Stratified, precision or personalised medicine? Cancer services in the 'real world' of a London hospital.

We conducted ethnographic research in collaboration with a large, research-intensive London breast cancer service in 2013-2014 so as to understand the practices and potential effects of stratified medicine. Stratified medicine is often seen as a synonym for both personalised and precision medicine but these three terms, we found, also related to distinct facets of treatment and care. Personalised medicine is the term adopted for the developing 2016 NHS England Strategy, in which breast cancer care is considered a prime example of improved biological precision and better patient outcomes. We asked how this biologically stratified medicine affected wider relations of care and treatment. We interviewed formally 33 patients and 23 of their carers, including healthcare workers; attended meetings associated with service improvements, medical decision-making, public engagement, and scientific developments as well as following patients through waiting rooms, clinical consultations and other settings. We found that the translation of new protocols based on biological research introduced further complications into an already-complex patient pathway. Combinations of new and historic forms of stratification had an impact on almost all patients, carers and staff, resulting in care that often felt less rather than more personal.

Data Resource: the National Pupil Database (NPD).

INTRODUCTION: The National Pupil Database (NPD) is a record-level administrative data resource curated by the UK government's Department for Education that is used for funding purposes, school performance tables, policy making, and research. PROCESSES: Data are sourced from schools, exam awarding bodies, and local authorities who collect data on an on-going basis and submit to the Department for Education either termly or yearly. DATA CONTENTS: NPD contains child-level and school-level data on all pupils in state schools in England (6.6 million in the 2016/17 academic year). The primary module is the census, which has information on characteristics and school enrolment. Other modules include alternative provision, exam attainment, absence and exclusions. Data from children's social care are also available on children referred for support and those who become looked after. Children's records are linkable across different modules and across time using a nationally unique, anonymised child-level identifier. Linkage to external datasets has also been accomplished using child-level identifiers. CONCLUSIONS: The NPD is an especially valuable data resource for researchers interested in the educational experience and outcomes of children and young people in England. Although limited by the fact that children in private schools or who are home schooled are not included, it provides a near-complete picture of school trajectories and outcomes for the majority of children. Linkage to other datasets can enhance analyses and provide answers to questions that would otherwise be costly, time consuming and difficult to find.

Inequalities in the care experiences of patients with cancer: analysis of data from the National Cancer Patient Experience Survey 2011-2012.

OBJECTIVES: To explore inequalities in the care experiences of of patients with cancer by patient, clinical and trust-level factors [corrected]. DESIGN: Secondary analysis of data from the National Cancer Patient Experience Survey 2011-2012. SETTING AND PARTICIPANTS: Adult patients with a primary diagnosis of cancer who attended an acute or specialist National Health Service (NHS) trust in England. OUTCOME MEASURE: OR of a patient rating their overall care positively, adjusting for other patient, clinical and trust-level factors. METHODS: Using cross-sectional data from 71 793 patients with cancer who completed the National Cancer Patient Experience Survey 2011-2012, we examined associations between patient, clinical and trust-level factors and a summary measure of patient experience, namely overall rating of care. Multivariate logistic regression was used to investigate variation by sociodemographic characteristics adjusting for other patient, clinical and trust-level factors. RESULTS: Female, non-white and younger patients were less likely to rate their overall care as excellent or very good. Patients with long-standing conditions, particularly those with learning disabilities or mental health conditions, also reported poorer overall care. This variation persisted when other patient, clinical and trust-level factors were controlled for, indicating that there are real differences in experiences among patients with cancer by sociodemographic characteristics. CONCLUSIONS: There is evidence of inequalities in the experiences of patients with cancer in the UK by sociodemographic characteristics such as gender, age, ethnicity and disability. Quality cancer care services must strive to meet the needs of a diverse patient population equally; this study identifies patient groups for whom it appears cancer care services are in greatest need of improvement.