Explorys was a spin-off of Cleveland Clinic and Case Western Reserve University that sought to apply big data via hadoop to improve health care by identifying cohorts of interest, predicting medical outcomes, and more.
Having spent 7 years in Enterprise at Progressive Insurance I wanted to get back into startup mode and live fast and take risks, and so I ultimately was persuaded to join.
Key Results
Delivered new admin dashboard supporting 10+ healthcare organizations
In this role I worked closely with two of several engineering directors and a team of junior recent graduate students on full-stack teams to build web frontends, web services, and big-data jobs to aid doctors and other users in obtaining knowledge and ultimately, better health outcomes for their patients.
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Project: New Admin Dashboard
New Admin Dashboard - Architected and implemented green field admin dashboard, worked with junior devs and leadership to bring about in the requested stack: Bootstrap / JQuery / Ruby / Java / MySQL / LDAP. Users used Admin Dashboard to administer Organization, Role, and other management aspects of the Explorys EPM Suite.
Dependency Injection Framework - To enable high testability, all components required dependencies to be passed in, and so eliminating factory boilerplate without adopting a complex DI system was desirable. Wrote and shared a simple runtime-reflection based DI framework with multiple projects / teams
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Key Results
Delivered new admin dashboard supporting 10+ healthcare organizations
Reduced user management operations time by 65% with streamlined UI
Created DI framework that enabled loose coupling needed for fast pivots
Temporal Sequencing - Architected, implemented and tested an enhancement to our proprietary Explorys MDL (measure definition language), which gave authors who use that language the ability to express dynamic temporal conditions as part of the predicate calculus that constitutes the measure being defined in a given MDL instance.
The solution runs in Hadoop as a mapper, where the MDL is parsed and a corresponding object graph is constructed, and then control is passed to the encapsulating object of that graph, resulting in a determination about the level of adherence of the given patient to the measure defined by the MDL which is then emitted for further processing.
The challenge here was authoring the solution without knowing the history or complexity of the existing system. The challenge was overcome by applying SOLID principles and TDD principles to express assumptions about the existing external system as interfaces, getting the solution to work in a test sandbox as a standalone application, and then once that was done, writing adapters between the actual system and the interfaces that were formerly mocked out for testing. The team which owned the system seemed impressed by and curious about the solution and the new patterns / tests involved.
By taking what had been considered a relatively tough problem, and, as an engineer with no history in the measure engine, applying an approach that allowed a fully tested solution to ultimately be plugged into the larger system very cleanly, as an implementation of a clear set of interfaces along the border of that system, I exposed the team to new patterns and solution design approaches that I hoped the team might take forward and build on as the system continued to evolve.
Example Use Case: Doctor wants measure of % of his/her patients having Hospitalization with outcome class X, where either 1 week later, Rehospitalization occurs or within 2 weeks, unexpected Office Appointment occurs. Doctor expresses using natural language oriented temporal sequencing expressions within model definition language.
