Impact of automation: evaluation of the implementation of diagnostic automation into the bacteriology laboratory as part of pathology modernisation

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 microorganisms. The shift from manual to automated operation poses a number of 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.

This research adopted a 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 NHS laboratories in England at various stages of implementation. It also investigated the impact on the workforce development of laboratory staff during the transformation period and changes in working practices in the four sites as they managed the shift from manual to automated procedures. A range of secondary data 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 14 individual semi-structured and 4 unstructured interviews was conducted with 21 participants, managers, and frontline staff, and the data was analysed thematically using NVivo. Rogers’ Diffusion of Innovation theory was used alongside statistical data to illuminate a range of interacting factors affecting the extent to which changes were implemented and embedded in each of the four sites.

The research found that diagnostic automation was successfully implemented in all four sites and that evaluation of long-term efficiency, testing turnaround time, and cost effectiveness was dependent on a range of technological, clinical, and organisational factors. The research proposes a systemic model of transformation based on pre-automation, transition, and post-automation to explain the various stages specific to technological innovation in this field and to assist in ongoing change management and evaluation.