Dataset Information

Protocol for the Data-Linkage Alcohol Cohort Study (DACS): investigating mortality, morbidity and offending among people with an alcohol-related problem using linked administrative data.

ABSTRACT:

Introduction

The aims of this program of research are to use linked health and law enforcement data to describe individuals presenting to emergency and inpatient healthcare services with an acute alcohol harm or problematic alcohol use; measure their health service utilisation and law enforcement engagement; and quantify morbidity, mortality, offending and incarceration.

Methods and analysis

We will assemble a retrospective cohort of people presenting to emergency departments and/or admitted to hospitals between 1 January 2005 and 31 December 2014 in New South Wales, Australia with a diagnosis denoting an acute alcohol harm or problematic alcohol use. We will link these data with records from other healthcare services (eg, community-based mental healthcare data, cancer registry), mortality, offending and incarceration data sets. The four overarching areas for analysis comprise: (1) describing the characteristics of the cohort at their first point of contact with emergency and inpatient hospital services in the study period with a diagnosis indicating an acute alcohol harm and/or problematic alcohol use; (2) quantifying health service utilisation and law enforcement engagement; (3) quantifying rates of mortality, morbidity, offending and incarceration; and (4) assessing predictors (eg, age, sex) of mortality, morbidity, offending and incarceration among this cohort.

Ethics and dissemination

Ethics approval has been provided by the New South Wales Population and Health Services Research Ethics Committee. We will report our findings in accordance with the REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement and Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) where appropriate. We will publish data in tabular, aggregate forms only. We will not disclose individual results. We will disseminate project findings at scientific conferences and in peer-reviewed journals. We will aim to present findings to relevant stakeholders (eg, addiction medicine and emergency medicine specialists, policy makers) to maximise translational impact of research findings.

SUBMITTER: Peacock A

PROVIDER: S-EPMC6687018 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Protocol for the Data-Linkage Alcohol Cohort Study (DACS): investigating mortality, morbidity and offending among people with an alcohol-related problem using linked administrative data.

Peacock Amy A Chiu Vivian V Leung Janni J Dobbins Timothy T Larney Sarah S Gisev Natasa N Pearson Sallie-Anne SA Degenhardt Louisa L

BMJ open 20190805 8

<h4>Introduction</h4>The aims of this program of research are to use linked health and law enforcement data to describe individuals presenting to emergency and inpatient healthcare services with an acute alcohol harm or problematic alcohol use; measure their health service utilisation and law enforcement engagement; and quantify morbidity, mortality, offending and incarceration.<h4>Methods and analysis</h4>We will assemble a retrospective cohort of people presenting to emergency departments and/ ...[more]

PMID: 31383711

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Project description:IntroductionCongenital anomalies (CAs) are a major cause of infant mortality, childhood morbidity and long-term disability. Over 130 000 children born in Europe every year will have a CA. This paper describes the EUROlinkCAT study, which is investigating the health and educational outcomes of children with CAs for the first 10 years of their lives.Methods and analysisEUROCAT is a European network of population-based registries for the epidemiological surveillance of CAs. EUROlinkCAT is using the EUROCAT infrastructure to support 22 EUROCAT registries in 14 countries to link their data on births with CAs to mortality, hospital discharge, prescription and educational databases. Once linked, each registry transforms their case data into a common data model (CDM) format and they are then supplied with common STATA syntax scripts to analyse their data. The resulting aggregate tables and analysis results are submitted to a central results repository (CRR) and meta-analyses are performed to summarise the results across all registries. The CRR currently contains data on 155 594 children with a CA followed up to age 10 from a population of 6 million births from 1995 to 2014.EthicsThe CA registries have the required ethics permissions for routine surveillance and transmission of anonymised data to the EUROCAT central database. Each registry is responsible for applying for and obtaining additional ethics and other permissions required for their participation in EUROlinkCAT.DisseminationThe CDM and associated documentation, including linkage and standardisation procedures, will be available post-EUROlinkCAT thus facilitating future local, national and European-level analyses to improve healthcare. Recommendations to improve the accuracy of routinely collected data will be made.Findings will provide evidence to inform parents, health professionals, public health authorities and national treatment guidelines to optimise diagnosis, prevention and treatment for these children with a view to reducing health inequalities in Europe.

Project description:IntroductionThe American Hospital Association (AHA) has hospital-level data, while the Centers for Medicare & Medicaid Services (CMS) has patient-level data. Merging these with other distinct databases would permit analyses of hospital-based specialties, units, or departments, and patient outcomes. One distinct database is the National Emergency Department Inventory (NEDI), which contains information about all EDs in the United States. However, a challenge with merging these databases is that NEDI lists all US EDs individually, while the AHA and CMS group some EDs by hospital network. Consolidating data for this merge may be preferential to excluding grouped EDs. Our objectives were to consolidate ED data to enable linkage with administrative datasets and to determine the effect of excluding grouped EDs on ED-level summary results.MethodsUsing the 2014 NEDI-USA database, we surveyed all New England EDs. We individually matched NEDI EDs with corresponding EDs in the AHA and CMS. A "group match" was assigned when more than one NEDI ED was matched to a single AHA or CMS facility identification number. Within each group, we consolidated individual ED data to create a single observation based on sums or weighted averages of responses as appropriate.ResultsOf the 195 EDs in New England, 169 (87%) completed the NEDI survey. Among these, 130 (77%) EDs were individually listed in AHA and CMS, while 39 were part of groups consisting of 2-3 EDs but represented by one facility ID. Compared to the individually listed EDs, the 39 EDs included in a "group match" had a larger number of annual visits and beds, were more likely to be freestanding, and were less likely to be rural (all P<0.05). Two grouped EDs were excluded because the listed ED did not respond to the NEDI survey; the remaining 37 EDs were consolidated into 19 observations. Thus, the consolidated dataset contained 149 observations representing 171 EDs; this consolidated dataset yielded summary results that were similar to those of the 169 responding EDs.ConclusionExcluding grouped EDs would have resulted in a non-representative dataset. The original vs consolidated NEDI datasets yielded similar results and enabled linkage with large administrative datasets. This approach presents a novel opportunity to use characteristics of hospital-based specialties, units, and departments in studies of patient-level outcomes, to advance health services research.

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Project description:Introduction:Innovative data platforms (e.g. biobanks, repositories) continually emerge to facilitate data sharing. Extant and emerging data platforms must navigate myriad tensions for successful data sharing and re-use. Two Alberta data platforms navigated such processes and factors regarding administrative, research and nonprofit data: the Child & Youth Data Laboratory (CYDL) and Secondary Analysis to Generate Evidence (SAGE). Objectives:To clarify the social and policy factors that influenced CYDL and SAGE establishment and implementation, and the relationships, if any, between these factors and data type. Methods:This paper involves a qualitative secondary analysis of two developmental evaluations on CYDL and SAGE establishment. Six-years post-implementation, the CYDL evaluation entailed document review; website user analysis; interviews (n=30); online stakeholder survey (n=260); and an environmental scan. One-year post implementation, the SAGE evaluation included 15 interviews and document review. We used thematic analysis and comparisons with the literature to identify key factors. Results:Three (not mutually exclusive) categories of social and policy factors influenced the navigation towards CYDL and SAGE realization: trusting relationships; sustainability amidst readiness; and privacy within social context. For these platforms to be able to manage, link or share data, trust had to be fostered and maintained across multiple, dynamic and intersecting relationships between primary data producers, data subjects, secondary users and institutions. Platform sustainability required capacity building and innovation. Privacy and information sharing evolved culturally and correspondingly for these data platforms, which required constant flexibility and awareness. Conclusions:This analysis calls for more empirical research on the value of data re-use or the detriment in not re-using data. While the culture of information sharing is progressing towards greater openness and capacity for data sharing and re-use, successful data platforms must advocate, facilitate and mobilize analysis and innovation using data re-use while being cognizant of social and policy influences.

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Dataset Information

Protocol for the Data-Linkage Alcohol Cohort Study (DACS): investigating mortality, morbidity and offending among people with an alcohol-related problem using linked administrative data.

Introduction

Methods and analysis

Ethics and dissemination

Publications

Protocol for the Data-Linkage Alcohol Cohort Study (DACS): investigating mortality, morbidity and offending among people with an alcohol-related problem using linked administrative data.

Similar Datasets

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