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Calculates the NEMSQA Seizure-02 Measure.

Calculates age-based seizure metrics for a dataset. This function filters data for patients based on incident information, diagnoses, and administered medications to assess adherence to Seizure-02 metrics.

Usage

seizure_02(
  df = NULL,
  patient_scene_table = NULL,
  response_table = NULL,
  situation_table = NULL,
  medications_table = NULL,
  erecord_01_col,
  incident_date_col = NULL,
  patient_DOB_col = NULL,
  epatient_15_col,
  epatient_16_col,
  eresponse_05_col,
  esituation_11_col,
  esituation_12_col,
  emedications_03_col,
  ...
)

Arguments

df

A data frame where each row is an observation, containing all necessary columns for analysis.

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.

medications_table

A data.frame or tibble containing only the emedications 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 name for patient age in numeric form.

epatient_16_col

Column name for age unit (e.g., "Years" or "Months").

eresponse_05_col

Column name for response codes; "911" call codes are filtered.

esituation_11_col

Column name for primary impressions.

esituation_12_col

Column name for secondary impressions.

emedications_03_col

Column name for medications administered; ideally a list column or string with comma-separated values.

...

Additional arguments passed to dplyr::summarize.

Value

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

measure: The name of the measure being calculated. pop: Population type (All, Adults, or 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_11 = rep("G40", 5),
    esituation_12 = rep("r56", 5),
    emedications_03 = rep(3322, 5)
  )

  # Run the function
  seizure_02(
    df = test_data,
    erecord_01_col = erecord_01,
    epatient_15_col = epatient_15,
    epatient_16_col = epatient_16,
    eresponse_05_col = eresponse_05,
    esituation_11_col = esituation_11,
    esituation_12_col = esituation_12,
    emedications_03_col = emedications_03,
  )
#> 
#> ── Seizure-02 ──────────────────────────────────────────────────────────────────
#> 
#> ── Gathering Records for Seizure-02 ──
#> 
#> Running `seizure_02_population()`  [Working on 1 of 10 tasks] ●●●●─────────────
#> Running `seizure_02_population()`  [Working on 2 of 10 tasks] ●●●●●●●──────────
#> Running `seizure_02_population()`  [Working on 3 of 10 tasks] ●●●●●●●●●●───────
#> Running `seizure_02_population()`  [Working on 4 of 10 tasks] ●●●●●●●●●●●●●────
#> Running `seizure_02_population()`  [Working on 5 of 10 tasks] ●●●●●●●●●●●●●●●●
#> Running `seizure_02_population()`  [Working on 6 of 10 tasks] ●●●●●●●●●●●●●●●●●
#> Running `seizure_02_population()`  [Working on 7 of 10 tasks] ●●●●●●●●●●●●●●●●●
#> Running `seizure_02_population()`  [Working on 8 of 10 tasks] ●●●●●●●●●●●●●●●●●
#> Running `seizure_02_population()`  [Working on 9 of 10 tasks] ●●●●●●●●●●●●●●●●●
#> Running `seizure_02_population()`  [Working on 10 of 10 tasks] ●●●●●●●●●●●●●●●●
#> 
#> 
#> 
#> ── Calculating Seizure-02 ──
#> 
#> 
#>  Function completed in 0.15s.
#> 
#> # A tibble: 3 × 6
#>   measure    pop    numerator denominator  prop prop_label
#>   <chr>      <chr>      <int>       <int> <dbl> <chr>     
#> 1 Seizure-02 Adults         3           3     1 100%      
#> 2 Seizure-02 Peds           1           1     1 100%      
#> 3 Seizure-02 All            5           5     1 100%