NHS Digital Data Release Register - reformatted
University Of Warwick
Project 1 — DARS-NIC-302792-X4T6B
Opt outs honoured: N
Sensitive: Non Sensitive, and Sensitive
When: 2017/09 — 2017/11.
Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC
- Hospital Episode Statistics Critical Care
- Hospital Episode Statistics Admitted Patient Care
- Hospital Episode Statistics Accident and Emergency
- Hospital Episode Statistics Outpatients
The PreFIT trial findings will be considered by NICE when deciding whether to continue to recommend funding selected falls prevention activities; specifically whether to recommend exercise to prevent falls and fractures or whether resources are best directed at multifactorial strategies e.g. in those who are at greatest risk of falling. Trial findings will be incorporated into Cochrane systematic review updates. The majority of trials published to date have sample sizes of less than 200 participants. This trial has 9821 participants and will contribute a great deal of certainty with regards to findings. Trial researchers were invited by Public Health England to present at a falls prevention event in 2016, to report on trial methods and to raise awareness of the near completion of the trial. PHE are awaiting the trial findings. We are also contacted regularly by consultant clinicians and falls prevention experts asking for updates on when the trial findings will be released. The findings from PreFIT will undoubtedly inform clinical and public health policy decision making. This is the largest ever RCT of community dwelling older adults and will provide valuable information on whether NHS funding should be reallocated to other areas of care. Falls are common in people aged over 70 years of age. Given the ageing population, the study expect the impact from this trial to be significant as will potentially affect a large number of older adults.
The following outputs will be produced: 1. An HTA monograph reporting the overall trial results to the funder (NIHR HTA). The monograph is due for submission in early 2018. 2. In parallel, the study intend to submit a number of peer-reviewed publications to leading medical journals. They expect the results of the trial to be of great interest to the academic community and anticipate publishing the ‘main’ findings in a leading journal eg. The Lancet, The New England Journal of Medicine (NEJM) or equivalent. There will be a number of related papers reporting subsidiary but clinically important research questions. 3. The study will publish the trial intervention manuals as open-access on the Warwick Research Archive Portal. The study have published the trial protocol paper (Bruce et al, BMJ Open 2016) and intervention papers are currently in press (BMC Geriatrics and Physiotherapy). 4. Trial findings will be summarised on the Warwick Clinical Trials Unit main website with further information within the PreFIT trial website: http://www2.warwick.ac.uk/fac/med/research/hscience/ctu/ http://www2.warwick.ac.uk/fac/med/research/hscience/ctu/trials/critical/prefit/patients/ 5. Findings will be disseminated to AgeUK charity and to Public Health England. 6. Findings will be submitted to academic conferences, including geriatric care, physiotherapy and falls prevention conferences (e.g. British Society of Geriatrics; World Confederation for Physical Therapy). 7. Findings will be disseminated on social media via the Warwick Clinical Trials Unit Twitter page: @WarwickCTU. This website currently has 134 followers (March 2017). Findings will also be disseminated by the Warwick Medical School Twitter account: @warwickmed / N=3136 followers.
Warwick Clinical Trials Unit will securely transfer a file of identifiers [NHS Number, Unique Trial/Study ID number, Date of Birth, and postcode] to NHS Digital. These identifiers will be provided over the SEFT system. The Unique Trial/Study ID is a 6 digit alphanumeric code and it is not possible to re-identify cohort members using this ID. NHS Digital will use the customer IDs (WCTU Study ID) to link HES APC, CC, A&E and OP datasets. NHS Digital will send the customer (WCTU) reports of record level HES Data to WCTU. Warwick Clinical Trials Unit will store these data on a server at the University of Warwick which can only be accessed by a restricted number of personnel. Professor Bojke, from University of Leeds Academic Unit of Health Economics will write the statistical code for economic analysis to be conducted at the Warwick CTU. No HES data will be transferred or shared with University of Leeds. Data will only be accessed by individuals within the WCTU who have authorisation from the Chief Investigator to access the data for the purposes described, all of whom are substantive employees of the University of Warwick. The Chief Investigator who is based at the University of Oxford will only have access to aggregated data will small numbers suppressed in line with the HES Analysis Guide. No further linkage to any other datasets will be undertaken. a) The data will be linked to the existing record level data. This is required to analyse fracture rates. b) There will be no requirement or attempt to reidentify individuals from the data. c) The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide. The study request a HES data download for three years: 2013/4; 2014/5 and 2015/6. This covers the period for one year before trial recruitment to the end of follow-up for main trial participants only (n=8019). Participants from the pilot study are not included in this request. The HES data already held by the trial will be securely destroyed once the new HES data has been received from NHS Digital. No geographical spread, this is for our trial cohort only, selected from five English regions. The trial have carefully selected the relevant variables for the purposes of analysis. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)
University of Warwick Clinical Trials Unit is the lead organisation where the PreFIT trial main team and trial office is based. The Chief Investigator is now based at the University of Oxford but holds an honorary position at University of Warwick. Other organisations involved in the trial include the University of Leeds Academic Unit of Health Economics. HES data will not be shared with the University of Leeds. Professor Bojke, Professor of Health Economics, holds an honorary contract with the University of Warwick and will provide the relevant statistical syntax for the economic analysis to be conducted by trial statisticians at the Warwick CTU. In summary, the Warwick CTU were funded by the National Institute for Health Research Health Technology Assessment (NIHR) (HTA) to undertake a large complex intervention trial to investigate alternative strategies to prevent falls and fractures in older adults. Historically, the lead applicant was involved with earlier research that identified gaps in evidence; this in turn led to the HTA grant award to investigate alternative interventions to prevent falls: (1) advice alone, versus (2) exercise; versus (3) multifactorial falls prevention (MFFP) intervention in older adults. The aim of the trial is to identify which falls prevention intervention is the most clinical effective and cost-effective, on outcomes of falls and fractures, in adults aged over 70 years. The Pre-FIT trial is the largest trial ever conducted on community based fall prevention on outcomes of fractures. Further details on the background and rationale are provided below. Falls and fractures are common and serious health problems for older people. The UK government recognised this problem and in 2004, in view of the importance of the problem, elected to develop a guideline through the National Institute of Clinical Excellence (NICE). The guideline was based on the available evidence at that time (up to 2003), which included a high quality review of all of the evidence conducted by the Cochrane Collaboration. Although the amount of evidence available was limited, the Cochrane systematic review concluded that MFFP services are likely to be effective. NICE took this recommendation forward, and undertook some preliminary economic evaluation. Following an evaluation for NICE, it was concluded that there was insufficient data available to determine cost-effectiveness of different options to treatment, including MFFP. NICE also commissioned an update the evidence and determine whether or not it would now be possible to generate economic models. The University of Warwick undertook a rigorous review of the evidence, published in the British Medical Journal (Gates et al). The results of this were surprising, with the accumulation of evidence, it does suggest that MFFP interventions are considerably less effective than originally anticipated, and there is little evidence that fractures can be prevented with these treatments. Concurrently, researchers from New Zealand published a review which suggested that exercise may be just as effective as MFFP, but would be considerably cheaper. This information raised uncertainty, and the need to conduct a large trial to answer several questions which would inform NHS services. Burden of falls The NHS commits £34 million each year to multifactorial falls prevention interventions; these are thought to be conservative estimates. The cost of falls to the NHS and Personal Social Services (PSS) is estimated to be £908.9 million, with 63% of the costs incurred from falls in those aged over 75 years (Scuffham and Chaplin 2002). Although most falls result in no serious injury, approximately 5% of older people living in the community who fall annually experience a fracture (Rubenstein 2001; Tinetti 1988). The total annual cost of fall-related fractures to the NHS is £1.7 billion (Torgerson 2001). The recently updated Cochrane review of interventions to prevent falling in community dwelling older people has suggested that exercise reduces fall rates by approximately 25%, dependent on mode of exercise. Most of the clinical trials conducted to date do not capture fracture as an outcome; fracture is the biggest burden, both to the patient & NHS. Given the money that the NHS invests each year, it is crucial to investigate whether this is an efficient use of scarce resources, exercise may be a cheaper strategy. This is a trial comparing alternative falls prevention interventions to prevent falls and fractures. Peripheral fractures, recorded within diagnosis codes in HES Inpatient, Critical Care, A&E and Outpatient datasets will be accepted as confirmed fracture. This is the primary outcome for the trial. Additional validation work will be conducted to compare ‘HES fractures’ to participant self-reported and fractures recorded in general practice. Other HES variables relating to hospital/episode duration (e.g. length of stay) will be used for economic analyses to determine the cost-effectiveness of alternative interventions. As this is a cohort of older adults aged over 70 years of age, we also require mortality data to accurately capture “time to event” outcomes, including fracture rates and falls rates over the duration of the study. This is the final request for HES data for this clinical trial. We requested interim waves of HES data in 2012-4. We hold full HES data for all participants included in the pilot study (n=1801) and partial HES data for subset of main trial participants (N=8019). These data have been used to calculate number and site of fractures. This is the last PreFIT request for the final wave of HES data for the last three years’ worth of hospital data for those consenting within the relevant timeframe (thus HES years 2013/4, 2014/5 and 2015/6). For this final request, we have excluded those participants for whom we already hold full data (excluded pilot study participants). This request is for data within the three year consented time period, thus from 2014 – 2016 for 8019 participants. For this final request, the study have restricted the request to the subset of main trial participants (excluding pilot study participants) to ensure the timing of individual signed participant consent falls within the approved three year timeline. To summarise, the study team request final HES data to allow accurate analysis of the trial primary outcome, to generate time to event outcomes (time to first fall; time to fracture etc). The study are unable to report the main trial findings without these HES data.
Project 2 — DARS-NIC-351810-N3G6N
Opt outs honoured: Y
Sensitive: Non Sensitive
When: 2016/04 (or before) — 2016/08.
Legal basis: Section 251 approval is in place for the flow of identifiable data
- MRIS - List Cleaning Report
By establishing a national Out of Hospital Cardiac Arrest Outcomes database there is potential in the future for considerable patient benefit. For example, Ambulance Services may use data to assess the impact of service improvement initiatives or researchers may use the data to assess the impact of interventions designed to improve survival, or understand the epidemiology of OHCA providing information about variation in outcome in the UK. This sort of understanding could help target interventions to improve patient outcomes. However, at this stage of the project, the focus is on developing and testing the best ways to collect the most accurate and reliable data for such a registry. The key expected benefits of this development phase will influence the next steps for establishing the OCHAO database. The results will inform the OCHAO team in making decisions about improving data completeness and quality for the remainder of the funding period (October 2018). It will also inform decisions about the feasibility of future data linkage work and the potential and value of extending this process to the whole database. The report to the funders will feed into their decision making about the feasibility of the data base and potential uses of the data for their future work. There are other elements of the OCHAO Project that will contribute to this decision-making. However this list cleaning and data linkage project will provide specific information about data collection and maximising data completeness and quality. The report to the Ambulance Services will provide feedback and inform decisions about data collection, data completeness and data quality for the remainder of the OCHAO project (October 2018). The paper in the peer-reviewed journal will provide knowledge to the research community about the methods of this data cleaning and linkage project and the survival outcomes for the subset of patients from the OCHAO database. It will inform researchers of the potential of the OCHAO database as an outcome database for future research to improve patient outcomes. Target date for publication: December 2017.
This application relates to a 10% sample of one year of data held on the OHCAO database and it's specific outputs will be 1. A report for the funders on the outcomes of this data linkage project this would contain details on how they link the mortality data to see if there is an increase to individuals who have out of hospital cardiac arrest. Target date April 2016 2. A report to the ambulance services. This would contain details of the 12 ambulance services across the country and within the report it would provide individual reports to showing how out of hospital cardiac arrests is linked to mortality for that region covered by that service linking the ambulance service within that region to cardiac outcomes in that area. Target date April 2016. 3. A paper in a peer reviewed journal. This is a high impact journal covering the UK detailing how mortality caused by out of hospital cardiac arrests are linked and survival rates Target publication date December 2017 All reports and papers will only contain data that is anonymised and aggregated in line with the HES Analysis Guidelines. It is the intention to report findings about the feasibility of linking the OCHAO data set with HSCIC/ONS data and the implications for expanding linkage to other HSCIC held data. It is also planned to report the results of survival analysis on the 10% sample.
The process of obtaining and using the data provided by HSCIC and the ONS will follow several steps. 1. OHCAO team will provide a 10% randomly selected sub-set of data held in the OHCAO database for the year 01/01/2014. to 31/12/2014 to HSCIC, via the HSCIC managed secure transfer system, which will contain the following variables: a. Patient forename and surname b. NHS Number c. Post Code d. Date of birth 2. HSCIC will provide a list cleaning service which will check the accuracy of the OHCAO data set and provide missing data where possible on the following variables: a. Hospital Number b. Post code c. Date of birth d. Date of death e. Surname f. Forename 3. HSCIC will link this data set to the ONS mortality data set, specifically to the variable "date of death". HSCIC will provide the “date of death” to OHCAO to allow OHCAO to calculate survival rates. OHCAO requires information on deaths from 01/01/2014 until 31/01/2015. This will be used to produce an outcome of 30-day survival from the work. For this reason, because OHCAO data set provided ends at the end of December 2014, mortality data is requested covering the period up to the end of January 2015. This will allow calculation of 30-day survival for any patients who had an arrest up to and including 31/12/2014. 4. HSCIC will securely transfer the list-cleaned data set and the linked date of death from the ONS to the OHCAO project team at Warwick University. 5. The data set will be held securely. The University’s network is protected by Cisco designed infrastructure incorporating firewalls, VLANS (used to secure distinct areas of the university’s campus) and Intrusion Detection Software to alert the Network Services team of potential risks. The Network Services team uses a comprehensive system for logging network activity. All servers are located in a purpose built data centre protected by a strictly policed access control system and CCTV surveillance. Occasional visitors/contractors are always escorted by an appropriate member of staff. Access to all systems requires a user name and password. Access to the database application requires an additional security role to be assigned to lock down features of the application to only those users who require them e.g. access to personally identifiable data. 6. Only the individuals with Approved Researcher accreditation will have access to the raw data. 7. The dataset will be used to establish the accuracy of the OHACO data base variables for NHS Number, Post Code, Date of Birth and Date of Death and used to update the database where necessary. Decisions will be taken on what are the minimum identifiers needed for data linkage and identifiers that are not required will be destroyed. For example, if it transpires that the NHS number and Date of Birth are sufficient for data collection by the ambulance services then the project will ask the ambulance service to stop collecting forename and surname in the future. 8. The data set will be analysed to investigate the 30-day survival rates for patients.
The British Heart Foundation and the Resuscitation Council UK have funded the development of a database of Out of Hospital Cardiac Arrests (OHCA) attended by an NHS ambulance emergency response. The project is called Epidemiology and Outcome from Out of Hospital Cardiac Arrest (OHCAO). It is run by the Emergency and Critical Care Team at the Warwick Clinical Trials Unit, University of Warwick. Data is collected by Ambulance Service Trusts and returned to a secure database run by the team. The project aims to establish the feasibility of developing and sustaining a national data base. This includes identifying the optimal process for case identification and outcome verification following OCHA. The project also aims to report on the epidemiology and outcome following OHCA. Survival is a key outcome. This application concerns the part of the OHCAO project, which aims to standardise and streamline the process for outcome verification for patients who did not die in the care of the ambulance services, to determine whether or not these survivors died subsequently. Initially a subset of data collected for the OHCAO project will be used to assess the feasibility of the data linkage process. Previous work by the team (Paramedic Study: NIHR HTA - 07/37/69) found that collecting data on mortality after a patient was admitted to hospital was challenging for the Ambulance Services. The ONS data on mortality is a single, accurate and reliable source or mortality, so the OCHAO project would like to establish the feasibility of linking the OHCAO project data set with ONS data. Given acknowledged difficulties for Ambulance Services to collect patients' NHS numbers, which are needed to make the link to the ONS data set, an objective is to assess the feasibility of improving the match rate of OHCAO dataset with the ONS and assess its accuracy through HSCIC's list cleaning service. The objectives of this application are therefore to use a randomly selected 10% sample of the OCHAO data collected in 2014 to: 1. Assess the completeness and quality of variables used for case identification, collected by the Ambulance Services, through the HSCIC list cleaning service. 2. Assess the quality and completeness of mortality data collected by the Ambulance Services through linkage with ONS mortality data, 3. Assess whether and by how much the HSCIC list cleaning will improve the match rate of the OHCAO data for data linkage to ONS mortality data 4. Use the resulting data set to analyse 30-day survival from OHCA
Project 3 — DARS-NIC-381887-X5W2S
Opt outs honoured: N
Sensitive: Non Sensitive, and Sensitive
When: 2016/09 — 2016/11.
Legal basis: Health and Social Care Act 2012, Approved researcher accreditation under section 39(4)(i) and 39(5) of the Statistical Registration Service Act 2007
Categories: Anonymised - ICO code compliant
- Hospital Episode Statistics Admitted Patient Care
- Hospital Episode Statistics Outpatients
- Office for National Statistics Mortality Data (linkable to HES)
This study aims to statistically model (i) variations in bowel cancer referral rates across GPs, and (ii) the survival rates, controlling for confounders. There has been an increasing concern about the differences in the referral rates for patients suspected of cancer (http://www.rightcare.nhs.uk/downloads/Right_Care_Diagnostics_Atlas_hi-res.pdf.). Variations in referral rates are considered as a source of inefficiency in the primary care services. This project will aim to identify various sources (for example specific socio-economic factors) that contribute to observed variations in referral rates. This will help policies to be targeted to ensure that the relevant population receives the appropriate care and hence reduce inefficiencies in the delivery of care. Given the very wide dissemination strategy, this will help policies to be targeted at the right population to ensure that they receive timely and appropriate care, and hence increase their health and wellbeing. Any beneficial change as a result of the outputs will be dependent on when the outcome of our research will be published. It will be ensured that all relevant bodies/organisations such as the NHS England, Public Health England, the Department of Health, Cancer Research UK, GPs and patients, involved in decision making with regard to bowel cancer diagnosis and treatment are informed about the research. For example, in 2010, Right Care working closely with NHS England, the Department of Health and the Public Health England, published for the first time the NHS Atlas of Variation in Health Care with the main aim to increase awareness regarding the variation existing in some clinical domains across different regions in England (http://www.rightcare.nhs.uk/atlas/qipp_nhsAtlas-LOW_261110c.pdf). The variation in cancer referral rates was considered very concerning and as they pointed out “Awareness is the first important step in identifying and addressing unwarranted variation” (Right Care 2010). By increasing awareness, they aimed to trigger the research for unwarranted variation and assess the value of the healthcare provided both to populations and to individuals. This research will contribute towards understanding part of the variation in cancer referral rates. The methodology used will be very easily generalizable to incidences of other types of cancers too. The outputs will therefore be beneficial to other researchers who wish to look at similar issues in other diseases which show very wide variations in detection and treatment across different geographical areas.
Specific outputs expected, including target date: The main product of this study will be the analysis carried out to answer the following important main questions: 1. What explains the observed variations in suspected bowel cancer referral rates? Is it possible to identify any particular groups of patients and particular areas that need to be targeted for efficient and effective referrals? 2. How have these observed variations changed over time and how this has impacted on mortality? 3. What has been the effect of the bowel screening program on the diagnosis of bowel cancer and the subsequent mortality? As part of the analysis there will be various tables with the results from the estimation methodology employed to conduct the analysis. The results will be grouped to the lowest Primary Care Trust (PCT) level, such that no patient nor doctor information will be identifiable. In cases where the number of practices/GPs in a given PCT is small, PCT sharing boundaries will be grouped together so that anonymity of the doctors and patients will be preserved. Expected outputs & dissemination activities: The journal articles will be authored by the two users of the data. The applicant will aim to publish the papers in general interest journal such as the British Medical Journal and specialist journal such as the Clinical Colorectal Cancer journal. These are peer-reviewed prestigious journals that reach a wide audience including health care professionals and individuals involved in policy making in the NHS. The statistical analysis to be carried out will be easily generalisable to other cancer incidences and hence the importance of also targeting of the general interest journals. The applicant will also ensure that the papers are made widely accessible through open-access policies of these journals to ensure that the results reach a wide audience including NHS staff who work with bowel cancer patients, policy makers and General Practitioners. Cancer Research UK will also be made aware of the research findings. The findings from the project will also be presented at relevant national and international conferences to disseminate the results. Some of the conferences that are of particular relevance to this study include the Annual conference and exhibition by the National Association of Primary Care (NAPC) and the Annual Education, Research and Innovation Symposium by the Royal College of General Practitioners (RCGP). Both NAPC and RCGP aim to improve the quality of the primary care services as well as to bridge the gap between the primary and the secondary care. RCGP Symposium is considered as a ‘must attend’ event by General Practitioners, GP registrars and academics who want to learn more and potentially contribute in primary care service improvement. Additionally, the findings will also disseminated at The King's Fund events and the Cancer Research UK Cambridge Institute (CRUK CI) Seminar events. The participants at these conferences will in turn help to disseminate the results to wider audiences. Non-technical executive summaries of the papers will be circulated to all the relevant organisations including those mentioned above. Warwick University has a very good media department which will ensure that all relevant results are publicised in an appropriate manner to reach the intended groups to achieve maximum benefits. If papers are accepted by the aforementioned journals, this it self will ensure that the results from this study reaches the right health professionals. Press-releases at the same time as publications will also ensure that the results get the maximum publicity. The tentative target dates for conducting the study are as follows: Months 0-3: The initial data cleaning is expected to take about 3 months. Months 4-12: Cross-sectional analysis of variations in observed patterns of referral rates and writing of the paper. A paper for a general interest medical journal such as the British Medical Journal, or a specialist interest journal such as the Clinical Colorectal Cancer journal. Months 9-36: Longitudinal analysis of variations, modelling using survival analysis, writing of the paper. A paper for a general interest medical journal such as the British Medical Journal, or a specialist interest journal such as the Clinical Colorectal Cancer journal. All outputs will have small numbers suppressed in line with the HES analysis guide.
Data creation for analyses i) The HES data extract will provide the Lower super Output Area (LSOA) identifiers which will be used to merge the local area population characteristics from the Census data with the HES information. This is crucial for the statistical analysis as this will enable the analysis to account for confounders and eliminate the bias in the estimation of the statistical models. ii) “The Quality Outcome Framework (QOF) is a voluntary annual reward and incentive programme for all GP surgeries in England, detailing practice achievement results. It is not about performance management but resourcing and then rewarding good practice.” See http://www.hscic.gov.uk/qof. QOF data provides some information on GP practice characteristics such as, the overall demographics of the pool of registered patients like the size of registered patients, their age group, etc. It also provides some information about the prevalence of different type of diseases like Cancer, Diabetes, Depression, Heart Disease, etc. But none of the information in QOF data are sensitive and these are freely available to retrieve from the HSCIC’s website. Matching of the QOF data to HES will enable the analysis to account for confounders such as the health of the patients attached to the GP practice. This will enable the applicant to model the probability of the referral leading to a confirmed diagnosis of bowel cancer. In summary, the HES data will be merged with the local patient characteristics that can be extracted from the QOF data and also the Census data at the LSOA level. This is crucial for valid statistical analysis. Statistical analyses This has three parts: (1) Starting with a linear model and cross-sectional data, first analysis with look at the effect of observed patients and GP Practice characteristics on suspected bowel cancer referral rates. All referrals will be grouped into three categories; immediate, urgent and non-urgent, and then standardized and adjusted for demographic and population characteristics obtained from the LOSAs. The results from this estimation will be used to test the hypothesis of whether the observed patients and GP Practice characteristics have a significant effect on explaining the variations in referral rates for suspected bowel cancer. (2) The second stage of the analysis will use the entire longitudinal dataset from 2003 to 2013 and panel data analysis to model the changes in behaviour through time. In addition, the analysis will be used to estimate the effect of the bowel screening program (introduced in 2006) on the observed patterns of referrals. (3) The final part of the project will use survival analysis to model the probability of death from bowel cancer conditioning on the type of referral and the characteristics of the patient and the GP practice. None of the processed data will be shared with any third party nor will they be used for commercial purposes or for marketing purposes. All individuals with access to the data are employees of the University of Warwick.
Background: There has been increasing concerns in recent years about differences in patient referral rates for suspected cancer across GPs. Each year there are nearly one million urgent GP referrals for suspected cancer (National Cancer Intelligence Network, 2014). In 2011, the rate of urgent referrals for suspected cancer in England ranged from 919.8 to 2957.4 per 100,000 populations. This 3.2 fold difference is evidence of a wide variation in cancer referral rates (Cancer Research UK, 2012). Socioeconomic factors and doctors characteristic have been shown to play a part in explaining variations in overall referral rates (O'Donnell, 2000). Overall GP referral rates for medical and surgical outpatient referrals are shown to be higher in high deprived areas, (Hippisley-Cox, Hardy, Pringle, Fielding, & Carlisle, 1997). This has not been tested for suspected bowel cancer referral rates. The characteristics that are expected to be associated with the referral rates are observed patients, local area characteristics, GP Practice characteristics and the incidence of bowel cancer in the particular GP area covered by the GP practice. Objective for processing: The main objective in processing the data is to carry out statistical analyses to explain observable variations in GP-practice referral rates for suspected bowel cancer and how this leads to positive diagnosis of cancer using patient, GP practice level characteristics and the local population characteristics. The research will try to explain how these observed variations has changed over time and how this has impacted on mortality. Another objective is to look at the effect of the Bowel Screening Program on the diagnosis of bowel cancer and the subsequent mortality. A comprehensive analysis using mortality data will enable the modelling of survival durations after referrals. The main product of this study will be the analysis carried out to answer three main questions: 1. What explains the observed variations in suspected bowel cancer referral rates? Is it possible to identify any particular groups of patients and particular areas that need to be targeted for efficient and effective referrals? 2. How have these observed variations changed over time and how this has impacted on mortality? 3. What has been the effect of the bowel screening program on the diagnosis of bowel cancer and the subsequent mortality? The research papers written as part of this project will be included as evidence as part of a PhD thesis if they fall within the timeframe for submission.