Abstract: Designing effective Clinical Decision Support (CDS) tools in an Electronic Health Record (EHR) can prove challenging, due to complex real-world scenarios and newly-discovered requirements. As such, deploying new CDS EHR tools shares much in common with new product development, where agile principles and practices consistently prove more effective than traditional project management. Typical agile principles and practices can thus prove helpful on CDS projects, including time-boxed sprints and lightweight requirements gathering with User Stories and acceptance criteria. Modeling CDS behavior removes ambiguity and promotes shared understanding of desired behavior, but risks analysis paralysis: an Agile Modeling approach can foster effective rapid-cycle CDS design and optimization. The agile practice of automated testing for test-driven design and regression testing can be applied to CDS development in EHRs using open-source tools. Ongoing monitoring of CDS behavior once released to production can identify anomalies and prompt rapid-cycle redesign to further enhance CDS effectiveness.
Using agile principles and practices, in calendar year 2015 our institution developed 58 EHR-based specialty patient registries, with 111 new CDS and data collection tools, supporting 134 clinical process and outcome clinical quality measures, and enrolling over 16,000 patients. Agile modeling proved key to joint understanding and communication during initial development--and to iteratively evolving CDS tools for optimal use in active clinical settings. The subset of UML and non-UML models found most consistently useful in designing, building, and iteratively evolving EHR-based Clinical Decision Support included User Stories, Domain Models, Use Case Diagrams, Decision Trees, Graphical User Interface Storyboards, Use Case text descriptions, and Solution Class Diagrams.
Lessons Learned from Your Experience: - Clinical Decision Support (CDS) tools built within Electronic Health Records (EHRs) combine internal complexity with deployment into the complex healthcare delivery environment. Commonly this complexity can yield initial unexpected or unwanted CDS tool behavior when deploying in active real-world clinical practice. Thus requirements evolution is to be expected and embraced, to help ensure new EHR tools work in clinicians’ actual workflows.
- Agile development with 2-week time-boxed iterations can be highly effective in developing and evolving CDS tools that met clinicians' needs and expectations.
- An “agile modeling” approach helps foster shared understanding of CDS requirements and design, removing ambiguities and promoting a shared mental model. A working set of structural and behavioral models promotes rapid-cycle evolution of EHR tool design in response to clinical feedback. A subset of diagram types proved most useful for constructing EHR-based specialty registries and associated CDS tools.
- An open source automated testing tool (FitNesse) can be used to specify desired CDS tool design as a form of test-driven development, and used for regression testing following release to production.
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