bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying Patterns of Comorbidities with Cancers of the Colon and Rectum, as Related to age at Diagnosis
Authors: Gheybi Kazzem , Roder David , Buckley Elizabeth , Virty Agnes 
Published: December 2020

IntroductionAustralians have a high incidence of Colorectal cancer (CRC) and it is the second leading cause of cancer death. CRC patients experience more comorbid conditions such as diabetes and heart diseases than expected from population norms. It is anticipated that older patients with CRC will have even more comorbidities.
ApproachData from South Australia Cancer Registry were linked with hospital inpatient separations (public and private) and Pharmaceutical Benefit Scheme data to acquire a detailed dataset of CRC patients in South Australia. We have investigated the prevalence of different comorbidities by age and subsite (colon vs rectal) in the 12 months period prior to CRC diagnosis using the chronic comorbid conditions used by Charlson and RX-risk indices.
ResultsOf 11,656 CRCs diagnosed in 2003-2013, a significant higher prevalence of comorbidity presented in colon than rectal cancer patients using either indices. The most prevalent comorbidities for colon and rectal cancers respectively were: hypertension (25.9%, 22.0%), diabetes (17.3%, 15.6%) and gastric disease (11.4%, 12.4%). Common medications for colon and rectal cancers respectively were: hyperlipidaemia (38.4%, 33.7%), hypertension (38.0%, 31.7%) and gastroesophageal reflux diseases (36.2%, 26.8%). In younger patients (<50 years) with colon and rectal cancer anaemia (9.1%) and diabetes (7.4%) were the most prevalent comorbidities and gastroesophageal reflux medications (17.1%) and opioids (14.5%) were used most frequently whereas, in older patients (>79 years) hypertension (36.7%, 32.7%) was the most prevalent comorbid condition and hypertensive drugs (52.23%, 51,72%)were the most frequently used medication respectively.
ConclusionAlthough often regarded as a single disease (CRC), colon and rectal cancers have different predisposing factors and clinical features. As expected, older patients have a higher prevalence of comorbid chronic diseases. We observe, however, that colon and rectal cancer have different comorbidity patterns by age.
DPUK Cohort Explorer: An Interactive Visualisation Tool
Authors: North Laura 
Published: December 2020

IntroductionThe Dementias Platform UK (DPUK) Cohort Explorer is an interactive, online visualisation tool that allows users to explore data for a number of DPUK cohorts. Over 30 variables across cohorts have been harmonised, including information on demographics, lifestyle, cognition, health, and genetic biomarkers.
Objectives and ApproachThe tool has been developed to complement existing DPUK cohort metadata to provide a visual representation of participant numbers and field-level information for a selection of cohorts. This enables users to determine a cohort’s eligibility before applying for access to a cohort’s data, and aid in shaping potential hypotheses. Developed using Microsoft PowerBI, the Explorer hosts a subset of the cohort’s baseline, harmonised data, allowing a user to interrogate the visualisations of the uploaded data in a secure manner on the DPUK Data Portal website. Visualisations are linked so that participant numbers and distributions can be explored interactively.
ResultsThis approach allows the user to explore the harmonised data across a number of cohorts simultaneously whilst setting and adjusting filters that are of interest to the user’s search criteria. This provides a better understanding of the real-world data and enables the user to determine the feasibility of each cohort for potential studies, whilst facilitating meaningful comparisons across cohorts. The tool currently visualises five DPUK cohorts with a total of 82,391 participants, however it is being incrementally developed with more cohorts being added continually.
Conclusion / ImplicationsBy combing an easy-to-use, interactive dashboard with harmonised sets of real-world data, the tool allows the user to explore, interrogate and better understand field-level information in a secure manner with zero data transfer. This provides more insight for the user when applying for access to a cohort dataset using the DPUK Data Portal and may help the user to make more informed decisions and/or hypotheses.
Benzodiazepine Use Before Conception and Risk of Ectopic Pregnancy
Authors: Wall-Wieler Elizabeth , Robakis Thalia K , Lyell Deirdre J , Masarwa Reem , Platt Robert W , Carmichael Suzan L 
Published: December 2020

IntroductionEctopic pregnancy occurs in 1% to 2% of the all recognized pregnancies, yet half of women who have an ectopic pregnancy do not have any known risk factors. A potential but unstudied risk factor for ectopic pregnancy is benzodiazepine use, which could affect muscle contraction in the fallopian tube.
Objectives and ApproachWe compared the risk of ectopic pregnancy among women with and women without benzodiazepine prescriptions before conception. using data from United States commercial insurance claims (IBM® MarketScan® Databases). We performed a cohort study of 1,691,366 pregnancies between November 1, 2008 and September 30, 2015, and used unadjusted and inverse probability of treatment (IPT) weighted log-binomial models to calculate relative risks (RR) of ectopic pregnancy for pregnant women who did and did not fill any prescriptions for benzodiazepines in the 90 days before conception. Sub-group analysis was conducted on women who had anxiety and women who had insomnia diagnoses in the year before conception.
ResultsOf the 1,691,366 pregnant women, 1.06% filled at least two benzodiazepine prescriptions in the 90 days before conception. Among women with a benzodiazepine prescription, there was an excess of 80 ectopic pregnancies per 10,000 pregnancies, and their IPT-weighted risk of ectopic pregnancies was 1.47 (95% CI 1.32 to 1.63) times greater relative to women without benzodiazepine prescriptions before conception. The IPT-weighted RR between ectopic pregnancy and benzodiazepine use was 1.34 (95% CI 1.18 to 1.53) among women with anxiety disorder diagnoses and 1.28 (95% CI 0.99 to 1.68) among women with an insomnia diagnosis.
Conclusion / ImplicationsThis study found that women who have a benzodiazepine prescription before conception are at an increased risk of ectopic pregnancy. This information can help women and their health care providers make more fully informed decisions about benzodiazepine use in their reproductive years.
Using Machine Learning to Measure Specialist Wait Times from Family Physicians’ Electronic Medical Records Linked to Ontario Health Administrative Data
Authors: Abdalla Mohamed , Lu Hong , Pinzaru Bogdan , Jaakkimainen Liisa 
Published: December 2020

IntroductionReliable information about the time spent waiting for health care services is a critical metric for measuring health system performance. Wait times are a useful measure of access to various health care sectors. Alongside the increased adoption of electronic medical records (EMR) by Canadian family physicians (FP), is the secondary use of FP EMR data for research. However, using FP EMR data can be challenging in its unstructured, free-text format.
Objectives and ApproachOur objective was to identify the target specialist physician type from the EMR FP referral note and then calculate wait times from a FP referral to a specialist physician visit. We used FP EMR data and linked to Ontario, Canada health administrative data (called EMRPC). EMRPC collects the entire clinical record from patients including the content of FP referral notes. We used machine learning (ML) methods to identify the type of specialist physician in which the referral was intended. Labels to test the ML methods were created from physicians’ claims data. Wait times were calculated from the FP EMR referral note date to the specialist physician claim date in administrative data.
ResultsOur ML models’ ability to classify 2016 FP EMR referral notes to selected medical and surgical specialists achieved sensitivity and positive predictive values ranging from the high 70s to low 80s.Compared to earlier analyses from 2008, we observed a similar relative ordering to see specific specialist physicians. Overall, the median wait times have increased by 14 days on average, with a maximum increase of 28 days to see a gastroenterologist.
Conclusion / ImplicationsThe accuracy of ML on unstructured FP EMR data is high, thereby providing a mechanism to “codifying” information in a timely manner. This information can help inform decision makers and providers about which patients or FP practices are experiencing long wait times in seeing specialist physicians.
Development and Initial Validation of a Harmonised Multi-Jurisdiction Work Injury Compensation Database
Authors: Collie Alex , Di Donato Michael , Beck Dianne , Sheehan Luke R 
Published: December 2020

IntroductionNearly one quarter of a million Australian workers experience a work injury annually and make a benefit claim through one of the nation’s eleven workers’ compensation (WC) systems. The total cost to Australian society has most recently been estimated at $61.8 billion or 4.1% of GDP. The disaggregation of legislative responsibility between jurisdictions has contributed to a lack of common data standards, and thus minimal understanding of the efficiency or effectiveness of service provision in the Australian WC sector.
Objectives and ApproachThis project developed a new multi-jurisdictional work disability database including detailed information on work disability duration, health and social care service provision. Service level payment data contained in structured WC insurance claims datasets held by five large WC jurisdictions with >60% coverage of the Australian labour force was collected for all cases of work-related low back pain, fractures and limb soft tissue disease over between 2010 and 2015. Database development involved creation and coding of harmonised service-level indicators for individual episodes of healthcare provision and weekly periods of wage replacement.
ResultsA total of 253,000 cases and 10.7 million service episodes are included in the database. Initial exploratory analyses focused on the frequency, prevalence, timing, intensity and continuity of General Practitioner (GP) services to each of the injury groups. Regression modelling examined occupational, injury, demographic and jurisdictional factors affecting GP service use outcomes. As anticipated, service patterns varied by injury type, age, gender and occupational group. Significant differences in service use between WC jurisdictions were observed.
Conclusion / ImplicationsThis exploratory study demonstrates the feasibility of developing a population-based service level database for monitoring health service delivery to injured Australian workers. Future studies will examine the impact of jurisdictional policy differences on service delivery, and the relationship between service delivery and outcomes such as disability duration.
Evaluating Binary Encoding Techniques in The Presence of Missing Values in Privacy-Preserving Record Linkage
Authors: Ranbaduge Thilina , Christen Peter 
Published: December 2020

IntroductionApplications in domains ranging from healthcare to national security increasingly require records about individuals in sensitive databases to be linked in privacy-preserving ways. Missing values make the linkage process challenging because they can affect the encoding of attribute values. No study has systematically investigated how missing values affect the outcomes of different encoding techniques used in privacy-preserving linkage applications.
Objectives and ApproachBinary encodings, such as Bloom filters, are popular for linking sensitive databases. They are now employed in real-world linkage applications. However, existing encoding techniques assume the quasi-identifying attributes used for encoding to be complete. Missing values can lead to incomplete encodings which can result in decreased or increased similarities and therefore to false non-matches or false matches. In this study we empirically evaluate three binary encoding techniques using real voter databases, where pairs of records that correspond to the same voter (with name or address changes) resulted in files of 100,000 and 500,000 records containing from 0% to 50% missing values.
ResultsWe encoded between two and four of the attributes first and last name, street, and city into three record-level binary encodings: Cryptographic long-term key (CLK) [Schnell et al. 2009], record-level Bloom filter (RBF) [Durham et al. 2014], and tabulation Min-hashing (TBH) [Smith 2017]. Experiments showed a 10% to 25% drop on average in both precision and recall for all encoding techniques when missing values are increasing. CLK resulted in the highest decrease in precision, while TBH resulted in the highest decrease in recall compared to the other encoding techniques.
ConclusionBinary encodings such as Bloom filters are now used in practical applications for linking sensitive databases. Our evaluation shows that such encoding techniques can result in lower linkage quality if there are missing values in quasi-identifying attributes. This highlights the need for novel encoding techniques that can overcome the challenge of missing values.
Using Linked Data to Explore the Association Between Statin Medicine Adherence and Hospitalisation Following A Large Patient Co-Payment Increase
Authors: Seaman Karla L , Bulsara Max K , Sanfilippo Frank M , Kemp-Casey Anna , Roughead Elizabeth Ellen , Bulsara Caroline E , Watts Gerald F , Preen David B 
Published: December 2020

IntroductionIn January 2005, the Australian Government increased the consumer medication co-payment by 21%. Previous research found that this affected population-level utilisation of statins, which fell by 5% following the co-payment increase. The subsequent health impact on individuals reducing or ceasing use of statins is unknown.
Objectives and ApproachTo explore the two-year risk of acute coronary syndrome (ACS) or stroke-related hospitalisation among individuals who discontinued, reduced or continued statin medicines after the 2005 PBS co-payments increase. This was achieved through a retrospective cohort study using linked administrative Commonwealth and State datasets for the Western Australian population. Outcomes were assessed using the Fine and Gray competing risks method, with death as the competing risk, adjusting for demographics, comorbidities and medication history.
ResultsThere were 207,066 individuals identified as using statins before the co-payment increase. After the increase, adherence reduced in 12.5% of this cohort, and 3.3% ceased use. There were 4,343 ACS and stroke-related hospitalisations for the cohort in the follow-up period. Multivariate analysis indicated ceasing statins increased the risk of hospitalisation for ACS or stroke-related events by 18% (95%CI=0.1-40%) compared to continuing therapy. The risk was greatest for males <70 years. No differences existed for women or older men who discontinued statins. There was no difference in hospitalisation risk for those who reduced statins compared to those who continued.
Conclusion / ImplicationsYounger men ceasing statins after the 2005 co-payments increase had a higher risk of ACS and stroke hospitalisations compared to individuals who continued using statins. The findings highlight the importance of continued adherence to prescribed statin medication, and that discontinuing therapy for non-clinical reasons (such as cost) can have negative consequences. Additionally, it demonstrates to policymakers that substantial increases in consumer co-payments can result in adverse health outcomes.
Evaluation of The Manitoba Healthy Baby Prenatal Benefit: Is It Improving Birth and Early Childhood Outcomes for Metis Families?
Authors: Brownell Marni , Sanguins Julianne , Chartier Mariette , Nickel Nathan , Enns Jennifer , Chateau Dan , Burland Elaine , Sarkar Joykrishna , Lee Janelle Boram , Struck Shannon , Hinds Aynslie , Quddus Farzana , Chartrand Frances 
Published: December 2020

IntroductionIn Manitoba, low-income pregnant women are eligible for the Healthy Baby Prenatal Benefit (HBPB), a prenatal income supplement. Research has demonstrated positive outcomes associated with HBPB, but it remains unknown if Metis women and children – who are of mixed European and Aboriginal descent and one of the most marginalized populations in Canada -- benefit from the program.
Objectives and ApproachThe Manitoba Metis Federation and the Manitoba Centre for Health Policy partnered to determine the impact of HBPB on Metis newborn and early childhood outcomes. We included all Metis women giving birth in Manitoba 2003-2011 who received income assistance during pregnancy (n=4,852), adjusting for differences between those receiving (n=3,681) and not receiving (n=1,171) HBPB with propensity score weighting. We used multi-variable regressions to compare outcomes between groups: breastfeeding initiation, low birth weight, preterm birth, small- and large-for-gestational age, Apgar scores, birth hospitalization length of stay (LOS), neonatal readmissions, infant hospitalizations, vaccinations at age 1 and 2, and child development scores at kindergarten.
ResultsHBPB receipt was associated with reductions in low birth weight (adjusted Relative Risk (aRR): 0.74 (95% CI: 0.58-0.94)) and preterm births (aRR: 0.78 (0.65-0.94)), and increases large-for-gestational age births (aRR: 1.21 (1.06-1.39)) and neonatal readmissions (aRR: 1.58 (1.05-2.37)). Birth hospitalization LOS was lower for newborns whose mothers received HBPB (Mean Difference 0.29 days). HBPB was associated with increases in vaccinations for children aged 1 (aRR: 1.08 (1.00-1.15)) and 2 (aRR: 1.12 (1.05-1.18)). No significant associations were found for small-for-gestational age births, Apgar scores, breastfeeding initiation, infant hospitalizations or child development scores.
Conclusion / ImplicationsA modest unconditional prenatal income supplement to low-income Metis women was associated with improved birth outcomes and child vaccinations; however, an association with increased neonatal readmissions warrants further exploration. Lack of significant associations between HBPB and child development measures suggests more sustained support may be necessary to improve longer-term outcomes.
Consent to Data Linkage in LSAC
Authors: Bandara Dinusha , Silbert Michelle , Daraganova Galina 
Published: December 2020

IntroductionLinking the existing longitudinal data assets with administrative datasets provide the opportunity to transform longitudinal data into valuable assets to inform research and policy development.
Objectives and ApproachThis paper will focus on Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) data linkage landscape and consents which are invaluable for the development of evidence-based health-social-economic policies.
ResultsLSAC is Australia’s first nationally-representative longitudinal study of child development. Since 2004, two cohorts of 5,000 children and their parents have been interviewed every two years (B (baby) cohort and K (kindergarten) cohort). Over the years, multiple data linkage has been undertaken based on either parental consent or study child consent.
In 2004 parents were asked to consent on behalf of the study child to link Medicare Benefits Schedule (MBS), Pharmaceutical Benefits Scheme (PBS)/Repatriation Pharmaceutical Benefits Scheme (RPBS) and Australian Childhood Immunisation Register (ACIR) administrative data to LSAC. The consent rate was 93% was for MBS, PBS and ACIR. Nearly 90% of B cohort parents provided consent to link Australian Early Development Census (AEDC)/National
Assessment Program – Literacy and Numeracy (NAPLAN) and 95.4% of K cohort parents provided consent to link NAPLAN.Then ten years later, children in the K cohort were asked to consent to MBS/PBS and income-support administrative data. The rates were 86.6% for MBS, 85.4% for PBS and 81.2% for income-support administrative data. Parental consent to link their MBS, PBS and income-support administrative data was also sought and these rates varied between 60% to 88%.
Conclusion/ImplicationsThe discussion will focus on differences in consent rates by time of consent, consenting individual and type of administrative data to be linked. Challenges and considerations that researches should be aware of when designing the linkage consent methodology will also be discussed.
Preparing Pathology Data for Linkage
Authors: Wiggins Nadine , Albion Tim , Stokes Brian , Jose Matthew 
Published: December 2020

IntroductionThe Tasmanian Data Linkage Unit (TDLU) undertook a complex data linkage project in 2019 linking public and private pathology data to five disparate health datasets. Having linked pathology data previously, the unit was aware of the challenges it faced linking a large dataset covering a fourteen-year time span. The aim of this study was to use data-linkage to develop a Tasmanian dataset to quantify the burden and distribution of chronic kidney disease, including identifying barriers to dialysis treatment services.
Objectives and ApproachA cohort was selected from public and private providers of pathology services in Tasmania from 2004-2017 to support the establishment of a comprehensive researchable dataset. A linkage plan was developed that included detailed processes for cleaning and de-duplicating the pathology data prior to linkage. The larger private pathology dataset comprised 3.9 million records and data cleaning strategies were implemented. De-duplication created extensive clerical review and methods to reduce this work were devised and implemented as part of the linkage process.
ResultsDe-duplication based on exact matches reduced the size of the dataset from 3.9 million to just over 520,000 individuals. Internal linkage of the dataset resulted in approximately 47,000 ‘groups’ eligible for review. Structured Query Language (SQL) queries were constructed and the number of groups eligible for review decreased by 42%. Further analysis was conducted, which resulted in an appropriate ‘cut off’ threshold being determined for clerical review and an estimate of false positive links remaining was calculated.
Conclusion / ImplicationsMethods of reducing the amount of manual clerical review can be incorporated into a linkage design when there is a thorough understanding of the characteristics and content of the dataset to be linked. The methods used for this linkage project will be utilised for future projects using pathology data.