clinical-qikit 0.1.2

SPC charts and QI tools for healthcare

qikit

SPC charts and quality improvement tools for healthcare, in Python.

One function. One result object. One .plot() call.

Install

pip install clinical-qikit

Quickstart

from qikit import qic

result = qic(y=values, chart="i")
result.plot()   # returns a Plotly figure

qic() mirrors R's qicharts2, the package most healthcare QI practitioners already know — same chart types, same run-chart signal detection, same mental model, now in Python.

Chart types

All chart types are computed by the same qic() entry point via the chart= argument:

chart=	Chart	Use for
run	Run chart	Any sequential data, median center line
i	Individuals (I) chart	Continuous data, one observation per subgroup
mr	Moving range	Variation between consecutive observations
xbar	X-bar chart	Continuous data with subgroups (paired with s)
s	S chart	Subgroup standard deviation
t	Time-between-events chart	Time or count between rare events
p	P chart	Proportion (percent) defective, unequal subgroup sizes
pp	P′ (Laney) chart	Proportion data with overdispersion
c	C chart	Count of defects, constant opportunity
u	U chart	Rate of defects, unequal opportunity
up	U′ (Laney) chart	Rate data with overdispersion
g	G chart	Number of opportunities between rare events

qic(..., funnel=True) renders a funnel plot instead, for cross-sectional comparison across p/pp/u/up charts sorted by denominator.

Beyond qic(), the package also provides:

• paretochart(x, data=...) — Pareto chart of categorical frequencies.
• bchart(...) — Bernoulli CUSUM chart for early detection of shifts in binary (pass/fail) data.
• design(factors, ...) / analyze(design_obj, response, ...) — full-factorial design of experiments (DOE) and effect analysis.

Excel add-in

A Microsoft Excel task-pane add-in built on the same charting engine (ported to TypeScript) lives in excel-addin/ — see its README for dev-harness and sideload instructions, and docs/excel-addin-roadmap.md for the roadmap.

Web app

app.py is a Streamlit front end over the same engine:

pip install -e .[app]
streamlit run app.py

Development

uv sync --extra dev
uv run ruff check .        # lint (CI-enforced)
uv run pytest tests/       # 176 tests incl. cross-language fixture conformance

The Python engine is authoritative; the TypeScript port in excel-addin/packages/engine conforms to it via the shared JSON fixtures in fixtures/. After intentional engine changes, regenerate the fixture snapshots with uv run python scripts/update_snapshots.py.

References

1. Montgomery DC. Introduction to Statistical Quality Control, 8th ed. Wiley, 2019.
2. Provost LP, Murray SK. The Health Care Data Guide, 2nd ed. Jossey-Bass, 2022.

License

MIT