Clinical practice guidelines for monitoring children's behavioural development at the 18‐month well‐baby visit: A decision analysis comparing the expected benefit of two alternative strategies

Abstract

Rationale, aims and objectives The current American Academy of Pediatrics policy calls for universal developmental screening (UDS) at the 18‐month well‐baby visit (18MWBV). In contrast, different clinical practice guidelines exist in other developed countries where only toddlers of concerned parents are referred for (selective) developmental screening (SDS). This study compares the expected benefit (EB) of these two strategies for monitoring children's behavioural development at the 18MWBV. Method A clinical decision analysis was performed, with EB defined as gain (probability of screening when appropriate + probability of not screening when appropriate) minus cost (probability of screening when not appropriate + probability of not screening when not appropriate). Accordingly, a strategy's EB referred to its efficiency at distinguishing between toddlers who need to be referred for screening and those who do not. Results The EB of the UDS strategy was estimated at −0.242. In contrast, the EB of the SDS strategy was much greater at 0.326. In fact, the EB of the UDS strategy could only equal or surpass that of the SDS strategy if screening toddlers with a problem was considered almost five times more important than not screening well toddlers. However, our monitoring effort should be more evenly distributed between these two imperatives. Also, the evidence in favour of the SDS strategy remained largely unchanged after considering a broad range of values for the (unique) probabilities in the decision tree. Conclusion There are many steps involved in the monitoring of children's early behavioural development, but when it comes to decide whether or not to use behavioural screening, there is evidence for adopting the SDS strategy, and screening only if a behavioural concern is being raised by parents.

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“…Empirical estimates such as a test's sensitivity (SE) and specificity (SP) often need to be calibrated (on a scale with values ranging from 0 to 1) before they can be used to assign probabilities to events in a probability tree. 7 An estimate of a test's SE depends on the proportion of individuals who obtained a positive test result in that particular study (i.e., the latter corresponding to the value of SE expected by chance alone). Also, an estimate of a test's SP depends on the proportion of individuals who obtained a negative test result in that particular study (i.e., the latter corresponding to the value of SP expected by chance alone).…”