Development of a Nationally Agreed Core Clinical Dataset for Childhood Onset Uveitis

Abstract

BackgroundChildhood onset uveitis comprises a group of rare inflammatory disorders characterized by clinical heterogeneity, chronicity, and uncertainties around long term outcomes. Standardized, detailed datasets with harmonized clinical definitions and terminology are needed to enable the clinical research necessary to stratify disease phenotype and interrogate the putative determinants of health outcomes. We aimed to develop a core routine clinical collection dataset for clinicians managing children with uveitis, suitable for multicenter and national clinical and experimental research initiatives.MethodsDevelopment of the dataset was undertaken in three phases: phase 1, a rapid review of published datasets used in clinical research studies; phase 2, a scoping review of disease or drug registries, national cohort studies and core outcome sets; and phase 3, a survey of members of a multicenter clinical network of specialists. Phases 1 and 2 provided candidates for a long list of variables for the dataset. In Phase 3, members of the UK's national network of stakeholder clinicians who manage childhood uveitis (the Pediatric Ocular Inflammation Group) were invited to select from this long-list their essential items for the core clinical dataset, to identify any omissions, and to support or revise the clinical definitions. Variables which met a threshold of at least 95% agreement were selected for inclusion in the core clinical dataset.ResultsThe reviews identified 42 relevant studies, and 9 disease or drug registries. In total, 138 discrete items were identified as candidates for the long-list. Of the 41 specialists invited to take part in the survey, 31 responded (response rate 78%). The survey resulted in inclusion of 89 data items within the final core dataset: 81 items to be collected at the first visit, and 64 items at follow up visits.DiscussionWe report development of a novel consensus core clinical dataset for the routine collection of clinical data for children diagnosed with non-infectious uveitis. The development of the dataset will provide a standardized approach to data capture able to support observational clinical studies embedded within routine clinical care and electronic patient record capture. It will be validated through a national prospective cohort study, the Uveitis in childhood prospective national cohort study (UNICORNS).

Development of the Advised Protocol for OCT Study Terminology and Elements Anterior Segment OCT extension reporting guidelines: APOSTEL-AS

“…17 NGT consensus exercises can be time consuming, particularly for large groups, but this work will benefit from facilitation undertaken by subject matter experts with experience in supporting consensus work. 18,19 The selection of the Delphi method for the development of the checklist enables this activity to be undertaken by a large, geographically and scientifically diverse group with different degrees and spheres of experience and expertise. A recently published EQUATOR (Enhancing the QUality and Transparency Of health Research) guideline for reporting consensus-based methods in biomedical research and clinical practice (the ACcurate COnsensus Reporting Document, or ACCORD) will be used to report study findings.…”

Standardising the structure of routinely collected data for childhood ocular inflammation: a SNOMED-CT mapping project

“…POIG is a multi-disciplinary group formed of clinicians who manage children with complex inflammatory disorders, with a central aim of delivering the evidence base needed to support the care of these children, and supporting the translation of that evidence base into changes in policy and practice. The group developed, through Delphi consensus, as reported elsewhere,(15) a consensus dataset for the routine collection of data for children diagnosed with uveitis. This dataset includes common data items (CDEs) on demographic details, pathways to diagnosis, ocular disease phenotype, activity level and severity scores, the presence, type and severity of co-existent systemic disease, clinical interventions, and laboratory and imaging findings.…”

“…(18) To enhance the interoperability of uveitis data, we created a SNOMED CT coded dataset derived from a core clinical dataset, developed in collaboration with the United Kingdom's Paediatric Ocular Inflammation Group (POIG). (15,19) We present an overview of the dataset and its development process.…”

“…(14) Several groups have developed approaches and resources with the aim of defining standardized datasets for the systematic collection of uveitis-related information. (15–17) However, while these represent important advances, more is needed to support interoperability, specifically, the common data elements within the developed datasets must be supported by coding derived from a clearly structured terminology standard.…”