Graphs for events and conditions added

analysis/report_measures.py

@@ -15,6 +15,25 @@
     # Pharmacy First service (qualifier value)
     "pharmacy_first_service": ["983341000000102"],
 }
+# The following codes come from codelists/user-chriswood-pharmacy-first-clinical-pathway-conditions.csv file.
+# Currently written as a hardcoded dictionary to allow for easy for looping (ln66-83), but will be imported from codelist csv in future commits.
+# Pharmacy First seven clinical conditions codelist
+pharmacy_first_conditions_codes = {
+    # Community Pharmacy (CP) Blood Pressure (BP) Check Service (procedure)
+    "acute_otitis_media": ["3110003"],
+    # Community Pharmacy (CP) Contraception Service (procedure)
+    "herpes_zoster": ["4740000"],
+    # Community Pharmacist (CP) Consultation Service for minor illness (procedure)
+    "acute_sinusitis": ["15805002"],
+    # Pharmacy First service (qualifier value)
+    "impetigo": ["48277006"],
+    # Community Pharmacy (CP) Contraception Service (procedure)
+    "infected_insect_bite": ["262550002"],
+    # Community Pharmacist (CP) Consultation Service for minor illness (procedure)
+    "acute_pharyngitis": ["363746003"],
+    # Pharmacy First service (qualifier value)
+    "uncomplicated_urinary_tract_infection": ["1090711000000102"],
+}
 
 registration = practice_registrations.for_patient_on(INTERVAL.end_date)
 
@@ -24,7 +43,7 @@
 )
 
 # Loop through each condition to create a measure
-for condition_name, codelist in pharmacy_first_event_codes.items():
+for pharmacy_first_event, codelist in pharmacy_first_event_codes.items():
     condition_events = selected_events.where(
         clinical_events.snomedct_code.is_in(codelist)
     )
@@ -36,33 +55,29 @@
     # Define the denominator as the number of patients registered
     denominator = registration.exists_for_patient()
 
-    # Define the measure
     measures.define_measure(
-        name=f"count_{condition_name}",
+        name=f"count_{pharmacy_first_event}",
         numerator=numerator,
         denominator=denominator,
         intervals=months(8).starting_on("2023-11-01")
     )
 
-# # Count pharmacy first codes
-# pharmacy_first_code_counts = {}
+# Loop through each CLINICAL condition to create a measure
+for condition_name, condition_code in pharmacy_first_conditions_codes.items():
+    condition_events = selected_events.where(
+        clinical_events.snomedct_code.is_in(condition_code)
+    )
 
-# for code_desc, code in pharmacy_first_event_codes.items():
-#     count_codes_query = selected_events.where(
-#         selected_events.snomedct_code.is_in(code)
-#     ).count_for_patient()
-#     pharmacy_first_code_counts[f"count_{code_desc}"] = count_codes_query
+    # Define the numerator as the count of events for the condition
+    numerator = condition_events.count_for_patient()
 
 
-# for measures_name, code_counts in pharmacy_first_code_counts.items():
-#     measures.define_measure(
-#         name=measures_name,
-#         numerator=code_counts,
-#         group_by={
-#             "practice_region": registration.practice_nuts1_region_name
-#             },
-#         denominator=patients.exists_for_patient(),
-#         intervals=intervals,
-#     )
+    # Define the denominator as the number of patients registered
+    denominator = registration.exists_for_patient()
 
-
+    measures.define_measure(
+        name=f"count_{condition_name}",
+        numerator=numerator,
+        denominator=denominator,
+        intervals=months(8).starting_on("2023-11-01")
+    )

analysis/reports/pf_report.Rmd

@@ -24,7 +24,6 @@ pre[class] {
 </style>
 
 
-
 ```{r setup, include=FALSE}
 knitr::opts_chunk$set(echo = FALSE)
 
@@ -34,13 +33,13 @@ library(readr)
 
 
 ```
-$~$
+<br>
 
 ## Background <a name="background"></a>
 
 Add background here.
 
-$~$
+<br>
 
 ## Methods <a name="methods"></a>
 
@@ -58,8 +57,7 @@ Links to the codelist for each analysis can be found beneath the relevant sectio
 
 This report contains the following sections:
 
-
-
+* [Clinical Services](#services)
 * [Clinical Pathways](#pathways)
   * [Clinical condition](#condition)
   * [Days of the week](#dotw)
@@ -82,9 +80,11 @@ This report contains the following sections:
   * [Age](#contra_age)
   * [Region](#contra_region)
 
-$~$
+<br>
 
-## Clinical services
+## Clinical Services <a name="services"></a>
+
+<br>
 
 ```{r, message=FALSE, warning=FALSE}
 # Load plotting function
@@ -94,12 +94,15 @@ df_measures <- readr::read_csv(
   here::here("output", "report", "conditions_measures.csv")
 )
 
-plot1_conditions <- plot_measures(df_measures,
+plot_services <- plot_measures(df_measures,
 title = "Number of consultations for each clinical service per month",
-x_label = "Month",
-y_label = "Number of Consultations",
-color_label = "Clinical Service")
-print(plot1_conditions)
+measure_names = c("count_blood_pressure_service", 
+                "count_contraception_service", 
+                "count_consultation_service", 
+                "count_pharmacy_first_service"),
+y_label = "Number of codes for consultations",
+)
+print(plot_services)
 ```
 
 ## Clinical Pathways <a name="pathways"></a>
@@ -116,6 +119,22 @@ Here we show the number of consultations for each of the Pharmacy First Clinical
 
 > LINE CHART WITH COUNT OF EACH CLINICAL CONDITION
 
+```{r, message=FALSE, warning=FALSE}
+
+plot_conditions <- plot_measures(df_measures,
+title = "Number of consultations for each clinical condition per month",
+measure_names = c("count_acute_otitis_media", 
+                  "count_herpes_zoster", 
+                  "count_acute_sinusitis", 
+                  "count_impetigo",
+                  "count_infected_insect_bite",
+                  "count_acute_pharyngitis",
+                  "count_uncomplicated_urinary_tract_infection"),
+y_label = "Number of codes for consultations",
+)
+print(plot_conditions)
+```
+
 ### Counts by day of the week <a name="dotw"></a>
 Here we show the number of consultations for the Pharmacy First Clinical Pathways by day of the week the consultation was conducted. (Mainly of interest to show what happens at weekends etc e.g. when GP practices are closed).
 

codelists/codelists.json

@@ -1,3 +1,10 @@
 {
-  "files": {}
+  "files": {
+    "user-chriswood-pharmacy-first-clinical-pathway-conditions.csv": {
+      "id": "user/chriswood/pharmacy-first-clinical-pathway-conditions/7ec97762",
+      "url": "https://www.opencodelists.org/codelist/user/chriswood/pharmacy-first-clinical-pathway-conditions/7ec97762/",
+      "downloaded_at": "2024-08-22 12:53:00.167017Z",
+      "sha": "bed7f74add5c2d2ac6f7120d89f5ba94e57a28cb"
+    }
+  }
 }

codelists/codelists.txt

@@ -0,0 +1 @@
+user/chriswood/pharmacy-first-clinical-pathway-conditions/7ec97762

codelists/user-chriswood-pharmacy-first-clinical-pathway-conditions.csv

@@ -0,0 +1,8 @@
+code,term
+1090711000000102,Uncomplicated urinary tract infection
+15805002,Acute sinusitis
+262550002,Infected insect bite
+3110003,Acute otitis media
+363746003,Acute pharyngitis
+4740000,Herpes zoster
+48277006,Impetigo

lib/functions/function_plot_measures.R

@@ -3,6 +3,7 @@
 #' Creates a line plot of measures over time, with customisable labels and colours.
 #' 
 #' @param data A dataframe containing the data to plot.
+#' @param measure_names Strings specifiying the names of measure columns to be plotted.
 #' @param title A string specifying the title of the plot. Default is NULL. 
 #' @param x_label A string specifying the label for the x-axis. Default is NULL.
 #' @param y_label A string specifying the label for the y-axis. Default is NULL. 
@@ -13,42 +14,80 @@
 #' 
 #' @return A ggplot object.
 
+# Define the function
 plot_measures <- function(
     data,
+    measure_names,
     date_col = "interval_end",
     value_col = "numerator",
     measure_col = "measure",
     title = NULL,
     x_label = NULL,
     y_label = NULL,
-    color_label = NULL) {
+    color_label = NULL,
+    axis_x_text_size = 7) {
+
+  # Check if the necessary columns exist in the data
+  if (date_col %in% names(data) == FALSE) {
+    stop("Data does not have a column with the name '", date_col, "'")
+  } else if (value_col %in% names(data) == FALSE) {
+    stop("Data does not have a column with the name '", value_col, "'")
+  } else if (measure_col %in% names(data) == FALSE) {
+    stop("Data does not have a column with the name '", measure_col, "'")
+  }
+
+  # Convert column names to symbols
+  date_sym <- sym(date_col)
+  value_sym <- sym(value_col)
+  measure_sym <- sym(measure_col)
+
+  # Ensure the date column is of Date type
+  data <- data %>%
+    mutate(!!date_sym := as.Date(!!date_sym))
+
+  # Filter measures column for user-specified measure names
+  data <- data %>%
+    filter(!!measure_sym %in% measure_names)
 
   # Create plot
   plot1 <- ggplot(
     data,
     aes(
-      x = {{date_col}},
-      y = {{value_col}},
-      color = {{measure_col}},
-      group = {{measure_col}}
+      x = !!date_sym,
+      y = !!value_sym,
+      color = !!measure_sym,
+      group = !!measure_sym
     )
   ) +
     geom_line() +
     labs(
       title = title,
       x = x_label,
       y = y_label,
-      color = "Condition"
+      color = color_label
+    ) +
+    scale_y_continuous(
+      limits = c(0, NA),
     ) +
-    # Setting the minimum y-value
-    ylim(0, NA) +
-    # Applying the minimal theme
     theme_minimal() +
+    theme(axis.text.x = element_text(size = axis_x_text_size), 
+    legend.position="bottom",
+    legend.key.size = unit(0.5, "cm"),
+    legend.text = element_text(size = 6),
+    legend.title = element_text(size = 8)) +
+    guides(
+    color = guide_legend(nrow = 2)  # Adjust number of rows in the legend
+) +
+    geom_vline(
+      xintercept = lubridate::as_date("2024-02-01"),
+      linetype = "dotted",
+      colour = "orange",
+      linewidth = .7) +
     scale_x_date(
-    date_breaks = "1 month",  
-    date_labels = "%b %Y",    
+      date_breaks = "1 month",  
+      date_labels = "%b %Y"
     )
 
-  # Return plot
+
   plot1
-}
+}