Assessing data linkage quality in cohort studies

Improving Clinical Registry Data Quality via Linkage With Survival Data From State-Based Population Registries

PURPOSE

Real-world data (RWD) collected on patients treated as part of routine clinical care form the basis of cancer clinical registries. Capturing accurate death data can be challenging, with inaccurate survival data potentially compromising the integrity of registry-based research. Here, we explore the utility of data linkage (DL) to state-based registries to enhance the capture of survival outcomes.

METHODS

We identified consecutive adult patients with brain tumors treated in the state of Victoria from the Brain Tumour Registry Australia: Innovation and Translation (BRAIN) database, who had no recorded date of death and no follow-up within the last 6 months. Full name and date of birth were used to match patients in the BRAIN registry with those in the Victorian Births, Deaths and Marriages (BDM) registry. Overall survival (OS) outcomes were compared pre- and post-DL.

RESULTS

Of the 7,346 clinical registry patients, 5,462 (74%) had no date of death and no follow-up recorded within the last 6 months. Of the 5,462 patients, 1,588 (29%) were matched with a date of death in BDM. Factors associated with an increased number of matches were poor prognosis tumors, older age, and social disadvantage. OS was significantly overestimated pre-DL compared with post-DL for the entire cohort (pre- v post-DL: hazard ratio, 1.43; P < .001; median, 29.9 months v 16.7 months) and for most individual tumor types. This finding was present independent of the tumor prognosis.

CONCLUSION

As revealed by linkage with BDM, a high proportion of patients in a brain cancer clinical registry had missing death data, contributed to by informative censoring, inflating OS calculations. DL to pertinent registries on an ongoing basis should be considered to ensure accurate reporting of survival data and interpretation of RWD outcomes.

Interventions to Prevent and Respond to Violence Against Justice-Involved Young Women: A Scoping Review

Young women who have had contact with the criminal justice system (justice-involved young women) have an increased risk of being a victim of violence. However, no reviews have synthesized the evidence on interventions to prevent or respond to violence against justice-involved young women. We conducted a scoping review to identify interventions designed to prevent or respond to violence against justice-involved young women. We searched Medline, Criminal Justice Abstracts, Web of Science, and Google Scholar for peer-reviewed and gray literature published in English from January 1, 2000 until March 23, 2021. Consistent with the public health approach to violence, we included primary, secondary, and tertiary interventions. Excluding duplicates, our search returned 5,603 records, 14 of which met our inclusion criteria. We narratively synthesized the included studies, all of which were conducted in the United States. Most included studies examined a tertiary intervention (n = 10), and few examined a primary (n = 2) or secondary (n = 2) intervention. Across the Joanna Briggs Institute Critical Appraisal Tools, the percentage of items met ranged from 0% to 78%. There was some limited evidence that tertiary interventions that included cognitive behavioral therapy reduced the mental health impacts of violence victimization among justice-involved young women. There was little evidence on primary and secondary interventions. Effective and evidence-based interventions to prevent violence victimization and revictimization against justice-involved young women remains a critical gap in knowledge.

Police and hospital data linkage for traffic injury surveillance: A systematic review

This systematic review examines studies of traffic injury that involved linkage of police crash data and hospital data and were published from 1994 to 2023 worldwide in English. Inclusion and exclusion criteria were the basis for selecting papers from PubMed, Web of Science, and Scopus, and for identifying additional relevant papers using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and supplementary snowballing (n = 60). The selected papers were reviewed in terms of research objectives, data items and sample size included, temporal and spatial coverage, linkage methods and software tools, as well as linkage rates and most significant findings. Many studies found that the number of clinically significant road injury cases was much higher according to hospital data than crash data. Under-estimation of cases in crash data differs by road user type, pedestrian cases commonly being highly under-counted. A limited number of the papers were from low- and middle-income countries. The papers reviewed lack consistency in what was reported and how, which limited comparability.

Examining the quality and population representativeness of linked survey and administrative data: guidance and illustration using linked 1958 National Child Development Study and Hospital Episode Statistics data

Introduction

Recent years have seen an increase in linkages between survey and administrative data. It is important to evaluate the quality of such data linkages to discern the likely reliability of ensuing research. Evaluation of linkage quality and bias can be conducted using different approaches, but many of these are not possible when there is a separation of processes for linkage and analysis to help preserve privacy, as is typically the case in the UK (and elsewhere).

Objectives

We aimed to describe a suite of generalisable methods to evaluate linkage quality and population representativeness of linked survey and administrative data which remain tractable when users of the linked data are not party to the linkage process itself. We emphasise issues particular to longitudinal survey data throughout.

Methods

Our proposed approaches cover several areas: i) Linkage rates, ii) Selection into response, linkage consent and successful linkage, iii) Linkage quality, and iv) Linked data population representativeness. We illustrate these methods using a recent linkage between the 1958 National Child Development Study (NCDS; a cohort following an initial 17,415 people born in Great Britain in a single week of 1958) and Hospital Episode Statistics (HES) databases (containing important information regarding admissions, accident and emergency attendances and outpatient appointments at NHS hospitals in England).

Results

Our illustrative analyses suggest that the linkage quality of the NCDS-HES data is high and that the linked sample maintains an excellent level of population representativeness with respect to the single dimension we assessed.

Conclusions

Through this work we hope to encourage providers and users of linked data resources to undertake and publish thorough evaluations. We further hope that providing illustrative analyses using linked NCDS-HES data will improve the quality and transparency of research using this particular linked data resource.

Establishment of a birth-to-education cohort of 1 million Palestinian refugees using electronic medical records and electronic education records

Introduction

By linking datasets, electronic records can be used to build large birth-cohorts, enabling researchers to cost-effectively answer questions relevant to populations over the life-course. Currently, around 5.8 million Palestinian refugees live in five settings: Jordan, Lebanon, Syria, West Bank, and Gaza Strip. The United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA) provides them with free primary health and elementary-school services. It maintains electronic records to do so.We aimed to establish a birth cohort of Palestinian refugees born between 1st January 2010 and 31st December 2020 living in five settings by linking mother obstetric records with child health and education records and to describe some of the cohort characteristics. In future, we plan to assess effects of size-at-birth on growth, health and educational attainment, among other questions.

Methods

We extracted all available data from 140 health centres and 702 schools across five settings, i.e. all UNRWA service users. Creating the cohort involved examining IDs and other data, preparing data, de-duplicating records, and identifying live-births, linking the mothers' and children's data using different deterministic linking algorithms, and understanding reasons for non-linkage.

Results

We established a birth cohort of Palestinian refugees using electronic records of 972,743 live births. We found high levels of linkage to health records overall (83%), which improved over time (from 73% to 86%), and variations in linkage rates by setting: these averaged 93% in Gaza, 89% in Lebanon, 75% in Jordan, 73% in West Bank and 68% in Syria. Of the 423,580 children age-eligible to go to school, 47% went to UNRWA schools and comprised of 197,479 children with both health and education records, and 2,447 children with only education records. In addition to year and setting, other factors associated with non-linkage included mortality and having a non-refugee mother. Misclassification errors were minimal.

Conclusion

This linked open birth-cohort is unique for refugees and the Arab region and forms the basis for many future studies, including to elucidate pathways for improved health and education in this vulnerable, understudied population. Our characterization of the cohort leads us to recommend using different sub-sets of the cohort depending on the research question and analytic purposes.

Associations between self-reported healthcare disruption due to covid-19 and avoidable hospital admission: evidence from seven linked longitudinal studies for England

OBJECTIVES

To examine whether there is an association between people who experienced disrupted access to healthcare during the covid-19 pandemic and risk of an avoidable hospital admission.

DESIGN

Observational analysis using evidence from seven linked longitudinal cohort studies for England.

SETTING

Studies linked to electronic health records from NHS Digital from 1 March 2020 to 25 August 2022. Data were accessed using the UK Longitudinal Linkage Collaboration trusted research environment.

PARTICIPANTS

Individual level records for 29 276 people.

MAIN OUTCOME MEASURES

Avoidable hospital admissions defined as emergency hospital admissions for ambulatory care sensitive and emergency urgent care sensitive conditions.

RESULTS

9742 participants (weighted percentage 35%, adjusted for sample structure of longitudinal cohorts) self-reported some form of disrupted access to healthcare during the covid-19 pandemic. People with disrupted access were at increased risk of any (odds ratio 1.80, 95% confidence interval 1.39 to 2.34), acute (2.01, 1.39 to 2.92), and chronic (1.80, 1.31 to 2.48) ambulatory care sensitive hospital admissions. For people who experienced disrupted access to appointments (eg, visiting their doctor or an outpatient department) and procedures (eg, surgery, cancer treatment), positive associations were found with measures of avoidable hospital admissions.

CONCLUSIONS

Evidence from linked individual level data shows that people whose access to healthcare was disrupted were more likely to have a potentially preventable hospital admission. The findings highlight the need to increase healthcare investment to tackle the short and long term implications of the pandemic, and to protect treatments and procedures during future pandemics.

Comparing primary caregivers' reported injury data with routinely recorded injury data to assess predictors of childhood injury

BACKGROUND

Linking self-reported data collected from longitudinal studies with administrative health records is timely and cost-effective, provides the opportunity to augment information contained in each and can offset some of the limitations of both data sources. The aim of this study was to compare maternal-reported child injury data with administrative injury records and assess the level of agreement.

METHODS

A deterministic linkage was undertaken to link injury-related data from the Growing up in New Zealand (GUiNZ) study to routinely collected injury records from New Zealand's Accident Compensation Corporation (ACC) for preschool children. The analyses compared: (i) the characteristics of mothers with linked data vs. those without, (ii) injury incidences from maternal recall with those recorded in ACC injury claims, and (iii) the demographic characteristics of concordant and discordant injury reports, including the validity and reliability of injury records from both data sources.

RESULTS

Of all mothers who responded to the injury questions in the GUiNZ study (n = 5836), more than 95% (n = 5637) agreed to have their child's record linked to routine administrative health records. The overall discordance in injury reports showed an increasing trend as children grew older (9% at 9 M to 29% at 54 M). The mothers of children with discordance between maternal injury reports and ACC records were more likely to be younger, of Pacific ethnicity, with lower educational attainment, and live in areas of high deprivation (p < 0.001). The level of agreement between maternal injury recall and ACC injury record decreased (κ = 0.83 to κ = 0.42) as the cohort moved through their preschool years.

CONCLUSIONS

In general, the findings of this study identified that there was underreporting and discordance of the maternal injury recall, which varied by the demographic characteristics of mothers and their child's age. Therefore, linking the routinely gathered injury data with maternal self-report child injury data has the potential to augment longitudinal birth cohort study data to investigate risk or protective factors associated with childhood injury.

Identification of over- and undertreatment in the Dutch national cervical cancer screening program: A data linkage study at the hospital level

Research into the quality of cancer screening programs often lacks the perspective of clinicians, missing insights into the performance of individual hospitals. This retrospective cohort study aimed to identify guideline deviation (specifically, overtreatment and undertreatment) related to the cervical cancer screening program in Dutch hospitals by deterministically linking nationwide insurance data with pathology data for cervical intraepithelial neoplasia (CIN). We then constructed quality indicators using the Dutch CIN guideline and National Health Care Institute recommendations to assess compliance with CIN management, treatment outcomes, and follow-up, using an empirical Bayes shrinkage model to correct for case-mix variation and hospitals with few observations. Data were linked for 115,899 of 125,751 (92%) eligible women. Overtreatment was observed in the see-and-treat approach (immediate treatment) for women with low-grade referral cytology (4%; hospital range, 0%-25%), CIN ≤ 1 treatment specimens (26%; hospital range, 10%-55%), and follow-up cervix cytology ≥2 months before the guideline recommendation after treatment for CIN 2 (2%; hospital range, 0%-9%) or CIN 3 (5%; hospital range, 0%-19%). By contrast, undertreatment was observed for treatment within 3 months after a CIN 3 biopsy result (90%; hospital range 59%-100%) and follow-up ≥2 months beyond the guideline recommendation after treatments for CIN 2 (21%, hospital range 7%-48%) and CIN 3 (20%, hospital range 7%-90%). In conclusion, we found evidence of CIN overtreatment and undertreatment in all measured domains at the hospital level. Guideline adherence could be improved by implementing the developed indicators in an audit and feedback instrument for use by healthcare professionals in routine practice.

Data linkage of two national databases: Lessons learned from linking the Dutch Arthroplasty Register with the Dutch Foundation for Pharmaceutical Statistics

BACKGROUND

To provide guidance on data linkage in case of non-unique identifiers, we present a case study linking the Dutch Foundation for Pharmaceutical Statistics and Dutch Arthroplasty Register to investigate opioid prescriptions before/after arthroplasty.

METHODS

Deterministic data linkage was used. Records were linked on: sex, birthyear, postcode, surgery date, or thromboprophylaxis initiation as a proxy for the surgery date. Different postcodes were used, depending on availability: patient postcode (available from 2013 onwards), hospital postcode with codes for physicians/hospitals, and hospital postcode with catchment area. Linkage was assessed in several groups: linked arthroplasties, linked on patient postcode, linked on patient postcode, and low-molecular-weight heparin(LWMH). Linkage quality was assessed by checking prescriptions after death, antibiotics after revision for infection, and presence of multiple prostheses. Representativeness was assessed by comparing the patient-postcode-LMWH group with the remaining arthroplasties. External validation was performed by comparing our opioid prescription rates with those derived from datasets from Statistics Netherlands.

RESULTS

We linked 317,899 arthroplasties on patient postcode/hospital postcode(48%). Linkage on the hospital postcode appeared insufficient. Linkage uncertainty ranged from roughly 30% in all arthroplasties to 10-21% in the patient-postcode-LMWH-group. This subset resulted in 166.357(42%) linked arthroplasties after 2013 with somewhat younger age, fewer females, and more often osteoarthritis than other indications compared to the other arthroplasties. External validation showed similar increases in opioid prescription rates.

CONCLUSIONS

After identifier selection, checking data availability and internal validity, assessing representativeness, and externally validating our results we found sufficient linkage quality in the patient-postcode-LMWH-group, which consisted of around 42% of the arthroplasties performed after 2013.

Biases arising from linked administrative data for epidemiological research: a conceptual framework from registration to analyses

Linked administrative data offer a rich source of information that can be harnessed to describe patterns of disease, understand their causes and evaluate interventions. However, administrative data are primarily collected for operational reasons such as recording vital events for legal purposes, and planning, provision and monitoring of services. The processes involved in generating and linking administrative datasets may generate sources of bias that are often not adequately considered by researchers. We provide a framework describing these biases, drawing on our experiences of using the 100 Million Brazilian Cohort (100MCohort) which contains records of more than 131 million people whose families applied for social assistance between 2001 and 2018. Datasets for epidemiological research were derived by linking the 100MCohort to health-related databases such as the Mortality Information System and the Hospital Information System. Using the framework, we demonstrate how selection and misclassification biases may be introduced in three different stages: registering and recording of people's life events and use of services, linkage across administrative databases, and cleaning and coding of variables from derived datasets. Finally, we suggest eight recommendations which may reduce biases when analysing data from administrative sources.

Use of Population-Level Administrative Data in Developmental Science

Population-level administrative data-data on individuals' interactions with administrative systems (e.g., health, criminal justice, and education)-have substantially advanced our understanding of life-course development. In this review, we focus on five areas where research using these data has made significant contributions to developmental science: (a) understanding small or difficult-to-study populations, (b) evaluating intergenerational and family influences, (c) enabling estimation of causal effects through natural experiments and regional comparisons, (d) identifying individuals at risk for negative developmental outcomes, and (e) assessing neighborhood and environmental influences. Further advances will be made by linking prospective surveys to administrative data to expand the range of developmental questions that can be tested; supporting efforts to establish new linked administrative data resources, including in developing countries; and conducting cross-national comparisons to test findings' generalizability. New administrative data initiatives should involve consultation with population subgroups including vulnerable groups, efforts to obtain social license, and strong ethical oversight and governance arrangements.

Enhancing Administrative Claims Data: Feasibility, Validation and Application of Linking Medicare Claims Data and National Marrow Donor Program Search Data

PURPOSE

Administrative claims data provide real-world service utilization of acute myeloid leukemia (AML) treatment, but lacks insight into treatment delays or barriers. The National Marrow Donor Program (NMDP)/Be The Match Search (Search) data contains information on donor search, but lacks information on treatment received if allogeneic hematopoietic cell transplant (HCT) is not performed. We hypothesized that linking these two data sets would create a rich resource to define factors associated with receiving HCT that could not be evaluated with either data set alone.

METHODS

A subset of 2010-2016 Medicare administrative claims data was linked with Search data. A total of 5,351 patients with AML age 65-74 years (HCT = 607, no HCT = 4,744) were identified using Medicare. These patients were then linked to 93,800 records with a donor search between 2009 and 2016. Patient date of birth, sex, disease, ZIP code, transplant center/hospital, and diagnosis date were used for matching. Exploratory analysis was conducted to identify predictors associated with receiving HCT for patients with AML who received a search.

RESULTS

The data sets were successfully linked, showing high sensitivity and specificity. The final cohort included 5,085 patients with AML (HCT = 533, no HCT = 4,552). Of 97 patients who received HCT without a matched search, more than 85% received a related donor HCT. Of those not receiving HCT, 609 had a matched NMDP search and 3,943 did not have a matched NMDP search. Multivariate analysis showed time to search, age, diagnosis year, race/ethnicity, and neighborhood education status associated with receiving HCT.

CONCLUSION

Methods herein demonstrate the feasibility of linking Search and Medicare data. Similar methods may be applied to answer critical questions regarding barriers to HCT, thereby identifying areas to improve access to care.

Linkage of multiple electronic health record datasets using a 'spine linkage' approach compared with all 'pairwise linkages'

BACKGROUND

Methods for linking records between two datasets are well established. However, guidance is needed for linking more than two datasets. Using all 'pairwise linkages'-linking each dataset to every other dataset-is the most inclusive, but resource-intensive, approach. The 'spine' approach links each dataset to a designated 'spine dataset', reducing the number of linkages, but potentially reducing linkage quality.

METHODS

We compared the pairwise and spine linkage approaches using real-world data on patients undergoing emergency bowel cancer surgery between 31 October 2013 and 30 April 2018. We linked an administrative hospital dataset (Hospital Episode Statistics; HES) capturing patients admitted to hospitals in England, and two clinical datasets comprising patients diagnosed with bowel cancer and patients undergoing emergency bowel surgery.

RESULTS

The spine linkage approach, with HES as the spine dataset, created an analysis cohort of 15 826 patients, equating to 98.3% of the 16 100 patients identified using the pairwise linkage approach. There were no systematic differences in patient characteristics between these analysis cohorts. Associations of patient and tumour characteristics with mortality, complications and length of stay were not sensitive to the linkage approach. When eligibility criteria were applied before linkage, spine linkage included 14 509 patients (90.0% compared with pairwise linkage).

CONCLUSION

Spine linkage can be used as an efficient alternative to pairwise linkage if case ascertainment in the spine dataset and data quality of linkage variables are high. These aspects should be systematically evaluated in the nominated spine dataset before spine linkage is used to create the analysis cohort.

Data linkage for crash outcome assessment: Linking police-reported crashes, emergency response data, and trauma registry records

INTRODUCTION

Traffic crash reports lack detailed information about emergency medical service (EMS) responses, the injuries, and the associated treatments, limiting the ability of safety analysts to account for that information. Integrating data from other sources can enable a better understanding of characteristics of serious crashes and further explain variance in injury outcomes. In this research, an approach is proposed and implemented to link crash data to EMS run data, patient care reports, and trauma registry data.

METHOD

A heuristic framework is developed to match EMS run reports to crashes through time, location, and other indicators present in both datasets. Types of matches between EMS and crashes were classified. To investigate the fidelity of the match approach, a manual review of a sample of data was conducted. A comparative bias analysis was implemented on several key variables.

RESULTS

72.2% of EMS run reports matched to a crash record and 69.3% of trauma registry records matched with a crash record. Females, individuals between 11 and 20 years old, and individuals involved in single vehicle or head on crashes were more likely to be present in linked data sets. Using the linked data sets, relationships between EMS response time and reported injury in the crash report, and between police-reported injury and injury severity score were examined.

CONCLUSION

Linking data from other sources can greatly enhance the information available to address road safety issues, data quality issues, and more. Linking data has the potential to result in biases that must be investigated as they relate to the use-case for the data.

PRACTICAL IMPLICATIONS

This research resulted in a transferable heuristic approach that can be used to link data sets that are commonly collected by agencies across the world. It also provides guidance on how to check the linked data for biases and errors.

Creating a Real-World Linked Research Platform for Analyzing the Urgent and Emergency Care System

Background

This article describes the development of a system-based data platform for research developed to provide a detailed picture of the characteristics of the Urgent and Emergency Care system in 1 region of the United Kingdom.

Data Set Development

CUREd is an integrated research data platform that describes the urgent and emergency care system in 1 region of the United Kingdom on almost 30 million patient contacts within the system. We describe regulatory approvals required, data acquisition, cleaning, and linkage.

Data Set Analyses

The data platform covers 2011 to 2017 for 14 acute National Health Service (NHS) Hospital Trusts, 1 ambulance service, the national telephone advice service (NHS 111), and 19 emergency departments. We describe 3 analyses undertaken: 1) Analyzing triage patterns from the NHS 111 telephone helpline using routine data linked to other urgent care services, we found that the current triage algorithms have high rates of misclassifying calls. 2) Applying an algorithm to consistently identify avoidable attendances for pediatric patients, we identified 21% of pediatric attendances to the emergency department as avoidable. 3) Using complex systems analysis to examine patterns of frequent attendance in urgent care, we found that frequent attendance is stable over time but varies by individual patient. This implies that frequent attendance is more likely to be a function of the system overall.

Discussion

We describe the processes necessary to produce research-ready data that link care across the components of the urgent and emergency care system. Making the use of routine data commonplace will require partnership between the collectors, owners, and guardians of the data and researchers and technical teams.

Highlights

Record linkage of population-based cohort data from minors with national register data: a scoping review and comparative legal analysis of four European countries

Background: The GDPR was implemented to build an overarching framework for personal data protection across the EU/EEA. Linkage of data directly collected from cohort participants, potentially serving as a prominent tool for health research, must respect data protection rules and privacy rights. Our objective was to investigate law possibilities of linking cohort data of minors with routinely collected education and health data comparing EU/EEA member states. Methods: A legal comparative analysis and scoping review was conducted of openly accessible published laws and regulations in EUR-Lex and national law databases on GDPR's implementation in Portugal, Finland, Norway, and the Netherlands and its connected national regulations purposing record linkage for health research that have been implemented up until April 30, 2021. Results: The GDPR does not ensure total uniformity in data protection legislation across member states offering flexibility for national legislation. Exceptions to process personal data, e.g., public interest and scientific research, must be laid down in EU/EEA or national law. Differences in national interpretation caused obstacles in cross-national research and record linkage: Portugal requires written consent and ethical approval; Finland allows linkage mostly without consent through the national Social and Health Data Permit Authority; Norway when based on regional ethics committee's approval and adequate information technology safeguarding confidentiality; the Netherlands mainly bases linkage on the opt-out system and Data Protection Impact Assessment. Conclusions: Though the GDPR is the most important legal framework, national legislation execution matters most when linking cohort data with routinely collected health and education data. As national interpretation varies, legal intervention balancing individual right to informational self-determination and public good is gravely needed for health research. More harmonization across EU/EEA could be helpful but should not be detrimental in those member states which already opened a leeway for registries and research for the public good without explicit consent.

Linking education and hospital data in England: linkage process and quality

INTRODUCTION

Linkage of administrative data for universal state education and National Health Service (NHS) hospital care would enable research into the inter-relationships between education and health for all children in England.

OBJECTIVES

We aim to describe the linkage process and evaluate the quality of linkage of four one-year birth cohorts within the National Pupil Database (NPD) and Hospital Episode Statistics (HES).

METHODS

We used multi-step deterministic linkage algorithms to link longitudinal records from state schools to the chronology of records in the NHS Personal Demographics Service (PDS; linkage stage 1), and HES (linkage stage 2). We calculated linkage rates and compared pupil characteristics in linked and unlinked samples for each stage of linkage and each cohort (1990/91, 1996/97, 1999/00, and 2004/05).

RESULTS

Of the 2,287,671 pupil records, 2,174,601 (95%) linked to HES. Linkage rates improved over time (92% in 1990/91 to 99% in 2004/05). Ethnic minority pupils and those living in more deprived areas were less likely to be matched to hospital records, but differences in pupil characteristics between linked and unlinked samples were moderate to small.

CONCLUSION

We linked nearly all pupils to at least one hospital record. The high coverage of the linkage represents a unique opportunity for wide-scale analyses across the domains of health and education. However, missed links disproportionately affected ethnic minorities or those living in the poorest neighbourhoods: selection bias could be mitigated by increasing the quality and completeness of identifiers recorded in administrative data or the application of statistical methods that account for missed links.

HIGHLIGHTS

Longitudinal administrative records for all children attending state school and acute hospital services in England have been used for research for more than two decades, but lack of a shared unique identifier has limited scope for linkage between these databases.We applied multi-step deterministic linkage algorithms to 4 one-year cohorts of children born 1 September-31 August in 1990/91, 1996/97, 1999/00 and 2004/05. In stage 1, full names, date of birth, and postcode histories from education data in the National Pupil Database were linked to the NHS Personal Demographic Service. In stage 2, NHS number, postcode, date of birth and sex were linked to hospital records in Hospital Episode Statistics.Between 92% and 99% of school pupils linked to at least one hospital record. Ethnic minority pupils and pupils who were living in the most deprived areas were least likely to link. Ethnic minority pupils were less likely than white children to link at the first step in both algorithms.Bias due to linkage errors could lead to an underestimate of the health needs in disadvantaged groups. Improved data quality, more sensitive linkage algorithms, and/or statistical methods that account for missed links in analyses, should be considered to reduce linkage bias.

Linking cohort-based data with electronic health records: a proof-of-concept methodological study in Hong Kong

OBJECTIVES

Data linkage of cohort-based data and electronic health records (EHRs) has been practised in many countries, but in Hong Kong there is still a lack of such research. To expand the use of multisource data, we aimed to identify a feasible way of linking two cohorts with EHRs in Hong Kong.

METHODS

Participants in the 'Children of 1997' birth cohort and the Chinese Early Development Instrument (CEDI) cohort were separated into several batches. The Hong Kong Identity Card Numbers (HKIDs) of each batch were then uploaded to the Hong Kong Clinical Data Analysis and Reporting System (CDARS) to retrieve EHRs. Within the same batch, each participant has a unique combination of date of birth and sex which can then be used for exact matching, as no HKID will be returned from CDARS. Raw data collected for the two cohorts were checked for the mismatched cases. After the matching, we conducted a simple descriptive analysis of attention deficit hyperactivity disorder (ADHD) information collected in the CEDI cohort via the Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour Scale (SWAN) and EHRs.

RESULTS

In total, 3473 and 910 HKIDs in the birth cohort and CEDI cohort were separated into 44 and 5 batches, respectively, and then submitted to the CDARS, with 100% and 97% being valid HKIDs respectively. The match rates were confirmed to be 100% and 99.75% after checking the cohort data. From our illustration using the ADHD information in the CEDI cohort, 36 (4.47%) individuals had ADHD-Combined score over the clinical cut-off in the SWAN survey, and 68 (8.31%) individuals had ADHD records in EHRs.

CONCLUSIONS

Using date of birth and sex as identifiable variables, we were able to link the cohort data and EHRs with high match rates. This method will assist in the generation of databases for future multidisciplinary research using both cohort data and EHRs.