# get the available datasets
d_datasets <- get_datasets()
# search the condition_name for Mental Health related string
d_datasets |>
filter(str_detect(tolower(reported_measure_name), "mental")) |>
glimpse()
#> Rows: 12
#> Columns: 8
#> $ data_id <chr> "904", "1329", "1336", "2735", "2742", "3515", "…
#> $ data_name <chr> "ADM 2011-12 - Number of admissions to hospital"…
#> $ start_date <chr> "2011-07-01", "2012-07-01", "2013-07-01", "2014-…
#> $ end_date <chr> "2012-06-30", "2013-06-30", "2014-06-30", "2015-…
#> $ outcome_measure_code <chr> "MYH0024", "MYH0024", "MYH0024", "MYH0024", "MYH…
#> $ outcome_measure_name <chr> "Number of admissions to hospital", "Number of a…
#> $ reported_measure_code <chr> "MYH-RM0216", "MYH-RM0216", "MYH-RM0216", "MYH-R…
#> $ reported_measure_name <chr> "Mental health", "Mental health", "Mental health…
# extract the dataset IDs
dataset_ids <- d_datasets |>
filter(str_detect(tolower(reported_measure_name), "mental")) |>
pull(data_id)
# read and combine the dataset_ids
d_mental_health_admissions <- read_dataset_ids(dataset_ids)
# aggregate by reporting period
d_mental_health_admissions |>
filter(unit_type_name == "Hospital") |>
summarize(
mental_health_admission_n = sum(as.numeric(number_of_admissions_to_hospital), na.rm = TRUE),
.by = c(start_date, end_date)
)
#> # A tibble: 12 × 3
#> start_date end_date mental_health_admission_n
#> <chr> <chr> <dbl>
#> 1 2011-07-01 2012-06-30 108542
#> 2 2012-07-01 2013-06-30 112624
#> 3 2013-07-01 2014-06-30 114119
#> 4 2014-07-01 2015-06-30 119799
#> 5 2015-07-01 2016-06-30 138689
#> 6 2016-07-01 2017-06-30 145112
#> 7 2017-07-01 2018-06-30 141012
#> 8 2018-07-01 2019-06-30 144800
#> 9 2019-07-01 2020-06-30 143179
#> 10 2020-07-01 2021-06-30 142318
#> 11 2021-07-01 2022-06-30 133535
#> 12 2022-07-01 2023-06-30 135711