Viv3ckj/add hyp001 measures

analysis/hyp_reg_measures.py

@@ -0,0 +1,80 @@
+from ehrql import INTERVAL, case, create_measures, months, when, codelist_from_csv, create_dataset
+from ehrql.tables.tpp import (
+    clinical_events, 
+    patients,
+    practice_registrations,
+)
+
+# Hypertension codes
+hyp_cod = codelist_from_csv(
+    "codelists/nhsd-primary-care-domain-refsets-hyp_cod.csv",
+    column="code"
+)
+# Hypertension resolved codes
+hypres_cod = codelist_from_csv(
+    "codelists/nhsd-primary-care-domain-refsets-hypres_cod.csv",
+    column="code"
+)
+
+index_date = "2024-03-31"
+measures = create_measures()
+
+### variables ###
+
+selected_events = clinical_events.where(
+    clinical_events.date.is_on_or_before(INTERVAL.end_date)
+)
+
+# date of the most recent hypertension diagnosis up to and including the achievement date
+hyplat_dat = (
+    selected_events.where(selected_events.snomedct_code.is_in(hyp_cod))
+    .sort_by(selected_events.date)
+    .last_for_patient()
+    .date
+)
+
+# date of the most recent hypertension diagnosis resolved code recorded after the most recent hypertension diagnosis and up to and including the achievement date
+hypres_dat = (
+    selected_events.where(selected_events.snomedct_code.is_in(hypres_cod))
+    .sort_by(selected_events.date)
+    .last_for_patient()
+    .date
+)
+
+# Rule for patients with a hypertension code that has not been resolved
+hyp_reg_r1 = hyplat_dat.is_not_null() & hypres_dat.is_null() | (hyplat_dat > hypres_dat)
+
+age = patients.age_on(INTERVAL.start_date)
+age_band = case(
+    when((age >= 0) & (age < 20)).then("0-19"),
+    when((age >= 20) & (age < 40)).then("20-39"),
+    when((age >= 40) & (age < 60)).then("40-59"),
+    when((age >= 60) & (age < 80)).then("60-79"),
+    when(age >= 80).then("80+"),
+)
+
+registration = practice_registrations.for_patient_on(INTERVAL.end_date)
+
+# Measure defining the rate of patients with unresolved hypertension per age band and sex
+measures.define_measure(
+    name="diagnosis_by_age",
+    numerator=hyp_reg_r1 == True,
+    denominator=registration.exists_for_patient(),
+    group_by={
+        "age_band": age_band,
+        "sex": patients.sex,
+    },
+    intervals=months(12).starting_on("2023-04-01"),
+)
+
+# Measure defining the rate of patients with resolved hypertension per age band and sex
+measures.define_measure(
+    name="resolved_by_age",
+    numerator=hyp_reg_r1 == False,
+    denominator=registration.exists_for_patient(),
+    group_by={
+        "age_band": age_band,
+        "sex": patients.sex,
+    },
+    intervals=months(12).starting_on("2023-04-01"),
+)

analysis/visualise_measures.R

@@ -0,0 +1,72 @@
+library(tidyverse)
+library(patchwork)
+library(here)
+
+# Load data
+df_measures <- read_csv(
+  here("output", "hyp", "hyp001_measures.csv")) %>%
+  replace_na(list(age_band = "(Missing)")) %>%
+  mutate(
+    start_date = as.Date(interval_start, format = "%Y-%m-%d"),
+    end_date = as.Date(interval_end, format = "%Y-%m-%d"),
+    age_band = factor(
+      age_band,
+      levels = c("0-19", "20-39", "40-59", "60-79", "80+", "(Missing)"),
+      labels = c("0-19", "20-39", "40-59", "60-79", "80+", "(Missing)")
+      )
+  )
+
+plot_hypres <- df_measures %>%
+    filter(measure == "resolved_by_age") %>%
+    ggplot(aes(
+      x = end_date, 
+      y = ratio,
+      colour = age_band,  
+    )) + 
+    geom_point() + 
+    geom_line(alpha = .5) + 
+    labs(
+      title = NULL,
+      x = NULL,
+      y = "Patients with hypertension resolved code",
+      colour = "Age Band"
+    ) + 
+    scale_y_continuous(
+      labels = scales::label_percent(), 
+      limits = c(0,1)
+    ) +
+    facet_wrap(~ factor(
+      sex,
+      levels = c("female", "male", "intersex", "unknown"),
+      labels = c("Female", "Male", "Intersex", "Unknown")
+    ))
+
+plot_hyp <- df_measures %>%
+    filter(measure == "diagnosis_by_age") %>%
+    ggplot(aes(
+      x = end_date, 
+      y = ratio,
+      colour = age_band,  
+    )) + 
+    geom_point() + 
+    geom_line(alpha = .5) + 
+    labs(
+      title = NULL,
+      x = NULL,
+      y = "Patients with hypertension code",
+      colour = "Age Band"
+    ) + 
+    scale_y_continuous(
+      labels = scales::label_percent(), 
+      limits = c(0,1)
+    ) +
+    facet_wrap(~ factor(
+      sex,
+      levels = c("female", "male", "intersex", "unknown"),
+      labels = c("Female", "Male", "Intersex", "Unknown")
+    ))
+
+plot_hyp <- (plot_hyp / plot_hypres) +
+plot_layout(guides = "collect")
+
+ggsave("output/hyp/hyp_plot.png", width = 8, height = 8)

project.yaml

@@ -39,3 +39,21 @@ actions:
     outputs:
       highly_sensitive:
         cohort: output/dm/dm017_milan.csv.gz
+
+  generate_hyp001_measures:
+    run: >
+      ehrql:v1 generate-measures analysis/hyp_reg_measures.py
+      --output output/hyp/hyp001_measures.csv
+    outputs:
+      moderately_sensitive:
+        measure: output/hyp/hyp001_measures.csv
+
+  generate_hyp001_plots:
+    run: > 
+      r:latest
+        analysis/visualise_measures.R
+        --output output/hyp/hyp_plot.png
+    needs: [generate_hyp001_measures]
+    outputs:
+      moderately_sensitive:
+        hyp_plot: output/hyp/hyp_plot.png