Using system-wide integrated data to investigate inequities in patient safety

Do you want to apply the latest data science methods and analytic techniques to system-wide integrated data to understand variations in the quality and safety of health care? Do you want to answer pressing research questions concerning sources of inequality in patient safety for marginalised groups? Do you want to develop patient safety intelligence solutions to support policy-makers and providers as they shape future healthcare systems? If so, this studentship opportunity will appeal to you.<br /> <br /> The NIHR Yorkshire and Humber Patient Safety Research Collaborative (PSRC) is inviting applications for a full-time PhD studentship, to start in 2024, as part of its interdisciplinary Safety Intelligence work stream. The studentship aims to enhance patient safety intelligence in healthcare, specifically concerning insight into inequities in patient safety across sociodemographic and marginalised groups, including the development of new data analytic and visualisation tools that harness the power of large-scale integrated datasets. The studentship will appeal to candidates from a range of backgrounds with specific interests in healthcare data science and quantitative health services research.

<p>Patient safety is an important field of health services research that focuses on promoting safe, equitable care by reducing adverse events (such as errors and complications), preventable harm and unintended variations in care across groups of patients. There is currently considerable interest amongst researchers and policy-makers in disparities in patient safety, with reduction in health-associated inequalities the target of a &pound;55 million investment by the National Institute for Health and Social Care Research. Health heterogeneity across sociodemographic and marginalised groups is a complex issue driven by interactions between ethnicity, social circumstances, deprivation, geographic location and variations in the adequacy of local healthcare services to provide equitable, multicultural care. Research evidence suggests that ethnic minority patients suffer higher rates of adverse events, such as medication errors, complications and hospital-acquired infections (Chauhan, 2020). Similarly, in primary care, women and black patients are more likely to receive inappropriate diagnosis, treatment or referrals (Piccardi, 2018). In addition, there exists growing reliance on clinical algorithms which may be biased due to historic data inequalities, leading to misdiagnoses and inappropriate treatment for marginalised groups (Celi et al. 2022). &nbsp;</p> <p>Understanding safety inequality requires population-level epidemiological research, employing 1) comprehensive data linkage at the whole-systems level to provide a comprehensive picture of risks and harms, and 2) data analytics capable of modelling the complex interactions amongst patterns of sociodemographic variables and patient safety outcomes, including intersectionality and the compounded risks faced by disadvantaged groups with multiple combined social identities (Harari and Lee, 2021). With the proliferation of electronic health service data across primary, social, secondary and prehospital care, there exists considerable opportunity to combine this data with non-health services data (e.g. education, housing, crime) in order to better address the complex, real-world challenges facing service providers in terms of design and provision of equitable healthcare for all. &nbsp;</p> <p>The studentship will involve working with data made available through Connected Bradford, a pioneering data linkage programme, conceived to address the types of complex research questions that can only be answered through analysis of system-wide, integrated data. Connected Bradford includes the entire population and leverages the NHS number to unite patient information across diverse healthcare settings, within a secure and trusted research environment, to provide comprehensive insights and facilitate population-level epidemiological research (Sohal, 2022).</p> <p>The research programme and thesis may focus on any combination of related aims, examples including:</p> <ul> <li>Development and evaluation of cutting-edge data integration, visualisation and feedback solutions for a range of stakeholders, including patient safety researchers, policy makers and health service providers.</li> <li>Exploratory analysis of inequity-related predictors for patient safety indicators and related proxy-outcomes.</li> <li>Modelling intersectionality using recently developed approaches such as MAIDHA (multilevel analysis of individual heterogeneity and discriminatory accuracy within an intersectional framework; Merlo, 2022).</li> <li>Extending current understanding of missed patient deterioration in primary care (e.g. Cecil, 2021) by developing risk prediction models based upon linked data.&nbsp;</li> <li>Application of contemporary causal inference theory and methods to key patient safety inequality research challenges, including use of DAGs to address various sources of bias and estimation of causal effects.</li> </ul> <p>The studentship will be based across the University of Leeds (with links to the Leeds Institute for Data Analytics) and the Patient Safety Research Collaborative (PSRC) located at the Bradford Institute for Health Research. The student will join a multidisciplinary team of researchers in Patient Safety Intelligence with expertise in data science, health and social science research methods. The supervision team includes expertise in patient safety research (specifically safety intelligence), data science and AI, statistics and clinical risk modelling. The team comprises Dr Jonathan Benn (School of Psychology, University of Leeds, and theme lead for Safety Intelligence, Yorkshire and Humber PSRC), Dr Muhammad Faisal (Faculty of Health Studies, University of Bradford) and Dr Luke Budworth (Senior Research Data Analyst, Yorkshire and Humber PSRC).</p> <p>Yorkshire and Humber PSRC PhD students will become NIHR trainees and you will benefit from a range of training support and resources to develop your knowledge and health research skills. You will also be embedded within the Yorkshire Quality and Safety Research Group, which is a friendly and dynamic group of researchers conducting high-quality, rigorous and applied health services research. YH PSRC is a collaboration between the Bradford Teaching Hospitals Foundation Trust and the Universities of Leeds and Bradford. Our mission is to deliver research to make healthcare safer. We are one of six NIHR Patient Safety Research Collaborations in England. Our work draws on the knowledge and expertise of well-established networks of researchers, patients, carers, clinicians and industry partners to develop ideas that address patient safety problems. Our research focusses on four themes: Safer systems, culture and practice; De-cluttering (safely) for safety; Supporting safe care in the home; and Rethinking safety intelligence for improvement.</p> <h5>References</h5> <ul> <li>Cecil E, Bottle A, Majeed A, Aylin P. Factors associated with potentially missed acute deterioration in primary care: cohort study of UK general practices. Br J Gen Pract. 2021 Jun 24;71(708):e547-e554. doi: 10.3399/BJGP.2020.0986. PMID: 33657010; PMCID: PMC8177954.</li> <li>Celi, L. A., Cellini, J., Charpignon, M. L., Dee, E. C., Dernoncourt, F., Eber, R., ... &amp; Yao, S. (2022). Sources of bias in artificial intelligence that perpetuate healthcare disparities&mdash;A global review. PLOS Digital Health, 1(3), e0000022.</li> <li>Chauhan, A., Walton, M., Manias, E., Walpola, R. L., Seale, H., Latanik, M., ... &amp; Harrison, R. (2020). The safety of health care for ethnic minority patients: a systematic review. International Journal for Equity in Health, 19(1), 1-25.</li> <li>Harari, L., &amp; Lee, C. (2021). Intersectionality in quantitative health disparities research: A systematic review of challenges and limitations in empirical studies. Social Science &amp; Medicine, 277, 113876.</li> <li>Merlo, J. (2018). Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) within an intersectional framework. Social Science &amp; Medicine, 203, 74-80.</li> <li>Piccardi, C., Detollenaere, J., Vanden Bussche, P., &amp; Willems, S. (2018). Social disparities in patient safety in primary care: a systematic review. International Journal for Equity in Health, 17, 1-9.</li> <li>Sohal, K., Mason, D., Birkinshaw, J., West, J., McEachan, R. R., Elshehaly, M., ... &amp; Wright, J. (2022). Connected Bradford: a whole system data linkage accelerator. Wellcome Open Research, 7.</li> </ul>

<p>To apply for this scholarship opportunity applicants should complete an <a href="https://medicinehealth.leeds.ac.uk/faculty-graduate-school/doc/apply-2">online application form</a> and attach the following documentation to support their application.&nbsp;</p> <ul> <li>A full academic CV</li> <li>Degree certificate and transcripts of marks</li> <li>Evidence that you meet the University&#39;s minimum English language requirements (if applicable)</li> </ul> <p>To help us identify that you are applying for this scholarship project please ensure you provide the following information on your application form;</p> <ul> <li>Select PhD in Psychology as your programme of study</li> <li>Give the full project title and name the supervisors listed in this advert</li> <li>For source of funding please state you are applying for a&nbsp;NIHR PSRC&nbsp;Scholarship</li> </ul> <p>If English is not your first language, you must provide evidence that you meet the University&#39;s minimum English language requirements (below).</p> <p><em>As an international research-intensive university, we welcome students from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Across all Faculties we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+ and people with disabilities. Applicants will always be selected based on merit and ability.</em></p>

Applicants to this scholarship should normally have (or be about to obtain) an Undergraduate degree of 2:1 or above (or international equivalent) in a relevant subject area. A Master&rsquo;s degree is desirable, but not essential (for example: a Master&rsquo;s degree in data science, or a health/medicine-related area such as epidemiology, public health, psychology or medical research). Additionally, experience with data processing, including statistical research methods, would be considered an advantage. Strong verbal and written communication skills are required for effective interdisciplinary collaboration and engagement with a broad range of research stakeholders including patients and the public. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Admissions Team prior to making an application.<br /> <br /> Other conditions:<br /> &bull; Due to limited funding, we can only consider applicants for this position who are eligible for UK fee status.<br /> &bull; Applicants must not have already been awarded or be currently studying for a doctoral degree.<br /> &bull; Awards must be taken up by 1st October 2024.<br /> &bull; Applicants must live within a reasonable distance of the University of Leeds whilst in receipt of this scholarship.

Candidates whose first language is not English must provide evidence that their English language is sufficient to meet the specific demands of their study. The minimum English language entry requirement for postgraduate research study in the School of Medicine is an IELTS of 6.5 overall with at least 6.0 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid.

<p>This opportunity is funded by the National Institute of Health Research (NIHR). The scholarship will attract an annual tax-free stipend of &pound;19,237 for year one, and this will increase each year for up to 3 years subject to satisfactory progress. Academic fees will also be paid at the UK fee rate. This scholarship opportunity is for Full-time study (duration: 3 years). The award will be made for one year in the first instance and renewable for a further period of up to two years, subject to satisfactory academic progress.</p>

<p>For informal enquiries regarding this project please contact Dr Jonathan Benn: <a href="mailto:J.Benn2@leeds.ac.uk">J.Benn2@leeds.ac.uk</a></p> <p>For further information about the admissions process please contact the Admissions Team at: <a href="mailto:fmhpgradmissions@leeds.ac.uk">fmhpgradmissions@leeds.ac.uk</a></p>