RESUMO
Type 1 diabetes is the result of autoimmune-mediated destruction and inflammation of the insulin-producing ß-cells of the pancreas. The excess morbidity and mortality from its complications coupled with its increasing incidence emphasize the importance to better understand the etiology of this condition. It has a strong genetic component, but a genetic predisposition is not the sole contributor to disease development as only 30% to 50% of identical twins both develop the disease. In addition, there are multiple lines of evidence to support that environmental factors contribute to the pathogenesis of type 1 diabetes. Environmental risk factors that have been proposed include infections, dietary factors, air pollution, vaccines, location of residence, childhood obesity, family environment and stress. Researchers have conducted many observational studies to identify and characterize these potential environmental factors, but findings have been inconsistent or inconclusive. Many studies have had inherent methodological issues in recruitment, participation, defining cases and exposures, and/or data analysis which may limit the interpretability of findings. Identifying and addressing these limitations may allow for greatly needed advances in our understanding of type 1 diabetes. As such, the purpose of this article is to review and discuss the limitations of observational studies that aim to determine environmental risk factors for type 1 diabetes and propose recommendations to overcome them.
RESUMO
BACKGROUND: Clinical Decision Support Systems (CDSS) can make patient care more efficient, cost-effective, and guideline-concordant. Many are created by clinicians who understand the challenges, but may publish concepts before considering subtle but important design details. Human-Centred Design (HCD) approaches provide necessary methods ensuring solid CDSS design. This article highlights HCD approaches in a pulmonary embolism CDSS case study context. METHODS: This pulmonary embolism CDSS results from collaborative work between computer science, psychology, and medicine. HCD methods used include: evaluations of pre-clinical prototype recordings, iterative usability expert reviews with software refinement, formative usability testing, and (separately-published) clinical pilot study. RESULTS: HCD methods were instrumental in iteratively creating an easy to use and functionally-sound CDSS. Retrospective evaluations revealed that participants spent considerable time on items that were out of order from natural cognitive diagnostic workflows. Features missing between original and study version were noted, confusing interface elements reworked, and currently-active decision tree branches were visually emphasized. From iterative usability reviews, positioning of information within the decision tree was radically reworked, information separated into levels of support for different user groups, and supportive versus directive language issues addressed. Formative studies identified issues such as interface adjustments and hospital workflow integration. CONCLUSIONS: Human-centred design approaches provide methods for integrating the skills and knowledge of many disciplines, illustrated by example in this pulmonary embolism CDSS creation. Advantages of leveraging many design guidelines as well as revealing new design considerations that would otherwise have remained hidden are described. The findings reported here support future CDSS design through HCD inclusion.
