The Health Foundation is an independent charity working to improve the quality of healthcare in the UK.

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1 Job description Job title: Reporting to: Salary: Intern in Data Analytics (six months fixed term contract) Data Manager 17,843 per annum (pro rata) Hours per week: 37.5 The Health Foundation The Health Foundation is an independent charity working to improve the quality of healthcare in the UK. We are here to support people working in healthcare practice and policy to make lasting improvements to health services. We carry out research and in-depth policy analysis, fund improvement programmes to put ideas into practice in the NHS, support and develop leaders and share evidence to encourage wider change. We want the UK to have a healthcare system of the highest possible quality safe, effective, person-centred, timely, efficient and equitable. Data analytics Data analytics offers the possibility of a better, smarter health care system. Traditional research methods often fail to meet the needs of patients, healthcare professionals and policy makers, by taking years to produce answers to very narrow research questions about the effectiveness of certain treatments for specific groups of people. Massive data sets and advanced mathematics can produce more tailored information that can be relayed more rapidly to care teams. Although analytics is used widely in the private sector (for example, to suggest new products on Amazon), it has not been used extensively in healthcare to improve outcomes for patients. 1

2 The data analytics team at the Health Foundation, established late last year, works creatively and collaboratively to harness the power of data analytics to improve care and the underlying data science. At the core of our work are partnerships with NHS teams to experiment with new ways of improving care using data analytics. The data analytics team works to design and evaluate improvement programmes in the NHS. We use secure, pseudonymised data sets to design better more targeted approaches in healthcare, to monitor their effectiveness, and to track their spread. Examples of current projects include: Named Accountable GP a project evaluating the impact of the named accountable GP policy (for patients aged 75 and above) on continuity of care, rates of GP attendance and rates of referrals to specialist care. We are analysing pseudonymised GP and hospital data on approximately 300,000 patients, using regression discontinuity methods. NHS111 a project to determine the feasibility of linking routine hospital and general practice (GP) data to NHS 111 data for children living in inner North West London. We are investigating rates of hospital use (including A&E visits) over the hours and days following the telephone call. In addition, we will determine which patient factors are associated with following the advice prescribed in terms of attending A&E departments. PAM The Patient Activation Measure (PAM) is a commonly used tool for assessing patient activation - the skills, confidence and knowledge a person has in managing their health. Focusing on data from Islington CCG, we will extract linked pseudonymised individual level patient data, for all patients with long-term condition sent a PAM questionnaire and investigate their baseline characteristics, and determine whether a change in PAM score over time impacts prevention, treatment and healthcare usage. Doing this work requires advanced methods from machine learning, causal inference, improvement science and graphic analytics, as well as access to large, anonymised linked data sets. We develop methods in these areas as needed to conduct our work, and in doing so partner with international teams of methodologists and improvement experts. The team The team aims to be creative about the use of big data, while working at the intersection of health care delivery, policy analysis and methodology. The 2

3 Foundation s endowment provides valuable independence and space to be thoughtful about analytical approaches. Moreover, its relationship with the NHS and improvement scientists means that we can apply analytics directly to real-world problems that are important for patients and policy makers. Successful applicants will have the opportunity to contribute towards a growing field that will likely shape the future delivery of healthcare. The Data Analytics team consists of five Data Analysts, a Data Manager and the Director of Data Analytics. The team members have varying backgrounds including econometrics, statistics, epidemiology and neuroscience. The data analytics team aims to be at the forefront of using novel and established data sets, such as the hospital episode statistics, the general practice electronic medical record, and operational data from other public services including social care. Over time, we expect more data sets to be added (including social media and health app data) to meet our ambitious programme of work, and to collaborate and share data with external research teams. Data management While all team members contribute towards data extraction, it requires special skills. The Intern in Data Analytics together with the Data Manager would lead on data collection across a number of projects, create projects specific extracts from larger data collections, prepare and document data for analysis and contribute to the Foundation s secure processing of data whilst safeguarding patient privacy. By actively participating in team meetings and discussions with colleagues the Intern in Data Analytics will get a thorough understanding of all the stages in an evaluation or research project, although a single project will often last for longer than six month due to the nature of (often lengthy) data access negotiations. Although the main focus of the internship is on the data management and data preparation side of quantitative analysis, there will be an opportunity for the Intern in Data Analytics to contribute to analysis of data as well. Opportunities for the Intern in Data Analytics The Health Foundation considers internships to be training placements, preparing the successful candidate for the job market. As Intern in Data Analytics you will have the opportunity to: 3

4 Develop and test useful skills in a safe environment; Have weekly meetings with the Data Manager to discuss expectations, development and provide feedback (both ways). Work with the Data Manager to gain skills and experience specific to data professionals; Talk to members of the Data Analytics team and the wider organisation about work experiences and career development; Shadow senior members of the Data Analytics team; Learn from current best practice at the Health Foundation and wider community through (team) meetings and seminars; and Partake in internal training sessions aimed at personal development; Key tasks and responsibilities 1. Have an understanding of information governance and information security policies and procedures for the secure storage, sharing, and destruction of data held by the team. 2. Apply Statistical Disclosure Control (SDC) on research outputs produced by the team to safeguard the confidentiality of patient information. 3. Create and apply consistent variable labels, value labels and data documentation for large data sets including HSCIC s Hospital Episode Statistics. 4. Create and clean projects specific data extracts from larger data collections so only the minimum amount of data required is used in processing. 5. Maintain a database of the permissions and specifications for each data sets and data extracts held by the team. 6. Support the Data Manager in working with data controllers and Caldicott guardians to negotiate permissions to use data. 7. Work with other team members and external information analysts to specify, pseudonymise, encrypt and transfer data sets in a timely manner. 8. Ensure that data sets are stored on the server in a logical way. 9. Contribute towards the analysis of data sets and the writing of reports and research articles. 4

5 Person specification Knowledge and experience 1. An understanding of statistical concepts and/or data linking methodologies. 2. Knowledge and experience of working with SAS, Stata, R or any other programming language. 3. Experience of conducting analyses using (large) data sets. 4. Experience of working on datasets in health and social care (desirable). 5. Currently undertaking or a recent graduate with a degree in a relevant quantitative subject Skills and abilities 1. Interest in information governance as well as data security. 2. Ability to quickly learn and apply Statistical Disclosure Control to research outputs. 3. Excellent analytical skills. 4. Proficient in Microsoft Office with particular skills in Excel to an advanced level. 5. A can-do attitude and resilience. 6. A person who is meticulous and exact. 7. A person who is flexible, respectful of colleagues, and adaptable. 8. An understanding of, and commitment to, equal opportunities and diversity. July