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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
<!-- badges: start -->
[![codecov.io](https://codecov.io/github/darwin-eu/CodelistGenerator/coverage.svg?branch=main)](https://codecov.io/github/darwin-eu/CodelistGenerator?branch=main)
[![R-CMD-check](https://github.com/darwin-eu/CodelistGenerator/workflows/R-CMD-check/badge.svg)](https://github.com/darwin-eu/CodelistGenerator/actions)
[![Lifecycle:Experimental](https://img.shields.io/badge/Lifecycle-Experimental-339999)](https://www.tidyverse.org/lifecycle/#experimental)
<!-- badges: end -->
# CodelistGenerator
## Introduction
CodelistGenerator is used to create a candidate set of codes for helping to define patient cohorts in data mapped to the OMOP common data model. A little like the process for a systematic review, the idea is that for a specified search strategy, CodelistGenerator will identify a set of concepts that may be relevant, with these then being screened to remove any irrelevant codes.
## Installation
You can install the development version of CodelistGenerator like so:
``` r
install.packages("remotes")
remotes::install_github("darwin-eu/CodelistGenerator")
```
## Connecting to the OMOP CDM vocabularies
```{r, eval=FALSE}
# example with postgres database connection details
server_dbi<-Sys.getenv("server")
user<-Sys.getenv("user")
password<- Sys.getenv("password")
port<-Sys.getenv("port")
host<-Sys.getenv("host")
db <- DBI::dbConnect(RPostgres::Postgres(),
dbname = server_dbi,
port = port,
host = host,
user = user,
password = password)
# name of vocabulary schema
vocabulary_database_schema<-Sys.getenv("vocabulary_schema")
```
## Example search
Every codelist is specific to a version of the OMOP CDM vocabularies, so we can first check the version.
```{r example, message=FALSE, warning=FALSE,echo=FALSE}
library(DBI)
library(RPostgres)
library(dplyr)
library(CodelistGenerator)
library(kableExtra)
# usethis::edit_r_environ()
server_dbi<-Sys.getenv("SERVER_DBI_FEB22")
user<-Sys.getenv("DB_USER_FEB22")
password<- Sys.getenv("DB_PASSWORD_FEB22")
port<-Sys.getenv("DB_PORT_FEB22")
host<-Sys.getenv("DB_HOST_FEB22")
db <- dbConnect(RPostgres::Postgres(),
dbname = server_dbi,
port = port,
host = host,
user = user,
password = password)
vocabulary_database_schema<-Sys.getenv("DB_VOCAB_FEB22")
```
```{r, message=FALSE, warning=FALSE}
dplyr::tbl(db, dplyr::sql(paste0(
"SELECT * FROM ",
vocabulary_database_schema,
".vocabulary"
))) %>%
dplyr::rename_with(tolower) %>%
dplyr::filter(.data$vocabulary_id == "None") %>%
dplyr::select("vocabulary_version") %>%
dplyr::collect() %>%
dplyr::pull()
```
We can then search for asthma like so
```{r, message=FALSE, warning=FALSE}
asthma_1<-get_candidate_codes(keywords="asthma",
domains = "Condition",
db=db,
vocabulary_database_schema = vocabulary_database_schema)
kable(head(asthma_1, 10))
```
Perhaps we want to exclude certain concepts as part of the search strategy, in which case this can be added like so
```{r, message=FALSE, warning=FALSE}
asthma_2<-get_candidate_codes(keywords="asthma",
domains = "Condition",
exclude = "Poisoning by antiasthmatic",
db=db,
vocabulary_database_schema = vocabulary_database_schema)
kable(head(asthma_2, 10))
```
We can then also see source codes these are mapped from, for example
```{r, message=FALSE, warning=FALSE}
asthma_icd_mappings<-show_mappings(candidate_codelist=asthma_2,
source_vocabularies="ICD10CM",
db=db,
vocabulary_database_schema = vocabulary_database_schema)
kable(head(asthma_icd_mappings %>%
select(standard_concept_name,
standard_vocabulary_id,
source_concept_name,
source_vocabulary_id),
10))
```
```{r, message=FALSE, warning=FALSE, echo=FALSE}
dbDisconnect(db)
```