Package: traumar 1.2.6.9000

traumar: Calculate Metrics for Trauma System Performance

Hospitals, hospital systems, and even trauma systems that provide care to injured patients may not be aware of robust metrics that can help gauge the efficacy of their programs in saving the lives of injured patients. 'traumar' provides robust functions driven by the academic literature to automate the calculation of relevant metrics to individuals desiring to measure the performance of their trauma center or even a trauma system. 'traumar' also provides some helper functions for the data analysis journey. Users can refer to the following publications for descriptions of the methods used in 'traumar'. TRISS methodology, including probability of survival, and the W, M, and Z Scores - Flora (1978) <doi:10.1097/00005373-197810000-00003>, Boyd et al. (1987, PMID:3106646), Llullaku et al. (2009) <doi:10.1186/1749-7922-4-2>, Singh et al. (2011) <doi:10.4103/0974-2700.86626>, Baker et al. (1974, PMID:4814394), and Champion et al. (1989) <doi:10.1097/00005373-198905000-00017>. For the Relative Mortality Metric, see Napoli et al. (2017) <doi:10.1080/24725579.2017.1325948>, Schroeder et al. (2019) <doi:10.1080/10903127.2018.1489021>, and Kassar et al. (2016) <doi:10.1177/00031348221093563>. For more information about methods to calculate over- and under-triage in trauma hospital populations and samples, please see the following publications - Peng & Xiang (2016) <doi:10.1016/j.ajem.2016.08.061>, Beam et al. (2022) <doi:10.23937/2474-3674/1510136>, Roden-Foreman et al. (2017) <doi:10.1097/JTN.0000000000000283>.

Authors:Nicolas Foss [aut, cre], Iowa Department of Health and Human Services [cph]

traumar_1.2.6.9000.tar.gz
traumar_1.2.6.9000.zip(r-4.7)traumar_1.2.6.9000.zip(r-4.6)traumar_1.2.6.9000.zip(r-4.5)
traumar_1.2.6.9000.tgz(r-4.6-any)traumar_1.2.6.9000.tgz(r-4.5-any)
traumar_1.2.6.9000.tar.gz(r-4.7-any)traumar_1.2.6.9000.tar.gz(r-4.6-any)
traumar_1.2.6.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
traumar/json (API)
NEWS

# Install 'traumar' in R:
install.packages('traumar', repos = c('https://bemts-hhs.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bemts-hhs/traumar/issues

Pkgdown/docs site:https://bemts-hhs.github.io

On CRAN:

Conda:

emsmortalitypiprobabilityqualitysurvivaltraumatriss

5.19 score 4 stars 60 scripts 479 downloads 30 exports 38 dependencies

Last updated from:d0a85414a7. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK158
source / vignettesOK184
linux-release-x86_64OK158
macos-release-arm64OK147
macos-oldrel-arm64OK141
windows-develOK142
windows-releaseOK132
windows-oldrelOK145
wasm-releaseOK109

Exports:%not_in%imputeis_it_normalnonlinear_binsnormalizepretty_numberpretty_percentprobability_of_survivalrm_bin_summaryrmmseasonseqic_indicator_1seqic_indicator_10seqic_indicator_11seqic_indicator_12seqic_indicator_13seqic_indicator_2seqic_indicator_3seqic_indicator_4seqic_indicator_5seqic_indicator_6seqic_indicator_7seqic_indicator_8seqic_indicator_9small_count_labelstat_sigtheme_cleanertrauma_case_mixtrauma_performanceweekend

Dependencies:backportsbroomclicpp11dplyrfarvergenericsggplot2gluegtablehmsinferisobandlabelinglifecyclelubridatemagrittrnemsqarnortestpatchworkpillarpkgconfigpurrrR6RColorBrewerrlangS7scalesstringistringrtibbletidyrtidyselecttimechangeutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Check if Elements Are Not in a Vector%not_in%
Impute Numeric Column Valuesimpute
Exploratory Data Analysis, Normality Testing, and Visualizationis_it_normal
Create Nonlinear Probability of Survival Binsnonlinear_bins
Normalize a Numeric Vectornormalize
Convert Numbers into Readable Abbreviated Formatspretty_number
Format Numeric Variables as Percentagespretty_percent
Calculate Probability of Survival Using TRISS Methodprobability_of_survival
Bin-Level Summary for Relative Mortality Metric (RMM)rm_bin_summary
Relative Mortality Metric (RMM) Calculationrmm
Get Season Based on a Dateseason
SEQIC Indicator 1 – Trauma Team Response Evaluationseqic_indicator_1
SEQIC Indicator 10 – Trauma Team Activation Appropriatenessseqic_indicator_10
SEQIC Indicator 11 – Overtriage for Minor Trauma Patientsseqic_indicator_11
SEQIC Indicator 12 - Timeliness of Data Entry Post-Dischargeseqic_indicator_12
SEQIC Indicator 13 – Validation of Trauma Registry Recordsseqic_indicator_13
SEQIC Indicator 2 – Missing Incident Timeseqic_indicator_2
SEQIC Indicator 3 - Presence of Probability of Survival Calculationsseqic_indicator_3
SEQIC Indicator 4 - Autopsy and Long LOS Without Autopsyseqic_indicator_4
SEQIC Indicator 5 - Alcohol and Drug Screeningseqic_indicator_5
SEQIC Indicator 6 - Delayed Arrival Following Low GCSseqic_indicator_6
SEQIC Indicator 7 - Delayed Arrival to Definitive Careseqic_indicator_7
SEQIC Indicator 8 - Survival by Risk Groupseqic_indicator_8
SEQIC Indicator 9 - Emergency Department Transfer Timelinessseqic_indicator_9
Label Small Counts Based on a Cutoffsmall_count_label
Assign Significance Codes Based on P-Valuesstat_sig
Customizable Minimalistic ggplot2 Themetheme_cleaner
View the Current Patient Population Case Mix Compared to the Major Trauma Study Case Mixtrauma_case_mix
Calculate Trauma Hospital Performance Based on Robust and Validated Measurestrauma_performance
Classify Dates as Weekday or Weekendweekend