Getting started with dxpr package

dxpr

I. Introduction

The proposed open-source dxpr package is a software tool aimed at expediting an integrated analysis of electronic health records (EHRs). The dxpr package provides mechanisms to integrate, analyze, and visualize clinical data, including diagnosis and procedure records.

Feature

  • Data integration Transform codes into uniform format and group code into several categories.
  • Data Wrangling Generate statistical information about dataset and transform data into wide format, which fits better to other analytical and plotting packages.
  • Visualization Provide overviews for the result of diagnoses standardization and the grouped categories of diagnosis codes.

Getting started

Development version 

# install.packages("remotes")
remotes::install_github("DHLab-TSENG/dxpr")

Overview

Usage 

library(dxpr)  
 
head(sampleDxFile)  
#>     ID  ICD       Date Version
#> 1:  A2 Z992 2020-05-22      10
#> 2:  A5 Z992 2020-01-24      10
#> 3:  A8 Z992 2015-10-27      10
#> 4: A13 Z992 2020-04-26      10
#> 5: A13 Z992 2025-02-02      10
#> 6: A15 Z992 2023-05-12      10

# I. Data integration
#   1. Data standardization
short <- icdDxDecimalToShort(dxDataFile = sampleDxFile, 
                             icdColName = ICD, 
                             dateColName = Date,
                             icd10usingDate = "2015/10/01")
head(short$ICD)
#>     ICD
#> 1: Z992
#> 2: Z992
#> 3: Z992
#> 4: Z992
#> 5: Z992
#> 6: Z992

tail(short$Error)
#>       ICD count IcdVersionInFile     WrongType Suggestion
#> 1:  75.52     4            ICD 9  Wrong format           
#> 2:  E03.0     4            ICD 9 Wrong version           
#> 3:    650     4           ICD 10 Wrong version           
#> 4: 123.45     3           ICD 10  Wrong format           
#> 5:  755.2     3            ICD 9  Wrong format     755.29
#> 6:   7552     2            ICD 9  Wrong format      75529

#   2. Data grouping
ELIX <- icdDxToComorbid(dxDataFile = sampleDxFile, 
                        idColName = ID, 
                        icdColName = ICD, 
                        dateColName = Date, 
                        icd10usingDate = "2015/10/01", 
                        comorbidMethod = elix)
head(ELIX$groupedDT)
#>    Short  ID  ICD       Date Comorbidity
#> 1:  Z992  A2 Z992 2020-05-22    RENLFAIL
#> 2:  Z992  A5 Z992 2020-01-24    RENLFAIL
#> 3:  Z992  A8 Z992 2015-10-27    RENLFAIL
#> 4:  Z992 A13 Z992 2020-04-26    RENLFAIL
#> 5:  Z992 A13 Z992 2025-02-02    RENLFAIL
#> 6:  Z992 A15 Z992 2023-05-12    RENLFAIL

head(ELIX$summarised_groupedDT)
#>     ID Comorbidity firstCaseDate endCaseDate count    period
#> 1:  A0    RENLFAIL    2009-07-25  2013-12-20     5 1609 days
#> 2:  A1    RENLFAIL    2006-11-29  2014-09-24     5 2856 days
#> 3: A10    RENLFAIL    2007-11-04  2012-07-30     5 1730 days
#> 4: A11    RENLFAIL    2008-03-09  2011-09-03     5 1273 days
#> 5: A12    RENLFAIL    2006-05-14  2015-06-29     5 3333 days
#> 6: A13    RENLFAIL    2006-04-29  2025-02-02     5 6854 days

# II. Data wrangling
groupedDataWide <- groupedDataLongToWide(dxDataFile = ELIX$groupedDT, 
                                         idColName = ID, 
                                         categoryColName = Comorbidity, 
                                         dateColName = Date)
head(groupedDataWide[,1:4])
#>     ID  ARTH CHRNLUNG  DMCX
#> 1:  A0 FALSE    FALSE FALSE
#> 2:  A1 FALSE    FALSE FALSE
#> 3: A10 FALSE    FALSE FALSE
#> 4: A11 FALSE    FALSE FALSE
#> 5: A12 FALSE    FALSE FALSE
#> 6: A13 FALSE    FALSE FALSE

# IV. Visualization
plot_errorICD <- plotICDError(short$Error)  
plot_groupedData <- plotDiagCat(groupedDataWide, ID)

plot_errorICD
#> $graph

#> 
#> $ICD
#>        ICD count CumCountPerc IcdVersionInFile     WrongType Suggestion
#>  1:  A0.11    20       18.35%           ICD 10  Wrong format           
#>  2:  V27.0    18       34.86%           ICD 10 Wrong version           
#>  3:   E114     8        42.2%           ICD 10  Wrong format           
#>  4: A01.05     8       49.54%            ICD 9 Wrong version           
#>  5:  42761     7       55.96%           ICD 10 Wrong version           
#>  6:  Z9.90     6       61.47%           ICD 10  Wrong format           
#>  7:    F42     6       66.97%           ICD 10  Wrong format           
#>  8:  V24.1     6       72.48%           ICD 10 Wrong version           
#>  9:  A0105     5       77.06%            ICD 9 Wrong version           
#> 10:    001     5       81.65%            ICD 9  Wrong format       0019
#> 11: others    20         100%            ICD 9  Wrong format

plot_groupedData
#> $graph

#> 
#> $sigCate
#>     DiagnosticCategory  N Percentage
#>  1:           RENLFAIL 24      63.16
#>  2:              TUMOR  6      15.79
#>  3:               ARTH  5      13.16
#>  4:              LYMPH  4      10.53
#>  5:              PSYCH  4      10.53
#>  6:               DRUG  3       7.89
#>  7:              NEURO  3       7.89
#>  8:               PARA  2       5.26
#>  9:           PERIVASC  2       5.26
#> 10:              VALVE  2       5.26

Getting help

See the GitHub issues page (https://github.com/DHLab-TSENG/dxpr/issues) to see open issues and feature requests.