Colleagues,
Since when I worked in the hospital, I’ve been interested in the frailty. Recently, a Hospital Frailty Risk Score (HFRS) based on ICD-10 code system was published in Lancet (Gilbert et al., Development and Validation of a Hospital Frailty Risk Score Focusing on Older People in Acute Care Settings Using Electronic Hospital Records: An Observational Study.” The Lancet 391, no. 10132 (May 5, 2018)).
I implemented this score in FeatureExtraction package, and I encourage you to review, evaluate, and validate this score in various real-world database.
The code below describes how to extract this score for your own cohort
devtools::install_github('ABMI/FeatureExtraction', ref= 'hfrs')
library(FeatureExtraction)
connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = dbms,
server = server,
user = user,
password = pw,
port = port)
cdmDatabaseSchema <- ""
cohortDatabaseSchema <- ""
cohortTable <- "cohort"
oracleTempSchema <- NULL
cdmVersion <- "5"
cohortId = cohort definition id of yours (INT)
settings<-createCovariateSettings(useHfrs = TRUE)
covs <- getDbCovariateData(connectionDetails = connectionDetails,
oracleTempSchema = oracleTempSchema,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortId = cohortId,
rowIdField = "subject_id",
covariateSettings = settings,
aggregated = FALSE)
cov.d<-as.data.frame(covs$covariates)
hist(cov.d$covariateValue)