Applications are invited for a fully-funded three year PhD to commence in October 2019.
The PhD will be based in the Faculty of Business and Law, and will be supervised by Professor Ashraf Labib, Professor Gordon Blunn and Dr Maria Barbati.
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 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. The research 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.
General admissions criteria
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.
Specific candidate requirements
We’d welcome candidates with a keen interest in both operational research and its application to healthcare.
How to Apply
We’d encourage you to contact Professor Ashraf Labib ([email protected]
) to discuss your interest before you apply, quoting the project code.
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. 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.
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.
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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.