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ICHT Inclusive Recruitment Analysis

Safe People

Organisation name

Imperial College London

Organisation sector

Academic Institute

Applicant name(s)

Sarindi Aryasinghe

Catalina Carenzo

Funders/ Sponsors

Louise ClarkKerri-Ann Barnett

DEA accredited researcher?

Unknown

Sub-licence arrangements (if any)?

No

Safe Projects

Project ID

NIBDAPC_2023_0023

Lay summary

NHS staff are essential to deliver high quality, safe, and kind services to patients and we know that many things can affect their health and wellbeing at work. However, for staff to ultimately provide safe care to patients, they must also feel supported to do their best at work. In the last few years, in particular due to the COVID-19 pandemic, it has been clear that White and Black and Minority Ethnic (BME) staff have had very different and unequal experiences of the NHS as a workplace. As well, men from white backgrounds tend to take on more senior roles, with black and minority ethnic staff taking on more junior roles. Therefore, as part of Imperial College Healthcare NHS Trust’s Equality, Diversity, and Inclusion Strategy, the Trust has started two recruitment programs in June 2022 to increase the diversity of the workforce. First, all interviews are expected to have a woman and an ethnic minority staff member on the interview panel, and second, all hiring managers are expected to write a letter to the Trust Chief Executive Officer (CEO), Tim Orchard, to provide reasons as to why their chosen candidate is the most suitable for the role. As well, the Trust runs a staff survey every year to understand the experiences of current staff members and whether feel they are supported to progress their careers within the organisation. The aim of this project will be to use recruitment and staff engagement survey data to understand whether the diversity of backgrounds of people making up the recruitment panels and Letters to the Trust CEO are increasing ethnic and gender diversity of new recruitments, and whether current employees feel they are supported to deliver their best and progress their careers within the Trust. A natural language processing algorithm – a computer programme that can analyse the words that are in the letters to the CEO – will also be developed to support the Trust’s Human Resources team to quickly get insights from the Letters to the Trust CEO so they can at a glance understand the reasons behind why a particular candidate is chosen. Although this project is using staff recruitment data and not patient data, we are submitting an application to the iCARE Data Access Committee because we want to ensure that we are still following the same data security and information governance rules to securely analyse the data and protect staff confidentiality.

Public benefit statement

The NHS was originally established on the principles of social justice and equity for all, and it is important to note that this also includes the staff that work within the system. The North West London and wider London populations are very diverse, and so healthcare teams that provide care should ideally be reflective of the patient demographics that they serve across all senior levels. Creating an inclusive workforce will benefit the Trusts patients and its relationships with the public as staff from diverse ethnic backgrounds will have a better understanding of the cultural, social, economic complexities of the patient experience. A workforce from diverse ethnic backgrounds will also help develop new care and treatments by bringing together different perspectives and new ways of thinking to deliver quality and safe care for direct patient benefit.

Request category type

Public Health Research

Other approval committees

Project start date

08/06/2023

Latest approval date

28/04/2023

Safe Data

Dataset(s) name

ICHT Inclusive Recruitment Dataset

Data sensitivity level

De-Personalised

Common Law Duty of Confidentiality

Not applicable

National data opt-out applied?

Not applicable

Request frequency

One-off

Release/Access date

08/06/2023

Safe Setting

Access type

TRE

Safe Outputs