One template, fifty reports: parameterised Quarto in practice

How we turn a single Quarto document into a batch of per-site or per-client reports with one line of R.

A pattern that pays for itself on almost every reporting project: write one Quarto document, declare its inputs as parameters, and render it once per site, clinic, region or client.

Declare the parameters

In the report’s YAML header:

---
title: "Monthly Quality Report — `r params$site`"
format: docx
params:
  site: "Site A"
  month: "2026-06"
---

Inside the document, params$site and params$month drive the filtering:

monthly <- readr::read_csv("data/measurements.csv") |>
  dplyr::filter(site == params$site,
                format(date, "%Y-%m") == params$month)

Render the batch

One small driver script produces the whole set:

sites <- c("Site A", "Site B", "Site C")

for (s in sites) {
  quarto::quarto_render(
    "monthly_report.qmd",
    execute_params = list(site = s, month = "2026-06"),
    output_file = paste0("report_", gsub(" ", "_", s), "_2026-06.docx")
  )
}

Fifty sites is the same loop with a longer vector.

Why this beats copy-paste

library(ggplot2)

d <- data.frame(
  n_reports = rep(1:50, 2),
  approach  = rep(c("Manual copy-paste", "Parameterised Quarto"), each = 50)
)
d$hours <- ifelse(d$approach == "Manual copy-paste",
                  d$n_reports * 1.5,          # ~1.5 h per hand-edited report
                  6 + d$n_reports * 0.02)     # one-time template + render time

ggplot(d, aes(n_reports, hours, colour = approach)) +
  geom_line(linewidth = 1.2) +
  scale_colour_manual(values = c("#1b2a4a", "#17a2b8")) +
  labs(
    title = "Cumulative effort: hand-edited vs. parameterised reports",
    subtitle = "Illustrative estimates — the template costs more up front, then almost nothing",
    x = "Number of reports", y = "Hours of analyst time", colour = NULL
  ) +
  theme_minimal() +
  theme(legend.position = "bottom",
        plot.title = element_text(face = "bold", colour = "#1b2a4a"))

Figure 1

Beyond the hours, the real win is consistency: every report is generated from the same logic, so a fix or improvement lands in all fifty at the next render — and none of them can silently drift out of sync with the data.