Decision-analytic determination of study size. The case of electronic fetal monitoring

There is uncertainty about the efficacy of electronic fetal monitoring (EFM) in lowering perinatal mortality among births at low prospective risk. A randomized controlled trial offers the greatest promise of reducing this uncertainty. Haphazard methods of evaluating decision making have prevailed in the past and have led to study sizes too small to estimate effects on perinatal mortality. Statistical methods can determine the study size necessary to meet statistical parameters. Choice of these parameters is, however, somewhat arbitrary. Decision-analytic methods calculate the expected value of information (EVI) as the likely worth of future decision guidance. The optimal size, cost, and focus for an evaluation study can then be taken as those maximizing the net EVI after consideration of study cost. This methodology indicates that, in evaluating EFM, two randomly-assigned groups of roughly 180,000 births each should be studied. This would achieve net expected societal benefits estimated at $118 million at a cost of roughly $22 million. The optimal study size is somewhat sensitive to analytic parameters. If feasible, a superior dynamic strategy is to allow study findings to determine the ultimate study size.