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Project Title
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General Project Information
Project Type
Research
Clinical Audit
Quality Improvement
Service Evaluation
Approval Type
Full
Provisional
Planned Project Start Date
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Planned Project End Date
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Overall Status
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Project Summary
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<div class="ck-content" data-wrapper="true" dir="ltr" style="--ck-image-style-spacing: 1.5em; --ck-inline-image-style-spacing: calc(var(--ck-image-style-spacing) / 2); --ck-color-selector-caption-background: hsl(0, 0%, 97%); --ck-color-selector-caption-text: hsl(0, 0%, 20%); font-family: 'Segoe UI','Helvetica Neue',sans-serif; font-size: 9pt;"><div style="font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">While antibiotic medicines are crucial in the treatment of infections caused by bacteria, one of the major concerns is the risk that they become less effective because of resistance to this medicine. To improve the appropriate use of antibiotics, antibiotic stewardship programs have been launched with the aim to monitor antibiotics use and ensure that guidelines on the use of antibiotics are adhered to.</span></span></div><div style="font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><br><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">The aim of this study is to estimate trends in the number of new users of common antibiotics potentially associated with antimicrobial resistance as listed for close surveillance by the World Health Organisation. In addition, we will describe the characteristics of the individuals taking these antibiotics and summarise the antibiotic use in terms of duration, route, and dose.</span></span></div></div>
Detailed Project Description
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<div class="ck-content" data-wrapper="true" dir="ltr" style="--ck-image-style-spacing: 1.5em; --ck-inline-image-style-spacing: calc(var(--ck-image-style-spacing) / 2); --ck-color-selector-caption-background: hsl(0, 0%, 97%); --ck-color-selector-caption-text: hsl(0, 0%, 20%); font-family: 'Segoe UI','Helvetica Neue',sans-serif; font-size: 9pt;"><div style="--ck-color-selector-caption-background:hsl(0, 0%, 97%);--ck-color-selector-caption-text:hsl(0, 0%, 20%);--ck-image-style-spacing:1.5em;--ck-inline-image-style-spacing:calc(var(--ck-image-style-spacing) / 2);font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><div><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;"><strong>BACKGROUND:</strong> </span></span><br><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">Barts Health has been chosen as a pilot centre in the HDRUK Real World Evidence (RWE) Network. This project is the first within the network and aims to audit antibiotic use across the UK. This project will only use the anonymised OMOP mapped OHDSI dataset.</span></span><br><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">While antibiotics are crucial in the treatment of infections caused by bacteria, one of the major concerns is the risk of resistance through their inappropriate use. To improve the appropriate use of antibiotics, antimicrobial stewardship programs have been set up with the aim to monitor antibiotics use and ensure that guidelines are strictly adhered to.</span></span></div><div><br><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;"><strong>POPULATION: </strong>All people in the OMOP mapped OHDSI database from 2012 to the end of data capture. </span></span><br> </div><div><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;"><strong>DRUGS OF INTEREST:</strong> Antibiotics from the WHO watch list.[1]</span></span><br> </div><div><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;"><strong>VARIABLES:</strong> Exposure to antibiotics will be based on prescription and/or dispensation data. Demographic information such as age and sex, other medicine use, and diagnoses of comorbidities and possible indications will be identified to characterise the antibiotics users. </span></span><br> </div><div><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;"><strong>ANALYSES:</strong></span></span></div><p style="list-style-position: inside; margin: 0; text-align: justify;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">1. Characterisation of the database, including a description of the characteristics of patients at entry in the database, summaries of trends in records across different domains over time, and analysis of missing data in required fields.</span></span></p><p style="list-style-position: inside; margin: 0; text-align: justify;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">2. Estimation of incidence rates of use of the most commonly used antibiotics on the WHO watch list.</span></span></p><p style="list-style-position: inside; margin: 0; text-align: justify;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">3. Characterisation of users of antibiotics, including diagnoses of relevant comorbidities and indications for treatment.</span></span></p><p style="list-style-position: inside; margin: 0; text-align: justify;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">4. Characterisation of antibiotic drug episodes, including summary of duration of use and initial dose.</span></span></p><p style="list-style-position: inside; margin: 0; text-align: justify;"> </p><p style="list-style-position: inside; margin: 0; text-align: justify;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><strong style="font-family:Calibri,sans-serif;font-size:11pt;">Outcomes to be measured</strong></span></p><p style="list-style-position: inside; margin: 0; text-align: justify;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">Quarterly incidence rates of antibiotics on the WHO watch list, characteristics of databases, new users of antibiotics, and antibiotic episodes.</span></span></p><p style="list-style-position: inside; margin: 0; text-align: justify;"> </p><p style="list-style-position: inside; margin: 0; text-align: justify;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;"><strong> Objectives: </strong>This study aims to characterise trends in the incidence of the use of common antibiotics from the WHO ‘Watch’ list, describe the characteristics of users and summarise typical duration of use and initial dose.</span></span><br><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;"> The objectives of this study are:</span></span></p><div style="list-style-position:inside;margin-bottom:13px;margin-left:8px;"><ol style="list-style-type: lower-roman; margin-bottom: 13px; margin-inline-end: 0px; margin-inline-start: 0px; padding-inline-start: 40px;"><li style="list-style-position:inside;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">To provide a general description of data domains captured in the databases contributing to the HDRUK RWE pilot network, and the characteristics of individuals at entry.</span></span></li><li style="list-style-position:inside;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">To estimate quarterly incidence rates of use of commonly used antibiotics from the WHO Watch list, overall and stratified by age and sex. </span></span></li><li style="list-style-position:inside;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">To describe the characteristics of users of antibiotics, including their demographics and prior diagnoses of potential indications and relevant comorbidities. </span></span></li><li style="list-style-position:inside;margin-bottom:13px;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">To describe antibiotic use, including a summary of duration of use and initial dose.</span></span></li></ol><div style="list-style-position:inside;margin-bottom:13px;margin-left:8px;"><p style="list-style-position: inside; margin: 0; text-align: justify;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;"><strong>Feasibility counts: </strong></span></span></p><p style="list-style-position: inside; margin: 0; text-align: justify;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">The 10 most prescribed antibiotics on the WHO watch list in each data source will be included.</span></span></p></div><div style="list-style-position:inside;margin-bottom:13px;margin-left:8px;"><br><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;"><strong>Study population:</strong></span></span><br><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">For objectives 1 and 2 - will include all individuals present in the database during the study period (1<sup>st</sup> January 2012 to last date of data availability).</span></span></div><div style="list-style-position:inside;margin-bottom:13px;margin-left:8px;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">For objective 2 a sensitivity analysis will be conducted where individuals only contribute to the incidence analysis once they have at least 30 days of observation time in the database.</span></span></div><div style="list-style-position:inside;margin-bottom:13px;margin-left:8px;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">For objectives 3 and 4 - will be the users of antibiotics of interest. Cohorts of users will be created and characterised for each antibiotic separately.</span></span><br> </div></div></div></div>
Requested Data Summary
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<div class="ck-content" data-wrapper="true" dir="ltr" style="--ck-image-style-spacing: 1.5em; --ck-inline-image-style-spacing: calc(var(--ck-image-style-spacing) / 2); --ck-color-selector-caption-background: hsl(0, 0%, 97%); --ck-color-selector-caption-text: hsl(0, 0%, 20%); font-family: 'Segoe UI','Helvetica Neue',sans-serif; font-size: 9pt;"><div style="font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><span style="font-family:Arial;font-size:9pt;"><span style="line-height:normal;">From the BHDWH, all antibiotics users, in the database from 2012 to the end of data capture. We require a list of all prescribed antibiotics from the WHO watch list. </span></span><br><span style="font-family:Arial;font-size:9pt;"><span style="line-height:normal;">The data needs to include information on all those who have had exposure to antibiotics, based on prescription and/or dispensation data. </span></span><br><span style="font-family:Arial;"> </span></div><div style="font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><span style="font-family:Arial;font-size:9pt;"><span style="line-height:normal;"><u>Looking at all structured data: </u></span></span><br><span style="font-family:Arial;font-size:9pt;"><span style="line-height:normal;">Demographic information: Age, Gender, Ethnicity, other medicine use, and diagnoses of comorbidities and possible indications will be identified to characterise the antibiotics users.</span></span><span style="font-family:Arial;font-size:12.0pt;"><span style="line-height:normal;"> </span></span><br> </div><div style="font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><div> </div></div></div>
Technical Description
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<div data-wrapper="true"><div><span style="font-size:9pt"><span style="font-family:"Segoe UI","Helvetica Neue",sans-serif"><span style="line-height:115%"><span style="font-family:Calibri,sans-serif"><span style="line-height:115%"><span style="font-family:"Aptos",sans-serif">Utilising the SDE and internal system, all analyses will be performed in the SDE or a Barts Health research server as an interim solution, and only mentioned BH employees in this application have access to the data.</span></span></span></span></span><br><br><span style="font-family:"Segoe UI","Helvetica Neue",sans-serif"><span style="vertical-align:baseline"><span style="font-family:"Times New Roman",serif"><span style="font-family:"Aptos",sans-serif">The BDWH will have characterisation conducted across the data from 1<sup>st</sup> Jan 2012 until latest available date, that has already been mapped to the OMOP CDM format. This will include the description of the characteristics of patients at entry in the database, summaries of trends in records across different domains over time, and analysis of missing data in required fields.</span> </span></span></span><br><br><span style="font-family:"Segoe UI","Helvetica Neue",sans-serif"><span style="vertical-align:baseline"><span style="font-family:"Times New Roman",serif"><span style="font-family:"Aptos",sans-serif">Conducting characterisation of users of antibiotics, including diagnoses of relevant comorbidities and indications for treatment. </span> </span></span></span><br><br><span style="font-family:"Segoe UI","Helvetica Neue",sans-serif"><span style="vertical-align:baseline"><span style="font-family:"Times New Roman",serif"><span style="font-family:"Aptos",sans-serif">Characterisation of antibiotic drug episodes, including summary of duration of use and initial dose.</span> </span></span></span><br><br><span style="font-family:"Segoe UI","Helvetica Neue",sans-serif"><span style="vertical-align:baseline"><span style="font-family:"Times New Roman",serif"><span style="background-color:white"><span style="font-family:"Aptos",sans-serif"><span style="color:black">For objective 1: </span></span></span></span></span></span><br><span style="font-family:"Segoe UI","Helvetica Neue",sans-serif"><span style="vertical-align:baseline"><span style="font-family:"Times New Roman",serif"><span style="background-color:white"><span style="font-family:"Aptos",sans-serif"><span style="color:black">To provide a general description of the data captured, trends in recording different data elements will be described. For different domains (conditions, drug exposures, drug exposures, measurements, and so on), a summary of the number of records and the subjects for which they pertain to will be calculated overall and over calendar time (N, %). A summary of missingness in OMOP CDM fields will be performed, along with plausibility checks (e.g. record end date after record start date). The characteristics of individuals relative to their start of data capture will also be described, including age (median, interquartile range [IQR]), sex (N, %), and follow-up in the database (median, IQR). </span></span></span> </span></span></span><br><br><span style="font-family:"Segoe UI","Helvetica Neue",sans-serif"><span style="background-color:white"><span style="line-height:115%"><span style="font-family:"Aptos",sans-serif"><span style="color:black">Incidence rates will be estimated separately for each antibiotic of interest. Quarterly incidence rates for each antibiotic will be calculated as the number of new users - after 30 days of no use - per 100,000 person-years of the population at risk of getting exposed during the period. Any study participants with use of the medication of interest prior to the date at which they would have otherwise satisfied the criteria to enter the denominator population will be excluded. Those study participants who enter the denominator population will then contribute time at risk up their first prescription during the study period. Or if they do not have a drug exposure, they will contribute time at risk up until the end of follow-up (e.g. study end, end of observation period, or the last day of maximum age). We will calculate the 95% confidence interval of the </span></span></span></span><span style="line-height:115%"><span style="font-family:Calibri,sans-serif"><span style="background-color:white"><span style="font-family:"Aptos",sans-serif"><span style="color:black">period, or the last day of maximum age). We will calculate the 95% confidence interval of the estimated rates using the Poisson distribution. Incidence rates will be calculated for the denominator population as a whole and stratified by covariates of interest, such as age group, sex, route of administration and patient indications. Unadjusted and age and sex standardised incidence rates will be reported.</span></span></span> </span></span></span><br><span style="font-family:"Segoe UI","Helvetica Neue",sans-serif"><span style="line-height:115%"><span style="font-family:Calibri,sans-serif"><span style="background-color:white"><span style="font-family:"Aptos",sans-serif"><span style="color:black">A data-driven large-scale characterisation will be used to identify potential indications for treatment. In this all diagnoses and observations recorded for individuals will be summarised based on records from the condition occurrence and observation tables in the OMOP CDM. For this large-scale characterisation, two different time windows will be used; one including all records from 7 days prior up to, and including, the index date, and another including only records from the index date.</span></span></span></span></span></span></span></div><div><br><span style="font-size:9pt"><span style="font-family:"Segoe UI","Helvetica Neue",sans-serif"><span style="background-color:white"><span style="line-height:115%"><span style="font-family:"Aptos",sans-serif"><span style="color:black">Open-source code will be used where feasible, the analysis code will be shared via github.</span></span></span></span></span></span></div></div>
Public and Patient Involvement and Engagement Summary
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<div class="ck-content" data-wrapper="true" dir="ltr" style="--ck-image-style-spacing: 1.5em; --ck-inline-image-style-spacing: calc(var(--ck-image-style-spacing) / 2); --ck-color-selector-caption-background: hsl(0, 0%, 97%); --ck-color-selector-caption-text: hsl(0, 0%, 20%); font-family: 'Segoe UI','Helvetica Neue',sans-serif; font-size: 9pt;"><div style="font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><span style="font-family:Arial;font-size:9pt;"><span style="line-height:115%;">PPIE has been considered in the development of this clinical audit and the HDR UK recognise the role of patients and public in providing health data.</span></span><span style="background-color:white;color:black;font-family:Arial;font-size:9pt;"><span style="line-height:115%;"> Co-designed with patients and citizens.</span></span><span style="font-family:Arial;font-size:9pt;"><span style="line-height:115%;"> </span></span></div><div style="font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><br><span style="font-family:Arial;font-size:9pt;"><span style="line-height:115%;">Due to the audit’s focus on routine care and its retrospective nature, direct patient involvement in the data collection process will not be conducted, however dissemination of findings will be tailored to include formats accessible to patients and the public, such as lay summaries or patient group presentations. </span></span></div><div style="font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"> </div><div style="font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><span style="font-family:Arial;font-size:9pt;"><span style="line-height:115%;">There is no PPIE attribution in the code and related digital artefacts. For any publications it will be acknowledged that this work uses data provided by patients and collected by the NHS as part of their care and support. No PPIE attribution in datasets made available. </span></span></div><div style="font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"> </div><div style="font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><span style="font-family:Arial;font-size:9pt;"><span style="line-height:115%;">Note that the results and any proposed actions from the audit will be shared with relevant patients’ groups and that all efforts have been made to anonymize all patient data, and no individual patient identifiers will be used in reports or publications arising from this audit.</span></span></div></div>
Reporting
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<div class="ck-content" data-wrapper="true" dir="ltr" style="--ck-image-style-spacing: 1.5em; --ck-inline-image-style-spacing: calc(var(--ck-image-style-spacing) / 2); --ck-color-selector-caption-background: hsl(0, 0%, 97%); --ck-color-selector-caption-text: hsl(0, 0%, 20%); font-family: 'Segoe UI','Helvetica Neue',sans-serif; font-size: 9pt;"><div style="--ck-color-selector-caption-background:hsl(0, 0%, 97%);--ck-color-selector-caption-text:hsl(0, 0%, 20%);--ck-image-style-spacing:1.5em;--ck-inline-image-style-spacing:calc(var(--ck-image-style-spacing) / 2);font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;"><strong>Exposures, outcomes and covariates</strong></span></span><br><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">For this study, the exposure of interest is use (during study period) of antibiotics from the “Watch” category of The WHO 2023 AWaRe classification of antibiotics (see table 1). This Watch category represents antibiotics that have higher resistance potential and includes most of the highest priority agents among the Critically Important Antimicrobials for Human Medicine and/or antibiotics that are at relatively high risk of selection of bacterial resistance. From this list, the top 10 most frequently used antibiotics in the data source over the study period from this list will be included in the analyses. </span></span><br><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">Additional covariates are age, sex and calendar time. Comorbidities of interest will be defined based on any time prior to the index date. A data-driven large-scale characterisation will be used to identify potential indications for treatment, where all diagnostic records captured will be summarised. For this latter analysis two different time windows will be used, one including condition occurrence records from 7 days prior up to the index date, and another including only records from the index date.</span></span></div><div style="--ck-color-selector-caption-background:hsl(0, 0%, 97%);--ck-color-selector-caption-text:hsl(0, 0%, 20%);--ck-image-style-spacing:1.5em;--ck-inline-image-style-spacing:calc(var(--ck-image-style-spacing) / 2);font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><br><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;"><strong>Data/statistical analysis</strong></span></span><br><span style="font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:normal;">All analyses will apply a risk mitigation strategy to minimise the risk of patient identification: no patient counts or cells with <5 people will be reported. Instead, such figures will be reported as “<5” as proposed by national information governance policies.</span></span><br> </div><div style="--ck-color-selector-caption-background:hsl(0, 0%, 97%);--ck-color-selector-caption-text:hsl(0, 0%, 20%);--ck-image-style-spacing:1.5em;--ck-inline-image-style-spacing:calc(var(--ck-image-style-spacing) / 2);font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"> </div><div style="--ck-color-selector-caption-background:hsl(0, 0%, 97%);--ck-color-selector-caption-text:hsl(0, 0%, 20%);--ck-image-style-spacing:1.5em;--ck-inline-image-style-spacing:calc(var(--ck-image-style-spacing) / 2);font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><span style="background-color:white;color:black;font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:115%;">All analyses will apply a risk mitigation strategy to minimise the risk of patient identification: no patient counts or cells with <5 people will be reported. Instead, such figures will be reported as “<5” as proposed by national information governance policies.</span></span><span style="font-family:Calibri,sans-serif;font-size:9pt;"><span style="line-height:115%;"> </span></span></div><div style="--ck-color-selector-caption-background:hsl(0, 0%, 97%);--ck-color-selector-caption-text:hsl(0, 0%, 20%);--ck-image-style-spacing:1.5em;--ck-inline-image-style-spacing:calc(var(--ck-image-style-spacing) / 2);font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"> </div><div style="--ck-color-selector-caption-background:hsl(0, 0%, 97%);--ck-color-selector-caption-text:hsl(0, 0%, 20%);--ck-image-style-spacing:1.5em;--ck-inline-image-style-spacing:calc(var(--ck-image-style-spacing) / 2);font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><span style="background-color:white;color:black;font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:115%;">All findings will be submitted to scientific conferences and/or published as manuscripts in scientific journals. Study codes and results will be made publicly available in GitHub and by means of Shiny apps.</span></span><span style="font-family:Calibri,sans-serif;font-size:9pt;"><span style="line-height:115%;"> The codes will be open source and reproducible.</span></span></div><div style="--ck-color-selector-caption-background:hsl(0, 0%, 97%);--ck-color-selector-caption-text:hsl(0, 0%, 20%);--ck-image-style-spacing:1.5em;--ck-inline-image-style-spacing:calc(var(--ck-image-style-spacing) / 2);font-family:'Segoe UI','Helvetica Neue',sans-serif;font-size:9pt;"><br><span style="background-color:white;color:black;font-family:"Aptos",sans-serif;font-size:9pt;"><span style="line-height:115%;">Intend to publicise and disseminate methods and findings through publication in peer-reviewed journals.</span></span><span style="background-color:white;color:black;font-family:"Aptos",sans-serif;font-size:11pt;"><span style="line-height:115%;"> </span></span><br> </div></div>
Contact Points
Project Lead Name
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Project Lead Position
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Project Lead Email
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Lead Organisation Name
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Lead Organisation Address
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The Royal London Hospital, Whitechapel Road, E1 1BB
Secure Data Environment (SDE)
Will you be using the BH SDE
Will you be using the BH SDE
No
Will you be using the BH SDE
Yes
Details of the location and IT system (the SDE) where the data extract will be kept and processed.
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