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Pediatrics-03B Calculation

Source: R/pediatrics_03b.R
pediatrics_03b.Rd

The function calculates a pediatric metric focused on EMS responses, specifically targeting responses that involve patients under 18 years of age, where certain weight-based medications were administered. This function filters EMS data to identify relevant 911 responses and further narrows down the dataset to cases involving children, calculating the proportion of cases with documented weight among those where weight-based medications were administered.

Usage

pediatrics_03b(
  df = NULL,
  patient_scene_table = NULL,
  response_table = NULL,
  exam_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,
  eexam_01_col,
  eexam_02_col,
  emedications_03_col,
  emedications_04_col,
  ...
)

Arguments

df

A data frame or tibble containing emergency response records. Default is NULL.

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.

exam_table

A data.frame or tibble containing only the eExam 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

Column for unique EMS record identifiers.

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 giving the calculated age value.

epatient_16_col

Column giving the provided age unit value.

eresponse_05_col

Column containing the EMS response codes.

eexam_01_col

Column containing documented weight information.

eexam_02_col

Another column for weight documentation, if applicable.

emedications_03_col

Column indicating medication administration.

emedications_04_col

Column listing medications administered.

...

Additional parameters for the dplyr::summarize output.

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, Peds). numerator: Count of incidents where patient weight was documented. denominator: Total count of incidents. prop: Proportion of incidents where patient weight was documented. 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"),
  incident_date = as.Date(c("2025-01-01", "2025-01-05", "2025-02-01",
  "2025-06-01", "2025-12-15")),
  patient_dob = as.Date(c("2021-01-01", "2020-01-01", "2022-02-01",
  "2023-06-01", "2019-12-15")),
  epatient_15 = c(4, 5, 3, 2, 6),  # Ages
  epatient_16 = c("Years", "Years", "Years", "Years", "Years"),
  eresponse_05 = rep(2205001, 5),
  emedications_03 = rep("stuff", 5),
  emedications_04 = c("Inhalation", "pill", "liquid", "pill", "liquid"),
  eexam_01 = c(60, 59, 58, 57, 56),
  eexam_02 = c("Red", "Purple", "Grey", "Yellow", "Orange")
)

# Run function
pediatrics_03b(
  df = test_data,
  erecord_01_col = erecord_01,
  incident_date_col = incident_date,
  patient_DOB_col = patient_dob,
  epatient_15_col = epatient_15,
  epatient_16_col = epatient_16,
  eresponse_05_col = eresponse_05,
  emedications_03_col = emedications_03,
  emedications_04_col = emedications_04,
  eexam_01_col = eexam_01,
  eexam_02_col = eexam_02
)
#> 
#> ── Pediatrics-03b ──────────────────────────────────────────────────────────────
#> 
#> ── Gathering Records for Pediatrics-03b ──
#> 
#> Running `pediatrics_03b_population()`  [Working on 1 of 9 tasks] ●●●●──────────…
#> Running `pediatrics_03b_population()`  [Working on 2 of 9 tasks] ●●●●●●●●──────…
#> Running `pediatrics_03b_population()`  [Working on 3 of 9 tasks] ●●●●●●●●●●●───…
#> Running `pediatrics_03b_population()`  [Working on 4 of 9 tasks] ●●●●●●●●●●●●●●…
#> Running `pediatrics_03b_population()`  [Working on 5 of 9 tasks] ●●●●●●●●●●●●●●…
#> Running `pediatrics_03b_population()`  [Working on 6 of 9 tasks] ●●●●●●●●●●●●●●…
#> Running `pediatrics_03b_population()`  [Working on 7 of 9 tasks] ●●●●●●●●●●●●●●…
#> Running `pediatrics_03b_population()`  [Working on 8 of 9 tasks] ●●●●●●●●●●●●●●…
#> Running `pediatrics_03b_population()`  [Working on 9 of 9 tasks] ●●●●●●●●●●●●●●…
#> 
#> 
#> 
#> ── Calculating Pediatrics-03b ──
#> 
#> 
#> ✔ Function completed in 0.14s.
#> 
#> # A tibble: 1 × 6
#>   measure        pop   numerator denominator  prop prop_label
#>   <chr>          <chr>     <int>       <int> <dbl> <chr>     
#> 1 Pediatrics-03b Peds          4           4     1 100%