bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effect of neighbourhood crime and deprivation on pregnancy outcomes. A quasi-experimental study using routine administrative records
Authors: Clemens Tom , Dibben Chris 
Published: September 2018

IntroductionWe know that rates of adverse pregnancy outcome such as low birthweight and preterm births vary both by socio-economic status and across geographical areas. Furthermore, more deprived neighbourhoods show higher rates of adverse outcomes. However, much of the evidence comes from cross-sectional observational studies where causality is difficult to assess.
Objectives and ApproachNeighbourhood crime and a resultant increase in maternal stress is a plausible explanation for the deprivation-birth outcome relationship. Without an experiment, isolating this pathway from other confounding effects is challenging. Because many mothers (within the Scottish maternity dataset) experience multiple pregnancies and varying exposure for the same person, we can assume a quasi-experimental allocation to exposure. We model associations as both within mother (comparing exposures between pregnancies to the same mother) and between mother (comparing different people between more and less deprived areas) partitioning the variation and effects accordingly.
ResultsWe find that both composite neighbourhood deprivation and neighbourhood crime specifically is associated with reduced birthweight. However, the composite neighbourhood deprivation measure is only significant when modelled as a between mother effect. Neighbourhood crime on the other hand is significantly associated with both between mother and within mother effects (though the latter is reduced compared to the former). These results suggest that much of the observed relationship with deprivation in general is therefore confounded by factors associated with the composition of individuals in these areas rather than an area deprivation effect per se. In contrast, the association with neighbourhood crime can be considered in isolation from the composition of individuals and is therefore likely to be an independent “area” effect.
Conclusion/ImplicationsThese results are important because outcomes of pregnancy including birthweight and premature births influence health and social outcomes not just in infancy but across the life course. This study suggests policies targeting neighbourhood crime may help to reduce neighbourhood disparities in pregnancy outcomes and therefore health inequalities in general.
Environmental Risk Factors on Suicide of Children and Young People
Authors: John Ann , Del Pozo Banos Marcos , Lloyd Keith 
Published: September 2018

IntroductionThe World Health Organization recognizes suicide as a public health priority. Recent studies have focused on health care contacts for those who complete suicide to highlight opportunities for intervention. In Wales, electronic health records (EHR) are routinely collected, providing an invaluable opportunity for researching suicide risk factors.
Objectives and ApproachWe aim at linking primary and secondary EHRs to identify suicide risk factors for those between 10 and 24 years of age. We linked 7 different demographic and health datasets from the Secure Anonymised Information Linkage Databank UK, and identified a total of 471 cases between 2001 and 2015, 10 matched controls of same gender and age (±1 year), as well as cases’ and controls’ mothers. We measured a number of factors from primary and secondary care including self-harm, mental health issues and drugs and alcohol misuse. We used conditional logistic regression to conduct our analyses.
ResultsPreliminary results suggest that environmental factors extracted from cohabitants and mothers have a statistically significant effect even after adjusting for deprivation. Self-harm, possible maltreatment and alcohol and drugs misuse seem to be strongest factors of those studied. Factors related to mental health have smaller and more complex effects when adjusting for deprivation.
Conclusion/ImplicationsOur preliminary analysis indicate that EHR can be linked to study the effect of the environment on suicide risk. Once completed, we hope this study will help to identify other suicide risk factors, improve our knowledge of the mechanisms underlying suicide and help to identify opportunities for intervention and improve care.
Establishment of a National Homelessness Prevention Programme dataset to enable an anonymised longitudinal dynamic cohort based study
Authors: Lowe Sarah , Johnson Rhodri , Jones Ian , Morrison-Rees Sian 
Published: September 2018

IntroductionWelsh Government invests over £120m annually in housing related support to help prevent and tackle homelessness under the ‘Supporting People Programme’.
A 2016 data-linkage Feasibility Study indicated health-service utilisation reductions post-intervention, and led to a four year project to create a national, all-Wales dataset to provide robust statistical results.
Objectives and ApproachEstablish data sharing agreements, acquire and import anonymised individual-level data into the SAIL Databank. Create a research ready dataset, designed to permit annual administrative data updates to form dynamic cohort and control groups.
Create several control group methods: 1) Internal Programme Data; 2) Matched controls; 3) Healthcare-Utilisation Patterns; 4) External Data Sources.
Link to routine health data, obtain and link to other public service data to gain a deeper understanding of the Programme; how it affects use of other public services, and whether it helps people live independently.
Complete statistical analysis using a Generalised Linear Mixed Modelling approach.
ResultsData sharing agreements, data acquisition and standardisation complete for nineteen of twenty-two Unitary Authorities in Wales. Temporal coverage varies by Unitary Authority (2003-2017). 2016 data measures: match rates >85%; 57% female; lead reason for support (top 5) : ‘General’ 20%, ‘Mental Health’ 15%, ‘Older People’ 14%, ‘Domestic Abuse’ 9%, ‘Young People’ 7%.
Various control group methods employed: 1) Internal ‘Programme’ Data – no support taken up; 2) Matched controls; 3) Healthcare-Utilisation Patterns – rejected due to sparse outcome data; 4) External Data Sources being further explored.
Health data-linkage (emergency admissions, emergency department attendance and primary care events) complete. Ongoing discussions to obtain sample social care, and police call data during 2018.
Statistical analysis underway with results planned to be published during the summer of 2018.
Conclusion/ImplicationsDespite many challenges, creation of a national linked dataset for people at risk of homelessness is possible with collaborative working between central government, academic and local government bodies. This ‘Administrative Data Research Centre Wales’ project has created a rich research resource enabling statistical analysis to answer research questions around homelessness.
Self-harm following release from incarceration: Patterns and measurement issues
Authors: Borschmann Rohan , Young Jesse , Kinner Stuart , Spittal Matthew 
Published: September 2018

IntroductionDespite an elevated prevalence of self-harm in the incarcerated adult population, little is known about patterns of self-harm following release from prison.
Objectives and ApproachBaseline self-report interviews with 1315 adults immediately prior to release from prison in Queensland, Australia, combined with interrogation of linked health data from >3750 post-release emergency department presentations, >2000 ambulance attendances, and corrections data during periods of re-incarceration.
ResultsApproximately 5% of all contacts with medical emergency services following release from prison resulted from self-harm. These were associated with being Indigenous, having a lifetime history of a mental disorder and having been identified by prison staff as being at risk of self-harm. Agreement between self-reported self-harm and medically-verified episodes of self-harm was poor.
Conclusion/ImplicationsEmergency services contacts resulting from self-harm following release from prison are common and represent an opportunity for tertiary intervention for self-harm. Our findings suggest that a self-reported history of self-harm should not be considered a reliable indicator of prior self-harm, or of future self-harm risk, in incarcerated adults.
Quality of linked data: Linking the National Hospital Care Survey Data to the National Death Index
Authors: Mirel Lisa , Resnick Dean , Campbell Scott , Golden Cordell 
Published: September 2018

IntroductionData linkages can produce rich data resources to address a variety of research topics. However, assessing linkage quality can be challenging given that there are many approaches and no clear best practices.
Objectives and ApproachThrough its Data Linkage Program, the National Center for Health Statistics (NCHS) links national survey data with vital and administrative records. A recent linkage of the National Hospital Care Survey data with the National Death Index employed a new linkage methodology, which included a first time approach for validating the results within the linkage algorithm.
ResultsThe new methodology includes two passes: a deterministic linkage, followed by a probabilistic approach based on the Fellegi-Sunter methodology. In the second pass, a key identifier, Social Security Number (SSN), was not used as a linkage variable but instead to determine link accuracy, when available on the patient record. A model was then built to predict link accuracy status according to the computed Fellegi-Sunter total pair weight and then used to estimate it for those patient records without an SSN. Results from this new approach were compared with results from prior linkage methodologies and generated higher match rates and lower error rates. The linkage methodology designed for this study is now being tested on other types of input data such as data from household surveys.
Conclusion/ImplicationsThe linkage approach may be incorporated into additional linkages conducted by NCHS. This talk will describe the input sources for this linkage, the methodology used, the error rate assessment and then discuss conclusions and implications for precision and efficiency.
Enhancing description of hospital-conditions with ICD-11 cluster coding: Better codes for monitoring and prevention
Authors: Southern Danielle , Eastwood Catherine , Quan Hude , Ghali William 
Published: September 2018

IntroductionExposure to health care events sometimes has unintended and undesired consequences. Health care and complications arising in the course of care are diverse and complex. Representing them comprehensively in information systems is challenging, and presently beyond the bounds of practicality for routine administrative information systems that include ICD coded data.
Objectives and ApproachThe ICD-11 conceptual model for hospital-acquired conditions has 3 components: 1) harm to patient 2) cause or source of harm and 3) mode or mechanism. A key feature of the Quality and Safety (Q\&S) code-set in ICD-11 is that a cluster of codes is required to represent an event or injury. Use of the term ‘cluster’ is novel in ICD-11 and so is the extent and the requirement for post-coordination. The cluster required to code a Q\&S case has three codes, one for each of the three components of the model given above.
ResultsThe first component, ‘harm’, is represented by an ICD–11 diagnosis code, from any chapter of the classification. Q\&S causes or sources of harm fall into 4 types that capture events caused by substances (drugs and medicaments, etc.), procedures, devices, and a mix of other types of causes (e.g. problems associated with transfusions, incorrect diagnosis, etc.). Q\&S ‘mode or mechanism’ refers to the main way in which the ‘cause’ leads to the ‘harm’ and are specific to the type of ‘cause’ (Table 1).
Table 1 - Examples of corresponding Q\&S Mode or Mechanism

Cause or Source of Harm
Mode or Mechanism

Substance
Overdose, under-dose, wrong substance.

Procedure
Accidental perforation of an organ during a procedure.

Device
Dislodgement. Malfunction.

Other cause
Mismatched blood. Patient dropped during transfer from OR table.

Conclusion/ImplicationsThis new conceptual model for coding healthcare-related harm, dependent on the clustering of codes, has great potential to improve the clinical detail of adverse event descriptions, and the overall quality of coded health data, for better monitoring and strategies for prevention.
Linking household level GIS-generated environmental exposure scores with individual level anonymised health data
Authors: Mizen Amy , Rodgers Sarah , Fry Richard , Lyons Ronan 
Published: September 2018

IntroductionThe dose-response relationship between exposure to food and BMI, has not been widely investigated. Furthermore, household-level, GIS-generated food environment exposure scores have not previously been linked with individual-level, anonymised BMI data. This study linked GIS-generated residential level environmental exposure scores with historical anonymised, health data held in the SAIL databank.
Objectives and ApproachHousehold level GIS-generated exposure data for a region of about 1 million people were anonymised into SAIL using the ‘split-file’ method. All individuals living in the 633,884 homes at the time of data collection (2009-2010) were flagged using a population register. Separately, a cohort of 1147, 11-13 year old pupils were linked to their health data before joining to their environmental exposures. Two subgroups were established within the linked dataset: individuals living at 4.8km or less from the school they attended were assumed to walk to school (“walkers”) and pupils who lived further than 4.8km were flagged as “non-walkers”.
ResultsA total of 916 pupils (80%) were successfully linked to the population register. The BMIs were collected in 2009-2010, but more recent data is likely to have a greater proportion of successful links (more recently, 97% of individuals and their health data have been linked to their home and exposures in SAIL). Erroneous BMIs were removed (n=33, 2.9%). Anonymised exposure data were linked with the remaining 883 (77%) individuals. The dataset contained 352 males (39.9%) and 531 females (60.1%); of these, 38% were from deprived areas and 62% lived in affluent areas. There were 431 (48.8%) pupils in the “walkers” group and 452 (51.2%) in the “non-walkers” group. In the “walkers” group, 13% were obese compared with 22% of “non-walkers” (chi-squared = 12.3, p <0.05).
Conclusion/ImplicationsWe generated novel regional exposures to combine with historical anonymised health data. Household and individual level linkage of environmental data to health cohorts contributed to the literature to help develop beneficial societal policies. We recommend routine national collections of height and weight for children to allow longitudinal retrospective analyses.
The Impact of Linked Administrative Data on Community Development of Integrated Mental Health Hubs: a Case Study
Authors: Parker Naomi , Salt Valerie , Scott Allison N , Scott Cathie , Lau Jason 
Published: September 2018

IntroductionIncreasingly, communities are designing and implementing contextualized approaches to integrated service delivery. Having communities in the lead is critical to successful design and implementation. However, how do researchers work with communities to ensure accurate contextual interpretations of linked administrative data?
Objectives and ApproachPolicyWise for Children & Families has been working with communities to create a framework and assist in the implementation of integrated Community-based Mental Health Service Hubs for youth ages 11-24. The approach used to support these communities included multiple sources of data to highlight the need for youth specific mental health care, integrated service delivery and the opportunity for system transformation. This included, but wasn’t limited to, a qualitative environmental scan and individual-level linked administrative data from PolicyWise’s Child and Youth Data Lab.
ResultsThe goal of presenting the qualitative and quantitative data summaries was to inform community-led design and implementation of the Mental Health Service Hubs. This presentation describes the constructive interplay of community context, qualitative literature and linked administrative data. Community context and the qualitative environmental scan assisted community members in interpreting the administrative data.
Conclusion/ImplicationsThis applied project provides an example of how community members contextualize information from linked administrative data and environmental scan findings to influence program development. The implications of this is that data can reinforce or reshape what communities know about service use and impact how they proceed with planning.
Measuring equity in per capita primary care investment in Ontario: Challenges for data linkage and analysis
Authors: Schultz Sue , Glazier Rick , Green Michael , Kiran Tara , Bayoumi Imaan , Tranmer Joan , Frymire Eliot 
Published: September 2018

IntroductionFifteen years ago almost all primary care physicians (PCPs) were paid fee-for-service. Now, many physicians receive other payments as well, including capitation payments, incentives and bonuses and funding for other health professionals. It is challenging to track these changes in primary care payment and understand how they relate to individual patients.
Objectives and ApproachThe objectives of this study were to assess changes in PCP payments from 2002/03 to 2011/12 and examine differences in per capita investment by urban-rural status, recent arrival (proxy for immigrant status) and income quintile. This required a three-step approach: assigning payments to physicians, assigning patients to physicians and then apportioning the payments by patient. Payments were apportioned based on the type of payment and how the data were captured. For example, capitation payments were paid monthly, but without any detail as to which patients they were for, so all capitation payments were summed and apportioned among all rostered patients.
ResultsAll PCPs for whom we had payment data and to whom patients could be assigned were included. Three types of physician-patient 'relationships' were identified: the patient was on the physician's formal roster; the patient was 'virtually' rostered to the physician who provided the plurality of their care; or the patient was part of the physician's overall panel, which includes all patients seen during the year, rostered and not. The type of relationship determined which payment were allocated to each patient. When the $3.5B in payments were apportioned and different populations compared, we found inequities in new primary care investment by income, immigrant status and rurality. For example, we found a disproportionate investment in interdisciplinary teams for non-immigrant Ontarians living in more well-off suburban areas.
Conclusion/ImplicationsEstimating per capita primary care investment is a challenging but worthwhile undertaking. The results of this study suggest that the Government of Ontario should facilitate increased participation in new primary care models by immigrants and people living in major urban centres.
The Use of Long-Acting Injectable Antipsychotic Therapy for Schizophrenia
Authors: Jiang Jason , Bakal Jeff , Chue Pierre , Snaterse Mark , Urichuk Liana , Dursun Serdar , McCabe Christopher , McAlister Finlay , James Deborah , Richer Lawrence 
Published: September 2018

IntroductionAntipsychotic medications form the cornerstone of schizophrenia treatment. However, only a minority of patients adhere to their initial antipsychotic regimen. It’s expected that Long-Acting Injectable (LAI) antipsychotics improves patient adherence to treatment, however previous research comparing the use of first generation LAI’s against oral antipsychotics reported results that were inconclusive.
Objectives and ApproachExplore the effectiveness of the use of LAI’s in the delivery of mental health services in Alberta.
Using linked data from AHS Analytics:

Physician claims
National Ambulatory Care Reporting System (NACRS),
Discharge Abstract database (DAD)
Pharmacy Information Network (PIN)
Alberta Provincial Registry data

Define a cohort of patients on antipsychotic medications.
Explore and contrast outcomes related to the use of LAIs against other antipsychotic medication types. Specifically using linked data to define:

Treatment Adherence
Utilization of LAI vs. other medication
Demographic differences
Outcomes pre- and post-LAI treatment

ResultsA patient cohort was established containing only cases from April 1, 2013 to March 31, 2015. Additional data was used to perform a two year washout and a one year follow-up.
Case and medication definitions were determined by a team of psychiatric clinicians. Patient comorbidity information was extracted using previously validated methods.
Overall, 6349 incident cases were identified.
Preliminary analysis indicate:

Overall patient cohort is older than expected
Use of additional medication types is correlated with greater health services utilization after diagnosis
Patients on only oral medications appear to have lower treatment adherence
Males seem to have higher treatment adherence than females
No significant differences were found between patients with rural vs. urban postal codes

Conclusion/ImplicationsWe faced significant challenges when defining cases, medication use and outcomes. However, the linkage of a large number of data sources gives us powerful and multi-faceted insight into the use of antipsychotic medication use in Alberta. Future work will include work on definition validations and deeper analysis of outcomes.