Syncope-01 Calculation

The syncope_01 function processes EMS dataset to identify potential syncope (fainting) cases based on specific criteria and calculates related ECG measures. This function dplyr::filters data for 911 response calls, assesses primary and associated symptoms for syncope, determines age-based populations (adult and pediatric), and aggregates results by unique patient encounters.

Usage

syncope_01(
  df = NULL,
  patient_scene_table = NULL,
  response_table = NULL,
  situation_table = NULL,
  vitals_table = NULL,
  erecord_01_col,
  incident_date_col = NULL,
  patient_DOB_col = NULL,
  epatient_15_col,
  epatient_16_col,
  eresponse_05_col,
  esituation_09_col,
  esituation_10_col,
  esituation_11_col,
  esituation_12_col,
  evitals_04_col,
  ...
)

Arguments

df

Main data frame containing EMS records.

patient_scene_table

A data frame or tibble containing only epatient and escene fields as a fact table. Default is NULL.

response_table

A data frame or tibble containing only the eresponse fields needed for this measure's calculations. Default is NULL.

situation_table

A data.frame or tibble containing only the esituation fields needed for this measure's calculations. Default is NULL.

vitals_table

A data.frame or tibble containing only the evitals fields needed for this measure's calculations. Default is NULL.

erecord_01_col

The column containing unique record identifiers for each encounter.

incident_date_col

Column that contains the incident date. This defaults to NULL as it is optional in case not available due to PII restrictions.

patient_DOB_col

Column that contains the patient's date of birth. This defaults to NULL as it is optional in case not available due to PII restrictions.

epatient_15_col

Column representing the patient age (numeric).

epatient_16_col

Column for the patient age units (e.g., "Years", "Months").

eresponse_05_col

Column containing response type codes, specifically 911 codes.

esituation_09_col

Column with primary symptoms associated with the patient encounter.

esituation_10_col

Column with other associated symptoms.

esituation_11_col

Column for primary impression code.

esituation_12_col

Column for secondary impression codes.

evitals_04_col

Column with ECG information if available.

...

Additional arguments passed to dplyr::summarize for grouped summaries.

Value

A tibble summarizing results for three population groups (Adults, and Peds) with the following columns:

measure: The name of the measure being calculated. pop: Population type (Adults, Peds). numerator: Count of incidents where beta-agonist medications were administered. denominator: Total count of incidents. prop: Proportion of incidents involving beta-agonist medications. prop_label: Proportion formatted as a percentage with a specified number of decimal places.

Author

Nicolas Foss, Ed.D., MS

Examples

# Synthetic test data
  test_data <- tibble::tibble(
    erecord_01 = c("R1", "R2", "R3", "R4", "R5"),
    epatient_15 = c(34, 5, 45, 2, 60),  # Ages
    epatient_16 = c("Years", "Years", "Years", "Months", "Years"),
    eresponse_05 = rep(2205001, 5),
    esituation_09 = c(rep("R55", 3), rep("R40.4", 2)),
    esituation_10 = c(rep("R40.4", 2), rep("R55", 3)),
    esituation_11 = c(rep("R55", 3), rep("R40.4", 2)),
    esituation_12 = c(rep("R40.4", 2), rep("R55", 3)),
    evitals_04 = rep("15 Lead", 5)
  )

  # Run function
  syncope_01(
    df = test_data,
    erecord_01_col = erecord_01,
    epatient_15_col = epatient_15,
    epatient_16_col = epatient_16,
    eresponse_05_col = eresponse_05,
    esituation_09_col = esituation_09,
    esituation_10_col = esituation_10,
    esituation_11_col = esituation_11,
    esituation_12_col = esituation_12,
    evitals_04_col = evitals_04
  )
#> 
#> ── Syncope-01 ──────────────────────────────────────────────────────────────────
#> 
#> ── Gathering Records for Syncope-01 ──
#> 
#> Running `syncope_01_population()`  [Working on 1 of 10 tasks] ●●●●─────────────…
#> Running `syncope_01_population()`  [Working on 2 of 10 tasks] ●●●●●●●──────────…
#> Running `syncope_01_population()`  [Working on 3 of 10 tasks] ●●●●●●●●●●───────…
#> Running `syncope_01_population()`  [Working on 4 of 10 tasks] ●●●●●●●●●●●●●────…
#> Running `syncope_01_population()`  [Working on 5 of 10 tasks] ●●●●●●●●●●●●●●●●─…
#> Running `syncope_01_population()`  [Working on 6 of 10 tasks] ●●●●●●●●●●●●●●●●●…
#> Running `syncope_01_population()`  [Working on 7 of 10 tasks] ●●●●●●●●●●●●●●●●●…
#> Running `syncope_01_population()`  [Working on 8 of 10 tasks] ●●●●●●●●●●●●●●●●●…
#> Running `syncope_01_population()`  [Working on 9 of 10 tasks] ●●●●●●●●●●●●●●●●●…
#> Running `syncope_01_population()`  [Working on 10 of 10 tasks] ●●●●●●●●●●●●●●●●…
#> 
#> 
#> 
#> ── Calculating Syncope-01 ──
#> 
#> 
#> ✔ Function completed in 0.16s.
#> 
#> # A tibble: 2 × 6
#>   measure    pop    numerator denominator  prop prop_label
#>   <chr>      <chr>      <int>       <int> <dbl> <chr>     
#> 1 Syncope-01 Adults         3           3     1 100%      
#> 2 Syncope-01 Peds           2           2     1 100%