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Selecting Patients for Early and Effective Discharge (SPEED): Patient outcomes and staff experience of criteria led discharge

Eligibility: UK/International (including EU) graduates with the required entry requirements

Funding details: Bursary plus tuition fees (UK/International (including EU at international rates from Sept 21)

Duration: Full-Time – between three and three and a half years fixed term

Application deadline: 30 July 2022

Interview date: Will be confirmed to shortlisted candidates

Start date: January 2023

For further details contact: Associate Professor Liz Deutsch Liz.lees-deutsch@nhs.net


Coventry University is inviting applications from suitably-qualified graduates for a fully-funded PhD studentship.

Introduction

Criteria led discharge (CLD) is a contemporary global innovation (in developed countries) to improve flow of patients out of hospital by expediting the discharge process. The adoption of CLD in hospitals across the UK remains disparate, despite supporting evidence, national policy and guidelines developed by NHS England. Nevertheless, there is a growing body of evidence related to process, feasibility, and pilot work (Lees-Deutsch et al, 2018, 2019, 2020 and Lees-Deutsch 2021).

The key principle of CLD is to delegate the responsibility for selected patient discharges from doctors to other registered professionals, following appropriate training. Clinical criteria/parameters are determined by the medical team caring for the patient, after which the most appropriate registered professional (usually a nurse) will lead the patient’s discharge.

Project Details

This project aims to understand the outcomes for patients who have been selected for criteria led discharge from hospital and the experience of staff using the process.

There is a lack of evidence regarding:

  • Patient outcomes if discharge expedited through CLD
  • What the patient experience is
  • How staff engage with the CLD process
  • How staff experience the CLD process

This PhD proposes the systematic review from 2018 would be updated and registered with PROSPERO.

A Collective Case Study Design (one study with conjoined elements across several hospital sites) to collect data retrospectively from sites who have successfully introduced CLD is also proposed.

The collective case study involves studying multiple cases of data simultaneously or sequentially to generate a broader appreciation of issues. Retrospective data from sites will be sampled, using theory to guide, interpret with data synthesis.

Survey work relating to the patient and staff experience will be required.

The Framework approach is proposed to organise and manage site data.

Benefits

The successful candidate will receive comprehensive research training including technical, personal and professional skills.

All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities.

Funding

Bursary plus tuition fees (UK/International (including EU at international rates from Sept 21).

Entry Requirements

  • A bachelor’s (honours) degree in a relevant discipline/subject area with a minimum classification of 2:1 and a minimum mark of 60% in the project element (or equivalent), or an equivalent award from an overseas institution.
    PLUS
  • the potential to engage in innovative research and to complete the PhD within 3.5 years
  • An adequate proficiency in English must be demonstrated by applicants whose first language is not English. The general requirement is a minimum overall IELTS Academic score of 7.0 with a minimum of 6.5 in each of the four sections, or the TOEFL iBT test with a minimum overall score of 95 with a minimum of 21 in each of the four sections.
Additional requirements

An appropriately registered healthcare professional with an interest in patient discharge from hospital in an acute care setting. An understanding of the NHS context for patient discharge in emergency and elective care. Experience with data handling is desired.


To find out more about the project please contact Associate Professor Liz Deutsch: Liz.lees-deutsch@nhs.net

For pre-determined (named) projects an up-to 2000-word supporting statement is required showing how the applicant’s expertise and interests are relevant to the project. 

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