Evaluate the Implementation of Diagnostic Automation into the Bacteriology Laboratory as part of Pathology Modernisation.
PHE ePoster Library. Mohammad G. Apr 9, 2019; 259608; 15576
Mr. Ghassan Mohammad
Mr. Ghassan Mohammad
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Abstract Pathology services globally are undergoing significant transformation in response to changing demographics and increased infection control demands, notably in relation to the growing challenges of identifying multidrug-resistant micro-organisms. Advances in diagnostic laboratory technologies form part of the future direction for configuration of pathology services in England, with an emphasis upon cost-efficiency, quality and innovation. The shift from manual to automated operation poses many challenges and opportunities for service design and delivery, workforce skill mix and the measurement of productivity, not least the extent to which new technologies are being implemented successfully and as originally planned. The research adopted an insider research case study approach combining quantitative and qualitative methods to investigate service improvements in the diagnostic automation of selected pathology laboratory services, including the extent of quality and productivity gains. The case focused on four PHE laboratories at various stages of implementation. It also investigated the impact on workforce development of laboratory staff in the four sites managing the shift from manual to automated procedures. A range of secondary data sets was collated and analysed using descriptive statistical methods to examine indicators of laboratory workload, diagnostic procedure turnaround time, laboratory productivity and workforce roles. A series of 19 individual semi-structured interviews was conducted with selected managers and frontline staff and data analysed thematically using NVivo. The research found that diagnostic automation was more successfully implemented (fully or partially in 4 out of four sites) and that evaluation of long-term efficiency and cost-effectiveness was dependent on a range of technological, clinical and organisational factors. The research proposed a systemic model of transformation based on 'pre-automation, transition, and post-automation' to explain the various stages specific to technology innovation in this field and to assist in ongoing change management and evaluation. Recommendations surrounding staff development and working practices are also proposed.
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