A study of computational compliance checking methods for healthcare accessibility

Abstract

Healthcare design is inherently complex, and the scope of accessibility requirements continues to grow as building programs expand in scale and functional diversity. Conventional compliance checking methods relying on manual inspection of two-dimensional drawings are labor intensive, time-consuming, and error-prone to the spatial complexity of facilities governed by multi-criteria regulatory rules such as the Americans with Disabilities Act (ADA). This thesis explores a semi-automated computational framework integrating Building Information Modeling (BIM) with algorithmic-parametric modeling to evaluate ADA compliance directly within the design environment. The framework operates through five sequential stages: parametric BIM preparation, ADA rule mapping, object filtering, attribute extraction, and automated compliance reporting. Implementation employed Autodesk Revit, Rhino.Inside.Revit (RIR), Grasshopper, and Python scripting. A restroom case study tested the framework against restroom accessibility, evaluating door widths, fixture heights, grab bar positions, and wheelchair turning radius against 2010 ADA standards. Results showed the framework's ability to accurately distinguish compliant from non-compliant elements and to generate Pass/Fail reports in BIM. The method has potential to reduce manual review effort and enable continuous compliance monitoring during iterative design development. It also supports extension to broader facility types and multiple building standards, with future research scope including full-facility deployment, and visualization. In conclusion, the proposed framework offers a scalable, parametric approach to accessibility compliance checking that embeds regulatory evaluation within the design process, supporting the creation of more accessible built environments from the early stages of design.