// the find
DrGo/sim
generates random admin data using a template
A Go tool for generating synthetic healthcare utilization data — patient records with hospitalizations, clinic visits, prescriptions, and geolocation codes — driven by a JSON config file. Aimed squarely at epidemiologists and health informaticists who need plausible test datasets without touching real patient data.
The frequency-distribution sampler in `rng/` is a genuinely useful piece: weighted random selection over probability distributions, with benchmarks included. The config-driven approach means non-programmers can adjust disease prevalence and population parameters without touching Go. The bundled demo (`identify-conditions-demo-sim/`) ships actual input CSVs and SAS/Python analysis scripts, so you can see the full pipeline end to end. Postal-code geolocation via weighted CSV lookup is a practical design — easy to swap in any country's codes.
Last commit was April 2020 and stars are at zero — this is effectively abandoned research code, not a maintained tool. The README is three paragraphs and barely explains the config schema; chronic disease and recurrence fields are documented as 'not implemented', so the model is incomplete. Compiled binaries (`sim`, `sim.exe`, `simStudy`) are checked into the repo, which is a red flag for any security-conscious team. The `stata/` subdirectory vendors an entire R package (`foreign`) as a tarball, suggesting scope creep that was never cleaned up.