bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysing the daily, weekly and yearly cycles of births and their implications for the NHS using linked data
Authors: Harper Gill , MacFarlane Alison , Dattani Nirupa , Dodwell Miranda , Gibson Rod , Cortina Mario , Martin Peter 
Published: April 2017

ABSTRACT
ObjectivesThis project builds on previous work linking routinely collected data from birth registration, birth notification, death registration and hospital discharges, extending it to six million births in England and Wales from 2005 to 2014. This linkage is creating a new dataset to investigate previously unanswerable questions about variations in time of birth and its outcome which are highly contested in the health service in England and Wales:
1. How do numbers of births vary according to time of day, day of the week and time of year of birth and how does this relate to modes of onset of labour and delivery?2. How do patterns of birth vary between maternity services in relation to variations in medical and midwifery staffing, patterns of intervention and size of unit?3. How does the outcome of pregnancy, in terms of mortality and morbidity rates at birth and in the first year of life, vary according to time of birth in relation to gestational age, and intervention in the onset of labour and delivery?4. Have the patterns changed over the years 2005 to 2014?
ApproachRoutinely collected national datasets for 2005-14 have been linked using patient identifiable data items. They differ in the way data items are recorded. Methods of linkage, quality assurance and data cleaning have been improved, compared with those developed in the original project.
This unique approach links clinical data from hospital admissions with more reliable data on birthweight from birth registration and with gestational age and time of birth from birth notification. This enables investigation of the associations between day and time of birth with its outcome.
This is also the first study to link mothers’ and babies’ hospital discharge data for England and Wales and to draw on public and patient involvement to include outcome measures specifically designed to be women-centred. Overall, the linkage has created a fuller range of data.
ResultsResults will be available by the time of the conference. Initial results already clearly illustrate differences in timings of birth by time of day and day of the week by mothers’ age, gestational age and birth setting and for singleton and multiple births.
ConclusionThe study has created a valuable linked dataset that will uniquely enable analyses of associations between timing of birth and its outcome. These results will potentially be able to inform and impact NHS service provision.
A population-based study comparing multiple sclerosis clinic users and non-users in British Columbia, Canada
Authors: McKay Kyla , Tremlett Helen , Zhu Feng , Kastrukoff Lorne , Marrie Ruth Ann , Kingwell Elaine 
Published: April 2017

ABSTRACTObjectivesMuch clinical knowledge about multiple sclerosis (MS) has been gained from patients who attend MS specialty clinics. However, there is limited information about whether these patients are representative of the wider MS population. The objective of this study was to compare incident MS cases who were MS clinic users to non-users of the specialty MS clinics in British Columbia, Canada.
ApproachThis was a retrospective record linkage cohort study using prospectively collected data from the BCMS database and province-wide health administrative databases. Incident MS cases were identified in the general population using a validated algorithm of hospital and physician diagnostic codes.
Results There were 2,841 incident MS cases between 1996 and 2004 including 1,648 (58%) that had registered at an MS clinic (‘clinic cases’) and 1,193 (42%) that had not (‘non-clinic cases’). Sex and socioeconomic status distributions were similar; however, non-clinic cases were older, accessed health services more frequently, and had a higher burden of comorbidity than clinic cases. Only 1% of the non-clinic cases had filled a prescription for an MS-specific disease-modifying therapy, compared to 51% of the clinic cases.
ConclusionOur findings have several important implications: even within a publicly funded healthcare system, a high proportion of individuals with MS may not access a specialty MS clinic; the needs of MS patients managed in the community may differ from those referred to an MS clinic; findings from studies involving clinic-based MS cohorts may not always be generalizable to the wider MS population; and access to population-based health administrative data offers the opportunity to gain a broader understanding of MS.
The importance of gaining the public’s confidence to use administrative data for public benefit in social science research
Authors: Verwulgen Ilse , Knight Judith 
Published: April 2017

ABSTRACTBackgroundThe Administrative Data Research Network (ADRN) is a UK-wide initiative, funded by the Economic and Social Research Council (ESRC). The Network facilitates safe access to linked de-identified administrative data for research which is aimed at providing a benefit to our society. Administrative data research can provide wide ranging and longitudinal evidence for policy makers which therefore has the potential to improve our society.
MethodRecognising the importance of public confidence and trust to the success of the ADRN, the ESRC commissioned a public consultation to gauge understanding of social research and the reactions to the use of administrative data in research. A comprehensive UK-wide communications and public engagement strategy has been developed. From this a number of initiatives been introduced over the past two years to address public concerns and these have been reviewed, revised and extended as the Network has evolved.
Now to extend the Network’s reach, the Administrative Data Research Network is developing a UK National Citizens Panel (CP). The panel will provide a representation of public views on potential changes to Network policy, procedures, governance and service provision issues. The CP will also assist with testing our public facing communications such as events, website and promotional materials.
ConclusionThis paper presents the previous and current public engagement initiatives that the Administrative Data Research Network has incorporated within its policies and service that enables better knowledge for a better society
Funded by the Economic & Social Research Council, the ADRN, set up as part of the UK Government’s Big Data initiative, is a UK-wide partnership between universities, government bodies, national statistics authorities and the wider research community. www.adrn.ac.uk.
Investigating Orthopaedic Surgical Prophylaxis Changes and Post-operative Acute Kidney Injury (AKI) in NHS Grampian – a Test Case for NHS Scotland
Authors: Marwick Charis , Sneddon Jacqui , Fletcher Eilidh , Patton Andrea , Bayne Gwen 
Published: April 2017

ABSTRACT
ObjectivesTo support reduction of Clostridium difficile infection (CDI), in 2008 the Scottish Antimicrobial Prescribing Group recommended that all NHS boards in Scotland restrict the use of antibiotics associated with a high risk of CDI. In NHS Grampian the policy for antibiotic prophylaxis in orthopaedic surgery was changed in June 2010. Trauma patients undergoing internal fixation or arthroplasty received flucloxacillin or co-amoxiclav before the policy change and flucloxacillin and gentamicin after the policy change. Previous studies have found similar policy changes resulted in an increase in post-operative acute kidney injury (AKI) and this study examined rates of post-operative AKI before and after this policy change in the NHS Grampian region of Scotland. Patients undergoing elective arthroplasty received either flucloxacillin or co-amoxiclav or cefuroxime before the policy change and cefuroxime afterwards.
ApproachAll NHS Grampian patients who underwent an orthopaedic surgical procedure with prophylaxis during the period 01 June 2008 to 31 May 2012 were selected. Cases were linked to local creatinine data to detect post-operative AKI. Cases were further linked to national coverage data: (i) hospital discharge data to create the Charlson score for comorbidity, (ii) patient-level community prescribing data to identify previous exposure to any medicines which predispose to renal impairment, (iii) patient-level infection data to identify any post-operative CDI and (iv) Scottish Renal Registry data for case exclusion purposes. Segmented regression analyses of interrupted time series were used to evaluate changes in level and trend associated with the intervention and estimate effect sizes.
Results3,870 trauma cases and 5,475 elective cases were examined. There was a significant increase in AKI rate following the policy change (β=0.28; 95%CI, 0.03 to 0.53; p=0.028) in trauma patients, equating to an increase of 0.28 cases of AKI per 100 procedures per month and a relative intervention effect at 24 months of 150% (95% CI 25% to 250%) There was no significant change in AKI rate among elective patients.
ConclusionWe found that a change in orthopaedic antibiotic prophylaxis policy in NHS Grampian to flucloxacillin plus gentamcin was associated with an increase in post-operative AKI. This is consistent with observations in other boards and supports the new recommendation away from this policy made by SAPG in 2012. In cohort of trauma patients we found the change in policy was associated with an increase in post-operative AKI rate.
Distilling data – A flexible method for producing research-ready Electronic Health Records
Authors: Hacker Alex 
Published: April 2017

ABSTRACT
ObjectivesPopulation health datasets need to combine data from multiple sources into a coherent whole. This presents significant technical challenges: both in standardising the data, and in presenting it in a form suitable for research. This presentation outlines a method that we have developed for managing the Electronic Health Records (EHRs) gathered by our biobank, and for aggregating them without obscuring important features. The technique is broadly applicable, illustrated with practical examples derived from our dataset of >1.7 million health events.
ApproachWe begin with a disparate set of EHRs from different sources: death certificates, a national disease registry, and multiple Health Insurance agencies.
Endpoint definitions - We first specify our outcomes of interest. Generally, these simply consist of a list of the ICD10 codes that define a disease, which could be as broad as 'vascular disease' or as narrow as 'macrovascular complications of diabetes'.
Events list - Then we standardise the required EHR variables. Typically these are just the diagnoses and the dates. Our standardisation methods necessarily vary by data source, but the goal is the same for each: a list of dated diagnoses in ICD10 format.
Endpoints – Finally, we automatically compare our definitions and events to determine whether each participant has experienced any of the endpoints and, if so, when their earliest occurrence was.
ResultsThe resulting endpoint dataset has many desirable properties. For example, analyses are simplified because each participant has a single value for each endpoint, regardless of the number of events that they have. Immediately we can answer common questions, such as 'How many of our participants have had a stroke, and how soon after we gathered their physical measurements?'
We retain the source of each event, so we can compare sources to check internal validity, or restrict our endpoints to only consider fatal events, for example. New events, and even entirely new sources of events, can be incorporated once the key variables are standardised. New endpoints can be created directly from their ICD10 definition.
More complex endpoints can be produced from any suitable variable. Second stroke, revascularisation surgery, antidepressant use: once we have the definition & data, a suitable endpoint can be created in exactly the same easy-to-use format.
ConclusionThis methodology facilitates validation, comparison and combination of data sources. It enables us to present complex EHR data in a clear and flexible form, allowing researchers to analyse it with ease and confidence.
Measuring morbidity and mortality attributable to rheumatic heart disease in Fiji: a prototype study of disease burden in a developing country by data linkage
Authors: Parks Tom , Kado Joseph , Tukana Isimeli , Steer Andrew 
Published: April 2017

ABSTRACT
ObjectivesRheumatic heart disease remains a major public health concern in developing countries. Motivated by the lack of up-to-date epidemiologic data from endemic settings, we sought to quantity morbidity and mortality attributable the condition in Fiji, a middle-income country where a high prevalence has consistently been reported. Having resolved to undertake the analysis using the existing routine clinical and administrative data at our disposal, we first set out to develop a data linkage procedure robust to the inherent limitations of data from low resource settings.
ApproachRecords were available from four sources: an electronic patient information system, a database of death certificates, a disease control register, and echocardiography clinic registers. All referred to 2008-2012.
Throughout the design and calibration process we used 1,406 known duplications in the patient information system from which we calculated the sensitivity and specificity. After cleaning, standardisation and preliminary blocking, we categorised identifiers including names, dates and demographics into agreement, partial agreement, disagreement or missing, accounting for issues such as out of order or misspelt names. After concentrating true matches by further blocking, we estimated match and nonmatch probabilities using expectation maximisation under the Fellegi-Sunter model of record linkage. We then derived the posterior match probability taking into consideration the size of block and prior information about the probability a match be present given the demographics of the individual concerned. In its final configuration, with record pairs considered a match if they achieved a posterior probability of over 50%, our procedure identified the known duplications with sensitivity of 91.4% and specificity of 99.9%.
ResultsHaving identified 2,619 cases from the 1,773,999 records available, we used the linked data to make population-based estimates of prevalence using capture-recapture analyses and cause-specific mortality using relative survival methods, the first such estimates for a developing country. Moreover, in sensitivity analyses, we found that changing posterior probability threshold above which record pairs were considered a match had limited impact on the results.
ConclusionAlthough data linkage is widely used for epidemiologic research in high-income settings, its application to developing countries has been limited. We developed and validated a data linkage procedure that can be used to turn largely unstudied routine clinical and administrative data into robust estimates of disease burden. With the growing availability of computerized data, we propose our approach has strong potential to assist the production of disease burden statistics in developing countries where civil registration systems are weak.
Yin and yang: why big data needs little data
Authors: Wright John 
Published: April 2017

ABSTRACTObjectivesBig data and data linkage offer great potential for improving health, but the shallowness of much routine data is a major limiting factor. We explore how connecting wide routine data (big data) and deep research data (little data) can harness the real potential of data linkage.
ApproachWe have linked routine clinical data from education and health (primary and secondary care) for a well-characterised birth cohort (Born in Bradford) with phenotype and genotype data on almost 14,000 families. We explore the potential for this combination of big and small data to address key research priorities in health and education research.
ResultsWe present examples of the complementarity of routine and research data linkage in four varied domains:
1) Health care: how does postnatal mental health need (small data) match with mental health demand (big data)?2) Education: how do early life exposures (small data) influence school readiness and standardised assessment tests (big data)?3) Genetics: what is the impact of rare mutations (small data) on health service uptake (big data)?4) Public health: how can big data and small data be used to evaluate the effectiveness of early life interventions?
Pros and cons of both big data and small data are identified. Some lifestyle and demographic factors are more likely to accurate from bespoke research data collection, but clinical and educational measures may be better gleaned from routine records. The reliability of the different sources of data is discussed.
ConclusionsOur results illustrate the symbiosis of combining research and routine datasets. Opportunities for harnessing this power through combining routine data with cohort studies, clinical trials and national surveys are explored.
Divergence of seafloor elevation and sea level rise in coral reef ecosystems
Authors: Yates Kimberly K. , Zawada David G. , Smiley Nathan A. , Tiling-Range Ginger 
Published: April 2017

Abstract. Coral reefs serve as natural barriers that protect adjacent shorelines from coastal hazards such as storms, waves, and erosion. Projections indicate global degradation of coral reefs due to anthropogenic impacts and climate change will cause a transition to net erosion by mid-century. Here, we provide a comprehensive assessment of the combined effect of all of the processes affecting seafloor accretion and erosion by measuring changes in seafloor elevation and volume for five coral reef ecosystems in the Atlantic, Pacific, and Caribbean over the last several decades. Regional-scale mean elevation and volume losses were observed at all five study sites and in 77 % of the 60 individual habitats that we examined across all study sites. Mean seafloor elevation losses for whole coral reef ecosystems in our study ranged from −0.09 to −0.8 m, corresponding to net volume losses ranging from 3.4  ×  106 to 80.5  ×  106 m3 for all study sites. Erosion of both coral-dominated substrate and non-coral substrate suggests that the current rate of carbonate production is no longer sufficient to support net accretion of coral reefs or adjacent habitats. We show that regional-scale loss of seafloor elevation and volume has accelerated the rate of relative sea level rise in these regions. Current water depths have increased to levels not predicted until near the year 2100, placing these ecosystems and nearby communities at elevated and accelerating risk to coastal hazards. Our results set a new baseline for projecting future impacts to coastal communities resulting from degradation of coral reef systems and associated losses of natural and socioeconomic resources.
قياس مدى تقبل أعضاء هيئة
التدريس بكليات العلوم التطبيقية
لمصادر المعلومات الإلكترونية
Authors: Alalawi Yasir , AlSagri M. , AlHarrasi N. 
Published: April 2017

Abstract
إن من أهم معايير نجاح خدمات المعلومات الرقمية هو رضى المستفيدين منها وتقبلهم لها. وعليه، فقياس معدلات الرضى هو ليس لمجرد التعرف على التفاعل الحاصل بين الخدمة المقدمة والمستفيدين منها، بل النظر بعمق الى بعض العوامل السلوكية التي تؤثر على مدى تقبل المستفيدين لمصادر المعلومات الرقمية. ووفقاً لمدى تأثير هذه العوامل، تحدد المؤسسة المزودة بالخدمة مقدار ومعدلات الاشتراك في هذه المصادر وحجم الإنفاق عليها.
هدفت هذه الدراسة الى قياس مدى تقبل أعضاء هيئة التدريس بكليات العلوم التطبيقية بسلطنة عمان لمصادر المعلومات الإلكترونية. ولتحقيق ذلك، تم الاعتماد على مجموعة من العوامل السلوكية كالنية السلوكية للاستخدام والفائدة المتوقعة. هذه العوامل وغيرها قد ترتبط أيضا بعوامل أخرى خارجية كجودة النظام وجودة المعلومات والفروقات الفردية بين المستفيدين.

تستفيد الدراسة كثيراً من نموذج تقبل التكنولوجيا Technology Acceptance model في التعرف على العوامل السلوكية والعوامل الخارجية. كما أن العلاقات بين مختلف هذه العوامل سيتم صياغتها كفرضيات للتحقق من ثباتها وصحتها. يعتبر هذا النموذج الأبرز في قياس تقبل التكنولوجيا كتقبل مصادر المعلومات الإلكترونية كما أنه شائع الانتشار وتم تطبيقه على دراسات علمية مشابهة وأثبت فعاليته ونجاحه.

مجتمع الدراسة يتشكل من أعضاء هيئة التدريس العاملين في ست كليات متخصصة في العلوم التطبيقية بسلطنة عمان. تم اختيار 120 فرداً منهم كعينة ممثله، وزعت عليهم استبانة شملت على عوامل مختلفة لقياس مدى تقبلهم لمصادر المعلومات الرقمية المتاحة على النظام الإلكتروني. وللتعرف على ثبات أو نفي الفرضيات طبقت المعادلات الرياضية والتحليل الاستدلالي والمتوسط الحسابي والانحراف المعياري.

أكدت نتائج الدراسة وجود علاقة دالة إحصائياً عند مستوى α ≤ 0.05 في تأثير العوامل السلوكية كسهولة الاستخدام المتوقعة والفائدة المتوقعة في استخدام مصادر المعلومات الإلكترونية. كما أشارت إلى وجود علاقة طردية تربط بين المتغيرات الخارجية (جودة المعلومات) والمتغيرات الإعتقادية (سهولة الاستخدام، الفائدة المتوقعة) والتي بدورها تؤثر على النية السلوكية للاستخدام.
المصادر الإليكترونية غير الرسمية من خلال المستودعات الرقمية المؤسساتية: النشر، قياس الاستخدام والمرئية
Authors: Kertiou Brahim , Battouche K. 
Published: April 2017

Abstractتعد المستودعات المؤسساتية أحدى القنوات غير الرسمية للاتصال العلمي الأكاديمي وذلك من خلال المصادر الإليكترونية العلمية المتاحة بها، والتي تمثل منافذ اتصال مهمة وشرعية. وعليه فالمستودعات المؤسساتية تلعب دوراً بالغ الأهمية في تعزيز الاتصال العلمي ودعمه وذلك من خلال نشر المصادر الإليكترونية العلمية بسهولة وسرعة كبيرة وبأقل تكلفة، فهي تعزز الوصول إلى هذه المصادر فضلا عن أنها تدعم تأثيرها وتقويتها وذلك عن طريق زيادة عرضها مما يسهل اكتشافها والوصول إليها. كما يمكن اعتبار هذه المستودعات إحدى الطرق غير الرسمية للاتصال العلمي، وذلك من خلال نشر المصادر الإليكترونية، التي لا تجد طريقها للنشر في وسائل النشر التقليدية مثل مسودات الأبحاث والعروض التقديمية للمؤتمرات والبيانات الخام.سنحاول من خلال هذه الورقة التطرق إلى مفهوم المصادر الإليكترونية، لاسيما غير الرسمية والمفاهيم ذات العلاقة، كالأدبيات الرمادية والمصادر الإليكترونية الأولية والثانوية. إضافة إلى التطرق لموضوع المستودعات المؤسساتية ودورها في إتاحة المصادر الإليكترونية، وطبيعة وأنواع المحتوى المودع فيها. كما سنستعرض مجموعات المستخدمين المستهدفة من استخدام المصادر الإليكترونية والأساليب المتبعة في قياس استخدام هذه المصادر. كما سنتناول أيضا النشر الإلكتروني وآثاره على الاتصال العلمي والنشر، ومستقبل النشر غير الرسمي وعدم وضوح الحدود الفاصلة في البيئة الرقمية.وسيقتصر تركيز هذه الدراسة على المصادر الإليكترونية التي تنشر خارج إطار النشر الإليكتروني الرسمي، ومع هذا وجب التنبه إلى المقالات الإليكترونية e-prints ، والتي يتم تقسيمها إلى نوعين: مقالات ما قبل النشر preprints ومقالات ما بعد النشر postprints . حيث أن مقالات ما قبل النشر preprints هي مسودات أو مخطوطات الأبحاث التي لم تنشر بعد ولكن قد تم مراجعتها وقبولها وفي انتظار نشرها، أما مقالات ما بعد النشر postprints هي المقالات النهائية أي النسخة المحكمة من المادة و تنتمي إلى عالم النشر الرسمي. وقد تم اعتبار مقالات ما قبل النشر في عالم الطباعة عموما أدبا رماديا على الرغم من أن وجهتها النهائية كان عالم النشر الإليكتروني الرسمي.