The question of a possible presence of attention deficit/hyperactivity disorder (ADHD) is raised with increasing frequency in pediatric practice. There are guidelines and expert recommendations for diagnostic approaches. But there are no instruments available to evaluate the structural, process and outcome quality. In this pilot study, a set of quality indicators on the treatment quality of ADHD was analyzed in terms of their feasibility in tertiary referral centers.A set of 39 quality indicators (QI) on ADHD developed in advance in a multistage procedure was assessed at 9 tertiary referral centers, with a focus on process verifiability and feasibility. QI values were calculated as ratios for individual centers as well as across centers, followed by an explorative analysis to assess feasibility under due consideration of possible influencing factors.QI assessment is possible but highly complex and expensive in practice. Calculated QI values showed a high degree of heterogeneity between facilities as well as between institutions, which was mainly due to a lack of standardization in the documentation of required data.Basically, it is possible to assess the quality of ADHD treatment via QIs. The approach described here in assessing QIs may be also applied to other types of developmental disorders.

Quality issue Quality assessment is challenging in children with developmental disorders. Previously, a set of quality indicators (QIs) was developed and analyzed in terms of feasibility of use with patients with attention-deficit/hyperactivity disorder (ADHD). QI assessment turned out to be possible but highly complex. Thus, we compared different technologies for automated extraction of data for assessment of QIs. Choice of solution Four automated extraction technologies (regular expressions, Apache Solr, Apache Mahout, Apache OpenNLP) were compared with respect to their properties regarding the complexity of implementing the QI, the complexity of implementing a check module, the reliability and quality of results, the complexity of preparation of interdisciplinary medical reports, and the complexity of deployment and installation. Implementation Twenty medical reports from different institutions were reviewed for compliance with three QIs by these technologies and compared with expert opinions. Evaluation Among the four technologies, Apache Solr had the best overall performance. For manual extraction of the three QIs, at least 77 s were necessary per medical report, whereas the prototype evaluated and extracted the QIs automatically in 8 s on average. Unexpectedly, different assessments of the degree of compliance by the experts turned out to be one of the stumbling blocks. An in-depth evaluation compared results on a semantic level. Lessons learned It is possible to extract QIs by post-processing automated technologies. This approach can also be applied to other developmental disorders. However, a more uniform documentation throughout institutions involved will be necessary in order to implement this method in daily practice.

This is the first study covering the aspect of quality measurement in children with developmental disorders, especially ADHD. For the next step a pilot evaluation is necessary to complete the evaluation of the quality indicators.