SHF: Small: Collaborative Research: Designing a Patient-Oriented Prescription Language: An Executable Medical Algorithm for Gestational Diabetes Mellitus

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Preventable errors in healthcare are a leading cause of patient injury and death. Despite considerable effort and the expenditure of billions of dollars, computerization has yet to improve the efficacy or safety of healthcare. To this problem, the PIs bring a novel insight: a prescription is a program. That is, they hypothesize that prescription writing is a long lost sibling of software engineering, using many computer programming constructs but without the benefit of the extensive conceptual framework provided by Computer Science. This project will test this hypothesis by exploiting software engineering and programming languages know?how to create a highly?intuitive, domain specific language for building and executing prescriptions. The PIs will then build and validate a "patient oriented prescription" to manage the care of patients with Gestational Diabetes Mellitus (GDM), a disease affecting 600,000 women annually.Limitations of current GDM management include low patient adherence, modest efficacy of interventions, time?burden for clinicians, and cost. Using extensive archives of rich data from real patients, including diet, activity, glucose readings, and insulin use, the PIs will perform pure computer-based simulations that will help them determine how their POP-GDM program will respond to real-world data. They will also perform simulations with real clinicians, actor patients, and simulated inputs from smartphones, glucometers, and accelerometers in our state of the art medical simulation facility. The PIs expect this work to generate multiple new insights regarding the building and maintenance of multi-stage programs, the development of new kinds of analyses of programs, and the discovery of new general methods for developing high-reliability software that facilitates collaboration between machines and humans.