The hypoglycemia_01 function calculates the NEMSQA measure evaluating how
often hypoglycemic patients with altered mental status receive hypoglycemia
treatment.
Usage
hypoglycemia_01(
df = NULL,
patient_scene_table = NULL,
response_table = NULL,
situation_table = NULL,
vitals_table = NULL,
medications_table = NULL,
procedures_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,
evitals_18_col,
evitals_23_col,
evitals_26_col,
emedications_03_col,
eprocedures_03_col,
...
)Arguments
- df
A data frame or tibble containing emergency response records. Default is
NULL.- patient_scene_table
A data.frame or tibble containing at least ePatient and eScene fields as a fact table. Default is
NULL.- response_table
A data.frame or tibble containing at least the eResponse fields needed for this measure's calculations. Default is
NULL.- situation_table
A data.frame or tibble containing at least the eSituation fields needed for this measure's calculations. Default is
NULL.- vitals_table
A data.frame or tibble containing at least the eVitals fields needed for this measure's calculations. Default is
NULL.- medications_table
A data.frame or tibble containing at least the eMedications fields needed for this measure's calculations. Default is
NULL.- procedures_table
A data.frame or tibble containing at least the eProcedures fields needed for this measure's calculations. Default is
NULL.- erecord_01_col
Column representing the unique record identifier.
- incident_date_col
Column that contains the incident date. This defaults to
NULLas 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
NULLas it is optional in case not available due to PII restrictions.- epatient_15_col
Column representing the patient's numeric age agnostic of unit.
- epatient_16_col
Column representing the patient's age unit ("Years", "Months", "Days", "Hours", or "Minute").
- eresponse_05_col
Column containing response type codes.
- esituation_11_col
Column for primary impression fields, containing ICD-10 codes.
- esituation_12_col
Column for secondary impression fields, containing ICD-10 codes.
- evitals_18_col
Column for blood glucose levels.
- evitals_23_col
Column for Glasgow Coma Scale (GCS) scores.
- evitals_26_col
Column for AVPU alertness levels.
- emedications_03_col
Column for administered medications.
- eprocedures_03_col
Column for procedures performed.
- ...
Additional arguments for summarization, passed to the summarize function.
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 specific hypoglycemia best practices were administered.
denominator: Total count of incidents.
prop: Proportion of incidents
where specific hypoglycemia best practices were administered.
prop_label:
Proportion formatted as a percentage with a specified number of decimal
places.
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 = c(rep("E13.64", 3), rep("E16.2", 2)),
esituation_12 = c(rep("E13.64", 2), rep("E16.2", 3)),
emedications_03 = c(372326, 376937,
377980, 4850,
4832),
evitals_18 = c(60, 59, 58, 57, 56),
evitals_23 = c(16, 15, 14, 13, 12),
evitals_26 = c("Alert", "Painful", "Verbal", "Unresponsive", "Alert"),
eprocedures_03 = rep("710925007", 5)
)
# Run the function
hypoglycemia_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_11_col = esituation_11,
esituation_12_col = esituation_12,
emedications_03_col = emedications_03,
evitals_18_col = evitals_18,
evitals_23_col = evitals_23,
evitals_26_col = evitals_26,
eprocedures_03_col = eprocedures_03
)
#>
#> ── Hypoglycemia-01 ─────────────────────────────────────────────────────────────
#>
#> ── Gathering Records for Hypoglycemia-01 ──
#>
#> Running `hypoglycemia_01_population()` [Working on 1 of 17 tasks] ●●●─────────…
#> Running `hypoglycemia_01_population()` [Working on 2 of 17 tasks] ●●●●●───────…
#> Running `hypoglycemia_01_population()` [Working on 3 of 17 tasks] ●●●●●●──────…
#> Running `hypoglycemia_01_population()` [Working on 4 of 17 tasks] ●●●●●●●●────…
#> Running `hypoglycemia_01_population()` [Working on 5 of 17 tasks] ●●●●●●●●●●──…
#> Running `hypoglycemia_01_population()` [Working on 6 of 17 tasks] ●●●●●●●●●●●●…
#> Running `hypoglycemia_01_population()` [Working on 7 of 17 tasks] ●●●●●●●●●●●●…
#> Running `hypoglycemia_01_population()` [Working on 8 of 17 tasks] ●●●●●●●●●●●●…
#> Running `hypoglycemia_01_population()` [Working on 9 of 17 tasks] ●●●●●●●●●●●●…
#> Running `hypoglycemia_01_population()` [Working on 10 of 17 tasks] ●●●●●●●●●●●…
#> Running `hypoglycemia_01_population()` [Working on 11 of 17 tasks] ●●●●●●●●●●●…
#> Running `hypoglycemia_01_population()` [Working on 12 of 17 tasks] ●●●●●●●●●●●…
#> Running `hypoglycemia_01_population()` [Working on 13 of 17 tasks] ●●●●●●●●●●●…
#> Running `hypoglycemia_01_population()` [Working on 14 of 17 tasks] ●●●●●●●●●●●…
#> Running `hypoglycemia_01_population()` [Working on 15 of 17 tasks] ●●●●●●●●●●●…
#> Running `hypoglycemia_01_population()` [Working on 16 of 17 tasks] ●●●●●●●●●●●…
#> Running `hypoglycemia_01_population()` [Working on 17 of 17 tasks] ●●●●●●●●●●●…
#>
#>
#>
#> ── Calculating Hypoglycemia-01 ──
#>
#>
#> ✔ Function completed in 0.23s.
#>
#> # A tibble: 3 × 6
#> measure pop numerator denominator prop prop_label
#> <chr> <chr> <int> <int> <dbl> <chr>
#> 1 Hypoglycemia-01 Adults 2 2 1 100%
#> 2 Hypoglycemia-01 Peds 2 2 1 100%
#> 3 Hypoglycemia-01 All 4 4 1 100%