Learning from failures in the health sector: Towards a high organisation reliability status
Funded PhD Project (UK, EU and international students)
BUSM4520219 (UK and EU students)
BUSM4550219 (International students)
Business and Management
Applications are invited for a fully-funded three year PhD to commence in October 2019.
Successful applicants will receive a bursary to cover tuition fees for three years and a stipend in line with the RCUK rate (£14,777 for 2018/2019). International (non-EEA) applicants will also receive one return flight to London during the duration of the course through the Portsmouth Global PhD scholarship scheme.As part of the bursary, the Faculty of Business and Law may fund fieldwork expenses (currently £2,000) over the total period of PhD study.
We also offer funding to attend conferences (currently £450), training (currently £450), and a work-based placement (currently a maximum of £3,000 tied up to the period of 12 weeks).
The work on this project will:
- focus on how to develop advanced root cause analysis methods that are capable of being used at prospective (at design stage) and retrospective (as a learning from failure analysis) phases
- focus on basic fundamental research on improvement of medical errors analysis and prevention technology through studies of accident development scenarios, simulations, probabilistic assessments and basic data review from the NHS registers, as well as interaction with key stakeholders
- develop a framework for assessing and improving the resilience of the health service
High Reliability Organizations (HROs) usually refer to industries such as nuclear and aviation where they possess a high degree of reliability despite their hazardous environment.
Health systems and HROs such as commercial aviation companies have many common characteristics. They both have a continuously changing organizational environment, with many interactive and interdependent processes, whose interactions may lead to unpredictable, unintentional consequences.
However, healthcare systems are currently far from being HROs: in 2002-2011, 1.6 deaths occurred per million flights, while it is estimated that 1300 to 2800 deaths occur per million hospitalizations in the U.S. due to medical errors.
The proposed research will assess both the seriousness and frequency of medical errors, with particular focus on potential errors and near-misses, such as unsafe conditions and events that did not reach the patients; these provide clues toward weaknesses in the system.
The research will adapt and develop models of high reliability organizational theory to redesign work processes and mitigate medication errors and patient accidents, and will include methods of extracting data about near-misses, performing root cause analysis, and the extraction of generic lessons. These techniques will be applied in a similar approach as applied to the cases of disasters in industrial engineering.
By introducing the practices of HROs into healthcare, our aim is to minimize the negligence cases frequently reported in healthcare. This will prepare NHS towards achieving higher standards of patient safety, adopting the most appropriate strategies, as suggested by the investigation conducted.
The project is designed to extend theory through extraction of generic lessons for prevention, mitigation and response to any future accidents.
- Ilo, K.C., Derby, E.J., Whittaker, R.K., Blunn, G.W., Skinner, J.A., & Hart, A.J. (2017). Fretting and corrosion between a metal shell and metal liner may explain the high rate of failure of R3 modular metal-on-metal hips. The Journal of Arthroplasty, 32(5), 1679-1683.
- Agwu, A.E., Labib, A.W., & Hadleigh-Dunn, S. (2019). Disaster prevention through a harmonized framework for high reliability organisations. Safety Science, 111, 298-312.
- Barbati, M., Greco, S., Kadziński, M., & Słowiński, R. (2018). Optimization of multiple satisfaction levels in portfolio decision analysis. Omega, 78, 192-204.
- Perris, T., & Labib, A.W. (2004). An intelligent system for prioritisation of organ transplant patient waiting lists using fuzzy logic. Journal of Operational Research Society, 55(2), 103-115, 2004.
- Labib A.W., & Perris, T. (2004). The prioritisation of organ transplant patient waiting lists: Application of Fuzzy Logic and Multiple Criteria Decision Making. The 46th Annual Conference of the O. R. Society, York, UK.
- You'll need a good first degree from an internationally recognised university (minimum second class or equivalent, depending on your chosen course) or a Master’s degree in an appropriate subject.
- In exceptional cases, we may consider equivalent professional experience and/or Qualifications.
- English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.
We’d welcome candidates with a keen interest in both operational research and its application to healthcare.
If you have project specific enquiries, please contact Professor Ashraf Labib (email@example.com) to discuss your interest before you apply, quoting the project code.
How to apply
When you are ready to apply, you can use our online application form and select ‘Business and Management’ as the subject area. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.
Please also include a research proposal of 1,000 words outlining the main features of your proposed research design – including how it meets the stated objectives, the challenges this project may present, and how the work will build on or challenge existing research in the above field.
Our ‘How to Apply’ page offers further guidance on the PhD application process.
If you want to be considered for this funded PhD opportunity you must quote project code BUSM4520219 (UK and EU students) or BUSM4550219 (International students) when applying.