',
'Public-data demonstration report: ',
'This is not an official Dorset HealthCare report. It uses public aggregate data only ',
'and requires human review and local owner confirmation before operational use.',
'
',
body_html,
''
)
}
verify_intro_short <- function(demo_link_html = "", trace_sentence = NULL) {
trace <- trace_sentence %||%
"Open the linked demo CSV or audit file, locate the RDY row, and confirm the value matches the published source."
paste0(
'
', trace, '
',
'
',
if (nzchar(demo_link_html)) demo_link_html else "",
'
',
bullet_list(bullets),
""
)
}
standard_human_checks <- function(extra = list()) {
base <- list(
list(
q = "Is this the same definition used locally?",
expl = "Public datasets may use national definitions. Local dashboards may use different filters, denominators or reporting dates."
),
list(
q = "Is this still the latest position?",
expl = "Public data may be delayed. Local operational data may have moved on since the reporting period shown."
),
list(
q = "Is the figure affected by data quality, suppression, coding or service model?",
expl = "A public figure can be affected by small numbers, exclusions, coding rules or how services are configured."
),
list(
q = "Who owns the local narrative?",
expl = "The accountable service, finance, workforce, quality or BI owner should confirm the explanation before use."
),
list(
q = "Is this suitable for board/service reporting, or only a prompt for further review?",
expl = "These briefs are first drafts — confirm whether the figure is ready for formal reporting or needs more local work."
)
)
c(base, extra)
}
NOF_METRIC_SPEC_URL <- "https://www.england.nhs.uk/long-read/nhs-oversight-framework-csv-metadata-file/"
NOF_SPEC_ACCESSED <- "2026-06-21"
NOF_SPEC_META <- list(
source_url = NOF_METRIC_SPEC_URL,
source_title = "NHS Oversight Framework technical metric specification",
source_publication_date = "Q4 2025/26 league tables",
accessed_date = NOF_SPEC_ACCESSED,
confidence = "confirmed"
)
TT_STANDARDS_URL <- "https://digital.nhs.uk/data-and-information/publications/statistical/mental-health-services/monthly-statistics-on-adult-early-intervention-in-psychosis-and-nhs-talking-therapies-for-anxiety-and-depression"
TT_STANDARDS_META <- list(
source_url = TT_STANDARDS_URL,
source_title = "NHS Talking Therapies monthly statistics — access standards",
source_publication_date = "April 2026",
accessed_date = "2026-06-21",
confidence = "confirmed"
)
CHS_WAITING_URL <- "https://www.england.nhs.uk/statistics/statistical-work-areas/community-health-services-waiting-lists/"
CHS_WAITING_META <- list(
source_url = CHS_WAITING_URL,
source_title = "NHS England community health services waiting lists",
source_publication_date = "2025/26 planning guidance",
accessed_date = "2026-06-21",
confidence = "confirmed"
)
NOF_METRIC_SPEC <- list(
OF0005 = list(
polarity = "lower_better",
standard = "Lower is better; 0% long waits is the ideal direction.",
validation_status = "Local owner confirmation needed",
scoring_note = "Long-wait community metric — confirm cohort and denominator."
),
OF0079 = list(
polarity = "unknown",
standard = "0% or surplus is best category per NHS England scoring; confirm sign convention locally.",
validation_status = "Finance sign-off required",
scoring_note = "Planned surplus/deficit excluding deficit support funding, divided by turnover/allocation."
),
OF0081 = list(
polarity = "unknown",
standard = "On-plan or better variance is favourable per NHS England scoring; confirm locally.",
validation_status = "Finance sign-off required",
scoring_note = "YTD actual less planned surplus/deficit, divided by turnover/allocation."
),
OF0082 = list(
polarity = "lower_better",
standard = "Lower sickness absence is generally preferable.",
validation_status = "Local owner confirmation needed"
),
OF0041 = list(
polarity = "higher_better",
standard = "Higher year-on-year CYP access change may indicate growth; confirm cohort.",
validation_status = "Local owner confirmation needed"
),
OF0061 = list(
polarity = "higher_better",
standard = "Higher staff survey sub-score is generally preferable.",
validation_status = "Local owner confirmation needed"
),
OF0084 = list(
polarity = "higher_better",
standard = "Higher engagement sub-score is generally preferable.",
validation_status = "Local owner confirmation needed"
),
OF0057 = list(
polarity = "higher_better",
standard = "≥70% avoids lowest scoring band (score 4.00); higher is better.",
validation_status = "Local owner confirmation needed",
scoring_note = "UCR 2-hour performance — quarterly metric."
),
OF0016 = list(
polarity = "higher_better",
standard = "Higher is better — MH crisis face-to-face within 24 hours.",
validation_status = "Local owner confirmation needed"
),
OF0086 = list(
polarity = "lower_better",
standard = "100 ≈ expected cost; lower is better per NHS England specification.",
validation_status = "Finance sign-off required"
),
OF0063 = list(
polarity = "lower_better",
standard = "Lower is better — adult MH inpatients with length of stay over 60 days.",
validation_status = "Local owner confirmation needed",
priority = TRUE
)
)
nof_judgement_text <- function(metric_id, row, spec, trend_obj = NULL) {
val_n <- to_num(row$Value)
med_n <- to_num(row$Median_value)
rank_n <- to_num(row$Rank)
pol <- spec$polarity %||% "unknown"
parts <- character()
if (isTRUE(spec$priority %||% FALSE)) {
parts <- c(parts, "Priority attention — large gap vs peer median.")
}
if (pol == "higher_better" && !is.na(val_n) && !is.na(med_n)) {
if (val_n < med_n) parts <- c(parts, "Below peer median.")
if (metric_id == "OF0057" && !is.na(val_n) && val_n >= 70) {
parts <- c(parts, "Above 70% scoring threshold but below peer median.")
}
}
if (pol == "lower_better" && !is.na(val_n) && !is.na(med_n)) {
if (val_n > med_n) parts <- c(parts, "Above peer median — review locally.")
}
if (!is.null(trend_obj) && isTRUE(trend_obj$available)) {
chg <- trend_obj$absolute_change
if (!is.na(chg)) {
dir <- if (chg > 0) "rising" else if (chg < 0) "falling" else "stable"
if (pol == "higher_better" && dir == "falling") parts <- c(parts, "Short trend is falling.")
if (pol == "lower_better" && dir == "rising") parts <- c(parts, "Short trend is rising.")
}
}
if (metric_id %in% c("OF0079", "OF0081")) {
parts <- c(parts, "Published spec suggests surplus/on-plan is favourable — finance owner should confirm plan version.")
}
if (length(parts) == 0) "Local review needed — confirm definition and local position."
else paste(unique(parts), collapse = " ")
}
nof_trend_direction_label <- function(trend_obj, polarity) {
if (is.null(trend_obj) || !isTRUE(trend_obj$available) || trend_obj$n_periods < 2) {
return(list(label = "Not available", css = "na"))
}
chg <- trend_obj$absolute_change
pct <- trend_obj$percent_change
stable <- (!is.na(pct) && abs(pct) <= 2) ||
(is.na(pct) && abs(chg) < max(1, abs(trend_obj$previous_value) * 0.02))
if (stable) return(list(label = "Stable", css = "stable"))
if (is.na(chg) || chg == 0) return(list(label = "Unclear", css = "unclear"))
if (polarity == "higher_better") {
label <- if (chg > 0) "Rising" else "Falling"
} else if (polarity == "lower_better") {
label <- if (chg < 0) "Falling" else "Rising"
} else {
label <- if (chg > 0) "Rising" else "Falling"
}
list(label = label, css = trend_badge_css(label))
}
nof_agent_flag_badge <- function(flag_label, flag_class) {
paste0(
'',
esc(flag_label), ''
)
}
nof_format_value_compare <- function(row) {
paste0(
"RDY value ", trimws(as.character(row$Value)),
" vs peer median ", trimws(as.character(row$Median_value)),
" (published rank ", trimws(as.character(row$Rank)), ")"
)
}
nof_how_to_read_table <- function() {
paste0(
'
How to read this table
',
'
',
'
Each row is one NHS Oversight Framework metric for Dorset HealthCare (RDY) in the published peer group.
',
'
Value is RDY’s published metric value from the NHS England file — not recalculated by this demo.
',
'
Median_value is the published peer median for the same metric, quarter and reporting date.
',
'
Rank is the published NHS England rank (1 = best in peer group per NOF methodology).
',
'
Whether higher or lower is better varies by metric — confirm polarity against the ',
'official NHS England NOF technical metric specification ',
'before any operational use. This specification was not bulk-downloaded in the public-data pipeline.
',
'
This table is part of a first-draft agent brief for demonstration — not an official Dorset HealthCare performance report.
',
'
'
)
}
nof_commentary_lookup <- function() {
list(
OF0005 = list(
flag = "Potential strength", flag_class = "strength",
plain_meaning = "Percentage of patients waiting over 52 weeks for community services.",
interpret = function(row) {
paste0(
"This is a long-wait metric where lower values are generally preferable. ",
nof_format_value_compare(row), ". ",
"RDY reports 0.00% compared with a peer median of 0.19%. ",
"The agent would note this as a potential strength relative to peers, ",
"but the denominator, local waiting-list definition and data quality must be checked before any operational use."
)
},
human_check = "Confirm cohort, denominator, reporting period (Mar-26) and whether local community waiting lists align with the national definition."
),
OF0079 = list(
flag = "Definition check required", flag_class = "definition",
plain_meaning = "Planned surplus/deficit for the financial year.",
interpret = function(row) {
paste0(
"This finance metric relates to the Trust’s planned financial position. ",
nof_format_value_compare(row), ". ",
"Positive and negative values have specific meanings in NHS finance reporting — ",
"the agent does not assume surplus/deficit interpretation without the official metric definition. ",
"Flag for finance-owner confirmation."
)
},
human_check = "Finance team to confirm sign convention, plan version (2025/26 plan) and whether this matches internal board reporting."
),
OF0081 = list(
flag = "Definition check required", flag_class = "definition",
plain_meaning = "Variance year-to-date to financial plan.",
interpret = function(row) {
paste0(
"This shows how far year-to-date performance varies from the approved plan. ",
nof_format_value_compare(row), ". ",
"The agent does not treat a higher or lower variance as automatically favourable without checking NHS England’s metric definition and local finance narrative."
)
},
human_check = "Finance owner to confirm Month 12 2025/26 YTD basis, plan assumptions and whether amendments have been published."
),
OF0082 = list(
flag = "Review locally", flag_class = "review",
plain_meaning = "Sickness absence rate across the workforce.",
interpret = function(row) {
paste0(
"Workforce sickness absence — lower values are usually preferable. ",
nof_format_value_compare(row), ". ",
"RDY is below the peer median (5.47 vs 6.22), which may indicate relatively lower absence, ",
"but reporting period (Q3 2025/26) and local workforce context should be confirmed."
)
},
human_check = "Workforce/HR lead to confirm reporting period, inclusion rules and whether local sickness dashboards use the same definition."
),
OF0041 = list(
flag = "Watch / clarify", flag_class = "watch",
plain_meaning = "Annual change in the number of children and young people accessing NHS-funded mental health services.",
interpret = function(row) {
paste0(
"This measures year-on-year change in CYP mental health access (Apr 25–Mar 26 vs prior year). ",
nof_format_value_compare(row), ". ",
"A higher figure may indicate growth in access relative to peers, but the agent would not treat this as demand or performance without confirming cohort, comparison year and service configuration."
)
},
human_check = "CYP mental health lead to confirm numerator, ICB/resident vs provider scope and whether local access data supports the direction of change."
),
OF0061 = list(
flag = "Review locally", flag_class = "review",
plain_meaning = "NHS Staff Survey sub-score on raising concerns.",
interpret = function(row) {
paste0(
"Staff survey theme — higher scores usually indicate more positive staff experience on this theme. ",
nof_format_value_compare(row), ". ",
"RDY is slightly above the peer median. The agent would not treat small differences as meaningful without checking survey methodology and response rates."
)
},
human_check = "Workforce/OD lead to confirm 2025 Staff Survey methodology, response rate and whether local culture survey data aligns."
),
OF0084 = list(
flag = "Review locally", flag_class = "review",
plain_meaning = "NHS Staff Survey engagement theme sub-score.",
interpret = function(row) {
paste0(
"Staff engagement theme from the NHS Staff Survey — higher is usually preferable. ",
nof_format_value_compare(row), ". ",
"RDY is marginally above the peer median. The agent would flag for local review rather than over-interpreting a small gap."
)
},
human_check = "Confirm 2025 survey cohort, theme definition and whether the difference is material in local workforce planning."
),
OF0057 = list(
flag = "Review locally", flag_class = "review",
plain_meaning = "Urgent Community Response 2-hour performance.",
interpret = function(row) {
paste0(
"Proportion of urgent community response contacts meeting the 2-hour standard — higher is generally preferable for access performance. ",
nof_format_value_compare(row), ". ",
"RDY is below the peer median (79.28 vs 87.18). ",
"The agent would flag this for local review and ask whether the latest local UCR position, referral volumes and service model explain the gap — not assume a single cause."
)
},
human_check = "Community urgent care/service owner to confirm UCR definition, Q4 2025/26 reporting period and local operational position."
),
OF0016 = list(
flag = "Review locally", flag_class = "review",
plain_meaning = "Percentage of patients in mental health crisis receiving face-to-face contact within 24 hours.",
interpret = function(row) {
paste0(
"Mental health crisis access metric — higher is generally preferable. ",
nof_format_value_compare(row), ". ",
"RDY is below the peer median (65.54 vs 71.97). ",
"The agent would flag this as an access and patient-safety themed metric needing local narrative and definition check."
)
},
human_check = "Crisis pathway owner to confirm crisis cohort, face-to-face definition, Q4 2025/26 period and alignment with local crisis standards."
),
OF0086 = list(
flag = "Review locally", flag_class = "review",
plain_meaning = "Relative difference in costs (National Cost Collection Index, adjusted for Market Forces Factor).",
interpret = function(row) {
paste0(
"Relative difference in costs compares provider actual cost with expected cost. ",
"A value of 100 is approximately expected cost; values above 100 indicate costs above expected; ",
"values below 100 indicate costs below expected. NHS England describes lower as better for this metric. ",
nof_format_value_compare(row), ". ",
"RDY’s published value is above both 100 and the peer median, so the agent would flag this for finance/productivity review ",
"rather than treating it as a definitive conclusion about efficiency or overspend."
)
},
human_check = "Finance/productivity owner to confirm 2024/25 cost index basis, MFF adjustment, peer group and local cost improvement narrative."
),
OF0063 = list(
flag = "Review locally", flag_class = "review",
plain_meaning = "Percentage of adult mental health inpatients with length of stay over 60 days.",
interpret = function(row) {
paste0(
"Long-stay inpatient metric — lower values are generally preferable. ",
nof_format_value_compare(row), ". ",
"RDY’s value (46.55) is substantially above the peer median (24.52). ",
"Because lower appears better for long-stay metrics, the agent would flag this for local review. ",
"A human reviewer would need to confirm the cohort, denominator, reporting period and whether the public figure aligns with local inpatient reporting."
)
},
human_check = "Acute/inpatient mental health lead to confirm >60-day definition, Q4 2025/26 cohort and local bed management data."
)
)
}
nof_metric_commentary_card <- function(row, entry) {
metric_label <- paste0(trimws(as.character(row$Metric_ID)), " — ",
trimws(as.character(row$Metric_description)))
interp <- if (is.function(entry$interpret)) entry$interpret(row) else entry$interpret
paste0(
'',
'
',
window_summary_table(stats_list, window_label),
window_stats_charts(stats_list),
caveat_html,
''
)
}
latest_from_trend <- function(trend_df, measure_id = NULL, measure_name = NULL) {
series <- extract_windowed_series(trend_df, measure_id, measure_name, window_months = 999L)
if (is.null(series) || nrow(series) == 0) return(NULL)
latest <- series[nrow(series), , drop = FALSE]
list(
value = latest$value[1],
period = format(latest$period[1], "%b %Y"),
status = latest$value_status[1]
)
}
CSDS_WINDOW_MEASURES <- list(
assess = list(
measure_name = "Assessment",
label = "CSDS — Assessment (CareActivities)",
note = "Activity counts reflect coded CSDS submissions — not unique patients."
),
clin = list(
measure_name = "Clinical Intervention",
label = "CSDS — Clinical Intervention (CareActivities)",
note = "Largest activity type where numeric — confirm service scope locally."
)
)
TT_WINDOW_MEASURES <- list(
M001 = list(
label = "M001 — Referrals received",
note = "Referral counts move with demand and recording — descriptive only."
),
M031 = list(
label = "M031 — People accessing services",
note = "Access counts differ from referrals received — do not conflate."
),
M053 = list(
label = "M053 — % accessing within 6 weeks (finished course)",
note = "Percentage measure — denominator checks required."
)
)
NOF_TREND_METRICS_META <- list(
OF0005 = list(label = "OF0005 — % waiting over 52 weeks (community)", note = "Lower is better; check cohort definition."),
OF0057 = list(label = "OF0057 — Urgent community response within 2 hours", note = "Higher is better; Q4 metric."),
OF0016 = list(label = "OF0016 — MH crisis face-to-face within 24 hours", note = "Higher is better."),
OF0086 = list(label = "OF0086 — Relative difference in costs", note = "Finance metric — local interpretation required.")
)
load_tt_trend <- function() {
tt <- load_trend_file("trend_talking_therapies_rdy.csv")
if (!is.null(tt) && nrow(tt) > 0) return(tt)
ts <- load_tt_time_series()
if (is.null(ts)) return(NULL)
stacked <- list()
for (mid in names(TT_WINDOW_MEASURES)) {
sub <- extract_tt_rdy_ts(ts, mid)
if (is.null(sub) || nrow(sub) < 2L) next
if (nrow(sub) > 6L) sub <- sub[(nrow(sub) - 5L):nrow(sub), , drop = FALSE]
for (i in seq_len(nrow(sub))) {
r <- sub[i, , drop = FALSE]
stacked[[length(stacked) + 1]] <- data.frame(
source_id = "talking_therapies_monthly",
publication_period = format(r$period[1], "%Y-%m"),
reporting_period_start = r$REPORTING_PERIOD_START[1],
reporting_period_end = r$REPORTING_PERIOD_END[1],
org_code = "RDY",
org_name = r$ORG_NAME2[1],
measure_id = mid,
measure_name = r$MEASURE_NAME[1],
metric_value = r$value[1],
metric_value_raw = as.character(r$value[1]),
value_status = "numeric",
source_file = "time_series_fallback",
caveats = "From bundled time-series extract.",
stringsAsFactors = FALSE
)
}
}
if (length(stacked) == 0) return(NULL)
do.call(rbind, stacked)
}
load_nof_trend <- function() {
load_trend_file("trend_nof_rdy.csv")
}
load_tt_time_series <- function() {
load_rdy_glob("^rdy_talking_therapies.*time_series\\.csv$")
}
parse_period_start <- function(x) {
x <- trimws(as.character(x))
d <- suppressWarnings(as.Date(x, format = "%d/%m/%Y"))
if (length(d) == 0 || all(is.na(d))) {
d <- suppressWarnings(as.Date(x, format = "%Y-%m-%d"))
}
d
}
extract_mhsds_rdy_ts <- function(df, measure_id, breakdown = "Provider") {
if (is.null(df)) return(NULL)
sub <- df[trimws(df$MEASURE_ID) == measure_id, , drop = FALSE]
if ("BREAKDOWN" %in% names(sub)) {
sub <- sub[trimws(sub$BREAKDOWN) == breakdown, , drop = FALSE]
}
sub <- sub[trimws(sub$PRIMARY_LEVEL) == "RDY", , drop = FALSE]
if (nrow(sub) == 0) return(NULL)
sub$period <- parse_period_start(sub$REPORTING_PERIOD_START)
sub$value <- to_num(sub$MEASURE_VALUE)
sub <- sub[!is.na(sub$period) & !is.na(sub$value), , drop = FALSE]
sub[order(sub$period), , drop = FALSE]
}
extract_tt_rdy_ts <- function(df, measure_id) {
if (is.null(df)) return(NULL)
sub <- df[
trimws(df$MEASURE_ID) == measure_id &
trimws(df$ORG_CODE2) == "RDY" &
trimws(df$GROUP_TYPE) == "Provider",
,
drop = FALSE
]
if (nrow(sub) == 0) return(NULL)
sub$period <- parse_period_start(sub$REPORTING_PERIOD_START)
sub$value <- to_num(sub$MEASURE_VALUE)
sub <- sub[!is.na(sub$period) & !is.na(sub$value), , drop = FALSE]
sub[order(sub$period), , drop = FALSE]
}
compute_period_trend <- function(ts_sub, measure_label = "") {
if (is.null(ts_sub) || nrow(ts_sub) < 2) {
return(list(
available = FALSE,
n_periods = if (is.null(ts_sub)) 0L else as.integer(nrow(ts_sub)),
measure_label = measure_label
))
}
latest <- ts_sub[nrow(ts_sub), , drop = FALSE]
prev <- ts_sub[nrow(ts_sub) - 1L, , drop = FALSE]
cur_v <- latest$value
prev_v <- prev$value
list(
available = TRUE,
n_periods = nrow(ts_sub),
measure_label = measure_label,
latest_period = format(latest$period, "%b %Y"),
previous_period = format(prev$period, "%b %Y"),
latest_value = cur_v,
previous_value = prev_v,
absolute_change = cur_v - prev_v,
percent_change = pct_change(cur_v, prev_v),
rolling_mean = if (nrow(ts_sub) >= 3) round(mean(ts_sub$value), 1) else NA_real_,
series = ts_sub
)
}
trend_summary_table <- function(trends_list) {
rows <- lapply(trends_list, function(t) {
if (is.null(t) || !isTRUE(t$available)) return(NULL)
data.frame(
Measure = t$measure_label,
Latest = paste0(format(t$latest_value, big.mark = ","), " (", t$latest_period, ")"),
Previous = paste0(format(t$previous_value, big.mark = ","), " (", t$previous_period, ")"),
Absolute_change = paste0(
if (t$absolute_change >= 0) "+" else "",
format(t$absolute_change, big.mark = ",")
),
Percent_change = if (is.na(t$percent_change)) {
"—"
} else {
paste0(if (t$percent_change >= 0) "+" else "", t$percent_change, "%")
},
Periods_in_extract = t$n_periods,
stringsAsFactors = FALSE
)
})
rows <- rows[!vapply(rows, is.null, logical(1))]
if (length(rows) == 0) return(NULL)
do.call(rbind, rows)
}
trend_not_available_section <- function(what_needed) {
paste0(
'',
'
Trend analysis not available from current extract
',
'
The downloaded public data for this report does not contain multiple comparable periods ',
'for the measures in the key figures table, or only a latest-period snapshot is present.
Trend analysis (from downloaded public time series)
',
'
Descriptive period-on-period change only — not causal. Figures may be provisional; ',
'suppression, rounding and definition changes may apply between months.
")
} else {
bullet_list(unlist(questions))
}
}
standard_bp_questions <- function() {
list(
list(
q = "Is this the same definition used locally?",
expl = paste(
"Public datasets may use national definitions. Local dashboards may use different filters,",
"denominators or reporting dates."
)
),
list(
q = "Is this still the latest position?",
expl = paste(
"Public data may be a delayed publication. Local operational data may have moved on",
"since the reporting period shown."
)
),
list(
q = "Who owns the narrative?",
expl = paste(
"The accountable service, finance, workforce, quality or BI owner should confirm",
"the explanation before the finding is used."
)
),
list(
q = "Is this a performance issue, a data quality issue, or a service model issue?",
expl = paste(
"A public figure can be affected by coding, exclusions, small numbers, local pathways",
"or publication rules."
)
)
)
}
agent_brief_sections <- function(config, key_findings_html, verify_body_html,
supporting_html = "") {
grouped_collapsed <- if (!is.null(config$grouped_findings) && length(config$grouped_findings) > 0) {
findings_group_section(config$grouped_findings)
} else {
""
}
summary_collapsed <- if (!is.null(config$agent_summary) && length(config$agent_summary) > 0) {
agent_summary_section(config$agent_summary)
} else {
""
}
audit_trail_extra <- paste0(
if (nzchar(grouped_collapsed)) {
collapsible_details("Key findings by review area (detail)", grouped_collapsed)
} else {
""
},
if (nzchar(summary_collapsed)) {
collapsible_details("Draft interpretation (detail)", summary_collapsed)
} else {
""
},
if (!is.null(config$prompt_excerpt) && nzchar(config$prompt_excerpt)) {
collapsible_details("Prompt excerpt", agent_prompt_box(config$prompt_excerpt))
} else {
""
},
supporting_html
)
scope <- config$scope %||% list()
paste0(
what_agent_asked_section(config$question, config$dataset_line),
if (isTRUE(config$provider_scope)) provider_scope_badge_html() else "",
data_used_section(config),
scope_section(scope$can %||% list(), scope$cannot %||% list()),
headline_reading_section(config$headline %||% list()),
if (!is.null(config$priority_callout)) config$priority_callout else "",
key_findings_html,
if (!is.null(config$why_useful)) why_this_is_useful_section(config$why_useful) else "",
human_checks_section(config$human_checks),
if (!is.null(config$bottom_line)) bottom_line_section(config$bottom_line) else "",
verify_section(
config$verify_intro %||% verify_intro_short(),
paste0(verify_body_html, audit_trail_extra)
),
human_review_warning()
)
}
`%||%` <- function(x, y) if (is.null(x) || length(x) == 0 || (length(x) == 1 && is.na(x))) y else x
write_public_report <- function(filename, title, subtitle, body) {
html <- paste0(
'',
'',
'', esc(title), '',
'',
'',
'',
'Skip to main content',
'
Raw NOF metrics with NHS England published rank and peer median (', esc(latest_q), ')
',
html_table(rank_table, 50)
)
commentary_html <- nof_metric_commentary_section(audit_source)
nof_lookup <- nof_commentary_lookup()
nof_kfe_specs <- lapply(seq_len(nrow(audit_source)), function(i) {
row <- audit_source[i, , drop = FALSE]
id <- trimws(as.character(row$Metric_ID))
entry <- nof_lookup[[id]]
spec <- NOF_METRIC_SPEC[[id]]
plain <- if (!is.null(entry)) entry$plain_meaning else trimws(as.character(row$Metric_description))
human <- if (!is.null(entry)) entry$human_check else "Confirm metric definition and rank polarity against NHS England NOF specification."
rank_txt <- trimws(as.character(row$Rank))
median_txt <- trimws(as.character(row$Median_value))
val_txt <- trimws(as.character(row$Value))
peer_pos <- if (is.na(to_num(median_txt)) && is.na(to_num(rank_txt))) {
"Median and rank not published for this metric in the extract."
} else {
format_peer_position_short(median_txt, rank_txt)
}
nof_trend_obj <- if (id %in% names(NOF_TREND_METRICS_META)) nof_trend_for_metric(id) else list(available = FALSE)
pol <- if (!is.null(spec)) spec$polarity else "unknown"
trend_lbl <- if (isTRUE(nof_trend_obj$available)) {
nof_trend_direction_label(nof_trend_obj, pol)$label
} else {
"Not available"
}
list(
figure = paste0(id, " — ", plain),
what = plain,
latest = paste0(val_txt, " (", latest_q, ")"),
standard_detail = if (!is.null(spec)) spec$standard else "Confirm against NHS England NOF specification.",
standard_metadata = NOF_SPEC_META,
peer_detail = peer_pos,
trend = if (isTRUE(nof_trend_obj$available)) nof_trend_obj else NULL,
polarity = pol,
trend_label = trend_lbl,
trend_override = if (isTRUE(nof_trend_obj$available)) NULL else "Not available",
trend_note = if (isTRUE(nof_trend_obj$available)) {
paste0("Quarter-over-quarter from trend_nof_rdy.csv (", nof_trend_window, ") — descriptive only.")
} else {
paste0("Cross-sectional snapshot for ", latest_q, " — no historic NOF trend for this metric.")
},
validation_status = if (!is.null(spec)) spec$validation_status else "Definition check required",
judgement = if (!is.null(spec)) {
nof_judgement_text(id, row, spec, nof_trend_obj)
} else {
nof_agent_reading(entry, row)
},
human_check = short_human_check(human)
)
})
kfe_supporting <- paste0(
collapsible_details("Full metric table and domain summary", key_figures),
collapsible_details("Additional metric commentary cards", commentary_html),
if (nof_has_q_trend) {
wrap_trend_collapsible(
window_stats_section(
nof_q_stats,
paste0("Quarter-over-quarter Value trends from trend_nof_rdy.csv (", nof_trend_window, "). Median/rank not trended."),
"Quarter-over-quarter",
c(
"Trend available for 4 headline metrics only; all others are latest-quarter snapshots.",
"Descriptive quarter-on-quarter change only — not causal."
)
),
"Quarter-over-quarter headline metrics"
)
} else ""
)
nof_trend_note <- if (nof_has_q_trend) {
paste(
"Trend is available for 4 headline metrics only (OF0005, OF0057, OF0016, OF0086).",
"Most metrics remain latest-quarter snapshots.",
"Peer median and published rank are NHS England pass-through fields — not recalculated."
)
} else {
paste(
"There is no multi-quarter NOF trend in the current extract.",
"Peer median and published rank are NHS England fields — not recalculated."
)
}
kfe_html <- key_figures_explained_section(
nof_kfe_specs,
paste(
"For each metric: latest RDY value, published standard where known, peer median/rank,",
"quarter-over-quarter trend where available, and a first-draft judgement for human review."
),
supporting_html = "",
show_trend = TRUE,
show_standard = TRUE,
show_peer = TRUE,
show_validation = TRUE,
trend_note = nof_trend_note,
period_caption = paste0("Latest quarter snapshot: ", latest_q,
if (nof_has_q_trend) paste0("; QoQ trend window: ", nof_trend_window) else "")
)
config <- list(
question = paste(
"Using the latest public NHS Oversight Framework file for mental health and community trusts,",
"prepare a first-draft RDY performance brief: which raw metrics exist,",
"what do published median/rank fields show, and what must a human verify?"
),
dataset_line = "NHS Oversight Framework MH/community CSV (RDY)",
prompt_excerpt = paste(
"Locate NHS England NOF MH/community trust CSV. Filter Trust_code=RDY.",
"Use latest quarter raw metrics (OF0xxx) only. Do not recalculate median or rank.",
"Summarise domains and ranked metrics descriptively. Flag rank-direction uncertainty.",
"No causal claims. Include verification paths to raw rows.",
sep = "\n"
),
scope = list(
can = c(
"Show where RDY appears to sit against published peer median and rank fields.",
"Help identify areas that may need local review."
),
cannot = c(
"Explain why a metric is high or low.",
"Confirm whether the public figure matches the latest internal position, local definitions or operational context."
)
),
headline = c(
"The clearest public-data review flags are long-stay adult mental health inpatients (OF0063: 46.55 vs peer median 24.52, rank 47), UCR 2-hour performance (below peer median), mental health crisis 24-hour face-to-face contact, and relative cost index.",
if (nof_has_q_trend) "UCR is also showing a short falling trend in the quarter-over-quarter extract." else NULL,
if (nof_has_q_trend) {
paste0("Trend is available for 4 headline metrics only (", nof_trend_window, "); most metrics remain latest-quarter snapshots.")
} else {
"There is no multi-quarter NOF trend in this extract."
}
),
priority_callout = priority_callout_html(c(
"OF0063 — adult MH inpatients with length of stay over 60 days: RDY 46.55 vs peer median 24.52 (rank 47). Priority validation before any review use.",
"OF0057 — UCR 2-hour performance: below peer median; confirm local UCR position and whether short trend is falling.",
"OF0016 — crisis face-to-face within 24 hours: below peer median — crisis pathway owner review.",
"OF0086 — relative cost index: above 100 and peer median — finance/productivity review."
)),
why_useful = c(
"The agent has not replaced local judgement.",
"It rapidly found the public RDY rows, summarised peer position, checked metric polarity where possible, highlighted likely review areas, and produced an audit trail for a human owner."
),
bottom_line = paste(
"The public NOF file suggests RDY's clearest review priorities are long-stay adult mental health inpatients,",
"urgent community response performance, crisis 24-hour contact, and relative cost index.",
"Several metrics look strong on published rank but still need local definition checks before any operational use.",
"A Business & Performance Partner should validate these figures with service and finance owners before drawing conclusions."
),
grouped_findings = nof_build_grouped_findings(audit_source, nof_lookup),
data_used_html = paste0(
'
',
'
NHS Oversight Framework (demo_nof_overview.csv + full RDY processed extract)
Assurance index (demo_assurance_profile.csv) where available
',
'
'
),
period = if (nof_has_q_trend) paste0(latest_q, " snapshot; quarter-over-quarter trend ", nof_trend_window) else period_text,
trend_available = if (nof_has_q_trend) {
paste0("Yes — quarter-over-quarter Value trends (", nof_trend_window, " from trend_nof_rdy.csv); median/rank latest quarter only")
} else {
"Not available — cross-sectional NOF snapshot only"
},
agent_summary = c(
paste0("Across ", latest_q, ", ", n_metrics, " raw NOF metrics span ", n_domains, " domains — several show strong published ranks (e.g. OF0005, OF0079) but need definition checks."),
"The agent flags OF0063, OF0057, OF0016 and OF0086 for local review where RDY sits below peer median on access/long-stay or above on cost index.",
"Finance metrics (OF0079, OF0081, OF0086) need finance-owner interpretation — the agent does not assume surplus/deficit meaning.",
"This snapshot cannot explain why performance changed or what action is needed without local validation."
),
human_checks = standard_human_checks(),
verify_intro = verify_intro_short(
paste0(
'
"
)
)
}
}
mh_kfe_html <- paste0(caveats_html, summary_table_html, charts_html)
config <- list(
question = paste(
"From six months of public MHSDS Provider/RDY data, summarise access and activity measures,",
"describe descriptive trends, and list what a mental health data owner must confirm."
),
dataset_line = "MHSDS Monthly Statistics — stacked Provider/RDY trend file",
prompt_excerpt = paste(
"Load trend_mhsds_access_rdy.csv for MHS23, MHS01, MHS29, MHS69.",
"Compute six-month descriptive stats and trend readings.",
"No causal claims. Do not sum provider and resident breakdowns.",
sep = "\n"
),
scope = list(
can = c(
"Summarise six months of key MHSDS access and activity measures for RDY as provider.",
"Show latest vs previous month and six-month descriptive change.",
"Flag suppression, provisional data and breakdown scope limits."
),
cannot = c(
"Support operational access conclusions without local MHSDS validation.",
"Combine provider and ICB-resident breakdowns into one headline.",
"Explain why trends changed or infer access improvement from contact counts alone."
)
),
headline = headline_bullets,
provider_scope = TRUE,
priority_callout = if ("MHS69" %in% names(mh_stats)[volatile]) {
priority_callout_html(c(
paste0(
"MHS69 shows very large volatile movement (latest: ",
format_mh_value(mh_stats$MHS69$latest_value), "). ",
"Do not read as sudden operational improvement. Financial-year counting logic, ",
"contact recording, or submission timing may explain the April movement."
)
))
} else {
NULL
},
why_useful = c(
"The agent assembled six months of Provider/RDY MHSDS measures with descriptive trends and suppression handling.",
"It flagged where stock measures and activity measures tell different stories, and where validation is needed before operational use."
),
bottom_line = paste(
"Over six months, open-referral stock measures rose while contact volume was broadly stable.",
"That pattern may signal caseload pressure but cannot prove whether access is improving or worsening.",
"MHS69 needs particular validation before any access finding.",
"A mental health data owner should confirm definitions and whether these Provider/RDY figures match local reporting."
),
grouped_findings = list(
list(
title = "Stock measures (caseload-style)",
items = list(
list(
title = "MHS23 — Open referrals",
body = paste0(
"Latest: ", format_mh_value(mh_stats$MHS23$latest_value, mh_stats$MHS23$latest_status),
". Six-month reading: ", mh_stats$MHS23$trend_reading,
". Open referrals are not new demand — higher counts are not automatically worse."
),
owner = "MHSDS/data owner to confirm open-referral definition."
),
list(
title = "MHS01 — People in contact",
body = paste0(
"Latest: ", format_mh_value(mh_stats$MHS01$latest_value, mh_stats$MHS01$latest_status),
". Six-month reading: ", mh_stats$MHS01$trend_reading,
". Movement may reflect activity, discharge or coding."
),
owner = "Confirm local in-contact definition matches MHSDS."
)
)
),
list(
title = "Activity measures",
items = list(
list(
title = "MHS29 — Contacts in reporting period",
body = paste0(
"Latest: ", format_mh_value(mh_stats$MHS29$latest_value, mh_stats$MHS29$latest_status),
". Six-month reading: ", mh_stats$MHS29$trend_reading,
". Contact volume does not automatically mean better access."
),
owner = "Service/BI owner to confirm contact counting rules."
),
list(
title = "MHS69 — CYP with two contacts",
body = paste0(
"Latest: ", format_mh_value(mh_stats$MHS69$latest_value, mh_stats$MHS69$latest_status),
if (mh_stats$MHS69$n_suppressed > 0) paste0(" (", mh_stats$MHS69$n_suppressed, " suppressed month(s) in window).") else ".",
" Confirm cohort and resident vs provider scope."
),
owner = "CYP mental health lead."
)
)
)
),
data_used_html = paste0(
'
Context:demo_mhsds_activity.csv — latest-month slice for suppression audit
' else "",
if (!is.null(ts_file_note)) paste0('
Fallback reference:', esc(ts_file_note), '
') else "",
"
"
),
period = trend_window,
trend_available = paste0(
"Yes — six-month stacked trend (", mh_stats[[1]]$n_periods, " months per measure from trend_mhsds_access_rdy.csv)"
),
agent_summary = c(
paste0("Six-month MHSDS brief (", trend_window, ") for RDY Provider rows."),
if (any(rising)) paste0("Rising over the window: ", paste(names(mh_stats)[rising], collapse = ", "), ".") else NULL,
if (any(falling)) paste0("Falling over the window: ", paste(names(mh_stats)[falling], collapse = ", "), ".") else NULL,
if (any(stable)) paste0("Broadly stable: ", paste(names(mh_stats)[stable], collapse = ", "), ".") else NULL,
"Descriptive trends only — not causal. Local MHSDS owner validation required before operational use."
),
human_checks = standard_human_checks(list(
list(
q = "Does the local MHSDS definition match these public Provider/RDY measures?",
expl = "Confirm MHS23 open referrals and MHS01 in-contact definitions with the data owner."
),
list(
q = "Are suppressed or missing months material for your reporting?",
expl = paste0(
"Check value_status in trend file — ",
paste(vapply(mh_stats, function(s) paste0(s$measure_id, ": ", s$n_suppressed, " suppressed"), character(1)), collapse = "; "),
"."
)
),
list(
q = "Should Provider or ICB-resident breakdowns be used for this question?",
expl = "This brief uses Provider/RDY only — do not sum with resident breakdowns."
)
)),
verify_intro = verify_intro_short(
'
'
),
period = if (csds_has_trend) paste0(trend_window, " (six-month trend); latest month ", latest_month_label) else period,
trend_available = if (csds_has_trend) {
paste0("Yes — six-month historic stack (", csds_window_stats[[1]]$n_periods %||% trend_assess$n_periods, " months in trend_csds_activity_rdy.csv)")
} else {
"Limited — latest month only or insufficient comparable periods"
},
agent_summary = c(
paste0("For ", period, ", care activity totals sum to ", format(total_contacts, big.mark = ","), " in the ActivityType slice."),
if (csds_has_trend) paste0("Historic CSDS stack (", trend_window, ") supports six-month descriptive comparison for Assessment and Clinical Intervention — not causal conclusions.") else "Trend analysis not available from current extract.",
"Public aggregate CSDS cannot prove referral demand, waiting times or team performance.",
"Sparse or zero activity in the demo slice needs local coding confirmation."
),
human_checks = standard_human_checks(),
verify_intro = verify_intro_short(
'
Annual IG assurance labels only — confirm current submission with the IG owner.
',
''
)
} else {
trend_not_available_section(c(
"Multiple DSPT assessment rows in the public organisation history",
"Consistent status labels across publication dates",
"IG owner confirmation of current-year submission"
))
}
fft_trend_section <- if (isTRUE(fft_trend_obj$available)) {
trend_section(
list(fft_trend_obj),
"trend_fft_rdy.csv",
c(
"FFT response rates vary; small number suppression may apply.",
"Confirm measure definition and setting scope with patient experience lead."
)
)
} else if (file.exists(fft_manual)) {
paste0(
'',
'
FFT trend not available from current extract
',
'
Public FFT summary XLSX files did not yield org-level RDY rows suitable for trend analysis.
',
'
See site/public-data/metadata/fft_manual_download_needed.md for URLs tried and recommended manual steps.
',
''
)
} else {
trend_not_available_section(c(
"Setting-level or trust-level FFT XLSX with RDY org code",
"At least two comparable publication months",
"Patient experience lead confirmation of response rates and suppression"
))
}
supporting_html <- paste0(
collapsible_details("Assurance source tables and DSPT history", key_figures),
collapsible_details("Additional source commentary", theme_commentary_section(commentary_cards)),
wrap_trend_collapsible(dspt_trend_section, "DSPT assessment history (descriptive)"),
if (nzchar(fft_trend_section)) wrap_trend_collapsible(fft_trend_section, "FFT trend detail") else ""
)
verify_extra <- paste0(
'Assurance index (demo extract — full columns)',
html_table(assurance),
'',
'CQC regulatory context note',
cqc_html,
''
)
config <- list(
question = paste(
"Which public assurance artefacts contain RDY rows, what is each useful for,",
"what are the gaps (FFT org-level, CQC non-statistical context),",
"and how should a Business & Performance Partner use this as a conversation starter?"
),
dataset_line = "KO41a, ERIC, DSPT, FFT and CQC public sources (assurance index)",
prompt_excerpt = paste(
"Index public assurance sources for RDY: KO41a, ERIC, DSPT, FFT, CQC.",
"Appropriate-use language only — no operational IG or complaints performance conclusions.",
sep = "\n"
),
scope = list(
can = c(
"Confirm which public assurance sources contain RDY rows and what each is useful for.",
"Document gaps such as missing org-level FFT rows or non-statistical CQC context."
),
cannot = c(
"Combine assurance sources into a performance score or league table.",
"Draw operational IG, complaints or patient experience conclusions without local owner validation."
)
),
headline = c(
if (!is.na(ko41a_new)) paste0("KO41a 2024-25: ", ko41a_new, " new written complaints, ", ko41a_upheld, " upheld — complaints team should confirm themes and local position.") else "KO41a confirms RDY participation in 2024-25 written complaints return.",
if (!is.na(eric_sites)) paste0("ERIC 2024/25: ", eric_sites, " sites with exemplar estate metrics extracted — estates owner should confirm amendments.") else "ERIC confirms RDY trust row in 2024/25 estates return.",
paste0("DSPT latest public assessment: ", dspt_latest, " — but 2025-26 v8 deadline is 30 June 2026; confirm current-year submission with IG."),
"FFT org-level rows absent — setting-specific files may hold relevant rows; patient experience lead follow-up needed.",
"CQC overall Outstanding (main report 2019) — regulatory context only, not a performance score."
),
why_useful = c(
"The agent mapped which public assurance sources contain RDY rows and what each can safely support.",
"It extracted traceable values where possible, flagged currentness risks, and named who to speak to next."
),
bottom_line = paste(
"This is an assurance source map, not a performance report.",
"Public data confirms RDY participation in key statutory returns and shows DSPT Standards met on the latest published assessment,",
"but FFT needs setting-level follow-up and all sources need owner confirmation before any meeting use."
),
grouped_findings = list(
list(
title = "Statutory participation confirmed",
items = list(
list(
title = "KO41a — Written complaints (annual)",
body = "RDY org-level row present in 2024-25 extract. Presence confirms participation — volume and themes need the complaints team.",
owner = "Complaints team to confirm 2024-25 figures and whether public row matches internal reporting."
),
list(
title = "ERIC — Estates returns (annual)",
body = "RDY trust row in 2024/25 ERIC extract. Supports facilities benchmarking — not a simple good/bad score.",
owner = "Estates/facilities owner to confirm amendments file and board reporting year."
)
)
),
list(
title = "IG and patient experience",
items = list(
list(
title = "DSPT — Data Security and Protection Toolkit",
body = paste0("Latest public assessment: ", dspt_latest, ". ", dspt_history_note),
owner = "IG/calendar owner to confirm current-year submission status."
),
list(
title = "FFT — Friends and Family Test (org-level gap)",
body = "No org-level RDY rows in downloaded FFT summary XLSX — workflow gap for analysts, not evidence of poor experience.",
owner = "Patient experience lead to confirm whether setting-level XLSX download fills the gap."
)
)
),
list(
title = "Regulatory context",
items = list(
list(
title = "CQC — Regulatory context",
body = "Care Quality Commission provider page captured as context note — inspection and regulatory background only.",
owner = "Quality/governance lead to confirm latest inspection status and internal action plans."
)
)
)
),
data_used_html = paste0(
'
',
'
demo_assurance_profile.csv
',
'
KO41a, ERIC, DSPT processed extracts
',
'
CQC context note (regulatory background only)
'
),
period = "KO41a 2024-25; ERIC 2024/25; DSPT public history; FFT/CQC as noted.",
trend_available = if (dspt_n >= 2) "Descriptive DSPT history only — not numeric performance trend" else "Annual snapshots only — KO41a/ERIC/FFT cannot support six-month numeric trends",
agent_summary = c(
"Public data confirms RDY participation in KO41a complaints and ERIC estates returns.",
paste0("Latest DSPT public assessment: ", dspt_latest, " — annual assurance label, not operational IG detail."),
"FFT org-level rows were absent in the downloaded summary file — patient experience lead follow-up needed.",
"CQC provides regulatory context only — not a performance score or league table."
),
human_checks = standard_human_checks(list(
list(
q = "Who is the named owner for each return this cycle?",
expl = "KO41a, ERIC, DSPT and FFT each have accountable teams — confirm before citing in assurance packs."
)
)),
verify_intro = verify_intro_short(
'
', html_table(dm01_summary, 15))
} else {
""
},
if (!is.null(dm01_summary)) {
bar_chart(dm01_summary$`Diagnostic Tests`, to_num(dm01_summary$`Total Activity`),
paste0("DM01 total activity by test (RDY, ", dm01_latest_period, ")"),
period_caption = dm01_latest_period)
} else {
""
}
)
commentary_cards <- c(
build_commentary_card(
"A&E monthly — RDY presence and zero ED attendances",
"Source validation only", "definition",
list(
"Plain-English meaning" = "Monthly A&E provider statistics — attendance and emergency admission columns.",
"Latest value / position" = paste0(
"RDY row present; Type 1/2 A&E attendances = 0",
if (!is.na(ae_other_adm)) paste0("; other emergency admissions = ", ae_other_adm) else ""
),
"Comparator / trend" = if (!is.null(ae_trend)) {
n_ae <- length(unique(na.omit(trimws(ae_trend$reporting_period_start))))
paste0(
"Historic A&E stack (", n_ae, " months) — ",
"Type 1/2 attendances remain zero; source validation only."
)
} else {
"Single month A&E extract — run script 05 for historic stack."
},
"Agent flag" = "Source validation only",
"Cautious interpretation" = paste0(
"Zero ED attendances are consistent with RDY not operating a Type 1/2 emergency department — ",
"this row confirms source presence and coding, not urgent care performance. ",
if (!is.na(ae_other_adm) && ae_other_adm <= 5) {
paste0("Small other emergency admission count (", ae_other_adm, ") needs service-owner confirmation of what is included.")
} else ""
),
"Human check required" = "Urgent/emergency care lead to confirm service model and what 'other emergency admissions' represents for RDY."
)
),
build_commentary_card(
paste0("DM01 — Diagnostic tests (", dm01_latest_period, ")"),
"Review locally", "review",
list(
"Plain-English meaning" = "Monthly diagnostic waiting list and activity by test type for RDY as provider.",
"Latest value / position" = if (!is.null(dm01)) paste0(nrow(dm01), " test rows; highest activity: ", dm01_top_test) else "Extract not found",
"Comparator / trend" = if (isTRUE(trend_dm01_activity$available)) {
paste0(
"Historic DM01 stack: latest vs previous month for ", dm01_top_test, " — ",
format(trend_dm01_activity$latest_value, big.mark = ","), " vs ",
format(trend_dm01_activity$previous_value, big.mark = ","), "."
)
} else if (!is.null(dm01_trend)) {
"Historic DM01 file present but fewer than two comparable months for top test."
} else {
"Single month in current extract — run script 05 for DM01 historic stack."
},
"Agent flag" = "Review locally",
"Cautious interpretation" = "Audiology and community diagnostics may dominate activity — do not infer national waiting position without local validation.",
"Human check required" = "Diagnostics service owner to confirm DM01 mapping to local community diagnostic pathways."
)
),
build_commentary_card(
"KH03 — Overnight mental illness beds (snapshot dates)",
if (isTRUE(kh03_trend$available)) "Watch / clarify" else "Trend not available",
if (isTRUE(kh03_trend$available)) "watch" else "definition",
list(
"Plain-English meaning" = "Quarterly overnight bed stock by sector — mental illness rows relevant to RDY as mental health provider.",
"Latest value / position" = if (isTRUE(kh03_trend$available)) {
paste0(format(kh03_trend$latest_value, big.mark = ","), " beds (", kh03_trend$latest_period, " snapshot)")
} else {
"Mixed snapshot dates in extract — verify latest quarter on NHS England site"
},
"Comparator / trend" = if (isTRUE(kh03_trend$available)) {
paste0(
"Historical snapshots span ", kh03_trend$n_periods, " dates — latest vs previous: ",
format(kh03_trend$latest_value, big.mark = ","), " vs ",
format(kh03_trend$previous_value, big.mark = ","),
". Irregular snapshot intervals — descriptive only."
)
} else {
"Insufficient comparable snapshots for trend in current slice."
},
"Agent flag" = if (isTRUE(kh03_trend$available)) "Watch / clarify" else "Trend not available",
"Cautious interpretation" = kh03_stale_note,
"Human check required" = "Bed management/ estates lead to confirm latest KH03 quarter and alignment with internal bed state."
)
)
)
kh03_trend_html <- if (isTRUE(kh03_trend$available)) {
trend_section(
list(kh03_trend),
"trend_kh03_beds_rdy.csv — Mental Illness sector, recent snapshots only",
c(
"Snapshot dates are irregular (quarterly, not monthly) — descriptive only.",
"Latest snapshot may lag NHS England publication — verify on source site."
)
)
} else {
trend_not_available_section(c(
"Latest KH03 quarterly snapshot aligned to board reporting date",
"Consistent sector filter (Mental Illness) across consecutive quarters"
))
}
ae_dm01_trends <- list()
if (isTRUE(trend_ae_other$available)) ae_dm01_trends <- c(ae_dm01_trends, list(trend_ae_other))
if (isTRUE(trend_dm01_activity$available)) ae_dm01_trends <- c(ae_dm01_trends, list(trend_dm01_activity))
ae_dm01_trend <- if (length(ae_dm01_trends) > 0) {
trend_section(
ae_dm01_trends,
"trend_ae_rdy.csv / trend_dm01_rdy.csv (historic stack from script 05)",
c(
"A&E trends are source validation only — zero Type 1/2 ED attendances expected at RDY.",
"Descriptive period-on-period change only — not operational cause."
)
)
} else {
trend_not_available_section(c(
"Run site/public-data/05_download_historic_public_data.R for trend_ae_rdy.csv and trend_dm01_rdy.csv",
"Service-owner confirmation that RDY service model excludes Type 1/2 ED activity"
))
}
urgent_window_stats <- c(
if (length(ae_window_stats) > 0) ae_window_stats else list(),
if (length(dm01_window_stats) > 0) dm01_window_stats else list()
)
urgent_window_html <- if (length(urgent_window_stats) > 0 &&
any(vapply(urgent_window_stats, function(s) isTRUE(s$available), logical(1)))) {
window_stats_section(
urgent_window_stats,
paste0(
"Six-month descriptive trends from trend_ae_rdy.csv (", ae_trend_window,
") and trend_dm01_rdy.csv (", dm01_trend_window, ")."
),
"Six-month",
c(
"A&E trends are source validation only — zero Type 1/2 ED attendances expected at RDY.",
"DM01 provisional monthly data — validate with diagnostics service owner."
)
)
} else {
""
}
supporting_html <- paste0(
collapsible_details("Source presence tables and charts", key_figures),
collapsible_details("Additional source commentary", theme_commentary_section(commentary_cards)),
if (nzchar(urgent_window_html)) wrap_trend_collapsible(urgent_window_html, "A&E and DM01 six-month window summary") else "",
wrap_trend_collapsible(ae_dm01_trend, "A&E trend detail"),
wrap_trend_collapsible(kh03_trend_html, "KH03 bed trend detail")
)
verify_extra <- paste0(
'A&E RDY row — full public data columns',
ae_detail_html,
'',
if (!is.null(kh03_mi)) paste0(
'KH03 mental illness beds (snapshots in extract)',
html_table(kh03_mi),
''
) else ""
)
config <- list(
question = paste(
"Check whether RDY appears in public A&E, DM01 and KH03 files;",
"explain what each source can safely support for a trust without an emergency department;",
"and where trend analysis is or is not available."
),
dataset_line = "A&E, DM01 and KH03 public provider files (RDY)",
prompt_excerpt = paste(
"Confirm RDY row presence per source. Report zero ED attendances explicitly.",
"No ED performance claims. No causal language.",
sep = "\n"
),
scope = list(
can = c(
"Confirm RDY row presence in public A&E, DM01 and KH03 files.",
"Show descriptive trends where stacked historic files support them.",
"Explain what each source can safely support for a trust without a Type 1/2 emergency department."
),
cannot = c(
"Prove urgent care or diagnostic performance standing from source validation alone.",
"Make ED performance claims — RDY shows zero Type 1/2 A&E attendances by service model."
)
),
headline = c(
"These sources are grouped because they were checked together, not because they form a single performance pathway.",
paste0(
"RDY appears in public A&E, DM01 and KH03 files — A&E confirms zero Type 1/2 ED attendances (source validation only, not ED performance)."
),
if (!is.na(dm01_aud_wl) && !is.na(dm01_wl_total)) {
paste0(
"DM01 (", dm01_latest_period, "): audiology accounts for most waiting-list volume (",
format(dm01_aud_wl, big.mark = ","), " of ", format(dm01_wl_total, big.mark = ","),
if (!is.na(dm01_wl_13)) paste0("; ", dm01_wl_13, " waits over 13 weeks in extract.") else ")."
)
} else if (!is.null(dm01)) {
paste0("DM01: ", nrow(dm01), " test rows for ", dm01_latest_period, " — ", dm01_top_test, " has highest activity.")
} else {
"DM01 extract not summarised."
},
if (isTRUE(kh03_trend$available)) kh03_stale_note else "KH03: confirm latest quarter before capacity discussions.",
paste0(
"Trend extracts: A&E ", ae_n_periods, " periods; DM01 ", dm01_n_periods,
" periods — headline uses latest period per source."
)
),
why_useful = c(
"The agent checked RDY presence across heterogeneous urgent-care, diagnostics and bed-stock sources.",
"It explained which sources are meaningful for a mental health/community trust and where local owners must confirm definitions."
),
bottom_line = paste(
"This is a source applicability check, not a unified performance report.",
"A&E rows validate RDY's service model rather than ED performance.",
"DM01 mainly describes audiology/community diagnostics waiting lists for RDY.",
"KH03 provides quarterly mental health bed-stock context.",
"Local owners should confirm all figures before operational use."
),
grouped_findings = list(
list(
title = "A&E source validation",
items = list(
list(
title = "A&E — RDY row and zero Type 1/2 attendances",
body = paste0(
"RDY row present in ", ae_latest_period, " A&E extract. Type 1/2 attendances = 0 — expected for RDY service model.",
if (!is.na(ae_other_adm)) paste0(" Other emergency admissions: ", ae_other_adm, ".") else ""
),
owner = "Urgent/emergency care lead to confirm service model and A&E return coding."
)
)
),
list(
title = "DM01 diagnostics",
items = list(
list(
title = paste0("DM01 — ", dm01_top_test),
body = paste0(
if (!is.null(dm01)) paste0(nrow(dm01), " diagnostic test rows for ", dm01_latest_period, ". ") else "",
if (!is.na(dm01_mar_activity)) paste0("Top test activity: ", format(dm01_mar_activity, big.mark = ","), ". ") else "",
"Audiology/community diagnostics may dominate — local validation required."
),
owner = "Diagnostics service owner to confirm DM01 mapping to local pathways."
)
)
),
list(
title = "KH03 bed snapshots",
items = list(
list(
title = "KH03 — Mental illness overnight beds",
body = if (isTRUE(kh03_trend$available)) {
paste0(
"Latest snapshot: ", format(kh03_trend$latest_value, big.mark = ","), " beds (",
kh03_trend$latest_period, "). Quarterly stack only — verify latest quarter on NHS England site."
)
} else {
"KH03 extract present — confirm latest quarter before capacity discussions."
},
owner = "Bed management/estates lead to confirm alignment with internal bed state."
)
)
)
),
data_used_html = paste0(
'
DM01 (demo_dm01_diagnostics.csv + full RDY extract)
',
'
KH03 (demo_kh03_beds.csv + trend file where used)
',
if (!is.null(ae_trend)) '
trend_ae_rdy.csv
' else "",
if (!is.null(dm01_trend)) '
trend_dm01_rdy.csv
' else "",
'
'
),
period = paste0("A&E ", ae_trend_window, "; DM01 ", dm01_trend_window, "; KH03 quarterly snapshots (", if (isTRUE(kh03_trend$available)) paste0(kh03_trend$previous_period, " to ", kh03_trend$latest_period) else "see trend file", ")."),
trend_available = if (urgent_has_ae_dm01_trend || isTRUE(kh03_trend$available)) {
paste0("Yes — six-month A&E/DM01 stacks where available; KH03 quarterly snapshots (", kh03_stale_note, ")")
} else {
"Limited — source validation only for some sources"
},
agent_summary = c(
paste0(
"RDY appears in public A&E, DM01 and KH03 files — interpretation needs service-owner confirmation.",
if (ae_ed_zero) " A&E shows zero Type 1/2 ED attendances (expected for RDY service model)." else ""
),
if (!is.null(dm01)) paste0("DM01: ", nrow(dm01), " test rows for ", dm01_latest_period, " — ", dm01_top_test, " has highest activity; six-month window ", dm01_trend_window, ".") else "DM01 extract not summarised.",
if (isTRUE(kh03_trend$available)) paste0("KH03: ", kh03_stale_note) else "KH03: confirm latest quarter before capacity discussions.",
"This brief validates source presence — it does not prove urgent care or diagnostic performance standing."
),
human_checks = standard_human_checks(list(
list(
q = "Which urgent care metrics apply locally without an ED?",
expl = "Many national urgent care indicators assume Type 1/2 ED activity — confirm which apply to RDY."
)
)),
verify_intro = verify_intro_short(
paste0(
'