Katie Harron

The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement

Routinely collected health data, obtained for administrative and clinical purposes without specific a priori research goals, are increasingly used for research. The rapid evolution and availability of these data have revealed issues not addressed by existing reporting guidelines, such as Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). The REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement was created to fill these gaps. RECORD was created as an extension to the STROBE statement to address reporting items specific to observational studies using routinely collected health data. RECORD consists of a checklist of 13 items related to the title, abstract, introduction, methods, results, and discussion section of articles, and other information required for inclusion in such research reports. This document contains the checklist and explanatory and elaboration information to enhance the use of the checklist. Examples of good reporting for each RECORD checklist item are also included herein. This document, as well as the accompanying website and message board (http://www.record-statement.org), will enhance the implementation and understanding of RECORD. Through implementation of RECORD, authors, journals editors, and peer reviewers can encourage transparency of research reporting.

Evaluating bias due to data linkage error in electronic healthcare records

BackgroundLinkage of electronic healthcare records is becoming increasingly important for research purposes. However, linkage error due to mis-recorded or missing identifiers can lead to biased results. We evaluated the impact of linkage error on estimated infection rates using two different methods for classifying links: highest-weight (HW) classification using probabilistic match weights and prior-informed imputation (PII) using match probabilities.MethodsA gold-standard dataset was created through deterministic linkage of unique identifiers in admission data from two hospitals and infection data recorded at the hospital laboratories (original data). Unique identifiers were then removed and data were re-linked by date of birth, sex and Soundex using two classification methods: i) HW classification - accepting the candidate record with the highest weight exceeding a threshold and ii) PII–imputing values from a match probability distribution. To evaluate methods for linking data with different error rates, non-random error and different match rates, we generated simulation data. Each set of simulated files was linked using both classification methods. Infection rates in the linked data were compared with those in the gold-standard data.ResultsIn the original gold-standard data, 1496/20924 admissions linked to an infection. In the linked original data, PII provided least biased results: 1481 and 1457 infections (upper/lower thresholds) compared with 1316 and 1287 (HW upper/lower thresholds). In the simulated data, substantial bias (up to 112%) was introduced when linkage error varied by hospital. Bias was also greater when the match rate was low or the identifier error rate was high and in these cases, PII performed better than HW classification at reducing bias due to false-matches.ConclusionsThis study highlights the importance of evaluating the potential impact of linkage error on results. PII can help incorporate linkage uncertainty into analysis and reduce bias due to linkage error, without requiring identifiers.

Impregnated central venous catheters for prevention of bloodstream infection in children (the CATCH trial): a randomised controlled trial

BACKGROUND Impregnated central venous catheters are recommended for adults to reduce bloodstream infections but not for children because there is not enough evidence to prove they are effective. We aimed to assess the effectiveness of any type of impregnation (antibiotic or heparin) compared with standard central venous catheters to prevent bloodstream infections in children needing intensive care. METHODS We did a randomised controlled trial of children admitted to 14 English paediatric intensive care units. Children younger than 16 years were eligible if they were admitted or being prepared for admission to a participating paediatric intensive care unit and were expected to need a central venous catheter for 3 or more days. Children were randomly assigned (1:1:1) to receive a central venous catheter impregnated with antibiotics, a central venous catheter impregnated with heparin, or a standard central venous catheter with computer generated randomisation in blocks of three and six, stratified by method of consent, site, and envelope storage location within the site. The clinician responsible for inserting the central venous catheter was not masked to allocation, but allocation was concealed from patients, their parents, and the paediatric intensive care unit personnel responsible for their care. The primary outcome was time to first bloodstream infection between 48 h after randomisation and 48 h after central venous catheter removal with impregnated (antibiotic or heparin) versus standard central venous catheters, assessed in the intention-to-treat population. Safety analyses compared central venous catheter-related adverse events in the subset of children for whom central venous catheter insertion was attempted (per-protocol population). This trial is registered with ISRCTN number, ISRCTN34884569. FINDINGS Between Nov 25, 2010, and Nov 30, 2012, 1485 children were recruited to this study. We randomly assigned 502 children to receive standard central venous catheters, 486 to receive antibiotic-impregnated catheters, and 497 to receive heparin-impregnated catheters. Bloodstream infection occurred in 18 (4%) of those in the standard catheters group, 7 (1%) in the antibiotic-impregnated group, and 17 (3%) assigned to heparin-impregnated catheters. Primary analyses showed no effect of impregnated (antibiotic or heparin) catheters compared with standard central venous catheters (hazard ratio [HR] for time to first bloodstream infection 0.71, 95% CI 0.37-1.34). Secondary analyses showed that antibiotic central venous catheters were better than standard central venous catheters (HR 0.43, 0.20-0.96) and heparin central venous catheters (HR 0.42, 0.19-0.93), but heparin did not differ from standard central venous catheters (HR 1.04, 0.53-2.03). Clinically important and statistically significant absolute risk differences were identified only for antibiotic-impregnated catheters versus standard catheters (-2.15%, 95% CI -4.09 to -0.20; number needed to treat [NNT] 47, 95% CI 25-500) and antibiotic-impregnated catheters versus heparin-impregnated catheters (-1.98%, -3.90 to -0.06, NNT 51, 26-1667). Nine children (2%) in the standard central venous catheter group, 14 (3%) in the antibiotic-impregnated group, and 8 (2%) in the heparin-impregnated group had catheter-related adverse events. 45 (8%) in the standard group, 35 (8%) antibiotic-impregnated group, and 29 (6%) in the heparin-impregnated group died during the study. INTERPRETATION Antibiotic-impregnated central venous catheters significantly reduced the risk of bloodstream infections compared with standard and heparin central venous catheters. Widespread use of antibiotic-impregnated central venous catheters could help prevent bloodstream infections in paediatric intensive care units. FUNDING National Institute for Health Research, UK.

Linkage, evaluation and analysis of national electronic healthcare data: application to providing enhanced blood-stream infection surveillance in paediatric intensive care.

Background Linkage of risk-factor data for blood-stream infection (BSI) in paediatric intensive care (PICU) with bacteraemia surveillance data to monitor risk-adjusted infection rates in PICU is complicated by a lack of unique identifiers and under-ascertainment in the national surveillance system. We linked, evaluated and performed preliminary analyses on these data to provide a practical guide on the steps required to handle linkage of such complex data sources. Methods Data on PICU admissions in England and Wales for 2003-2010 were extracted from the Paediatric Intensive Care Audit Network. Records of all positive isolates from blood cultures taken for children <16 years and captured by the national voluntary laboratory surveillance system for 2003-2010 were extracted from the Public Health England database, LabBase2. “Gold-standard” datasets with unique identifiers were obtained directly from three laboratories, containing microbiology reports that were eligible for submission to LabBase2 (defined as “clinically significant” by laboratory microbiologists). Reports in the gold-standard datasets were compared to those in LabBase2 to estimate ascertainment in LabBase2. Linkage evaluated by comparing results from two classification methods (highest-weight classification of match weights and prior-informed imputation using match probabilities) with linked records in the gold-standard data. BSI rate was estimated as the proportion of admissions associated with at least one BSI. Results Reporting gaps were identified in 548/2596 lab-months of LabBase2. Ascertainment of clinically significant BSI in the remaining months was approximately 80-95%. Prior-informed imputation provided the least biased estimate of BSI rate (5.8% of admissions). Adjusting for ascertainment, the estimated BSI rate was 6.1-7.3%. Conclusion Linkage of PICU admission data with national BSI surveillance provides the opportunity for enhanced surveillance but analyses based on these data need to take account of biases due to ascertainment and linkage error. This study provides a generalisable guide for linkage, evaluation and analysis of complex electronic healthcare data.

Rising rates of all types of diabetes in south Asian and non-south Asian children and young people aged 0-29 years in West Yorkshire, U.K., 1991-2006.

OBJECTIVE To investigate incidence trends of all diabetes types in all children and young people and in the south Asian subpopulation. RESEARCH DESIGN AND METHODS Annual incidence per 100,000 and time trends (1991–2006) were analyzed for 2,889 individuals aged 0–29 years diagnosed with diabetes while resident in West Yorkshire, U.K. RESULTS Diagnoses comprised type 1 (83%), type 2 (12%), maturity-onset diabetes of the young (0.7%), “J”-type/other (0.1%), and uncertain/unclassified (4%). There was a lower incidence of type 1 and a threefold excess of type 2 in south Asians compared with non-south Asians. Type 1 incidence leveled out and type 2 increased after the first south Asian case of type 2 was diagnosed in 1999. Type 2 and unclassified diabetes incidence rose in all population subgroups. CONCLUSIONS The burden of diabetes increased over time for both ethnic groups, with a significant excess of type 2 diabetes in south Asians. The rising incidence of type 1 diabetes in south Asians attenuated as type 2 diabetes increased after 1999.

Opening the black box of record linkage

The UK governments plan for a secure data service— Strengthening the international competitiveness of UK life sciences research —will transform the availability of linked electronic health records to support service provision, planning and research. In April 2012, the new Clinical Practice Research Datalink was established to provide linked national e-health records, facilitating large-scale, population-based research and service evaluation. Such comprehensive data-linkages have been successfully established in other areas, notably in Western Australia, where a code of best practice …

Consistency between guidelines and reported practice for reducing the risk of catheter-related infection in British paediatric intensive care units

PurposeOptimal strategies for reducing catheter-related blood stream infection (CR-BSI) differ for adults and children. National guidelines do not make child-specific recommendations. We determined whether evidence explained the inconsistencies between guidelines and reported practice in paediatric intensive care units (PICUs).MethodsWe conducted a survey of eight interventions for reducing CR-BSI in all 25 British PICUs in 2009. Interventions were categorised as requiring child-specific evidence, generalisable to adults and children, or organisational recommendations.ResultsTwenty-four of the 25 PICUs responded. For child-specific interventions, practice diverged from guidelines for “Insert into subclavian/jugular veins” (18 PICUs frequently used femoral veins, supported by observational evidence for increased safety in children). Practice reflected guidelines for “Use standard but consider antimicrobial-impregnated central venous catheters (CVCs) for high-risk patients” (14 used standard only, 3 used standard and antimicrobial-impregnated despite no randomised controlled trial (RCT) evidence for antimicrobial-impregnated CVCs in children, 7 used heparin-bonded for some or all children); “Use 2% chlorhexidine for skin preparation” (20 PICUs); “Avoid routine CVC replacement” (20 PICUs). For generalisable interventions, practice was consistent with guidelines for “Administration set replacement” (21 PICUs) but deviated for “Maintenance of CVC asepsis” (11 PICUs used alcohol due to inconclusive evidence for chlorhexidine). Practice diverged from guidelines for organisational interventions: “Train healthcare workers in CVC care” (9 PICUs); “Monitor blood stream infection (BSI) rates” (8 PICUs).ConclusionsGuidelines should explicitly address paediatric practice and report the quality of evidence and strength of recommendations. Organisations should ensure doctors are trained in CVC insertion and invest in BSI monitoring, especially in PICUs. The type of CVC and insertion site are important gaps in evidence for children.

Methodological Developments in Data Linkage

The increasing availability of large administrative databases has led to a dramatic rise in the use of data linkage, yet the standard texts on linkage are still those which describe the seminal work from the 1950-60s, with some updates. Linkage and analysis of data across sources remains problematic due to lack of discriminatory and accurate identifiers, missing data and regulatory issues. Recent developments in data linkage methodology have concentrated on bias and analysis of linked data, novel approaches to organising relationships between databases and privacy-preserving linkage.

Linking Data for Mothers and Babies in De-Identified Electronic Health Data.

Objective Linkage of longitudinal administrative data for mothers and babies supports research and service evaluation in several populations around the world. We established a linked mother-baby cohort using pseudonymised, population-level data for England. Design and Setting Retrospective linkage study using electronic hospital records of mothers and babies admitted to NHS hospitals in England, captured in Hospital Episode Statistics between April 2001 and March 2013. Results Of 672,955 baby records in 2012/13, 280,470 (42%) linked deterministically to a maternal record using hospital, GP practice, maternal age, birthweight, gestation, birth order and sex. A further 380,164 (56%) records linked using probabilistic methods incorporating additional variables that could differ between mother/baby records (admission dates, ethnicity, 3/4-character postcode district) or that include missing values (delivery variables). The false-match rate was estimated at 0.15% using synthetic data. Data quality improved over time: for 2001/02, 91% of baby records were linked (holding the estimated false-match rate at 0.15%). The linked cohort was representative of national distributions of gender, gestation, birth weight and maternal age, and captured approximately 97% of births in England. Conclusion Probabilistic linkage of maternal and baby healthcare characteristics offers an efficient way to enrich maternity data, improve data quality, and create longitudinal cohorts for research and service evaluation. This approach could be extended to linkage of other datasets that have non-disclosive characteristics in common.

Data linkage errors in hospital administrative data when applying a pseudonymisation algorithm to paediatric intensive care records.

Objectives Our aim was to estimate the rate of data linkage error in Hospital Episode Statistics (HES) by testing the HESID pseudoanonymisation algorithm against a reference standard, in a national registry of paediatric intensive care records. Setting The Paediatric Intensive Care Audit Network (PICANet) database, covering 33 paediatric intensive care units in England, Scotland and Wales. Participants Data from infants and young people aged 0–19 years admitted between 1 January 2004 and 21 February 2014. Primary and secondary outcome measures PICANet admission records were classified as matches (records belonging to the same patient who had been readmitted) or non-matches (records belonging to different patients) after applying the HESID algorithm to PICANet records. False-match and missed-match rates were calculated by comparing results of the HESID algorithm with the reference standard PICANet ID. The effect of linkage errors on readmission rate was evaluated. Results Of 166 406 admissions, 88 596 were true matches (where the same patient had been readmitted). The HESID pseudonymisation algorithm produced few false matches (n=176/77 810; 0.2%) but a larger proportion of missed matches (n=3609/88 596; 4.1%). The true readmission rate was underestimated by 3.8% due to linkage errors. Patients who were younger, male, from Asian/Black/Other ethnic groups (vs White) were more likely to experience a false match. Missed matches were more common for younger patients, for Asian/Black/Other ethnic groups (vs White) and for patients whose records had missing data. Conclusions The deterministic algorithm used to link all episodes of hospital care for the same patient in England has a high missed match rate which underestimates the true readmission rate and will produce biased analyses. To reduce linkage error, pseudoanonymisation algorithms need to be validated against good quality reference standards. Pseudonymisation of data ‘at source’ does not itself address errors in patient identifiers and the impact these errors have on data linkage.