bluuebunny/crossref_metadata_2025 huggingface dataset:
The use of linked data to develop and validate measures of variation in mortality and readmissions for public reporting purposes in New South Wales, Australia
Authors: Sutherland Kim , Marashi-Pour Sadaf , Chen Huei-Yang , Lévesque Jean-Frédéric
Published: April 2017

ABSTRACTObjectivesTo investigate variation across 78 New South Wales public hospitals, in mortality in the 30 days following admission and in returns to acute care (readmissions) in the 30 days following discharge for acute myocardial infarction, ischaemic stroke, heart failure, pneumonia, hip fracture surgery.

ApproachLinked data were used to (1) construct an analytic unit – an index period of care that comprised concatenated acute, contiguous hospitalisations with the principal diagnosis of interest; (2) to capture outcomes both within the index hospital and following discharge, wherever they occurred; (3) to enhance risk adjustment with one year look back for relevant comorbidities; (4) to assess fair attribution of outcomes. A risk-standardised mortality ratio (RSMR) and a risk standardised readmission ratio (RSRR) were calculated as the ratio of the observed to the expected number events at a given hospital, by developing and validating condition specific system-level prediction models. Funnel plots identified outliers. For the RSRR, the competing risk of death was considered.

ResultsFor both outcome indicators, sensitivity was enhanced by the use of linked data (33%-100% more deaths; 23%–32% more returns to acute care or readmissions). For mortality, RSMRs that only capture deaths in hospital, as opposed to deaths within 30 days of admission, were shown to be biased and change the outlier status of about 20% of hospitals. Including socioeconomic status in risk adjustment models altered the outlier status of about 10% of hospitals on the cusp of statistical significance but did not significantly alter the RSMRs. For returns to acute care, sensitivity analyses that included socioeconomic status in the models found there was no significant improvement in discriminatory power. For example, in the case of ischaemic stroke, the c-statistic for the model without inclusion of SES was 0.593 (0.578-0.610); inclusion of SES resulted in a c-statistic of 0.600 (0.583-0.616). There were some changes in hospital-level results but there was no clear evidence of a systematic effect on results.

ConclusionThe risk-standardised ratio method, based on linked data, compares a hospital’s results given its case mix with an average New South Wales hospital with the same case mix. Ratio-based indicators have been reported publicly and have proven to be a valuable screening tool to identify hospitals where further investigation may be required locally.
Data linkage of Psychiatric and Maternity data to investigate the pregnancy outcomes of women with Non-affective Psychosis in Scotland
Authors: Mcskimming Paula , Barry Sarah , Park John , Bhattacharya Sohinee , MacBeth Angus
Published: April 2017

ABSTRACTObjectiveWomen with a diagnosis of non-affective psychosis have a lower fertility rate than the general population. However, perinatal outcomes in mothers with non-affective psychosis are under-researched. What is the general fertility rate (GFR) of women with a lifetime diagnosis of non-affective psychosis in Scotland? Does such a diagnosis affect the outcome of pregnancy?

ApproachAn ‘exposed’ cohort with non-affective psychosis and at least one pregnancy was established using a combined dataset derived via data linkage in local safe havens of routine psychiatric and maternity data from two Scottish regions:•NHS Grampian (NHSGr): Aberdeen Maternity and Neonatal Databank (AMND); psychiatric casenotes•NHS Greater Glasgow and Clyde (NHSGG&C): SMR02; PsyCIS bespoke psychiatric databaseExposed women were matched to women without a diagnosis of non-affective psychosis, by maternal age (NHSGG&C only), year of first birth, parity and deprivation, sourced from AMND/SMR02 in a 3:1 unexposed:exposed ratio.

Demographics and pregnancy outcomes of exposed versus unexposed women were analysed to describe effect of psychosis on pregnancy.

ResultsMany challenges were encountered in terms of having legal agreements in place between institutions and safe havens, constructing cohorts and datasets within each study site and joining the data to analyse the overall cohort. Challenges with the data itself included discrepancies between the variables measured in datasets in different sites and missing information within patient records, particularly in earlier years. Preliminary results for the NHSGG&C region show that the average GFR for exposed women aged 15-44 from 2005 to 2014 was 14.38 compared to the general population rate of 55.26. The number of women ever having a miscarriage was significantly higher in the exposed group (23.4% vs 9.9%; p-value <0.001). However during the study period (1996 to 2014), more unexposed women had miscarriages (0.5% vs 4.7%; p-value = 0.002). There were no significant differences in pregnancy complications for the study period. The mean birthweight of babies was lower (3.23kg vs 3.35kg; p-value = 0.029) and more babies were admitted to neonatal units (17.5% vs 9.8%; p-value = 0.004) in the exposed group. Results for the NHSGr region and the combined dataset will also be reported.

ConclusionThis work highlights that there remain hurdles to linking data across sites, despite availability of rich datasets within Scotland. Women with non-affective psychosis within NHSGG&C region had a lower fertility rate on average than the general population and some poorer outcomes, such as birthweight and rate of admission to neonatal units.
Looked after children and access to dental services and oral health in Scotland: a national data-linkage study (LAC-DENTAL)
Authors: McMahon Alex , Sharpe Katharine , Macpherson Lorna , Wood Rachael , Connelly Graham , Milligan Ian , Wilson Philip , King Albert , Elliott Lawrie , Conway David
Published: April 2017

ABSTRACTObjectivesChildren that are ‘looked after’ include those that are accommodated in foster, kinship and residential care placements, as well as those at home on compulsory supervision. They have poorer physical and mental health than their peers and there are concerns about the relatively high levels of untreated morbidity. Oral health and access to dental services among Looked After Children (LAC) has received limited attention to date. The objective of this study was to compare the oral health and access to dental services of children who are looked after by the state, with comparable children in the general population.

ApproachSchool and Social Work datasets were able to be linked using the Scottish Exchange of Data (ScotXed) Unit. This in turn was linked with health data making use of the Scottish national record-linkage system provided by the NHS eDRIS team for the FARR Institute Scotland. All of the following datasets used in this study are complete national datasets for the time periods noted. School Pupil Census 2012: a census of children in local authority primary and secondary schools that provides each child’s age, sex and socioeconomic status as measured by the Scottish Index of Multiple Deprivation (SIMD). The other datasets cover the period 2008-2012: LAC- all children with social work referrals for various types of placement; registration with dentists; hospital discharge data for all episodes of tooth extraction; National Dental Inspection Programme (NDIP) data from Primary 1 and Primary 7 school years (dental decay). The LAC group were compared to their peers by logistic regression adjusted by SIMD, using remote access to the National Safe Haven.

ResultsThere were 633204 subjects in the study group (10927 LAC, 622280 nonLAC). Ages ranged from four to 17 years (mean 12 LAC and 10 nonLAC); with 53% male for LAC and 51% nonLAC; and 42% in the most deprived SIMD level for LAC and 21% for non-LAC. The subjects in the LAC group were more likely to have dental decay at Primary 1, odds-ratio (OR) 2.93 (2.55, 3.38), and Primary 7, OR 1.81 (1.68, 1.94). LAC subjects were less likely to be registered with a dentist, OR 0.50 (0.43, 0.59), and more likely to have teeth extracted, OR 1.50 (1.40, 1.60). All tests p<0.001.

ConclusionLooked after children are more likely to have dental problems and less likely to use dental services than their peers, after adjustment for socioeconomic status.
Hospital admissions in children who had pelvicalyceal diltation detected on ultrasound scan during pregnancy: an e-cohort study
Authors: Wright Melissa , Paranjothy Shantini , Fone David , Brophy Sinead , Demmler Joanne
Published: April 2017

ABSTRACTObjectiveTo explore whether children with pelvicalyceal dilatation (PCD, a marker detected during the 18-20 week gestation ultrasound scan in which there is enlargement of tubes that collect urine in the kidney) have more hospital admissions for kidney problems in childhood compared to children without the marker.

Approach We were funded by NISCHR to study outcomes associated with markers of uncertain significance at the second trimester anomaly scan (Welsh Study of Mothers and Babies). Data collected in the WSMB was uploaded to the Secure Anonymised Information Linkage (SAIL) databank and record linked to hospital activity data. Patterns of hospital admissions for renal causes were described and compared between those with no markers and those with PCD. Children were followed up from birth until 31st December 2014 or until the age of 5. A Cox Proportional Hazard Model was used to investigate the impact of PCD on time to first presentation.

Results (Preliminary)Of the WSMB cohort, 20,834 children were eligible for inclusion in analyses. Those with PCD had 6.29 times the hazard of a renal admission compared to those without the marker (95% CI: 3.69 to 10.72). Children with PCD were more likely to have multiple renal admissions to hospital - median (interquartile range) number of renal admissions, 2.5 (1 to 5) compared to 1 (1 , 1) in children without markers.

ConclusionPreliminary analysis suggests there is increased childhood renal morbidity associated with the presence of a PCD marker detected on the 18-20 week gestation ultrasound scan. These findings will inform the discussions clinicians have with parents when discussing the implications of this marker for the health of the chid.
Using linked health survey and Census data to understand transitions to instutional care among Canadian seniors
Authors: Sanmartin Claudia , Garner Rochelle
Published: April 2017

ABSTRACT

ObjectivesWhile existing data sources, such as the 2011 Census, provide an accurate count of who is currently institutionalized, there is a significant gap in terms of our understanding of who is at risk for institutionalization and what the future demand for care will be. The objective of this study is to use linked national health survey, the 2005 Canadian Community health Survey (CCHS), to the 2011 Census to identify factors associated with transitions from private households to alternative living arrangements, specifically long-term care (nursing homes), and retirement homes among Canadians 55 years of age and older.

ApproachHierarchical deterministic methods were used to link the 2005 CCHS (n=114,000) to the 2011 Census (n=35 million) using identifying variables common to both data sets (i.e. name, birthdate, sex, postal code, social insurance number). Sex specific multivariate regression models with multiple outcomes were used to assess the impact of a comprehensive set of factors (i.e. demographic, socio-economic, health status, chronic conditions and marital status) available in the CCHS on the likelihood of residing in three possible home environments, relative to living in a private dwelling (PD): long-term care (LTC), retirement homes (RH) or private dwelling with support (PDS) as identified in the 2011 Census. Analyses were adjusted for mortality.

ResultsOver 85% of CCHS records were linked to the 2011 Census (n=92,849). Among those 55 years of age and older (n=29,934), approximately 2.0% and 1.6% were living in LTC and RH respectively: an additional 7.2% were living in PDS. Results of the regression analyses, revealed that those with Alzheimer’s disease were at highest risk of transition to LTC (OR=11.7 females; 6.8 males). Losing a spouse was significantly associated with transitions to LTC, RH and PDS for both men and women. Being an immigrant was protective, with immigrant seniors less likely to transition to LTC and RH. Other factors significantly associated with transitions to LTC included low income, poor mental health (women only), and assistance with activities of daily living (meal preparation for women, finances for men). Regional variations were also noted.

ConclusionNewly linked health survey and census data provide a unique opportunity to take a comprehensive look at those most at risk for institutionalization.
Automated de-identification of clinical free-text
Authors: Dehghan Azad , Liptrot Tom , O’hara Catherine , Barker-Hewitt Matthew , Tibble Daniel , Nenadic Goran
Published: April 2017

ABSTRACTObjectivesIncreasing interest to use unstructured electronic patient records for research has attracted attention to automated de-identification methods to conduct large scale removal of Personal Identifiable Information (PII). PII mainly include identifiable information such as person names, dates (e.g., date of birth), reference numbers (e.g., hospital number, NHS number), locations (e.g., hospital names, addresses), contacts (e.g., telephone, e-mail), occupation, age, and other identity information (ethnical, religion, sexual) mentioned in a private context. 

De-identification of clinical free-text remains crucial to enable large-scale data access for health research while adhering to legal (Data Protection Act 1998) and ethical obligations. Here we present a computational method developed to automatically remove PII from clinical text.

ApproachIn order to automatically identify PII in clinical text, we have developed and validated a Natural Language Processing (NLP) method which combine knowledge- (lexical dictionaries and rules) and data-driven (linear-chain conditional random fields) techniques. In addition, we have designed a novel two-pass recognition approach that uses the output of the initial pass to create patient-level and run-time dictionaries used to identify PII mentions that lack specific contextual clues considered by the initial entity extraction modules. The labelled data used to model and validate our techniques were generated using six human annotators and two distinct types of free-text from The Christie NHS Foundation Trust: (1) clinical correspondence (400 documents) and (2) clinical notes (1,300 documents).

ResultsThe de-identification approach was developed and validated using a 60/40 percent split between the development and test datasets. The preliminary results show that our method achieves 97% and 93% token-level F1-measure on clinical correspondence and clinical notes respectively. In addition, the proposed two-pass recognition method was found particularly effective for longitudinal records. Notably, the performances are comparable to human benchmarks (using inter annotator agreements) of 97% and 90% F1 respectively.

ConclusionsWe have developed and validated a state-of-the-art method that matches human benchmarks in identification and removal of PII from free-text clinical records. The method has been further validated across multiple institutions and countries (United States and United Kingdom), where we have identified a notable NLP challenge of cross-dataset adaption and have proposed using active learning methods to address this problem. The algorithm, including an active learning component, will be provided as open source to the healthcare community.
Obtaining structured clinical data from unstructured data using natural language processing software
Authors: Lacey Arron S , Fonferko-Shadrach Beata , Lyons Ronan A , Kerr Mike P , Ford David V , Rees Mark I , Pickrell Owen W
Published: April 2017

ABSTRACT

BackgroundFree text documents in healthcare settings contain a wealth of information not captured in electronic healthcare records (EHRs). Epilepsy clinic letters are an example of an unstructured data source containing a large amount of intricate disease information. Extracting meaningful and contextually correct clinical information from free text sources, to enhance EHRs, remains a significant challenge. SCANR (Swansea University Collaborative in the Analysis of NLP Research) was set up to use natural language processing (NLP) technology to extract structured data from unstructured sources.

IBM Watson Content Analytics software (ICA) uses NLP technology. It enables users to define annotations based on dictionaries and language characteristics to create parsing rules that highlight relevant items. These include clinical details such as symptoms and diagnoses, medication and test results, as well as personal identifiers.

 

ApproachTo use ICA to build a pipeline to accurately extract detailed epilepsy information from clinic letters.

MethodsWe used ICA to retrieve important epilepsy information from 41 pseudo-anonymized unstructured epilepsy clinic letters. The 41 letters consisted of 13 ‘new’ and 28 ‘follow-up’ letters (for 15 different patients) written by 12 different doctors in different styles. We designed dictionaries and annotators to enable ICA to extract epilepsy type (focal, generalized or unclassified), epilepsy cause, age of onset, investigation results (EEG, CT and MRI), medication, and clinic date. Epilepsy clinicians assessed the accuracy of the pipeline.

ResultsThe accuracy (sensitivity, specificity) of each concept was: epilepsy diagnosis 98% (97%, 100%), focal epilepsy 100%, generalized epilepsy 98% (93%, 100%), medication 95% (93%, 100%), age of onset 100% and clinic date 95% (95%, 100%).

Precision and recall for each concept were respectively, 98% and 97% for epilepsy diagnosis, 100% each for focal epilepsy, 100% and 93% for generalized epilepsy, 100% each for age of onset, 100% and 93% for medication, 100% and 96% for EEG results, 100% and 83% for MRI scan results, and 100% and 95% for clinic date.

Conclusions ICA is capable of extracting detailed, structured epilepsy information from unstructured clinic letters to a high degree of accuracy. This data can be used to populate relational databases and be linked to EHRs. Researchers can build in custom rules to identify concepts of interest from letters and produce structured information. We plan to extend our work to hundreds and then thousands of clinic letters, to provide phenotypically rich epilepsy data to link with other anonymised, routinely collected data.
A Federated Data Linkage Strategy to Support Population Health Research in Canada
Authors: Flanagan Tanya , Moore Céline , Sandoval Carolyn
Published: April 2017

ABSTRACT

ObjectivesCanada has established a pan-Canadian cohort with over 300,000 volunteer participants aged 35-69, to support research on cancer and chronic disease. A key feature of the cohort is that participants have consented to link their cohort data with administrative datasets. This prospective cohort, representing nearly 1 in 50 Canadians in this age range will be followed for multiple decades, building a platform that supports access to timely, high-quality, data related to cancer and other chronic diseases, which will enable researchers to answer complex system questions and achieve better health outcomes for Canadians.

ApproachA baseline “core” questionnaire was administered to participants capturing information on socio-demographics, economic characteristics, personal and familial history of diseases and lifestyle and health behaviours. A re-contact questionnaire is planned for 2016 to update baseline information and add depth to specific areas and capture changes over time. To realize the full potential for this cohort to support transformative research it is crucial to be able to link this data with other provincial datasets, such as cancer registries, hospital records and mortality data.

For the most part, health data in Canada resides under the purview of health providers and, or government custodians in each of the provinces and territories. As such, an innovative federated data linkage strategy is required to link cohort data with health administrative data in each regions, adhering to existing privacy and regulatory requirements, while providing central access for researchers.

ResultsTo date, 40% of all cohort participants have been linked with priority provincial administrative data. Each province has its own unique data linkage challenges, requiring unique customized solutions. By the end of 2017 we anticipate that the number of participants who will have had their data linked will increase to nearly 70%. The federated data linkage strategy and infrastructure offer an innovative approach that others can learn from; however to realize the full potential of the cohort and support transformative research partnerships and collaborations are required.

ConclusionEfforts to organize resources and establish systems for data linkage and optimize data sharing and utilization in Canada are underway and include discussions with the provincial privacy commissioners, national and provincial and territorial data custodians and other thought leaders in the field.
Barriers to high quality coding of hospital chart information to administrative data: A qualitative study
Authors: Tang Karen , Lucyk Kelsey , Quan Hude
Published: April 2017

ABSTRACTObjectives Administrative data are widely used in research, health policy, and the evaluation of health service delivery. We undertook a qualitative study to explore the barriers to high quality coding of chart information to administrative data, at the level of coders in Canada.

ApproachOur study design is qualitative. We recruited professional medical chart coders and data users working across Alberta, Canada, using a multimodal recruitment strategy. We conducted an in-depth, semi-structured interview with each participant. All interviews were audio-recorded and transcribed. We conducted thematic analysis (e.g., line-by-line open coding) of interview transcripts. Codes were then collated into themes and compared across our dataset to ensure accurate interpretations of the data. The study team met to discuss, modify, and interpret emergent themes in the context of the barriers to coding administrative data.

ResultsWe recruited 28 coding specialists. In general, coders had high job satisfaction and sense of collegiality, as well as sufficient resources to address their coding questions. They believed themselves to be adequately trained and consistently put in the extra effort when searching charts to find additional information that accurately reflected the patient journey. Barriers to high quality coding from the coder perspective included: 1) Incomplete and inaccurate information in physician progress notes and discharge summaries; 2) Difficulty navigating a complex hybrid of paper and electronic medical records; 3) Focus on productivity rather than quality by the employer, which at times resulted in inconsistent instructions for coding secondary diagnoses and discordant expectations between the employer and the coders’ professional standards.

ConclusionFuture interventions to improve the quality of administrative data should focus on physician education of necessary components in charting, evaluation of electronic medical records from the perspectives of those who play a key role in abstracting data, and evaluation of productivity guidelines for coders and their effects on data quality.
Business datasets and record linkage: Correlates of linkage and estimating risks of non-linkage biases.
Authors: Moore Jamie , Durrant Gabriele , Smith Peter W.
Published: April 2017

ABSTRACT

ObjectivesOur first objective is to investigate how between subject differences in the likelihood of record linkage consent and record linkability determine the composition of and so risks of biases in estimates from linkable business datasets. The utility of datasets linking information from multiple sources is compromised by such non-linkage biases, but both components of the linkage process have rarely been considered. Our second objective is to introduce methods for evaluating non-linkage bias risks in datasets. Such evaluations can inform linkage method choice and assessment of the validity of linked dataset findings. Previous work, often lacking non-linked subject information on non-sample dataset covariates, tends to utilise overall linkage rates as quality measures, but in the related area of survey non-response correlations between analogous response rates and non-response biases are weak.

Approach We utilise the UK 2010 Small Business Survey (SBS) dataset. If a survey subject consents to record linkage, an attempt is made to append their Inter-Departmental Business Register (IDBR) identifier (if one exists), enabling linkage to other surveys etc. Given this, we evaluate bias risks arising from variation in subject linkage consent and identifier appendability, as well as its product, overall linkability, utilising representativeness indicators developed to evaluate survey non-response bias risks. These measure risks in terms of sample-subset similarity (representativeness) given an attribute covariate set obtained from the sample dataset, based on variation in subject inclusion propensities estimated by logistic regression, and are decomposable to assess correlates of inclusion propensity variation. Specifically, we use the CV (the standard deviation of inclusion propensities divided their mean), computed given nine attribute covariates describing business demography and perceived performance.

ResultsWe give full details in our presentation. Briefly, overall CVs suggest the linkable dataset exhibits substantial non-representativeness and non-linkage bias risk. Decompositions suggest main impacts on the linkable dataset are under-representation of very small businesses (those with low turnovers, few employees and / or un-incorporated), due to being both less likely to consent and less likely to have an identifier appended, and under-representation of businesses unable / refusing to respond to survey items, due to being less likely to consent.

Conclusions Our analyses provide evidence of non-linkage bias risks in linked SBS datasets caused by under-representation of several sample subgroups. Each is explicable given known IDBR under-coverage or knowledge of business response processes. We also conclude that representativeness indicators are an easily applied method by which such risks can be evaluated.
Business Intelligence System for Government and the Community
Authors: Radbone Christopher
Published: April 2017

ABSTRACT

ObjectivesBusiness Intelligence System for Government and the Community's goal is to assist the delivery of quality publically funded services and infrastructure informed by evaluation and research. Governments drive for open data can facilitate reduced budget expenditure and maximised value and benefit to citizens from government funded services and infrastructure. The challenge is to incorporate non-for-profit and for-profit organisation's data into this business intelligence and reporting capacity. Obviously there are necessary governance issues to be resolved to include non-government data. These issues include ensuring the legal release of data as well maintaining the trust of the community through adequate data security, privacy protection and demonstration of public benefit from the use of sensitive data. In building on the government's capability to bring together data for public good purposes, the wider community needs to be included for the ability to monitor, evaluate and perform research at a unit record level on publically funded government and non-for-profit provided services.

ApproachIt is critically important to demonstrate trust to both the community and delegated Data Custodians responsible for approving data release and use. This ability to bridge across the government and community has three goals including:

1. Striving for world class public funded services and infrastructure including Health & Wellbeing, Education, Training, Economic, Employment, Criminal and Justice, Social Services.2. Providing the evidence base to inform Policy, Planning, Evaluation, Monitoring of Programs, and to promote Innovation.3. Providing cost effective and appropriate service delivery, infrastructure and programs - informed by Science & Research.

With multiple tiers of government and multiple agencies collecting and maintaining large databases, resulting in silos which prevent bringing together an evidence base, consideration is required on how best to collect and utilise the data from the non-for-profit and for-profit sectors to inform government planning, priorities and spending.

A federated model is required to bring together data from multiple agencies and organisations, with the critical role of a trusted third party data broker for assurance of privacy protecting and governance.

ResultsThere are significant challenges from multiple jurisdictions and tiers government, and the need to facilitates legal data access for ethically approved use. Legislative reform is required to provide the approved processes to demonstrate assurance to the community, and enable data custodians participation.

ConclusionA Business Intelligence System for Government and the Community requires political leadership, the establishment of trust and the active engagement across the community.
General Public Views on Uses and Users of Administrative Health Data
Authors: Paprica P. Alison , Schull Michael
Published: April 2017

ABSTRACTObjectivesHigh profile initiatives and reports highlight the potential benefits that could be realized by increasing access to health data, but do members of the general public share this view? The objective was to gain insight into the general public’s attitudes toward users and uses of administrative health data.

ApproachIn fall 2015, four professionally-moderated focus groups with a total of 31 Ontario participants were conducted; two in Thunder Bay, two in Toronto. Participants were asked to review and comment on: general information about research based on linked administrative health data, a case study and models through which various users might use administrative health data.

ResultsSupport for research based on linked administrative health data was strongest when people agreed with the purposes for which studies were conducted. The main concerns related to the security of personal data generally (e.g., Canada Revenue Agency hacking incidents were noted) and potentially inappropriate uses of health data, particularly by the private sector (e.g., strong reservations about studies done solely or primarily with a profit motive). Participants were reassured when provided with information about the process for removing or coding identifying information from health data, and about the oversight provided by the Information and Privacy Commissioner of Ontario. However, even when fully informed of privacy and security safeguards, participants still felt that risks unavoidably increase when there are more people and organizations accessing data.

ConclusionsMembers of general public were generally supportive of research based on linked administrative health data but with conditions, particularly when the possibility of private sector research was discussed. Notably, and citing security concerns, focus group participants preferred models that had a limited number of individuals or organizations accessing data.
The inpatient, outpatient and social care costs associated with atrial fibrillation in Scotland: a record linkage study
Authors: Ciminata Giorgio , Wu Olivia , Geue Claudia
Published: April 2017

ABSTRACTBackgroundAtrial Fibrillation (AF) is a highly debilitating condition with significant economic burden. Previous studies have estimated the cost of hospitalisations associated with AF in Scotland. However, patients with AF are often elderly with co-morbidities requiring substantial outpatient and social care.

ObjectivesThis study seeks to estimate inpatient, outpatient and social care costs associated with AF in a Scottish cohort, by using individual-level linked data.

MethodsThe AF cohort of 50 years and older patients, hospitalised with a known diagnosis of AF or atrial flutter between 1997 and 2014, was followed up for five years following the first AF event. Individual-level data on hospitalisation and discharge to social care home were obtained from the Scottish Morbidity Records (SMR01); whereas data on outpatient attendance were obtained from (SMR00). Death records for the same time period were extracted from National Records of Scotland (NRS). Hospital and outpatient costs associated with the corresponding data were estimated utilising the Scottish National Tariff (SNT) based on Healthcare Resource Groups (HRGs), and the Scottish Health Service Costs report, respectively. Social care costs were identified from the Care Home Census. Following data linkage, the econometric analysis was carried out using a two-part model where, the first part estimates through a probit model the probability of using a healthcare service, and the second part estimates costs conditional on having incurred positive costs. The regression model was adjusted for demographic characteristics, socio-economic status, year of admission and location.

ResultsOverall, a cohort of 253,963 AF patients accounted for 2,988,607 hospital admissions and 4,452,476 outpatient attendances. The mean cost per patient was estimated to be £3,071 (95% CI 3,033-3,109). Overall, hospital admissions and outpatient visits accounted for 71.7% and 3.7% of the total cost, respectively; social care accounted for 24.6% of the total costs. The cost increased with age and females incurred higher costs than males. Significant differences were observed among the urban/rural classifications, individual health boards and the socio-economic status.

ConclusionsThis study has shown the importance of taking into account healthcare resource use incurred beyond hospitalisation. In addition to inpatient costs, outpatient and social care costs contribute considerably to the overall economic burden.
The Impact of Pre-existing Health Conditions on Cost of Recovery after Workplace Injury: Insight from population-based data linkage in the State of Victoria, Australia
Authors: Hassani-M Behrooz , Berecki-Gisolf Janneke , Collie Alex
Published: April 2017

ABSTRACTObjectiveComorbidity is known to affect length of hospital stay and mortality after trauma but less is known about its impact on recovery beyond the acute care period. A main challenge to study the impact of pre-existing conditions is that information on these conditions is not collected systematically and comprehensively. The aim of this study was to investigate the role of pre-existing health conditions in recovery from workplace injury using linked data. ApproachIn Victoria, Australia, approximately 85% of the labour force is covered by the state workers compensation scheme regulated by WorkSafe Victoria. The scheme provides financial compensation for healthcare and income support to eligible injured workers. . One year of WorkSafe claims for injuries that occurred between 1/07/2008 and 31/06/2009 (N = 49,171) were linked to eight years of pre-injury hospital admission admissions and emergency department presentations, received from the state Department of Health and Human Services. Main outcomes of the study included the total and categorical cost of recovery (e.g. hospital, medical, allied health) measured over short (2-6 months), medium (1-2 years) and long-term (5 years) periods. All models controlled for characteristics of the worker, workplace and injury.ResultsThe preliminary results show that the cost of recovery from workplace injury is significantly associated with history of pre-injury admissions: Workers with pre-injury admissions have higher cost of recovery including longer periods of time off work as well as further cost of health service use during recovery. As this is an ongoing project, further detailed results will be presented at the conference such as the impact of admission under each category of pre-existing conditions according to ICD codes on a wide range of outcomes after workplace injury.Conclusion Our findings are expected to help government injury compensation regulators to better understand the drivers of compensation costs and other key system outcomes such as return to work. The findings will support better allocation of financial resources, better internal management of claims and efficient allocation of physical and human resources and therefore greater client satisfaction leading to ensuring faster recovery, return to work and more effective as well as efficient service provision.
Public understanding of, and attitudes towards, data linkage in research
Authors: Moody Gwenllian , Lugg Fiona
Published: April 2017

ABSTRACTObjectivesThere is an ongoing need to involve and inform the public about data linkage research. Projects at the South East Wales Trials Unit (SEWTU) and Division of Population Medicine, Cardiff University have focused on participant and public understanding of, and attitudes towards the use of routine/linked data for research purposes.

ApproachHealthWise Wales is a Welsh national cohort using prospectively collected data linked with NHS records. Face-to-face and online focus groups were conducted to explore the barriers and facilitators to signing up to this project as well as discussing the best way to communicate the technical details of the project. MINIMAL PhD conducted a focus group with care-experienced young people to gather attitudes towards the collection and linkage of child maltreatment data. The Public and Patient Involvement activities of the Building Blocks 2-6 Study included meetings with a young mothers group utilising their skills as advisors on communicating data linkage issues with study participants. These projects have been undertaken independently however comprise the same underlying questions – Do the public understand why routine & linked data is used for research? Will this be a barrier to participating? How can we communicate study design to ensure participants are fully informed? This presentation will summarise the similarities and contrasting attitudes and beliefs emerging from these projects.

ResultsWe have identified similar emerging themes from both the HealthWise Wales focus groups and MINIMAL PhD focus groups. Participants found it challenging to understand the methodology of data linkage and this acted as a barrier to taking part in data linkage projects. Once participants felt fully informed of the method, their concerns around data safety and confidentiality were reduced. Participants required assurances that their data were safe, that they could not be identified, and that researchers can be trusted to access these data before considering the research project in discussion. Participants also discussed the collection of sensitive data from various sources through data linkage, consent issues, and the balance between research risk/benefit for the MINIMAL PhD focus group.

ConclusionThese qualitative studies will contribute to knowledge of how to better inform members of the public about routine / linked data, as it is clear than there remains a lack of understanding of the research conducted in this area, and the importance for researchers to utilise these data. Researchers need to get the communication right in order to be successful at recruiting and retaining participants.
Investigation and reporting of Data Quality within and between linked SAIL datasets
Authors: Rees Sarah , Rees Arfon
Published: April 2017

ABSTRACTObjectivesThe SAIL databank brings together a range of datasets gathered primarily for administrative rather than research processes. These datasets contain information regarding different aspects of an individual’s contact with services which when combined form a detailed health record for individuals living (or deceased) in Wales.

Understanding the quality of data in SAIL supports the research process by providing a level of assurance about the robustness of data, identifying and describing where there may be sources of potential bias due to invalid, incomplete, inconsistent or inaccurate data and therefore helping to increase the accuracy of research using these data.

Designing processes to investigate and report on data quality within and between multiple datasets can be a time-consuming task to undertake; it requires a high degree of effort to ensure it is genuinely meaningful and useful to SAIL users and may require a range of different approaches.

ApproachData quality tests for each dataset were written, considering a range of data quality dimensions including validity, consistency, accuracy and completeness. Tests were designed to capture not just the quality of data within each dataset, but also to assess consistency of data items between datasets. SQL scripts were written to test each of these aspects: in order to minimise repetition, automated processes were implemented where appropriate.

Batch automation was used to called SQL stored procedures, which utilise metadata to generate dynamic SQL. The metadata (created as part of the data quality process) describes each dataset and the measurement parameters used to assess each field within the dataset. However automation on its own is insufficient and data quality process outputs require scrutiny and oversight to ensure they are actually capturing what they set out to do.

SAIL users were consulted on the development of the data quality reports to ensure usability and appropriateness to support data utilisation for research.

ResultsThe data quality reporting process is beneficial to the SAIL databank as it provides additional information to support the research process and in some cases may act as a diagnostic tool, detecting problems with data which can then be rectified.

ConclusionThe development of data quality processes in SAIL is ongoing, and changes or developments in each dataset lead to new requirements for data quality measurement and reporting. A vital component of the process is the production of output that is genuinely meaningful and useful.
Resistencia antibiótica de bacilos gramnegativos de ambientes intrahospitalarios
Authors: Guerrero Barrantes César , Guillén Oneeglio Alfredo , Rojas León Roberto , Díaz Tello Alberto , Noriega Romero Edix
Published: April 2017

Los bacilos gramnegativos están comprometidos como causales de infecciones intrahospitalarias,  siendo necesario mantener una vigilancia constante de los ambientes críticos de los centros de salud y determinar la resistencia antibiótica de las bacterias, los géneros más resistentes, las resistencias frecuentes observadas en ellos y los servicios mayormente contaminados. Se evaluaron 74 cultivos aislados de diferentes superficies de los servicios hospitalarios, obtenidos por frotis de las superficies y su respectivo cultivo e identificación bacteriana. Las especies aisladas fueron:  E. coli (29), Enterobacter cloacae (11), Enterobacter agglomerans (10), Klebsiella pneumoniae (9), Citrobacter freundii (3), Serratia marcescens (5), Pantoea agglomerans (4), Aeromonas spp. (2) y Proteus vulgaris (1). Los servicios mayormente contaminados fueron: Cuidados Intermedios, Medicina Interna, Cirugía y Neurología.  La resistencia promedio  en los cultivos evaluados fue del 33%,  con el 58% para Ampicilina, el 45% para Cefoxitina, el  41% para Aztreonam,  el 39% para Ceftazidima, Ceftriaxona y Nitrofurantoina, mientras que para Imipenem fue el 22%, para Meropenem  el 27%, para Amikacin el 11% y Piperacilina-Tazobactan el 9%. La multirresistencia antibiótica se dio en el 69% de los cultivos, especialmente en Aeromonas,  Proteus vulgaris, Klebsiella pneumoniae,  Citrobacter freundii, Sarratia marcescens y E. coli. La tendencia de la resistencia antibiótica es ascendente, especialmente a las cefalosporinas y carbapenemes.Palabras clave: Resistencia, bacilos gram-negatiivos, ambientes intrahospitalarios
Diseño y prueba en aulas de clases de una aplicación con realidad aumentada para soporte a la difusión de conocimientos de los dioses moche de manera gradual en educación primaria
Authors: León Lescano Norma , Eyzaguirre Mamani Sandra
Published: April 2017

El desarrollo de aplicaciones con realidad aumentada aplicado a la educación es casi nuevo en el Perú. El objetivo del presente trabajo fue describir el diseño y mostrar los resultados de la prueba de una aplicación de realidad aumentada para soporte a la difusión de conocimientos sobre las culturas peruanas. La prueba se hizo sobre la cultura Moche y particularmente cómo se identifica a sus dioses Ni, Luna e Iguana; en estudiantes del cuarto, quinto y sexto grado de educación primaria. Para el diseño de la aplicación se usó el método de diseño de software y para la prueba con los estudiantes el método cualitativo con observación participante. Para probar la interacción y aceptación de la aplicación se tomó como muestra cuatro aulas de educación primaria con dieciocho estudiantes promedio cada una, de un colegio particular situado en el distrito de San Juan de Lurigancho. Se logró comprobar que los estudiantes identificaron los dioses, y aceptaron la tecnología con naturalidad.
Gestão Ambiental: uma análise da Evidenciação das Empresas que compõem o Índice de Sustentabilidade Empresarial (ISE)
Authors: Silva Júlio Orestes da , Rocha Irani , Wienhage Paulo , Rausch Rita Buzzi
Published: April 2017

Essa pesquisa buscou analisar as informações relacionadas à gestão ambiental mais evidenciadas nos relatórios de administração e notas explicativas das empresas que compõem o Índice de Sustentabilidade Empresarial (ISE). Para tal, optou-se por uma pesquisa documental descritiva, com abordagem qualitativa, por meio de análise de conteúdo. A amostra constitui-se de todas as empresas que compõem o Índice de Sustentabilidade Empresarial 2009/2010 da BOVESPA, totalizando 29 empresas. Constatou-se nas análises realizadas que a evidenciação ambiental destacou-se em 128 observações, que correspondem a 12% do total possível de evidenciação ambiental com base no modelo proposto. Ressalta-se ainda que as informações de gestão ambiental mais evidenciadas referem-se a “Resíduos” e a “Energia”, porém por serem empresas que fazem parte de um índice que considera questões ambientais na escolha das empresas participantes, compreende-se que a evidenciação de informações de gestão ambiental deva ser mais comumente explicitada nos relatórios, que servem como fontes de informação na tomada de decisão dos diversos usuários.Palavras-chave:Gestão Ambiental. Evidenciação. Índice de Sustentabilidade Empresarial.AbstractThis research investigates the information related to environmental management more evident in reports of management and notes of the companies that compose the Corporate Sustainability Index (CSI). For this purpose, a descriptive documental analysis was chosen, with qualitative method, using content analysis. The sample consisted of all the companies that compose the Corporate Sustainability Index of BOVESPA 2009/2010, comprehending 29 companies. It was found that the environmental disclosure noted in 128 observations, which represent 12% of the possible total amount of environmental disclosure based on the proposed model. It was noted that the more evident information on environmental management refer to "waste" and "Energy", but because they are companies that are part of an index that considers environmental issues in the choice of participating companies, it is understood that disclosure of information of environmental management must be more clearly demonstrated in the reports, which serve as sources of information in decision-making of different users.Keywords:Environmental Management. Disclosure. Sustainability Index.