joanna Briggs Institute (JBI) were used in this review. This scoping review followed methods published in a study protocol. Searches were performed (January 2012-March 2023) in MEDLINE, EMBASE and Web of Science Core Collection using key-terms relating to two areas: (i) people who have been incarcerated and (ii) primary care. Using eligibility criteria, two authors independently screened publication titles and abstracts (step 1), and subsequently, screened full text publications (step 2). Discrepancies were resolved with a third author. Two authors independently charted data from included publications. Findings were mapped by methodology, key findings and gaps in research.
RESULTS: The database searches generated 1,050 publications which were screened by title and abstract. Following this, publications were fully screened (n = 63 reviewer 1 and n = 87 reviewer 2), leading to the inclusion of 17 publications. Among the included studies, primary care use after prison release was variable. Early contact with primary care services after prison release (e.g. first month) was positively associated with an increased health service use, but an investigation found that a large proportion of individuals did not access primary care during the first month. The quality of care was found to be largely inadequate (measured continuity of care) for moderate multimorbidity. There were lower levels of colorectal and breast cancer screening among people released from custody. The review identified studies of enhanced primary care programmes for individuals following release from prison, with studies reporting a reduction in reincarceration and criminal justice system costs.
CONCLUSIONS: This review has suggested mixed evidence regarding primary care use after prison release and has highlighted challenges and areas of suboptimal care. Further research has been discussed in relation to the scoping review findings.

Data stand as the foundation for studying, evaluating, and addressing the multifaceted challenges within environmental health research. This chapter highlights the contributions of the Canadian Urban Environmental Health Research Consortium (CANUE) in generating and democratizing access to environmental exposure data across Canada. Through a consortium-driven approach, CANUE standardizes a variety of datasets - including air quality, greenness, neighborhood characteristics, and weather and climatic factors - into a centralized, analysis-ready, postal code-indexed database. CANUE\'s mandate extends beyond data integration, encompassing the design and development of environmental health-related web applications, facilitating the linkage of data to a wide range of health databases and sociodemographic data, and providing educational training and events such as webinars, summits, and workshops. The operational and technical aspects of CANUE are explored in this chapter, detailing its human resources, data sources, computational infrastructure, and data management practices. These efforts collectively enhance research capabilities and public awareness, fostering strategic collaboration and generating actionable insights that promote physical and mental health and well-being.

BACKGROUND: The very long-term outcomes of off-pump versus on-pump Coronary Artery Bypass Grafting (CABG) and Percutaneous Coronary Intervention (PCI) are largely unclear. We linked 20-years outcomes of two randomized trials to evaluate re-intervention and mortality outcomes for on-pump CABG, off-pump CABG and PCI.
METHODS: A data linkage project was performed using data as registered within the Netherlands Heart Registration (NHR), Statistics Netherlands (CBS) and the Octopus trials. Between 1998 and 2000, these trials randomized patients with coronary artery disease to on-pump versus off-pump CABG (OctoPump trial), or to PCI versus off-pump CABG (OctoStent trial). With data linkage, the original 5 years follow-up time for clinical events was extended to 20 years, including mortality and coronary reinterventions.
RESULTS: After 20 years, in the OctoPump trial all-cause mortality was 50.0% after on-pump, and 46.5% after off-pump CABG. There was no difference in the combined outcome of mortality and re-interventions (HR 0.82, 95% CI 0.59-1.12). In the OctoStent trial, all-cause mortality was 56.7% after PCI and 52.5% after off-pump CABG. There was no difference in the combined outcome of mortality and re-interventions (HR 0.76, 95% CI 0.57-1.04). Off-pump CABG patients underwent less re-interventions than PCI patients (HR 0.52, 95% CI 0.33-0.80).
CONCLUSIONS: This study revealed no differences in 20-year survival between patients randomized to on-pump versus off-pump CABG, or to PCI versus off-pump-CABG. However, off-pump CABG patients underwent less re-interventions than PCI patients.