bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Mortality After Release from Incarceration Consortium (MARIC) study: Strengths of international data linkage
Authors: Borschmann Rohan , Kinner Stuart , Spittal Matthew 
Published: September 2018

IntroductionAdults released from incarceration experience complex physical and mental health problems, and are at markedly increased risk of preventable death. Despite this, not enough is known about the granular epidemiology of mortality in this population to inform development of targeted, evidence-based responses.
Objectives and ApproachWe created the Mortality After Release from Incarceration Consortium (MARIC), a multi-disciplinary collaboration from 12 countries representing 30 cohorts of adults with a history of incarceration. The combined sample size is 1,210,168, with 58,840 deaths recorded over 8,261,743 person-years of follow-up time. In this protocol paper, using a two-step, individual participant data meta-analysis (IPDM-A) methodology involving 22 MARIC cohorts, we calculated 1) a crude mortality rate (CMR; with 95% confidence intervals) for each individual cohort over the first 84 days (12 weeks) following release; and 2) a combined, meta-analysed CMR for the same period.
ResultsOf 1,704,208 individual releases, we observed 4,018 deaths over the first 84 days. The overall CMR over the first 84 days after release was 1610.97 deaths per 100,000 person-years (95% CI: 1263.4 - 1958.5). The rate was highest on the day of release (5768.0; 95% CI: 3296.5 - 8239.4), which was significantly higher than on days 4-84.
Conclusion/ImplicationsAdults released from incarceration were at an acutely increased risk of death on the day of release, and this risk remained elevated for at least the first 12 weeks. The MARIC study will provide decisive and empirical evidence to guide clinicians and policy makers in reducing mortality in this marginalized
The prevalence of multimorbidity measured by linked healthcare data and its association with mortality in a large longitudinal cohort
Authors: Johnston Marjorie , Black Corri , Mercer Stewart , Prescott Gordon , Butler Jessica 
Published: September 2018

IntroductionMultimorbidity, the co-existence of two or more health conditions, is a growing challenge. It may be measured using health service administrative data via the emerging consensus measure by Barnett. However, the original Barnett was developed using Scottish-specific primary care coding, which restricts its application in other health systems.
Objectives and ApproachThe aim was to create and test International Classification of Disease (ICD) coding algorithms for all 40 Barnett conditions.
We evaluated this new measure by:

Assessing the prevalence of secondary care multimorbidity in 2001
Assessing the association between multimorbidity and mortality rate over 15 years

Participants of the Aberdeen Children of the 1950s cohort (ACONF) were linked to their secondary-care healthcare records and mortality records. Multimorbidity was defined as the presence of two or more of the 40 conditions. The association between multimorbidity and mortality was assessed using Cox proportional hazards regression with adjustment for key covariates.
ResultsWe combined results of a review of the coding literature with codes used commonly by the National Health Service in Scotland, to apply ICD codes to each Barnett condition.
The ACONF were aged 45 to 51 years in 2001. Of 8,094 members who were alive and linked to Scottish administrative data, 246 (3%) had multimorbidity. There were 629 deaths by 2016 with 83 occurring in the multimorbidity group.
Relative to those without multimorbidity, those with multimorbidity in 2001 had a mortality hazard ratio (HR) of 5.9 (95% CI 4.6-7.4) over 15 years follow-up. This was unchanged when adjusted for age, gender, social class at birth, cognition at age 7, secondary school type and educational attainment (HR 6.2, 95% CI 4.4-8.5).
Conclusion/ImplicationsWe have created a new version of the influential Barnett measure using ICD codes, which allows for its wider application across health systems. We found that this measure of multimorbidity was associated with greatly increased mortality, indicating it could help predict poor outcome using administrative records.
Variation in Access to Specialist Care and Risk of Surgery in Patients with Inflammatory Bowel Disease: A Population-Based Cohort Study
Authors: Kuenzig Ellen , Stukel Therese , Murthy Sanjay , Nguyen Geoffrey , Talarico Robert , Benchimol Eric 
Published: September 2018

IntroductionInflammatory bowel disease (IBD; subtypes: Crohn’s disease (CD) and ulcerative colitis (UC)) is a chronic disease of the gastrointestinal tract with rising prevalence among people ≥65y. Rural residents, especially those ≥65y, have decreased access to specialist care. Specialist care is associated with lower risk of hospitalization and surgery.
Objectives and ApproachWe evaluated variation across physician networks in access to specialist care and surgery among incident patients ≥65y in Ontario health administrative data. Access to specialist care was defined as: ≥1 outpatient visit to gastroenterologists or the majority of IBD-specific outpatient care by gastroenterologists. Variation was assessed with multilevel logistic regression and median odds ratios (MOR), adjusting for age, sex, distance from IBD physician, comorbidities, neighbourhood income, and rural/urban. Models evaluating surgical risk also adjusted for specialist care use, emergency department visits, and hospitalization at diagnosis. Network-level variables included rurality (RIO score), population colonoscopy and gastroenterologist supply.
ResultsThere was significant variation in having ≥1 gastroenterologist visit (CD p=0.0001, MOR 3.3; UC p<0.0001, MOR 3.1) and gastroenterologist providing the majority of care (CD p=0.0001, MOR 3.0; UC p<0.0001, MOR 3.7) within 12 months of diagnosis. Variation remained significant after accounting for network-level characteristics (≥1 gastroenterologist visit: CD p=0.0002, MOR 2.6, UC p<0.0001, MOR 2.2; majority of care: CD p=0.0002, MOR 2.4; UC p<0.0001, MOR 2.4). In CD, there was no variation in the five-year risk of surgery (p=0.07, MOR 1.3) and was unchanged by network-level factors (p=0.13, MOR 1.3). Variation in the risk of colectomy exists for patients with UC (p=0.016, MOR 1.3) and was not reduced when accounting for network-level characteristics (p=0.019, MOR 1.3).
Conclusion/ImplicationsAccess to specialist care among patients with elderly-onset IBD is varies greatly between networks but this variation cannot be explained by differing provision of gastroenterological services across physician networks. Further research is needed to understand the factors that influence access to care and outcomes in elderly patients with IBD.
Mapping Clinical Contents onto Longitudinal Depictions of Cross-Continuum Service Events in Island Health: Clinical Context Coding Scheme
Authors: Koval Andriy , Moselle Kenneth 
Published: September 2018

IntroductionAll bits of clinical information acquire meaning against a backdrop of longitudinal engagement with a potentially large constellation of services. Full cross-continuum transactional data will be refractory to analysis unless the full continuum of service locations can be rendered in a form that is transparent with regard to target populations.
Objectives and ApproachThe work entailed two streams of activity: (1) building a six-dimensional framework (Clinical Context Coding Scheme - CCCS) that is layered directly onto the full array of secondary and tertiary service locations to render transparent the clinical function of the services; and (2) developing tools that work from that framework to reduce very large numbers of granular service entities down to a smaller number of clinically-functionally homogeneous entities. This solution serves both to supply the data in an analyzable form, and to address problems of small cell sizes and associated challenges around risk for re-identification of high-dimensional longitudinal data sets.
ResultsThe CCCS consists of an extensible array of meta-data categories (currently six) that are layered onto each of the 1700 service locations extracted from the location build in Island Health’s deployment of the Cerner EHR. This scheme was linked to the large body of longitudinal encounter data in Island Health. Service encounters, classified and aggregated using this CCCS scheme, were used to perform the following functions: (a) supply a base longitudinal encounter layer onto which other data sets could be superimposed (linked); (b) generate within-person-over-time visualizations of individual patients that reflects full secondary and tertiary cross-continuum service utilization; (c) generate cohort definitions reflecting patterns of service utilization, and (d) generate aggregate level reports that summarize full cross-continuum service utilization for cohorts.
Conclusion/Implications
The CCCS produces views of patients that are more complete and/or quite different from those created with the “usual datasets” (e.g., Acute Care + ER). Applying the scheme to diverse populations (e.g. addictions; stroke patients) illustrates the scheme’s viability – and the consequences/costs of NOT bring the full continuum into focus.
How integration of the federal Indian Register has enhanced First Nations-specific analysis of ICES data
Authors: Schultz Sue , Jones Carmen , Walker Jennifer 
Published: September 2018

IntroductionIn Ontario, First Nations are increasingly seeking population-level data about the health of their citizens. However, First Nations people are not readily identified in standard health administrative data and indirect strategies, such as the use of on-reserve addresses, are limited in scope and validity.
Objectives and ApproachThe Chiefs of Ontario entered into a Data Governance Agreement with the Institute for Clinical Evaluative Sciences (ICES) that enabled the linkage of the federal Indian Register (IR) to data at ICES. This study examined the impact of the IR linkage on First Nations population estimates and location of residence, measured by postal code or residence code. Overall, and for each First Nation community in Ontario, we compared First Nations population estimates from the ICES data with and without the IR linkage to estimates available from Indigenous and Northern Affairs Canada (INAC).
ResultsWithout the IR, using only Ontario residence codes or postal codes that were unique to a given community, 62,242 individuals were identified as living in First Nations communities. This is approximately 30% lower than the current INAC on-reserve population estimate of 92,234 for First Nations communities in Ontario. Adding the IR allowed the use of non-unique postal codes as well, resulting in the identification of an additional 15,183 First Nations individuals. It also allowed the identification of over 113,000 First Nations individuals who live outside of First Nations communities, especially in urban areas. Finally, the combination of residence information and the IR permits communities to identify their registered member living within and outside their communities.
Conclusion/ImplicationsUsing the IR in combination with geographic residence information, made possible through the Data Governance Agreement signed between Chiefs of Ontario and ICES, will provide First Nations communities with more accurate and complete population estimates, which is key to the production of useful and relevant First Nations-specific health research.
Cancer Screening in the Toronto Central LHIN by Sub-region and Neighbourhood: Evidence from an Applied Health Research Question (AHRQ)
Authors: Ellison Lisa , Graves Erin , Ishiguro Lisa , Lofters Aisha , Vahabi Mandana , Damba Cynthia 
Published: September 2018

IntroductionThe Toronto Central (TC) LHIN has aligned its vision with the Ministry of Health and Long-Term Care and Cancer Care Ontario to prioritize participation in population-based cancer screening programs and to address screening inequities. This request was accepted by the ICES AHRQ review team to help impact policy and programs.
Objectives and ApproachBy linking cancer screening data to geographic, provider and immigration databases, underlying contributors and barriers to cancer screening can be better understood and used to target interventions to specific groups and areas of the province. Thus, the purpose of this study was to: 1) determine the rates of cancer screening in the TC LHIN by sub-region and neighbourhood, and 2) determine how these differences vary by immigration status, primary care provider characteristics and neighbourhood income level. Using OHIP billing claims, screening for breast, cervical and colorectal cancer was identified between fiscal years 2013 to 2016.
ResultsDuring the study period, 58.4% of eligible TC LHIN residents received a mammogram, 57.1% received a pap smear and 55.1% received colorectal cancer screening. Screening rates varied by Toronto neighbourhood: 48.4%–72.9%, 38.8%–70.1% and 42.7%–68.7% for mammograms, pap smears and colorectal cancer screening respectively. Residents who recently immigrated to Ontario received less cancer screening than non-immigrants; 51.8% of immigrant women eligible for cervical cancer screening received a pap smear compared to 60.4% of non-immigrant women in the TC LHIN East region. Not having a female physician (54.3% vs 68.6%), lacking comprehensive care (55.6% vs 62.5%), having a foreign trained physician (56.6% vs 64.7\%) and living in a lower income neighbourhood (51.6%-62.5%) were other factors associated with lower rates of cancer screening.
Conclusion/ImplicationsCancer screening rates vary according to neighbourhood, and certain groups may be vulnerable to inadequate screening. These findings will help to address cancer screening disparities due to structural barriers, and will help in the delivery of culturally appropriate and relevant cancer screening educational packages and outreach programs in Toronto.
Challenges in linking administrative data for monitoring bloodstream infection in neonatal units in England and Wales
Authors: Fraser Caroline , Gilbert Ruth , Blackburn Ruth , Muller-Pebody Berit , Harron Katie 
Published: September 2018

IntroductionMonitoring risk-adjusted trends of neonatal bloodstream infection (BSI) is vital and linkage of neonatal electronic health records to national infection surveillance enables this. We demonstrate why changes in data quality and collection methods over time must be accounted for to minimise spurious findings.
Objectives and ApproachFirst, we determined the effect of a system change in 2014 (changed from only clinically relevant BSI to automated reporting of all BSI), by investigating changes in number of all BSI and BSI excluding the contaminants coagulase-negative staphylococci for infants aged <1 year reported to infection surveillance, using interrupted-time-series Poisson regression. Second, we evaluated the impact of changes in identifier completeness over time in each database, and determined variation in infection rates according to linkage method (deterministic linkage on NHS number or probabilistic linkage). Third, we will use multiple imputation when link status cannot be determined due to missing identifiers.
ResultsThe number of BSI reported to infection surveillance system following the change in data collection increased by 34% (incidence rate ratio (IRR) of 1.34, 95% confidence interval 1.28-1.40) for all BSI compared to 19% (IRR 1.19, 1.12-1.27) excluding coagulase-negative staphylococci. Completeness of NHS number in infection surveillance increased from 69% (3,296/4,792) in 2010 to 92% (3,037/3,307) in 2017. We linked 12,003 neonatal admissions to 15,571 BSI episodes (2% of 497,936 admissions and 41% of 37,660 BSI). The proportion of links that were deterministic changed from 83% (1,089/1,307) in 2010 to 96% (968/1,008) in 2017. There were 12,094 BSI for which the link status could not be determined due to missing identifiers; multiple imputation will be used to determine if any are links.
Conclusion/ImplicationsSpurious trends in infection incidence can arise from changes in data collection and quality, impacting the quality of linkage to clinical data. Data quality and system changes must be explored in each source dataset before analysis. Probabilistic linkage and imputation of missing data minimises spurious findings due to data quality.
Cross-sector service use among youth and young adults involved in the Alberta provincial justice system
Authors: Cui Xinjie , Werk Christine 
Published: September 2018

IntroductionYouth and young adults who are involved in justice and correctional system often have complex service needs and experience poor health and social outcomes. To improve outcomes for these young Albertans, it is important to understand their characteristics and service utilization patterns across health and social areas.
Objectives and ApproachThe current analysis provides cross-sector service use information on Alberta youth and young adults aged 12 to 25 who were involved in the criminal justice system from 2005 to 2011. Administrative data linked data across multiple Alberta provincial ministries were used for the analysis. These included over 20 programs and services in areas such as health, education, child intervention, disability supports, income support, and justice and corrections.
ResultsOffence types and court outcomes varied by social-demographic characteristics such as age, sex, social economic status, and residential mobility. Elevated mental health and high cost health services use was observed among youth involved in the criminal justice system. Access of social programs such as Child Invention service, Child Support services, Income Support and disability support services was more prevalent among youth and young adults who were involved in the justice system. A higher number of offences was associated with worse education and health outcomes.
Conclusion/ImplicationsCross-sector data linkage and analysis offer a unique opportunity for better understanding of clients/patients and services/programs at the broad system level. Knowledge gained through linked data can inform cross-ministry policies and integration of services.
Using linked routinely collected health data to explore the burden of respiratory syncytial virus (RSV) in Scotland
Authors: Reeves Rachel , Douglas Anne , Campbell Harry 
Published: September 2018

IntroductionRespiratory syncytial virus (RSV) is the most frequent cause of lower respiratory tract infections (RTIs), particularly bronchiolitis, in young children worldwide. In order to inform policymaking and regulatory decisions regarding novel RSV vaccines and therapeutics, the health and economic burden of RSV needs to be quantified in further detail.
Objectives and ApproachThis project is part of the REspiratory Syncytial virus Consortium in Europe (RESCEU), a collaborative IMI funded EU project assembling routinely collected health data from at least seven European countries to produce detailed estimates of RSV health and economic burden. This study links national data on hospital admissions, deaths, RSV laboratory testing, prescriptions, and maternal/perinatal data. Using this linked data we calculate rates of hospital admissions, intensive care unit (ICU) admissions, and deaths (a) potentially due to RSV, (b) likely due to RSV, and (c) confirmed due to RSV. We also investigate maternal and perinatal characteristics associated with RSV-related episodes.
ResultsRSV is a major cause of hospital admission in Scotland, particularly in children <6 months old. Around 2,000 admissions with a primary diagnosis of bronchiolitis occur in children <12 months old per year, on average, with approximately 75% of these estimated to be due to RSV. Children with known clinical risk factors, such as prematurity or chronic conditions, are at increased risk of ICU admission and death due to RSV. Results will be presented on the age- and risk-group specific hospitalisation, ICU admission and mortality rates for RSV-associated RTI in children <5 years old. The maternal and perinatal characteristics (e.g. maternal smoking, type of delivery, breastfeeding status, birthweight, APGAR score (5 mins), mechanical ventilation, oxygen use) associated with RSV-related RTI hospital episodes will be presented.
Conclusion/ImplicationsThis is the first study to explore the national burden of RSV in Scotland. Our results demonstrate the benefits of using linked routinely collected data to explore the epidemiology and burden of infectious diseases and inform policymaking and regulatory decisions. Our methodology can be applied to other countries and pathogens.
The BC SUPPORT Unit Data Platform: Offering Data-Related Services To Researchers In British Columbia
Authors: Kesselring Sarah , Mander Bryony , Djurdjev Ognjenka , Moselle Kenneth , Portales-Casamar Elodie , Schuckel Victoria , Singer Joel , Sobolev Boris , Wong Shirley , Brasher Penny , Cherban Erin , Young Ella , Sanderson Kelly , Neuman Maureen , Moran Kelly , Enjo Dan , McGrail Kim 
Published: September 2018

IntroductionThe Canadian Institutes of Health Research (CIHR) and provinces co-fund local Units to increase the quality and quantity of patient-oriented research. These SUPPORT (Support for People and Patient-Oriented Research and Trials) Units include a prominent Data Plan component. The BC Plan is the result of collaboration between many organizational partners.
Objectives and ApproachA Data Advisory Committee comprised of eight organizational partners worked together for several months in 2016-2017 to develop BC’s provincial Data Plan. The Data Plan includes seven objectives; in general, the plan seeks to make additional data available for research, increase the speed and transparency of data access, and offer services to enable more efficient data use. The services resulting from the Data Plan are intended to improve support for the entire continuum of a research project, from developing a research question to analyzing the results. Several projects are part of Ministry of Health-led work developing a Health Data Platform.
ResultsThe projects initiated so far as part of the Data Plan include:

BC Data Scout\textsuperscript{TM}: an online tool that provides aggregate cohort information to inform research question development;
REDCap: software to support privacy-sensitive data collection and management;
INFORM: software to support data collection for complex clinical research studies and trials;
Direct Access: enables Population Data BC to access BC Ministry of Health databases so researchers have access to up-to-date data;
Streamlining: making the data request process more efficient;
New datasets: several projects that will provide new data sources, including patient experience and outcome measures and secondary use data drawn from electronic medical records; and
Inventory: an online catalog for all high-value and linkable data sets available to researchers.

Conclusion/ImplicationsThe services and tools included in BC’s Data Plan will help researchers develop and deliver world-class research and inform important health care decisions. The patient-oriented focus of these services help to ensure that research is done in partnership with patients and centered on research questions that matter to them.