bluuebunny/crossref_metadata_2025 huggingface dataset:
Linking lab, program, and administrative data to provide comprehensive colorectal cancer screening status of patients to primary care providers in Calgary, Alberta
Authors: Law Jessica , Viczko Jeannine , Hilsden Robert , McKenzie Emily , Watt Mark , Potestio Melissa , McGregor S Elizabeth
Published: September 2018

IntroductionColorectal cancer (CRC) screening is associated with significant reductions in burden, mortality and cost. Primary care providers in Alberta do not have access to integrated CRC testing histories for patients. Providing this information will support CRC screening among patients at average and high risk, follow-up of abnormal tests, and surveillance.

Objectives and ApproachCalgary Laboratory Services, Colon Cancer Screening Centre, Alberta Cancer Registry, and endoscopy data were linked to create a comprehensive CRC screening history at the patient level. Based on screening histories and the current Clinical Practice Guideline, an algorithm was created to determine CRC screening statuses with the aim of providing accurate screening rates when linked to primary care provider patient panels. Results from the linkage are designed to be incorporated into clinic and EMR workflow processes to support adherence to evidence-based screening recommendations at the point of care.

ResultsA comprehensive assessment of screening status was determined by integrating Fecal Immunochemical Test (FIT) and colonoscopy data. Among a sample cohort, patients were identified as being due for screening with FIT, requiring follow-up for a positive FIT test, or requiring appropriate surveillance for a positive-screen or abnormal colonoscopy findings. A summary report, actionable list, and resources were developed to convey findings. The summary report displayed CRC screening rates for a provider’s panel. The actionable list provided CRC screening statuses for each patient aged 40 to 84 indicating patients due for screening with FIT, for follow-up of positive FIT, or for surveillance colonoscopy. The resources were developed to support quality improvement for colorectal cancer screening for patients.

Conclusion/ImplicationsThe data linkages and algorithm provide comprehensive CRC screening, follow-up, and surveillance information that could support guideline-adherent screening, increase screening rates, reduce duplication or unnecessary testing, and provide primary care providers with timely and robust information to support clinical decisions for individuals inside and outside of the target screening population.
Improving the quality of care pathways for sarcoma patients and the advantages of using WCISU’s (Welsh Cancer Intelligence Surveillance Unit) national cancer registry
Authors: Griffiths Rowena , Akbari Ashley , Huws Dyfed , Lyons Ronan , Rolles Martin , Vass Johanne
Published: September 2018

IntroductionSoft Tissue Sarcoma (STS) diagnosis is difficult due to its nature and the variability of its occurrence on the body. To improve patient outcomes a better understanding was needed of the care pathways experienced by the patient from initial presentation to final treatment.

Objectives and ApproachSeveral items of information are necessary, within the data, to identify a care pathway. A correct STS diagnosis, a presentation date or first investigation date, a diagnosis date and any subsequent treatment dates. Identifying cases in hospital data, using International Classification of Diseases (ICD10) codes - C40, C41, C47 and C49 - based on cancer site - can miss cases and cause difficulties when trying to distinguish the difference between the investigation and treatment stages. Having access to WCISU’s national cancer registry, proved advantageous and enabled the routine data to be validated.

ResultsAttempts to identify differences between investigative and treatment procedures using the procedure codes available in hospital data was unhelpful due to variations in coding.

However, WCISU’s national cancer registry records all cases of cancer diagnosed in Wales using both ICD10 and International Classification of Diseases for Oncology codes to record cancer morphology. In addition, it records the date of diagnosis and treatment start dates. Using the cancer registry it was possible to cross-check the cases extracted from the hospital data and identify the diagnosis and treatment dates. By matching the treatment dates back to the hospital data it then became possible to analyse the procedure codes to see how many treatments were being delivered, the type of treatment and the periods covered.

Conclusion/ImplicationsOnce accurate diagnosis and treatments dates were identified, it was possible to drill further into the hospital data to see the finer detail of the procedures the patient received. Utilising independent data sources made it possible to develop an enriched view of patient care pathways from diagnosis through to treatment.
Validation of Acute Kidney Injury e-alert system in Wales
Authors: Davies Gareth , Scale Timothy , Akbari Ashley , Chess James , Lyons Ronan
Published: September 2018

IntroductionAcute Kidney Injury (AKI) is a serious condition associated with increased mortality/morbidity and occurs in approximately 20% of hospital admissions. A Welsh AKI alert (e-alert) system has been in place since 2014, aiming to improve patient outcomes and care standards through early recognition of AKI using a retrospective dataset.

Objectives and ApproachThe e-alert algorithm was re-produced in SQL (structured query language) and applied to serum creatinine (SCr) values for patients from pathology departments in Abertawe Bro Morgannwg health board (ABMUHB)  2011-2014, held in the Secure Anonymised Information Linkage (SAIL) databank. The algorithm utilises ratios between current SCr value (C1) to lowest SCr value within the previous 7 days (RV1), SCr median values from the previous 8-365 days (RV2), and lowest SCr within 48hrs (D). >50% increase in RV1 or RV2 or >26µmol/L above D triggers an alert. Using a renal dataset to create a timeline we created a temporal AKI cohort.

Results2,407,590 SCr tests were performed on adult patients with 2,077,493 of these coming from people in the local area who were not on renal replacement during the time-period. The average ABMUHB population for 2011-2014 was 520,293 (2011: 517,981; 2012: 519,481; 2013: 520,710; 2014: 523,001). 85,272 (4.1%) of these tests triggered alerts for AKI. The incidence per 100,000 population of AKI for 2011-2014 were 1767, 1723, 1717, 1660 (average 1,717). The first AKI episodes per year for 2011-2014 respectively were stage 1 (least severe): 78.9%, 79.3%, 79.3%, 79.4% (average 79.2%); stage 2: 13.3%, 13.7%, 13.1%, 13.7% (average 13.5%);  stage 3 (most severe): 7.8%, 7.0%, 7.6%, 6.9% (average 7.3%).

Conclusion/ImplicationsThe AKI e-alert algorithm can be effectively reproduced using standard query language. The AKI findings in this population are comparable to others published. The use of a renal dataset using both records of renal replacement timeline and individual dialysis session may identify and rectify where alerts have not been generated.
Postpartum Hemorrhage: Differences in Definition, Data and Incidence
Authors: Walther Diana , Halfon Patricia , Desseauve David , Vial Yvan , Burnand Bernard , Le Pogam Marie Annick
Published: September 2018

IntroductionPostpartum hemorrhage (PPH) remains a major cause of morbidity and mortality worldwide. Geo-temporal comparisons of in-hospital PPH incidence remain a challenge due to differences in definition, data quality and the absence of accurate, validated indicators.

Objectives and ApproachTo compare the incidence of PPH using different definitions to assess the need for a validated indicator. Singleton births from 2014-2016 at Lausanne University Hospital, Switzerland, were included. PPH was defined based on 1) clinical diagnosis using International Classification of Diseases (ICD-10-GM) PPH diagnostic codes, 2) volume of blood loss ≥500ml for vaginal births and ≥1000ml for cesareans 3) peripartum Hb change >2g/dl in vaginal births and ≥4g/dl in cesareans and 4) fulfillment of criteria from definition one, two or three. Data were extracted from hospital discharge data and linked with electronic health records.

ResultsThere were 2529, 2660 and 2715 singleton births in 2014, 2015 and 2016, respectively, 28.8% were cesareans. Peripartum change in Hb was available for 17% of births. The incidence (95% CI) of PPH in 2014, 2015 and 2016 was, respectively: 1)6.0% (5.1, 7.0), 6.3% (5.4, 7.3) and 7.9% (6.9, 9.0) based on diagnostic codes; 2)7.9% (6.8, 9.0), 7.1% (6.2, 8.2) and 7.2% (6.3, 8.3) based on blood loss volumes; 3)2.4% (1.8, 3.1), 2.7% (2.1, 3.4) and 3.5% (2.9, 4.3) based on change in Hb; 4)11.3% (10.1, 12.6), 10.4% (9.3, 11.6) and 11.0% (9.9, 12.3) based on the combined definition. Differences in PPH incidence by year between definitions one and four, two and four and three and four were all statistically significant (McNemar p-values

Conclusion/ImplicationsIncidence varied widely according to definition and data availability, not to mention data quality. Our results highlight the need for a validated PPH indicator to enable monitoring. Future prospects include the validation of a diagnostic code based PPH indicator aided by text mining in electronic health records.
High quality linked data for stroke obtained using non-government clinical registry and routinely collected hospital and death data
Authors: Kilkenny Monique , Kim Joosup , Andrew Nadine , Sundararajan Vijaya , Thrift Amanda , Katzenellenbogen Judith , Flack Felicity , Gattellari Melina , Boyd James , Anderson Phil , Lannin Natasha , Sipthorp Mark , Chen Ying , Johnston Trisha
Published: September 2018

IntroductionRecent advances in data linkage infrastructure in Australia mean that data can be linked based on various identifiers across datasets. In a first for Australia, we tested the feasibility of linking data between a clinical quality disease registry with Australian and state government health data across multiple jurisdictions.

Objectives and ApproachTo determine whether high quality linked data for stroke can be obtained using a non-government managed registry (Australian Stroke Clinical Registry, AuSCR), national death registry data (Australian government), and hospital admission and emergency presentation data (state governments) to assess the accuracy of consistent variables across the different datasets. We used a cohort design with probabilistic data linkage to merge patient-level records. Descriptive statistics presented for matching concordance and Cohen’s kappa for concordance across demographic variables. The sensitivity and specificity of in-hospital deaths collected in the AuSCR was assessed against national death registrations.

ResultsThere were 16,214 registrants in the study cohort. Their identifiers in the AuSCR from 2009-2013 were linked with death, emergency department and hospital discharge data from April 2004 to December 2016. In total, 99% of the AuSCR registrants were linked to one or more datasets; 98\% were linked with emergency presentation (80%) and/or admission (95%) data. Linkage to national death registrations identified 4,183 death; 1440 of these were identified as in-hospital deaths in both data sets demonstrating that in-hospital death classification in AuSCR had a 98.7% sensitivity and 99.6% specificity. Concordance between common demographic variables was excellent (kappa 0.84 for aboriginal status and kappa 0.99 for sex).

Conclusion/ImplicationsThe majority of AuSCR registrants were accurately linked to the Australian and state government datasets. Linkage quality was excellent and there was high concordance between common variables. The ability to reliably merge the datasets assures future comprehensive analyses of stroke care, ongoing health care resource utilisation and patient outcomes.
Using family physician Electronic Medical Record data to measure the pathways of cancer care
Authors: Jaakkimainen Liisa , Crampton Noah , Pinzaru V. Bogdan , DelGiudice Lisa , Tu Karen
Published: September 2018

IntroductionGaps in care have been identified along the disease pathway for specific cancers. However, no real-world data exists to identify wait times along these cancer pathways. Secondary use of family physician (FP) electronic medical record data (EMR) can augment existing health administrative data in measuring steps in the care pathways.

Objectives and ApproachWe used FP EMR data to identify care pathways for lung cancer and breast cancer patients from the description of symptoms, to the initiation of investigations, referrals to specialty care and the receipt of specific treatments (surgery, chemotherapy, radiation treatment). Data from the Electronic Medical Record Administrative data Linked Database (EMRALD) held at the Institute for Clinical Evaluative Sciences (ICES) was used to identify a cohort of lung cancer and breast cancer patients. Data abstractors examined the FP EMR notes to identify pre-diagnostic symptoms, pre-diagnostic radiological test, biopsy results, oncology and surgical specialist referrals and post-diagnostic surgical and oncological consultations.

ResultsTo date, abstractors have reviewed the FP EMR notes for 300 lung cancer patient and 1200 breast cancer patients. Abstractors identified an index date where there was documentation of the first abnormal test result and/or a FP progress note documenting a “suspicious” or “concerning” sign or symptom. For both lung cancer and breast cancer patients, a pre-diagnostic index date was identified in 88.5% of FP EMR notes. For lung cancer patients 66.7% based were based on abnormal chest x-rays and for breast cancer patients 81.1% were based on abnormal mammograms. Pre-diagnostic symptoms were identified in 62.1% of FP EMR notes and 81.6% had post-diagnostic consultation notes. Wait times from the index date to seeing an oncological specialist were less than four weeks for all patients.

Conclusion/ImplicationsWe are able to use information from FP EMRs linked to health administrative data to identify pre-diagnostic care received by patients prior to their cancer diagnosis. This information can be used to identify care gaps and measure wait times in receiving cancer care from a patient’s perspective.
The impact of primary care management and comorbidities of COPD on length of hospital stay
Authors: Smith Kendal , Al Sallakh Mohammad , Akbari Ashley , Davies Gwyneth
Published: September 2018

IntroductionHealth Resource Groups (HRGs) are bundles of care that absorb similar financial resources. Variations in hospital length of stay (LOS) of patients with the same admission diagnosis and assigned HRG may reflect differences in pre-admission primary care services received by patients.

Objectives and ApproachWe investigated whether within HRGs, variations of LOS of chronic obstructive pulmonary disease (COPD) admissions were associated with differences in COPD management services received in primary care. Individual-level primary and secondary care data from the Secure Anonymised Information Linkage (SAIL) databank of Wales was used for admissions in 2015 with high-volume (n>30) HRGs. Effects of selected COPD primary care quality surrogate measures and comorbidities on LOS were analysed using a linear regression model adjusted for a modified Charlson co-morbidity index. The effect of completed pulmonary rehabilitation (PR) was analysed in a separate dataset for the Cwm Taf Health Board.

ResultsWe included 77,791 COPD patients, with mean age of 73.4 [SD=11.0], and 51.6% of which were males. Patients who were referred for a PR course prior to admission stayed 0.58 less days (95% CI = [0.18, 0.98], p<0.01), while those who completed a PR course stayed 0.76 less days ([0.25, 1.27], p<0.01). Non-significant associations were found where female patients stayed 0.34 days longer than males ([-0.01, 0.68], p=0.05), patients given flu vaccination stayed 0.39 less days ([-0.07, 0.86], p=0.10), and patients with anxiety diagnosis stayed 0.43 more days ([-0.03, 0.88], p=0.06).

Conclusion/ImplicationsLOS for COPD could potentially be reduced with further targeted services provided in primary care. Countries using HRGs with access to linked primary and secondary care data can unlock care insights, enabling live monitoring of the effectiveness of primary care interventions. This approach can be also used for other conditions.
NHS Scotland Public Benefit and Privacy Panel (PBPP) – Does a Proportionate Governance Review Work?
Authors: Morris Carole , Grey Ashley
Published: September 2018

IntroductionSince its’ inception in 2015, the NHS Scotland Public Benefit and Privacy Panel (PBPP) has approved over 200 applications for access to data. The PBPP are accountable to the public and must demonstrate their assessment of applications for data use in terms of envisaged public benefit and potential privacy risks.

Objectives and ApproachIn 2017 the first annual audit took place. The purpose of the audit exercise was twofold; establish that the governance process is robust and that proportionate governance criteria are the correct measurement tool. The full PBPP committee reviewed a random selection of 10 applications approved at Tier 1 between January 2016 and December 2016.

Committee members were split into groups and sent paperwork relating to the application. A review record was completed covering the questions within the proportionate governance criteria. Review records were sent to the PBPP Panel Manager for collation and an audit record compiled for each application.

ResultsApplications were identified where a discrepancy existed between the Tier 1 decision and the PBPP Committee audit review. These audit records were tabled for discussion at a workshop involving a subgroup of PBPP Committee and Tier 1 panel members. From the ten applications that were randomly selected, six were consistently reviewed by both the Tier 1 and Tier 2 Committee with no referral points identified from the either Tier. 4 were identified for discussion in a workshop including representatives from both Tiers. During the discussion it was agreed that 2 out of the 4 should have triggered a further review by Tier 2 but that the decision to approve all 4 applications would have remained.

Conclusion/ImplicationsThis suggests that both Tiers have a sound understanding of the proportionate governance criteria and that for the majority of applications this is being interpreted uniformly and that the audit process is required to ensure this is maintained going forward.
Clinically driven analysis reveals gene-socioeconomic status interaction influencing periodontal disease in the electronic health record-linked Generation Scotland: Scottish Family Health Study (GS: SFHS) cohort.
Authors: Bermingham Mairead L , Campbell Archie , Porteous David , Walls Angus
Published: September 2018

IntroductionHeritability (proportion of trait variation attributable to genetic factors) is not a fixed property. It can vary across different social settings and environments. Exploration of gene-environment interaction has been limited by lack of large sample sizes. Biobanks linked to electronic health records pose a solution to this sample size problem.

Objectives and ApproachSocial inequalities in periodontal health have been well documented in the dental scientific literature. However, gene-socioeconomic status interaction has yet to be examined. We identified 2,192 cases and 11,525 controls from linked electronic periodontal treatment records within the Generation Scotland: Scottish Family Health Study (GS: SFHS) (www.generationscotland.org). The measure of socioeconomic status used was the Scottish Index of Multiple Deprivation. The objective of this study was to investigate the gene-socioeconomic status interaction within this data. A reaction norm model was used to evaluate the presence of a gene-socioeconomic status interaction in the statistical software ASReml.

ResultsWe estimated the heritability of periodontal disease at 10.42% (95% confidence interval 5.97-14.88%). Socioeconomic status modified the heritability of periodontal disease. The heritability of was 13.37%, 0.14% and 11.70% in areas of high, moderate and low deprivation respectively; indicating the occurrence of a gene-socioeconomic status interaction with periodontal disease. These results indicate that socioeconomic status explains a large portion of genetic variation in periodontal disease risk. This information suggests that effective intervention and prevention programs for periodontal disease should involve socioeconomic aspects in their planning, implementations and evaluation. For instance, interventions targeted to reduce smoking in more deprived subjects with a genetic predisposition to periodontal disease could enhance the effect of health promotion strategies in reducing risk.

Conclusion/ImplicationsThis study presents contemporary evidence in a large population based cohort that gene-socioeconomic interaction leads to the progression of periodontal disease. This information may lead to the development of better preventative strategies for clinical dentistry.
A Regional Collaboration of Health (ARCH): Using health survey and linked routine data to understand wellbeing
Authors: Torabi Fatemeh , Akbari Ashley , Lyons Jane , Castagnet Mathilde , Lyons Ronan
Published: September 2018

IntroductionMonitoring social wellbeing and its relationship to health service utilisation by means of appropriate measurement tools can potentially provide a complementary view for influencing service development. Aspects of wellbeing have been collected in the Welsh Health Survey (WHS) while routine health data captures health service utilisation.

Objectives and ApproachWHS was used to link self-reported wellbeing to health outcomes, prior to linking to routinely collected data. Initially, a measure for personal wellbeing was developed using the four personal wellbeing questions defined by The Office of National Statistics (ONS), included in national surveys from 2011 onward. We conducted regression analysis to identify potential predictors of personal wellbeing scores our model included self-reported lifestyle behaviour, self-reported health, education, work, household and general demographics. Links to primary care, hospital and emergency department datasets are being developed to provide insight into the relationship between wellbeing, multi-morbidity and health service utilisation.

ResultsFour wellbeing questions had similar scoring patterns across age groups which is different to most health indicators that tend to show a marked health decline with increasing age. There is a difference between mean wellbeing score for males and females. Our finding showed that self-reported of ‘excellent’ or ‘very good’ general health has the largest positive effect on wellbeing while positive viewpoint on self-health has the second largest effect on our model. In addition, being retired from a paid job, eating at least one or 5+ portion of fruit and vegetables and giving up smoking have positive impact on population wellbeing. In contrast, not being able to work, intermediate household occupancy, consuming alcohol in last 12-months, having long-standing illness, showed a negative impact on wellbeing.

Conclusion/ImplicationsThis project established robust methodology on utilizing survey and routine health data for monitoring and evaluation purposes. We also evaluated the linkability of survey data The latest release of National Survey for Wales (NSW) will cover a combination of self-reported health measures and aims for a higher linkage consent rate.
Comparison of Health Behaviour Mortality Hazards in Canada and the United States
Authors: Fisher Stacey , Bennett Carol , Hennessy Deirdre , Fines Philippe , Jessri Mahsa , Eddeen Anan Bader , Sanmartin Claudia , Manuel Doug
Published: September 2018

IntroductionNational health surveys, available in over 100 countries, are the most common data used for health behaviour surveillance and are increasingly being linked to individual-level health outcomes. We propose that improved health behaviour hazard estimates can be obtained from pooled international population health surveys linked to outcome data.

Objectives and ApproachThe objective of this study was to compare smoking, alcohol, diet and physical activity all-cause mortality hazards in Canada and the United States using individual-level, linked population health survey data and common model specifications. The Canadian Community Health Survey (CCHS) (2003-2007) and the United States National Health Interview Survey (NHIS) (2000, 2005) linked to individual-level mortality outcomes with follow up to December 31, 2011 were used. Variable definitions consistent across the CCHS and NHIS were developed and used to estimate country-specific mortality hazards with sex-specific Cox proportional hazard models, including health behaviours, sociodemographic indicators and proximal factors including disease history.

ResultsA total of 296,407 respondents and 1,813,884 million person-years of follow-up from the CCHS and 62,226 respondents and 497,909 person-years from the NHIS were included. Hazards of smoking, alcohol consumption, diet and physical activity in Canada and the United States are of similar magnitude and direction, with similar dose response relationships. The largest health behaviour mortality hazards were associated with female heavy smokers in both Canada (HR: 3.36, 95% CI: 2.86, 3.95) and the United States (Female HR: 2.63, 95% CI: 2.11, 3.27), compared to non-smokers.

Conclusion/ImplicationsHealth behaviour mortality hazards are comparable in Canada and the United States, supporting the use of hazards obtained from pooled analyses for population heath. These hazards can replace those obtained from independent epidemiology studies that are often incompletely adjusted, rarely population-based and often not generalizable to the population of interest.
Development of a frailty score based on hospital discharge data linked to cohort data
Authors: Le Pogam Marie Annick , Trächsel Bastien , Seematter Laurence , Rousson Valentin , Burnand Bernard , Santos-Eggimann Brigitte
Published: September 2018

IntroductionFrailty is strongly associated with adverse health outcomes and health care costs in elders. However, we have almost no idea of the prevalence of frail older inpatients in Swiss hospitals. Hospital discharge data could contribute to predicting frailty in these patients, and eventually improving SwissDRGs system or casemix-adjustment.

Objectives and ApproachThe HFrailty project aimed to develop a predictive model of Fried’s Frailty Phenotype (FFP) based on hospital discharge data. We linked Lausanne University Hospital (CHUV) discharge data to clinical data from the Lausanne cohort study (Lc65+) over the period 2004-2015. The Lc65+ is a longitudinal population-based cohort comprising three random samples of approximately 1500 Lausanne residents aged 65 to 70, born respectively before, during and after World War II. With stepwise and lasso penalized logistic regression, random forest and neural networks, we identified the best-performing model for predicting FFP using CHUV’s data recorded within 12 months prior to frailty assessments.

ResultsAmong Lc65+ participants, 1649 were assessed for frailty and hospitalized at least once during the follow-up period, resulting in 3499 FFP assessments of which 544 were preceded by at least one hospitalization within 12 months.  In total, 45.7% of the participants were men and 9.4% were frail (FFP score ≥ 3). As expected, prevalence of frailty increased with age from 4.1% in the 66-70 age group, to 5.3% and 10.5% in the 71-75 and 76-80 groups, respectively. Logistic regression with lasso penalty was finally the best model regarding both performance and complexity. It had an area under receiver operating curve of 0.67 to predict FFP based on detailed diagnosis and procedure codes.

Conclusion/ImplicationsHospital discharge data may be used to identify frail and non-frail individuals and estimate their prevalence in the Swiss non-institutionalized population. Our predictive model showed limited performance and could be improved. We are currently testing groups of diagnosis and procedure codes, as predictors, instead of detailed ones.
Secondary care provision for children and young people with Cerebral palsy: A data-linkage study
Authors: Carter Bethan , Jones Hywel , Bethell Jackie , Kemp Alison , Wang Ting , Perra Oliver
Published: September 2018

IntroductionData on children with cerebral palsies are often held in registries, but these contain limited information with varying levels of follow-up. Here we show how record-linkage with healthcare datasets has enabled longitudinal follow-up if these children to understand how they use secondary care health services.

Objectives and ApproachOur primary aim was to explore healthcare utilisation for children and young people (CYP) with CP aged 0-25 years between 2004 and 2014 by severity, measured by recorded Gross Motor Function Classification System (GMFCS) level. This was achieved by linking Northern Ireland Cerebral Palsy Register (NICPR) data to routinely collected secondary care data. Comparison was made to the population of CYP who were not on the NICPR i.e. non CP cases.

ResultsThere were 1,693 cases in the NICPR cohort born 1981-2011. Of those, 286 (16.9%) were GMFCS 1, 662 (39.1%) GMFCS 2, 277 (16.4%) GMFCS 3, 105 (6.2%) GMFCS 4 and 342 (20.2%) were GMFCS 5 (21 (1.2%) missing).

NICPR cases had 11,844 hospital admissions and 19,750 outpatient appointments during the study period accounting for 1.7% of both inpatient and outpatient attendances. Those with severe CP were more likely to have an inpatient admission and had longer stays in hospital than those with less severe CP and those without CP. 592/948 (62.4%) patients with GMFCS 1&2 had an admission compared to 345/447 (77.2%) of GMFCS 4&5 cases. The proportion of elective to emergency admissions was 72.4% versus 53.7% for non CP.

Conclusion/ImplicationsThis study adds to understanding of service utilisation for those with CP in the UK, and provides comparable figures with a recent study in Australia. Thus, further demonstrating that linkage between CP registers and routinely collected healthcare may be useful for health services research and informing healthcare delivery.
Using Administrative Health Data to Define a Cohort of Youth Affected by Chronic Health Conditions: Preparing for Cross-Sectoral Data Linkage
Authors: Schraeder Kyleigh , Barrett Olesya , Nettel-Aguirre Alberto , Dimitropoulos Gina , Mackie Andrew , Samuel Susan
Published: September 2018

IntroductionIn Alberta, 2,400 youth with chronic needs transition to adulthood every year, and many are not prepared for this change. Transferring youth from pediatric to adult-oriented care is poorly managed. To improve this process, we need to know how youth patients use health services during this period.

Objectives and ApproachWe used the Alberta Health Services Corporate Data Repository (CDR-9), which collects records of ambulatory visits, to define a cohort of patients with chronic disease using pediatric tertiary care; data is available from 2008 to 2016. Personal health numbers allowed for deterministic data linkage to CDR-9, registry data (e.g., death dates, moves out of province), and area deprivation indices. Eligible patients were: (a) between ages 12-15 years in 2008 (for ≥2 years observation in adulthood, after age 18), (b) involved with a Chronic Care Clinic (CCC) at Alberta Children’s Hospital, and (c) had repeated CCC visits with ≥3 months between visits.

ResultsWe identified 26 Chronic Care Clinics (CCC) at Alberta Children’s Hospital (Calgary, Alberta), with stakeholder input. Using CDR-9, a total of 10,111 patients at the hospital were identified who were 12 to 15 years old at the start of the study window (in 2008), and who visited a CCC before age 18. Less than 1% (n=418) were excluded due to moving out of province or having an invalid personal heath number. Final sample sizes were captured across 3 algorithms (A1, A2, A3), based on frequency of CCC visits within a 2-year period: (i) A1: ≥2 CCC visits (N=4123); (ii) A2: ≥3 CCC visits (N=2242); (iii) A3: ≥4 CCC visits (N=1344).

Conclusion/ImplicationsOur identified cohort of youth affected by chronic conditions is the first of its kind in Alberta, and can answer important questions about patterns of service utilization in other sectors of care. Our next step is to link the cohort to population-level datasets (e.g., physician claims, NACRS, CIHI-DAD).
NHS Scotland Public Benefit and Privacy Panel (PBPP) – Much Ado about Governance 3 years on
Authors: Morris Carole , Gray Ashley , Scott Jennifer
Published: September 2018

IntroductionSince its’ inception in May 2015, the Public Benefit and Privacy Panel has provided a centralised, simplified and truly national Information Governance scrutiny process. It has successfully harnessed expertise across NHS Scotland health boards implementing a collaborative approach which contributes to consistency and continued capacity development across the sector.

Objectives and ApproachOver the last 3 years PBPP developed several procedures within its’ operations to become more efficient and achieve consistent decision making to ensure there is adequate information sharing amongst both Tier 1 and Tier 2 PBPP members. These components include:

Integrated working with eDRIS team to support applicants pre submission

Established an operational group with action plan

Monthly reporting to NHS Boards Information Governance colleagues

Annual learning and sharing workshop

Annual audit of Tier 1 Proportionate Governance approved applications

Documented Case Law

Information Sheets on categories of applications to aid consistent decision making

ResultsTier 1 panel members have noted that the quality of applications is noticeably improved when assistance is provided pre-submission aiding the speed of their proportionate review and that reference documents provide valuable information on the foundations of previous decisions. As a result of this and other improvements 90% of all applications are approved by Tier 1. Only those deemed highly complex or novel proposals are usually referred to Tier 2 at which 8% are reviewed and approved out of committee via email and the remaining 2% are heard at a Full Committee meeting. Whilst the average “clocked” days for an application is approximately 31 days.

Conclusion/ImplicationsPBPP needs to continue to evolve in order to continue providing efficient and pragmatic IG assessments for new technologies, more complex, voluminous data linkages and innovation. This is no mean feat in a fast paced environment and we have to ensure those involved are given sufficient time to do so.
Validating coding for a chronic condition (Cerebral Palsy) in routinely collected hospital admissions data
Authors: Carter Bethan , Jones Hywel , Bethell Jackie , Kemp Alison , Wang Ting
Published: September 2018

IntroductionData-linkage provides an opportunity to evaluate healthcare utilisation of patients with chronic health conditions. However the consistency and accuracy of recording chronic conditions in routinely collected healthcare data is unclear and we aim to explore this in children and young people (CYP) with a cerebral palsy (CP).

Objectives and ApproachThe study aims to validate CP case identification in routinely collected data by data-linking cases from The Northern Ireland Cerebral Palsy Register (NICPR) born 1981-2011 with routinely collected hospital admission data and cross-referencing cases between the two datasets. CP cases were identified in the administrative data using ICD-10 codes G80 (cerebral palsy), G81 (hemiplegia), G82 (paraplegia and tetraplegia) and G83.0-83.3 (diplegia and monoplegias).

ResultsThere were 1,693 cases in the NICPR cohort and 1,733 cases of CP identified in the hospital admissions data, 915 of which were on the NICPR giving a positive predictive value for identifying a CP case within routinely collected data of 52.8%. Specificity was high (99.8%) however sensitivity was low (54.1%).

1,157 (68.3%) patients on the NICPR had at least one hospital admission. 914 (79.0 %) cases were coded at some time point with G80-83.3 (829 (71.7%) G80, 328 (28.3%)  G81-83.3). NICPR cases had a total 11,844 hospital admissions and a CP code was recorded during 6,397 (54.0%).

The type of CP was recorded in NICPR for 1,673 (98.8%) cases whereas in the hospital admissions, data the majority (70.6%) were coded as other/unspecified CP (G80.8-9).

Conclusion/ImplicationsThis study adds to understanding of CP coding practices within routinely collected hospital data, further supporting claims that coding of CP within such datasets is poor. Coding must be accurate and consistent if data are to be meaningful, comparable and useful to inform health outcome reviews and patient care.
The association between maternal and offspring preterm birth. Results from a sibling design
Authors: Urquia Marcelo
Published: September 2018

IntroductionPrevious studies have reported an intergenerational association between maternal and offspring preterm birth (PTB) but the nature of the association remains unclear.

Objectives and ApproachThe objective was to revisit the association between maternal and offspring preterm birth using a quasi-experimental sibling design and distinguishing between preterm birth types. We conducted a retrospective intergenerational cohort study of 39,573 women born singleton in Manitoba, Canada (1980-2002) who gave birth to 79,198 singleton infants (1995-2016). To account for familial confounding we defined a matched subcohort of 1033 sister mothers with discordant PTB status and compared offspring PTB rates between 2,499 differentially exposed cousins using log-binomial fixed-effects generalized estimating equation models. PTB was defined as a delivery < 37 gestation weeks, divided into spontaneous and provider-initiated.

ResultsIn the population, mothers born preterm were more likely to give birth preterm [Adjusted Relative Risk (ARR): 1.39; 95\% Confidence Interval (CI): 1.25, 1.54]. The intergenerational association was not apparent among births to sisters with discordant PTB status [ARR: 1.02; 95\% CI: 0.77, 1.34]. However, the lack of association in the sibling analyses is explained by the fact that infants whose maternal aunts, but not their mothers, were born preterm had similarly elevated risk of PTB (10\%) than infants whose mothers were born preterm. Intergenerational patterns were observed for spontaneous PTB but not for provider-initiated PTB.

Conclusion/ImplicationsThese findings suggest that it is not the fact of having been born preterm that puts women at higher risk of delivering preterm, but the fact of having been born to a mother who ever delivered a preterm baby. Consideration of family history of PTB may better identify women-at-risk.
Concordance of EDI-based prevalence rates of health disorders with administrative data in two Canadian provinces
Authors: Reid-Westoby Caroline , Horner Matt , Janus Magdalena
Published: September 2018

IntroductionPopulation level data provide unprecedented opportunities to explore low-frequency health disorders, yet few suitable sources exist for young children. Early Development Instrument (EDI) data on child development in kindergarten in publically-funded schools in Canada include information on children’s health disorders that may be used as a source for prevalence estimates.

Objectives and ApproachWe aimed to examine the concordance of EDI-based prevalence rates of health disorders with administrative data in two Canadian provinces by linking data at various levels. In Manitoba, individual EDI data were linked with health and educational data containing information on diagnosis prior to kindergarten for six health disorders: Autism Spectrum Disorder (ASD), Fetal Alcohol Spectrum Disorder (FASD), Attention Deficit and Hyperactivity Disorder (ADHD), Cerebral Palsy (CP), Anxiety, and Asthma. In Ontario, the prevalence rate of ASD based on the EDI was compared to the prevalence rate obtained from regional ASD service providers, matched on area geocodes.

ResultsIn Manitoba, the total number of children with one of the six diagnoses in the linked database was 10,181. EDI data from 2011 and 2013 demonstrated concordance rates ranging from 0% (Anxiety) to 37% (ASD) between EDI and pre-kindergarten individual administrative data for the prevalence of the health disorders. In Ontario, interrater reliability was established with 2010-2012 EDI data in 12 regions (total number of children with ASD based on the EDI =1,329) to examine consistency among the two data sources. Results showed a “fair” concordance rate for the two sources of ASD prevalence information (Kappa = 0.329; p < 0.001), with rates varying from 0.85% to 1.05%. Linkages with subsequent cohorts of children are ongoing and will be examined for consistency with current results.

Conclusion/ImplicationsWhile the results are somewhat lower than expected, they established feasibility of linkages in 2 provinces and will be repeated in others, potentially with a broader time-frame (up to 1-2 years post-kindergarten). This will further inform successful utilization of existing data sources to monitor the prevalence of children’s health disorders.
Spatial epidemiology of premature mortality in Ontario, Canada
Authors: Buajitti Emmalin , Watson Tristan , Norwood Todd , Rosella Laura
Published: September 2018

IntroductionGeographic disparities in health indicators, such as premature mortality, may reveal area-level weaknesses in health system performance. Monitoring geographic trends can therefore have powerful implications for system evaluation and planning. However, attempts to understand patterns of population health can be complicated by underlying regional differences in demographics and behaviours.

Objectives and ApproachThis study aimed to identify regional disparities in premature mortality (defined as death before age 75), and to investigate how fully these disparities can be explained by population-level characteristics. Ontario’s 76 administrative Local Health Integration Network (LHIN) sub-regions, which vary in geographic and population size, were analyzed using linked population-level data from the Institute for Clinical Evaluative Sciences and Cancer Care Ontario.

Spatially structured, sex-stratified Bayesian hierarchical models were used to estimate standardized mortality ratios (SMRs) for each LHIN sub-region in the 2011-2015 period. Models were adjusted for key population-level demographic and behavioural risk factors.

ResultsLarge disparities in premature mortality presented at the sub-region level in males and females. Low premature mortality clustered around large, urban population centers in Ottawa and Toronto. Premature mortality was comparatively higher throughout the rest of the province, particularly in northern and southeast Ontario.

Higher prevalence of material deprivation, overweight and obesity, sedentary behaviour, and smoking were all significantly (α=0.05) associated with elevated premature mortality risk, while increased alcohol consumption and immigrant population were associated with decreased risk.

Adjusting for model covariates reduced variance of sub-region SMR estimates by 87% in males and 89% in females. Population-level characteristics thus explain a large proportion of geographic inequality in premature mortality. However, residual spatial variation suggests that systematic regional differences in premature mortality extend beyond population-level traits.

Conclusion/Implications

This study represents a novel application of small-area analytic techniques to Ontario mortality data, made possible by comprehensive linkage of vital statistics. The findings highlight the importance of population composition to geographic disparities in health. Future work should investigate the influence of system-level factors in areas with elevated premature mortality.
Connecting the dots: a qualitative study of dog-bite data in Calgary (AB, Canada)
Authors: Mouton Morgan , Rault Dawn , Rock Melanie
Published: September 2018

IntroductionWorldwide, dog-bites remain a leading cause of pediatric injuries. Local governments are key because they can enact and enforce policies on dogs. The City of Calgary has earned an international reputation for its approach to regulating dogs and dog-owners, which has resulted in marked reductions in per capita dog-aggression complaints.

Objectives and ApproachThis presentation reflects on how data on dogs are collected, sorted and used by local governments. Our approach has been qualitative in nature: we observed bylaw officers during ride-alongs, and we conducted in-depth interviews with officials who conceived and/or use the databases involving dogs in Calgary. We took a particular interest in the migration of the City of Calgary’s ‘canine data’ (e.g., dog licensing, reports by enforcement officers) to a more comprehensive database listing all of the incidents recorded by municipal services (including ‘911’ and ‘311’ calls, etc.).

ResultsPreliminary results point to difficulties in linking data stemming from several sources. Within the municipality itself, the transition comes with important challenges. Moreover, to improve public health surveillance for dog-bites, and ultimately to improve preventive strategies, other sources of data should be linked, including emergency services, animal welfare charities, and and veterinary clinics. This fragmentation of available data would be difficult to overcome. Local governments and animal welfare charities may cooperate during investigations but do not share their administrative data. The issue of privacy is a strong barrier for municipal services to obtain healthcare data, while veterinary clinics are private entities that have few incentives to align with administrative data held by local governments or healthcare services.

Conclusion/ImplicationsIn a city whose model is built upon the close monitoring of pets and their people, the issue of data linkages is critical. New partnerships and new solutions, respectful of citizen privacy and organizations’ respective scope of practice, should be developed.