15657
The Developmental Clinical Instrument (DCI): Structured Data Collection for the Autism-Focused Clinical Exam
Yet, despite high fidelity use of the ADOS and ADI-R, case-ascertained ASD samples continue to possess heterogeneity due to a myriad of physical, medical and psychological conditions inherent to the disorder. Such heterogeneity varies within and across study populations and can influence effectiveness research, outcomes research, and cost-effectiveness research.
The clinical examination provides an opportunity to recognize such phenotypic variability. But clinical exam data typically resides in unstructured free text forms. This prevents systematic collection of comparable data and as a result, a wealth of information reflecting physical, medical and psychological conditions within and across groups of patients remains underutilized.
We developed the Developmental Clinical Instrument (DCI), which standardizes the documentation of an autism-focused clinical examination. The DCI does not change a physician’s behaviors; it simply structures data collection. Importantly, the DCI contains embedded quantitative data elements that can facilitate entry into an online data capture system. Use of the DCI and its embedded data elements can reduce the time and cost of data collection, improve data quality, facilitate data sharing and improve opportunities for meta-analysis and comparison of data across different sites and clinical populations. The DCI also has a customizable section for additional study-specific data elements.
Objectives: To implement the DCI at an autism research center as a means of standardizing the collection of embedded data elements and to facilitate the rapid generation of cross sectional data for specific data elements in our study population.
Methods: The DCI was used to structure documentation of study physicians’ clinical examination at the Seaver Autism Center for Research and Treatment. The clinical examination is one part of the IRB approved assessment protocol that also includes the ADOS, ADI-R, and other cognitive and adaptive measures. The data elements contained in each DCI of 20 consecutive research subjects were entered into a customized data collection system that generates real time analyses. Reports were rapidly generated to reflect cross sectional data.
Results: Clinician buy-in and compliance with the DCI was high. In this population of research subjects, cross sectional data reflecting the distribution of each data element contained in the medical history of the DCI was generated. A chart reflecting this data is displayed in figure 1.
Conclusions: The DCI facilitates structured data collection for the autism-focused clinical examination. When used with a customized data capture system, the DCI can facilitate the generation of reports that display distributions of specific data elements within a population. Furthermore, structured data collection of physical, medical and psychological data can lay the foundation for multivariate or case control analyses to support hypothesis generation. Finally, use of the DCI in non-research clinical settings can lay the foundation for epidemiologic surveillance of data elements in populations not typically exposed to research.