bluuebunny/crossref_metadata_2025_split huggingface dataset:
Linking AWPS and CARIS data to estimate perinatal mortality in Wales due to congenital anomalies
Authors: Rolfe Kim , Chakraborty Mallinath , Tucker David 
Published: April 2017

ABSTRACTObjectivesThe All Wales Perinatal Survey (AWPS) collects mortality data on perinatal, neonatal and infant mortality in Wales up to a year of age. The Congenital Anomaly Register and Information Service (CARIS) collects clinical data on all congenital anomalies in foeti, infants and children in Wales. This was the first attempt to link the AWPS and CARIS databases.ApproachThe AWPS database coded stillbirths, terminations and deaths by the clinic-pathologic classification until 2012, assigning each case a survey number. The CARIS database started collecting data from 1998. Thus, the common period between 1998 and 2012 (15 years) was chosen for this study. Using CARIS as the main dataset, AWPS data were matched against the CARIS database using NHS numbers, along with soft linking on date of birth, maternal date of birth, and postcode. The unique AWPS survey number and coding was then added to the matched record within the CARIS dataset. This final ‘linked’ dataset was used to look at trend data.
ResultsBetween 1998 and 2012 a total of 20,574 cases were recorded in the CARIS database. After excluding cases where no gestation or date of death were recorded, and including deaths between >19 weeks’ gestation up to 365 days after birth, there were 1306 foetal losses/terminations, 231 stillbirths, and 662 livebirths (total 2,199) records left in the CARIS database who died with congenital anomalies. In the comparable period, using the same criteria, there were 6,909 records identified in the AWPS database. Of those, 1,765 had a recorded lethal congenital anomaly. By using the above criteria, a total of 2,039 cases in the CARIS database were linked to the AWPS database. 241 cases in the CARIS database and 151 cases in the AWPS database could not be linked by the above methods.Analysing the CARIS cases alone showed that consistently more than 80% of foeti are live-born, and survive. Chromosomal (22%), cardiovascular (21%) and brain (15%) anomalies are the most common congenital anomalies in the linked cases, which contribute to infant mortality. This pattern has remained largely unchanged over the study period. ConclusionUsing NHS numbers and soft linking, the majority of CARIS cases were linked to AWPS cases. Although both these databases should closely reflect each other, missing cases suggest there is scope for improvement in data collection. Sharing of data could also improve the quality of both databases.
Observational Data Exploration Via Online Tool For For Drugs and Cancer Risk
Authors: Iqbal Usman , Nguyen Phung Anh , Syed-Abdul Shabbir , Jian Wen-Shan , Li Yu-Chuan Jack 
Published: April 2017

ABSTRACTObjectiveRapid change in health information technology system had dramatically increased health data accumulated. We aimed to develop an online informatics tool in order to evaluate the risk of drugs for cancer by utilizing medical big data.
Data SourceWe use the Taiwan’s National Health Insurance Database that has provided a huge data which covered all health information including characteristics and all drug information i.e. prescriptions, etc. of 23 million Taiwanese population. Front-end development: Web-based interface was developed by using PHP package and Javascript. In addition, we included the guidelines of evidence based medicine (EBM) level 3 for observational study such as cohort, case-control, and/or case serial self-control in order to support users interact with system. Back-end development: A package of Apache, MySQL & PHP was used to build the serve-side of the system. We integrated the Elasticsearch API5 to our system in order to search and analyze data immediately. The example of data transform to person-level from Taiwan NHI database is shown in Box 1. After then, we also integrated the analytics package (ie. R package) to perform the statistical analysis to a given study.
This online analytical tool has capability to massively explore and visualize big data for long term use drugs and cancers through OMOSC system which will help to do mass online studies for long term use drugs and cancer risk. It would help to direct the health care professionals with lack of datamining skills to lead the study. The constructed online system would generate automatically case and controls by utilizing large databases for long term drug exposures and cancer risk. ResultsThe results are shown in odds ratio (OR) and if selected some confounding factors then could also get adjusted odds ratio (AOR) for risk estimation with 95% Confidence Intervals (CI). We used SAS statistical software on the same dataset to validate the OMOSC system results. It could help to do massive online studies which will saves time and cost effective.
ConclusionSince the clinical trials are impossible to conduct due to cultural, cost, ethical, political or social obstacles. Therefore, this kind of research model would play an important role in health care industry by providing an excellent opportunities for solving the technological, informatics, and organizational issues towards other broad domains of drugs evaluation by utilizing large-scale databases.
Linkage of health care claims data and apps data: The ADVOCATE oral health care dashboard
Authors: Gabel Frank , O’hanlon Karen , Brankin Pamela , Bryce Robert , Trescher Anna-Lena , Haux Christian , Whelton Helen , Van der Heijden Geert , Listl Stefan 
Published: April 2017

ABSTRACT
ObjectivesOral diseases are highly prevalent worldwide and their treatment places considerable economic burden on individuals and society. The ADVOCATE (Added value for Oral Care) project aims to promote new, patient-centred preventively oriented primary care and treatment.
As part of the project, a benchmarking dashboard is being developed to give stakeholders (i.e. health professionals, policy makers and health service planners) access to routinely collected data through a number of indicators such as: the types of care provided, costs of care and care outcomes, enabling comparisons across countries to be made.
ApproachAt the core of the ADVOCATE project, health data from several European countries are being collected. A bidirectional approach is used. Routinely collected claims data from 9 health insurers (insurance companies and NHS schemes) are being gathered. Concurrently, a patient e-questionnaire is being developed. Patients will be asked to answer additional health information questions anonymously whilst in the dental practitioner’s office using an app, thus providing data that isn’t available through the routinely collected claims data.
A previously developed set of indicators is being implemented in an electronic benchmarking dashboard. With the help of the linkage of aggregated forms of both claims data and data from the patient e-questionnaire, the dashboard will be used to visualize these indicators in order to monitor, direct and evaluate system change and related behaviors of patients, professionals, policymakers and insurers.
ResultsA pilot version of a dental healthcare dashboard has been developed using data from the Survey of Health, Aging, and Retirement Europe (SHARE).
In this context, the number of remaining teeth (indicating oral health status), the proportion of replaced teeth (indicating restorative activity of dentists) and the mean number of dentist visits per day (indicating oral health awareness of the population) were modeled and visualized for 12 European countries and Israel, resulting in highly diverse country groups in terms of the above indicators.
ConclusionThe ADVOCATE oral healthcare dashboard, containing essential information from both claims data and data from a patient e-questionnaire (via an app), can be used to review compliance with best practice guidelines and help close the guideline implementation gap.
It will be the first time that oral health professionals, insurers, and health policy makers will have the opportunity to review oral health care performance against standards.
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 635183".
The DASSL or Data Access, Storage, Sharing and Linkage Model & Proposals for an Enabling Data Environment for Health and Related Research in Ireland
Authors: Moran Rosalyn 
Published: April 2017

ABSTRACTObjectivesThis project set out 1)to examine the barriers and facilitators which impact on researchers’ ability to access, share and link data and thus carry out health and related research in Ireland and 2)to explore possible solutions.
ApproachInterviews were conducted with individuals involved in the collection, use, storage, sharing and linkage of data in Ireland. Data-related needs, practices and attitudes were explored, as were respondents’ views regarding both existing and required infrastructure and services for the safe sharing and linkage of data. Ongoing discussions with key stakeholders, visits to centres of excellence abroad and a review of the international literature informed results.
ResultsBased on the work carried out a model for safe access, sharing and linkage of data within the Irish context was developed – the DASSL or data access, storage, sharing and linkage model. The model comprises seven elements – five related to infrastructure and services [a health research data hub, safe haven, trusted third party and data linkage service, output checking and disclosure control and a research support unit] required for safeguarding data, and two related to the broad legislative and socio-cultural context needed to facilitate implementation of the model i.e. governance and public engagement. It is suggested that a research data trust [RDT] would be established to house the DASSL elements and to provide the institutional and technical environment to respond to the growing data-related needs within the Irish health research environment and the broader data ecosystem.
ConclusionThe proposals put forward for creating a safe environment for access, sharing and linkage of research and related data need to be considered by all key stakeholders. It is suggested that a Data to Benefits Committee be established to drive strategic discussions and action towards the implementation of the DASSL model elements. Implementation of the DASSL model will allow for safe usage of currently under-exploited data which can help inform health and wellbeing but also serve national economic and social agendas.
Statin therapy and mortality among new long-term care residents in Ontario, Canada: the contribution of clinical assessment data to a population-based cohort study
Authors: Campitelli Michael , Bronskill Susan , Giannakeas Vasily , Morris Andrew , Maxwell Colleen , Bell Chaim 
Published: April 2017

ABSTRACTObjectiveThere is limited evidence from randomized trials and observational studies to guide clinical practice regarding the use of statins in long-term care (LTC); the effectiveness of statins among those with limited life expectancy is not clear and there is concern that the risk of drug-related adverse events might outweigh any benefit. We examined the impact of initiating statin therapy on mortality for patients newly admitted to LTC.
ApproachPopulation-based health administrative data from Ontario, Canada were used to conduct a retrospective cohort study of newly admitted LTC residents, aged 66+ years and no statin use in the previous year, between January 1 2011 and December 31 2014. This cohort was linked to Resident Assessment Instrument (interRAI) data to capture clinical and functional characteristics (including frailty, activities of daily living, and cognitive function). The primary exposure was statin use within 30 days following LTC entry; residents who died or did not receive an interRAI assessment within 30 days were excluded. A propensity score for receiving statins was computed using resident demographic, clinical and functional characteristics. We matched exposed to unexposed patients on the basis of age (±1 year), sex, prior myocardial infarction(MI)/stroke hospitalization, frailty and propensity score (±0.2 standard deviations). Patients were followed in an intention-to-treat manner from the end of the exposure window until the earliest of death or March 31 2015. Cox regression was used to compare mortality between the study groups.
ResultsWe identified 39,560 newly admitted LTC residents aged 66+ years with no statin use in the previous year, of which 1,953 (4.9%) were prescribed a statin within 30 days of LTC entry. Propensity score matching resulted in 1,710 pairs of exposed and unexposed patients. In the matched cohort, those receiving statins had a lower rate of mortality compared with those not receiving statins (Hazard Ratio 0.77; 95% Confidence Interval [CI] 0.70-0.85). In pre-specified subgroup analyses, the association between statin use and reduced mortality persisted among those with and without a prior MI/stroke hospitalization and among those categorized as frail and not frail.
ConclusionOur data suggest initiating statins may be beneficial in reducing mortality risk among LTC residents, despite the complexity and advanced age of the patients. By linking rich resident-level health and functional assessment data with health administrative data we were able to characterize the association between demographic and clinical characteristics (including frailty) and exposure to statins more fully than with administrative data alone.
Geocoding routinely collected administrative data to measure access to alcohol outlets in Wales
Authors: Fry Richard , Rodgers Sarah , Orford Scott , Morgan Jennifer , Fone David 
Published: April 2017

ABSTRACTObjectivesA substantial level of excess alcohol consumption results in a wide range of harm and the potential impact on health at the population level of a reduction in consumption is considerable. A proposed policy for reducing alcohol consumption is restricting the availability of alcohol through reducing the density of alcohol outlets. We set out to create a high spatial resolution alcohol outlet dataset suitable for evaluating longitudinal changes in chronic alcohol related conditions.
ApproachRequests were made for the names and location of all licensed alcohol outlets within each of the 22 Unitary Authorities in Wales, between Nov 2005 and Dec 2011. Data requested for each outlet consisted of: the date permission was granted or the licence became active, the licence expiry date or an indicated date of outlet closure, whether this premise is licensed for ON and/or OFF premise sales, the hours permissible to sell alcohol or general opening hours of the outlet and the type of premise as assigned by the LA if available. Our approach included collating, geocoding and manually matching alcohol outlet data received from each unitary authority for use in a longitudinal analysis of outlet density.
ResultsAll authorities were able to provide an actual or approximate license issue date, allowing us to summarise the number of outlets annually. Several authorities were unable to provide precise outlet closure dates, so the date of the last interaction with the outlet was used to generate an approximate end date. One-half of the unitary authorities were able to provide the On/Off sales status of outlets, and 9 were able to provide opening hours. From these data we were able to geocode 53% (range 28% to 72% by local authority) using GIS, the remaining 47% were matched using Google products to verify and extract a precise geographic location.
Conclusions The collation and processing of retrospective alcohol outlet data was successfully completed to enable the building of a longitudinal exposure dataset. There was considerable variation between the unitary authorities in the quality of address data, and data related to the availability of alcohol, for example opening hours. The lack of address structure required us to devise a manual address matching process to capture the addresses that could not be geocoded. To aid future data linkage based evaluations to provide policy evidence in a timely manner, local government datasets should use standardised data fields, including addresses and Point-of-Capture address verification.
Data safe havens to combine health and genomic data: benefits and challenges
Authors: Jones Kerina H , Lacey Arron S , Perkins Brian L , Rees Mark I 
Published: April 2017

ABSTRACTObjectivesData safe havens can bring together and combine a rich array of anonymised person-based data for research and policy evaluation within a secure setting. To date, the majority of available datasets have been structured micro-data derived from routine health-related records. Possibilities are opening up for the greater reuse of genomic data such as Genome Wide Association studies (GWAS) and Whole Exome/Genome Sequencing (WES or WGS). However, there are considerable challenges to be addressed if the benefits of using these data in combination with health-related data are to be realized safely.
ApproachWe explore the benefits and challenges of using genomic datasets with health-related data, and using the Secure Anonymised Information Linkage (SAIL) system as a case study, the implications and way forward for Data Safe Havens in seeking to incorporate genomic data for use with health-related data.
ResultsThe benefits of using GWAS, WES and WGS data in conjunction with health-related data include the potential to explore genetics at a population level and open up novel research areas. These include the ability to increasingly stratify and personalize how medical indications are detected and treated through precision medicine by understanding rare conditions and adding socioeconomic and environmental context to genomic data. Among the challenges are: data availability, computing capacity, technical solutions, legal and regulatory frameworks, public perceptions, individual privacy and organizational risk. Many of the challenges within these areas are common to person-based data in general, and often Data Safe Havens have been designed to address these. But there are also aspects of these challenges, and other challenges, specific to genomic data. These include issues due to the unknown clinical significance of genomic information now or in the future, with corresponding risks for privacy and impact on individuals.
ConclusionGenomic data sets contain vast amounts of valuable information, some of which is currently undefined, but which may have direct bearing on individual health at some point. The use of these data in combination with health-related data has the potential to bring great benefits, better clinical trial stratification, epidemiology project design and clinical improvements. It is, therefore, essential that such data are surrounded by a properly-designed, robust governance framework including technical and procedural access controls that enable the data to be used safely.
iConsent an Electronic Consent Platform with the MS Register
Authors: Middleton Rod , Ford David , Naeh Daniel 
Published: April 2017

ABSTRACT
ObjectivesThe UK MS Register is a large scale observational research platform, capturing data from patients, NHS and carries out linkage with routine data from the SAIL databank.
We have 14,000 People with MS (PwMS) submitting Patient Reported Outcome Measures (PRoMS) quarterly and over 3000 patients consenting at NHS Sites around the UK
A differentiating factor between Register and previous attempts to capture PRoMS and clinical data was the goal that it be paperless. One area, where paper had to be used, was obtaining informed consent. Clinical participants are consented using a triplicate consent form, one copy for the patient, one for medical notes and one for the Register
It’s desirable for patients to be able to electronically consent, providing the following benefits:

Tablet computers already in use to collect PRoMS
Printing costs
Participant expectations
Improved content and user experience: improved feedback, of multimedia elements about informed consent
Increased familiarity with tablets

ApproachChanging consent methodology is complex, all documentation, processes and changes are reviewed by the ethics committee. A privacy protecting, secure software package (iConsent) was developed by modifying an existing package from Welsh Cancer Bank.
The software is server based, running on a Secured MS SQLServer 2014 and developed in .net to iOS/Android tablets
The practitioner taking consent explains the process, participants then see the approved documentation and materials. Finally they fill in their email address and name, and are presented with the consent form, the participant uses a stylus to sign. The practitioner then countersigns.
Once completed a digitally signed, secure pdf is generated on the server. Links are sent by email to the participant, the Register and unit administrator. The pdf is functionally identical to the paper.
ResultsThe South West Central Bristol ethics committee approved the software following guidance on security and documentation design. Staff were trained in system usage.
A number of patients were successfully e-consented, Of note was a potential issue with some patients and how MS impacts their ability to sign without resting a hand on the screen.
ConclusionPatients who have been e-consented have expressed satisfaction in the ease of use and security of the software. Patients being unable to rest their hands on the screen is being examined. Newer tablets can ignore inputs other than the stylus.
The MS Register intends to use the software in additional centres to capture patient consent.