nemsqar 1.1.2
CRAN release: 2025-07-21
- Fixed broken URLs in the documentation for
nemsqa_binomial_confint()
.
nemsqar 1.1.1
CRAN release: 2025-07-16
In
airway_01_population()
, the filter_process object had one text descriptor"All initial population successful intubation with no hypoxia or hypoxia/hypotension"
which was corrected to be"All initial population successful intubation with no hypoxia/hypotension"
.Also, in
trauma_14_population()
, thefilter_process
object has one text descriptor"Tournique procedure"
which was corrected to be"Tourniquet procedure"
.Additionally, trauma_14_population() should just work after passing an arbitrary number of (applicable) columns to the
transport_disposition
argument. In {nemsqar} 1.1.0, only one column will work as thegrepl()
call is not wrapped indpyr::if_any()
. This was fixed so that users can reference other columns that contain transport disposition data, such as eDisposition.12 from NEMSIS 3.4 (or earlier versions as applicable). This helps with back compatibility when using this measure to earlier versions of NEMSIS, or later versions.
nemsqar 1.1.0
CRAN release: 2025-03-13
Enhancements
-
Optional Confidence Intervals: Added the ability to compute confidence intervals using the Wilson or Clopper-Pearson (exact) method. This feature is optional and can be enabled when working with sample data.
- Introduced
nemsqa_binomial_confint()
, a lightweight wrapper aroundprop.test()
andbinom.test()
for calculating Wilson and exact confidence intervals. This function eliminates the need for an additional package dependency.- Ensure warning messages where any
denominator
< 10 are elegant and helpful, andnemsqa_binomial_confit()
handles division by zero cases well.
- Ensure warning messages where any
- Updated all wrapper functions (e.g.,
airway_01()
) to support optional confidence interval calculation. - Maintained full backward compatibility with nemsqar 1.0.0 by setting
confidence_interval = FALSE
as the default behavior.
- Introduced
-
Dynamic
results_summarize()
: Enhancedresults_summarize()
to dynamically calculate only the specified groups, utilizing the previously unusedpopulation_labels
object. This reduces unnecessary calculations and streamlines function performance. -
Improved Documentation:
- Updated and expanded the documentation for
results_summarize()
andsummarize_measure()
, offering clearer usage instructions and examples to enhance the user experience. - Refined the documentation for multiple other functions, improving clarity and usability.
- Updated and expanded the documentation for
nemsqar 0.1.0
Package Inception
- nemsqar is born! This initial version laid the foundation for calculating National EMS Quality Alliance (NEMSQA) performance measures in a structured and modular way.
Key Features
- Designed core functions to identify target populations and compute performance measures for EMS quality metrics.
- Implemented a modular structure for measure calculations, with
_population
workhorse functions handling data extraction andmeasure_##
wrapper functions streamlining performance calculations. - Developed functions to align with NEMSQA measure technical documents.
Implemented Functions
Population Functions
-
airway_01_population()
,airway_05_population()
,airway_18_population()
-
asthma_01_population()
,hypoglycemia_01_population()
,pediatrics_03b_population()
-
respiratory_01_population()
,respiratory_02_population()
,safety_01_population()
-
safety_02_population()
,safety_04_population()
,seizure_02_population()
-
stroke_01_population()
,syncope_01_population()
,tbi_01_population()
-
trauma_01_population()
,trauma_03_population()
,trauma_04_population()
-
trauma_08_population()
,trauma_14_population()
,ttr_01_population()