Cervical screening programmes: can automation help? Evidence from systematic reviews, an economic analysis and a simulation modelling exercise applied to the UK.
OBJECTIVE
To assess the effectiveness and cost-effectiveness of adding automated image analysis to cervical screening programmes.


METHODS
Searching of all major electronic databases to the end of 2000 was supplemented by a detailed survey for unpublished UK literature.


METHODS
Four systematic reviews were conducted according to recognised guidance. The review of 'clinical effectiveness' included studies assessing reproducibility and impact on health outcomes and processes in addition to evaluations of test accuracy. A discrete event simulation model was developed, although the economic evaluation ultimately relied on a cost-minimisation analysis.


RESULTS
The predominant finding from the systematic reviews was the very limited amount of rigorous primary research. None of the included studies refers to the only commercially available automated image analysis device in 2002, the AutoPap Guided Screening (GS) System. The results of the included studies were debatably most compatible with automated image analysis being equivalent in test performance to manual screening. Concerning process, there was evidence that automation does lead to reductions in average slide processing times. In the PRISMATIC trial this was reduced from 10.4 to 3.9 minutes, a statistically significant and practically important difference. The economic evaluation tentatively suggested that the AutoPap GS System may be efficient. The key proviso is that credible data become available to support that the AutoPap GS System has test performance and processing times equivalent to those obtained for PAPNET.


CONCLUSIONS
The available evidence is still insufficient to recommend implementation of automated image analysis systems. The priority for action remains further research, particularly the 'clinical effectiveness' of the AutoPap GS System. Assessing the cost-effectiveness of introducing automation alongside other approaches is also a priority.
Willis
B H
BH
ARIF, Department of Public Health and Epidemiology, University of Birmingham, UK.
Barton
P
P
Pearmain
P
P
Bryan
S
S
Hyde
C
C
D001331:Automation; D003362:Cost-Benefit Analysis; D017598:Efficiency, Organizational; D019317:Evidence-Based Medicine; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008403:Mass Screening; D013222:State Medicine; D013996:Time and Motion Studies; D006113:United Kingdom; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis*; D014626:Vaginal Smears