bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying hospitalization episodes of care among people with and without HIV in British Columbia, Canada
Authors: Emerson Scott , McLinden Taylor , Sereda Paul , Yonkman Amanda , Trigg Jason , Barrios Rolando , Hogg Robert 
Published: September 2024

BackgroundHospitalizations are a resource-intensive form of healthcare use, particularly for persons with chronic conditions such as those with HIV. Interhospital transfers typically appear as separate records in Canadian databases; misclassifying transfers as independent hospitalizations can bias key metrics such as readmission rates. We examined approaches of combining sequential, related records into hospitalization episodes of care (HEoCs) among persons with and without HIV (PWH; PWoH) in British Columbia (BC), Canada.
MethodsBC hospitalization records (1992 to 2020) were sourced from the Comparative Outcomes and Service Utilization Trends (COAST) study, a data linkage that includes samples of PWH and PWoH. We constructed 8 HEoC definitions that varied by the: a) time gap between records, and b) transfer indication. Comparisons were informed by the proportion of multi-record HEoCs (mHEoCs; episodes with multiple hospitalization records) generated, and feasibility given data quality.
ResultsWe analyzed 98,553 hospitalization records from 13,498 PWH, and 1,874,507 hospitalization records from 385,011 PWoH. Across the definitions, the proportion of mHEoCs varied from 2.46% to 5.27% for PWH and 2.73% to 4.18% for PWoH. Definitions requiring no transfer indication yielded the highest proportion of mHEoCs, whereas those requiring two-way agreement of hospital identifiers yielded the lowest proportion of mHEoCs. Patterns were comparable among PWH and PWoH. A pragmatic approach to defining HEoCs can be a reasonable option for general purposes – requiring at least one populated hospital identifier field, and ≤ 1 day gap between hospitalizations.
ConclusionsVarious approaches can be employed to combine sequential, related hospitalization records into HEoCs to help provide less biased estimates of hospitalization-related metrics.
Adaptive Governance: Empowering Data Sharing for Public Health Impact - Insights from North Carolina Department of Health and Human Services
Authors: Hawn Nelson Amy , Hogle Paul , Zanti Sharon , Proescholdbell Scott , Tenenbaum Jessie 
Published: September 2024

Objective and ApproachAt the 2022 IPDLN Conference, we presented work led by the North Carolina Department of Health and Human Services (NCDHSS), in partnership with university-based researchers, to build legal and ethical processes for routine data sharing. This session provides significant updates on the methods, results, and implications of these efforts–namely, that NCDHHS implemented an enterprise-wide data governance process and a legal framework that has enabled timely, impactful use of cross-sector data. We relied on Participatory Action Research and Deliberative Dialogue methods to engage a diverse range of partners in a data landscape overview and the co-creation of new data sharing processes that better enables the enterprise to adapt to a changing world.
ResultsFour key actions were taken as a result of the participatory research process: NCDHHS developed a data strategy, created a data sharing guidebook, staffed their Data Office, and implemented a new legal framework. In addition to describing how these actions support data use across a large US state health and human services agency, we provide three use cases demonstrating the impact of this work.
ConclusionsEstablishing routine data sharing presents legal, technical, and cultural challenges, particularly in large agencies. Through a collaborative, participatory approach, the NCDHHS successfully established enterprise-wide data governance and a legal framework to support data-driven policymaking and, ultimately, improve health outcomes for residents.
ImplicationsThis research presents a successful, actionable, and replicable framework for developing and implementing processes to support intradepartmental data access, linkage, and use.
Investigating the quality of NHS number linkage of COVID 19 vaccines data to Census 2021.
Authors: O'Dair Hannah , Cummins Sarah , Huck Rachel 
Published: September 2024

Objectives Due to the availability of data and the speed of delivery required, NHS number (Health ID) was used during the COVID-19 pandemic to join different health datasets to census 2021. This research sought to assess the quality of linkage done by NHS number, between COVID-19 vaccinations data and census 2021, by comparing to the quality that could be achieved with deterministic linkage using Personal Identifiable Information (PII). Specifically, we wanted to assure against concern that unlinked records may have been misclassified as unvaccinated due to inaccurate recording of NHS number at time of vaccination.
Approach We used deterministic (rules-based) linkage to identify extra links that were not made on NHS number. We also investigated how many links were incongruent between NHS number linkage and PII deterministic linkage.
Results We were able to link 98.5% of census records to vaccines data, with a precision of 98.94% and a recall of 99.71% This identified 1,833,626 additional links made using PII linkage. Furthermore, analysis of the linked data was re-run with the additional links.
Conclusion We were able to assure that the NHS number linkage used to produce COVID-19 vaccinations statistics, was valid. Whilst 1,833,626 more links were made, the findings resulting from the linked data were unchanged.
Implications Whilst this research demonstrates the utility of NHS number-based linkage, acquisition and use of PII on health datasets can increase the link rate and plays a vital role in estimating linkage error.
Socio-demographic variations in prostate cancer diagnosis recording: Primary care compared to the Cancer Registry in England
Authors: Somathilake Gayasha , Ford Elizabeth , Armes Jo , Moschoyiannis Sotiris , Otter Sophie , Lemanska Agnieszka 
Published: September 2024

IntroductionIn the UK, primary care data are often used for cancer-related research, but the accuracy of cancer information is uncertain.
ObjectiveWe investigated socio-demographic variation based on the recording date of prostate cancer diagnosis between primary care and the National Cancer Registry (CR).
ApproachWe utilised a data extract of 1,600,000 patients over 65 years from Clinical Practice Research Datalink (CPRD). We extracted prostate cancer diagnoses using Read and SNOMED-CT codes from primary care, and ICD-10 from CR. Initial code entry determined diagnosis dates. We categorised recording timing differences as earlier, same-day or later in primary care than CR and used the chi-squared test and logistic regression (adjusted for recording year) to compare these discrepancies across age, deprivation, and ethnicity.
ResultsWe included 26,875 men with prostate cancer diagnoses commonly recorded in both sources during 2000-2016 (1,030 excluded with missing ethnicity). Compared to CR, 1,747 (7%) had diagnoses recorded on the same day in primary care, while 20,615 (77%) had later recordings with a median delay of 21 days (IQR: 13-38). Age at diagnosis was associated with recording discrepancies (p<0.001); older men were more likely to have earlier/same-day recordings. Adjusted ORs for age groups were 1.4 (95%CI: 1.3-1.5) for 60-69, 1.3 (1.2-1.5) for 70-79, and 0.9 (0.8-1.0) for ≥80 compared to <60. No associations were found between deprivation (p=0.096) or ethnicity (p=0.067) and recording differences.
Conclusion/ ImplicationsThe discrepancy in prostate cancer information between primary care and CR underscores potential biases in studies relying solely on one data source.
Federating governance, access and infrastructure to support researcher use of synthetic data
Authors: O'Sullivan Katherine , Caldwell Jackie , Cole Christian , Harrison Kathy , Mayor Charlie , Chaliou Antonietta , Dymiter Jaroslaw , Dawson Stacey , Brown Diane , Wilde Katie 
Published: September 2024

Synthetic Data has the potential to improve efficiency of data analysis for researchers. However, there is no standard approach to synthetic data governance, access controls or infrastructure requirements, and researchers may face inconsistencies in how they can access or use synthetic data across trusted research environments. We present a federated solution taken by the Scottish Safe Haven Network to address these barriers to facilitate researcher use of synthetic data. We documented and evaluated existing governance pathways, access controls and infrastructure design for non-synthetic data across the Network, recognising uniformity and establishing equivalence using the 5 Safes framework, ISO27001 standards and the SATRE TRE specification. We also interviewed current and potential researchers using our trusted research environments to identify common use cases for accessing synthetic data. We then mapped researcher requirements against the documented equivalencies, validating with current and prospective users. We identified several use cases: to undertake feasibility studies, to understand dataset structure and format and to write analysis code whilst waiting on the project-specific data to be provided. By mapping the use cases onto existing governance and access processes and infrastructure designs, we were able to agree to a standard application process, access control mechanism, and infrastructure platform across the Network to provide a consistent process for researchers. A federated approach to synthetic data access will improve the speed at which research can be conducted as well as improving the transparency and consistency of data governance and access across organisations, ultimately improving the experience for researchers using TREs.
Disabilities in children receiving care and support in Wales and risk factors associated with being placed in care: A population-based data linkage study
Authors: Childs Jeanne , Griffiths Lucy , Hodges Helen , Bailey Grace , Elliott Martin , Cowley Laura 
Published: September 2024

ObjectiveTo determine the prevalence of functional impairments in children with disabilities receiving care and support in Wales between 2016 and 2022, and to investigate risk factors associated with being placed in care amongst these children.
MethodThis study used Children Receiving Care and Support (CRCS) Census records held in the Secure Anonymised Information Linkage Databank. We examined the proportion of children with specific impairments by their looked-after status, using bar charts and Upset plots. CRCS records were linked to demographic datasets to obtain information on area-level deprivation, and we conducted multivariable logistic regression analyses to model risk factors associated with being placed in care for children with disabilities.
ResultsOf 38,165 children receiving care and support, 10,075 (26%) had a disability, and 3,360 (33%) of these children were placed in care. Older children were less likely to be placed in care than infants (e.g. for age group 1‒4: OR 0.37 (95% CI 0.24‒0.56)). Children of mixed ethnicity were more likely to be placed in care compared to White children (2.17 (1.65‒2.85)). Child mental health problems were associated with being placed in care (1.82 (1.60‒2.07)) as were parental mental health problems (1.44 (1.29‒1.60)), parental substance/alcohol misuse (3.16 (2.81‒3.56)), parental learning disability (2.92 (2.51‒3.38)), and domestic abuse (1.48 (1.31‒1.66)).
ConclusionsThis new evidence may assist in the planning and provision of appropriate ongoing care and support for these children and their families to help prevent entry into the care system.
Balancing constraints and requirements in an application process
Authors: McLachlan Stela , Evans Katharine , Whitehorn Rebecca , Turner Emma , Oakley Jacqueline , Boyd Andy , Flaig Robin 
Published: September 2024

ObjectivesDeveloping a rigorous application process for linked data within the UK Longitudinal Linkage Collaboration’s Trusted Research Environment (TRE) included balancing the requirements of >20 longitudinal studies and several data providers with the need to provision data to researchers in a safe, ethical and efficient manner.
ApproachUK LLC was commissioned as a resource to enable the investigation of COVID-19 questions: a secure setting where longitudinal population studies (LPS) can be linked efficiently to regularly refreshed NHS electronic health records, and then accessed by researchers. UK LLC received funding to continue as a resource for any research in public good and to link to the administrative records (education, occupation, tax and benefits). To accommodate the constraints imposed by a new set of data controllers and to account for wide variety of proposals expected, we expanded our data access process.
ResultsUK LLC has a three-stage application and review process. The addition of administrative data meant that there is additional review for those applications requesting that data (Stage 4) and need to align processes with the UK Statistics Authority. There is also need to review complexity of the data requests and ethical implications of any application to access the data. We have developed an ethics decision tree to help guide the decision making around ethics requirements.
ConclusionOur process is evolving as we are trying to meet the challenge of balancing the needs of >20 studies, stakeholders, applicants, and participant/public contributors, to create a process that can handle complex needs and requirements.
Leveraging Fuzzy Match: Building an Automated Record Linkage Template in SAS Dataflux
Authors: Ma Charlotte , Kalappa Gangamma , Wang Nan , Azimaee Mahmoud , Shen Winnie 
Published: September 2024

Background ICES has conducted Probabilistic Record Linkage (PRL) for heath and non-health data for over 15 years. The PRL process has made data linkable to many ICES data holdings. However, due to the manual gray area resolution, record linkages for large datasets are time consuming with inconsistent results.
ApproachAdapting from many years of experience with PRL methodology, record linkage templates were built in SAS Dataflux. By using combination of deterministic linkage and fuzzy match algorithms, the multi-pass linkage strategy is maintained by passing unlinked records in subsequent linkage comparison cycles. The new template uses personal identifiers of multiple given names, surnames, date of birth, death date (if applicable) and sex. In each pass, the pool of possible matched pairs is created by merging on low sensitive matchcodes with different conditions. Then, using a rule-based approach, possible pairs are examined, flags are assigned, and survival rules are applied to select the best matched records.
ResultsBy feeding a pre-prepared linkage file along with updating the input and output file names, the record linkage job will be conducted automatically in SAS Dataflux through submitting a “run” command. It significantly reduces the turnaround time with no clerical review required, achieves a similar linkage rate as PRL consistently, and is utilized by various research projects.
ConclusionThe automated SAS Dataflux record linkage template is more efficient than the traditional PRL process. It eliminates the human intervention of gray area resolution, while reducing project turnaround times, and maintaining a comparable accuracy and linkage rate.
Towards standardised cross-sectoral agreements for data depositing and data access in Trusted Research Environments: streamlined contracting to advance public benefit research.
Authors: Brophy Rachel , Smith Cassie , Boyd Andy , Pan UK Data Governance Steering Group  
Published: September 2024

Objective Trusted Research Environments (TREs) rely on Data Contributor Agreements (DCAs) and Data Access Agreements (DAAs) to bind organisations to terms and conditions in place to protect data. Our objective is to develop and drive adoption of DCA and DAA standardised templates which are optimised for data science in TREs. This is intended to reduce delays arising from the legal review process yet must not compromise on the safeguards needed for trustworthy data science.
ApproachA template DAA and DCA have been developed by the Pan-UK Data Governance Steering Group of the UK Health Data Research Alliance, underpinned by a core set of principles, and informed by a benchmarking exercise of existing DCAs/DAAs and meaningful involvement of public members and stakeholders.
ResultsPrinciples for TRE data contribution and data access in TREs have been mapped to core DCA and DAA terms for UK-based TREs and assigned to Five Safes’ categories. Flexibility will be ensured by including terms specific to TREs or specific data/data owners in customisable annexes to the agreements. Public views obtained through public involvement and engagement (PIE) activities have been formative in the development of the outputs.
Conclusions By providing a familiar structure and terms, the templates should build trust among data owners and the UK public and provide clarity to all parties on their data protection obligations.
ImplicationsThis familiar structure and terms are intended to accelerate data research by enabling faster ingress of data into TREs and approval of projects, enabling more timely research.
Navigating the barriers to multi-regional research administrative data access: Forward thinking solutions
Authors: Curtis Maillet Donna , Yada Nicole 
Published: September 2024

In 2021, aware of both the importance of pan-Canadian data access for advancing health research and the conditions and requirements that make administrative data access onerous, HDRN Canada worked with CATCO the Canadian arm of an international COVID-19 clinical trial to create a roadmap for navigating the barriers to multi-regional administrative data access in Canada.
While developing the roadmap, data access request processes were studied in real time for a multi-region study seeking access to link administrative data to clinical trial data, at the individual level. The intent was to move beyond anecdotal evidence and document the specific nature of policy and processes that hamper data access. The case study allowed the study team to define the barriers permitting application of tangible mitigating measures.
In 2022, barriers such as the lack of ability to share data across provincial borders became too great to continue the study. Although the roadmap was not completed, insights were gained for waypoints along the path enabling HDRN Canada to make important process improvement to harmonize data access across regions. Solutions to challenges with data access request forms, regional data flows, data sharing partner relationships, data sharing agreements, and REB and project reviews were identified.
Recently pan-Canadian initiatives have released important guidance for addressing data access challenges. The adoption of this guidance is paramount to ensure Canada continues to meaningfully contribute to health research.
Forward thinking solutions to data access challenges today will establish the necessary infrastructure for a future with minimal data access barriers.
Identifying homelessness using health administrative data in Ontario, Canada: how coding policies impact case validity
Authors: Richard Lucie , Carter Brooke , Nisenbaum Rosane , Liu Michael , Hwang Stephen 
Published: September 2024

Conducting longitudinal research about the health of people experiencing homelessness poses unique challenges. In Canada, we previously demonstrated that identification through health administrative databases permits population-level studies, despite relatively low sensitivity. Since then, coding of homelessness became mandatory in hospitals nationally. As a result, case validity since 2018 is unknown.
We re-validated case definitions for identifying homelessness in health administrative databases between 2018 and 2022 against the longitudinally collected housing history of a representative sample of people experiencing homelessness (n=640) and randomly selected, housed people (n=128,000) in Toronto, Canada. We calculated sensitivity, specificity, positive and negative predictive values, and positive likelihood ratios for 42 unique case definitions. We compared the resulting true positives against false positives and false negatives to identify potential causes of misclassification.
The optimal case (best sensitivity/scalability beyond Ontario) definition included any indicator during a hospital-based encounter within 180 days of a period of homelessness (sensitivity=52.9%; specificity=99.5%). Among periods of homelessness with ≥1 hospital-based encounter, the optimal case definition had good sensitivity (75.1%) with minimal reduction in specificity (98.5%). Review of false positives suggests homeless status is sometimes improperly carried forward in healthcare encounters occurring after transitioning out of homelessness.
Case definitions to identify homelessness using health administrative data exhibit moderate sensitivity and excellent specificity, with two-fold increases in sensitivity since the implementation of mandatory coding in Canada. Mandatory collection of social determinants of health information within administrative data present invaluable opportunities for advancing research on the health and healthcare needs of people experiencing homelessness.
Persisting social disadvantage and intercensal social mobility in Northern Ireland: an examination of morbidity and all-cause mortality using three waves of the Northern Ireland Longitudinal Study (NILS).
Authors: McCarter Rachel , Rosato Michael , Leavey Gerard 
Published: September 2024

Objective and ApproachUsing census returns from three waves of NILS (1991, 2001, 2011) linked with mortality data, we examined morbidity/mortality outcomes by socio-economic disadvantage over time (using an individual-level deprivation index derived from educational attainment, social class, housing tenure and household car availability at each census). These were combined to generate two indicators of Intercensal social mobility: measuring no change, and upward/downward mobility between censuses. The relationship between mobility (2001-2011) and (separately) self-reported mental ill-health (MIH) at the 2011 Census and all-cause mortality (2011-2015) were examined using logistic regression and Cox PH modelling respectively.
Results Population comprised 288,262 individuals aged 25-74 in 2011, recording 19,318 deaths (2011-2015) and 23,959 (8.3%) reporting MIH. MIH: those with no intercensal mobility followed the standard pathway associated with persisting disadvantage (comparing with the most advantaged the least advantaged recorded OR=16.13:95%CI=13.50,19.28); and while both the upwardly and downwardly mobile generally recorded higher ORs than those consistently most advantaged, the magnitude of ORs increased with social distance traversed; and ORs for downward mobility were consistently higher than with upward mobility. Patterns associated with all-cause mortality were similar.
ConclusionsThis suggests: upward mobility retains something of the social patterning pertaining in social disadvantage levels left behind; downward mobility may be connected to ongoing health issues. Poor health outcomes remain strongly associated with socio-economic circumstance.
Implications Research focusing on relationship between social mobility, disadvantage and health outcomes in NI is limited: access to more precise administrative data will enhance possibilities associated with evidence-based policy formation.