Retrieves a list of all tags from the CVDPREVENT API that can be used to filter indicators. Tags provide a way to categorise and search for indicators by clinical or reporting groupings (such as "Priority Group", "Pathway Group" or other clinical categories).
Use this function to obtain valid tag IDs for use in functions that support filtering by tag, such as cvd_indicator().
Value
A tibble with one row per available indicator tag, containing the following colunns:
- IndicatorTagID
Integer. Unique identifier for the tag associated with an indicator.
- IndicatorTagName
Character. Descriptive label categorising the indicator (e.g., "monitoring", "prevention", "smoking").
If no tags are found, returns a tibble describing the error.
Details
Tags are useful for grouping or filtering indicators in dashboards, reports or scripted analyses. Tag IDs returned by this function can be supplied to functions like cvd_indicator() via the tag_id argument for targeted queries.
See also
cvd_indicator_list(), cvd_indicator_metric_list(), cvd_indicator(), cvd_indicator_details(), cvd_indicator_sibling(), cvd_indicator_child_data(), cvd_indicator_data(), cvd_indicator_metric_data(), cvd_indicator_raw_data(), cvd_indicator_nationalarea_metric_data(), cvd_indicator_priority_groups(), cvd_indicator_pathway_group(), cvd_indicator_group(), cvd_indicator_metric_timeseries(), cvd_indicator_person_timeseries(), cvd_indicator_metric_systemlevel_comparison(), cvd_indicator_metric_area_breakdown()
Examples
# \donttest{
# List the first five indicator tags
cvd_indicator_tags() |>
dplyr::arrange(IndicatorTagID) |>
dplyr::slice_head(n = 5)
#> # A tibble: 5 × 2
#> IndicatorTagID IndicatorTagName
#> <int> <chr>
#> 1 1 prevalence
#> 2 2 atrial fibrillation
#> 3 3 hypertension
#> 4 4 blood pressure measures
#> 5 5 cardiovascular disease
# Use a tag ID to filter indicators in another query
tags <- cvd_indicator_tags()
tag_id <- tags$IndicatorTagID[1]
cvd_indicator(time_period_id = 17, area_id = 3, tag_id = tag_id)
#> $indicators
#> # A tibble: 8 × 14
#> AxisCharacter DataUpdateInterval FormatDisplayName HighestPriorityNotif…¹
#> <chr> <lgl> <chr> <chr>
#> 1 "%" NA Proportion % NA
#> 2 "%" NA Proportion % NA
#> 3 "%" NA Proportion % NA
#> 4 "%" NA Proportion % NA
#> 5 "%" NA Proportion % NA
#> 6 "%" NA Proportion % NA
#> 7 "%" NA Proportion % NA
#> 8 " " NA Rate per 10,000 patie… Blue
#> # ℹ abbreviated name: ¹HighestPriorityNotificationType
#> # ℹ 10 more variables: IndicatorCode <chr>, IndicatorFormatID <int>,
#> # IndicatorID <int>, IndicatorName <chr>, IndicatorOrder <int>,
#> # IndicatorShortName <chr>, IndicatorStatus <lgl>, IndicatorTypeID <int>,
#> # IndicatorTypeName <chr>, NotificationCount <int>
#>
#> $metric_categories
#> # A tibble: 144 × 7
#> IndicatorID CategoryAttribute MetricCategoryID MetricCategoryName
#> <int> <chr> <int> <chr>
#> 1 1 Persons 30 Persons
#> 2 1 Female 28 Female
#> 3 1 Male 29 Male
#> 4 1 Male 4 18-39
#> 5 1 Female 5 18-39
#> 6 1 Persons 6 18-39
#> 7 1 Male 7 40-59
#> 8 1 Female 8 40-59
#> 9 1 Persons 9 40-59
#> 10 1 Male 10 60-79
#> # ℹ 134 more rows
#> # ℹ 3 more variables: MetricCategoryOrder <int>, MetricCategoryTypeName <chr>,
#> # MetricID <int>
#>
#> $metric_data
#> # A tibble: 144 × 1
#> MetricID
#> <int>
#> 1 190
#> 2 171
#> 3 172
#> 4 177
#> 5 180
#> 6 186
#> 7 175
#> 8 173
#> 9 187
#> 10 179
#> # ℹ 134 more rows
#>
#> $timeseries_data
#> # A tibble: 495 × 7
#> MetricID EndDate Median StartDate TimePeriodID TimePeriodName Value
#> <int> <chr> <dbl> <chr> <int> <chr> <dbl>
#> 1 190 Tue, 31 Mar 2020… 2.65 Mon, 01 … 1 To March 2020 2.4
#> 2 190 Wed, 31 Mar 2021… 2.5 Mon, 01 … 2 To March 2021 2.4
#> 3 190 Thu, 30 Sep 2021… 2.5 Mon, 01 … 3 To September … 2.3
#> 4 190 Thu, 31 Mar 2022… 2.54 Mon, 01 … 4 To March 2022 2.32
#> 5 171 Tue, 31 Mar 2020… 2.2 Mon, 01 … 1 To March 2020 2
#> 6 171 Wed, 31 Mar 2021… 2.1 Mon, 01 … 2 To March 2021 2
#> 7 171 Thu, 30 Sep 2021… 2.1 Mon, 01 … 3 To September … 2
#> 8 171 Thu, 31 Mar 2022… 2.11 Mon, 01 … 4 To March 2022 1.94
#> 9 172 Tue, 31 Mar 2020… 3.1 Mon, 01 … 1 To March 2020 2.8
#> 10 172 Wed, 31 Mar 2021… 3 Mon, 01 … 2 To March 2021 2.8
#> # ℹ 485 more rows
#>
# }