Getting started with osdc • osdc

This package serves two overarching purposes:

To provide an open-source, code-based algorithm to classify type 1 and type 2 diabetes using Danish registers as data sources.
To inspire discussions within the Danish register-based research space on the openness and ease of use on the existing tooling and registers, and on the need for an official process for updating or contributing to existing data sources.

To read up on the overall design of this package as well as on the algorithm, check out the vignette("design"). For more explanation on the motivations, rationale, and needs for this algorithm and package, check out the vignette("rationale").

Usage

First, let’s load up the package, as well as dplyr.

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(osdc)

The core of this package depends on the list of variables within different registers that are needed in order to classify the diabetes status of an individual. This can be found in the dataset:

variable_description
#> # A tibble: 38 × 7
#>    register_name               register_abbrev variable_name start_year end_year
#>    <chr>                       <chr>           <chr>              <dbl>    <dbl>
#>  1 CPR-registerets befolkning… bef             pnr                 1968       NA
#>  2 CPR-registerets befolkning… bef             koen                1968       NA
#>  3 CPR-registerets befolkning… bef             foed_dato           1968       NA
#>  4 Laegemiddelstatistikregist… lmdb            pnr                 1995       NA
#>  5 Laegemiddelstatistikregist… lmdb            eksd                1995       NA
#>  6 Laegemiddelstatistikregist… lmdb            atc                 1995       NA
#>  7 Laegemiddelstatistikregist… lmdb            volume              1995       NA
#>  8 Laegemiddelstatistikregist… lmdb            apk                 1995       NA
#>  9 Laegemiddelstatistikregist… lmdb            indo                1995       NA
#> 10 Laegemiddelstatistikregist… lmdb            name                1995       NA
#> # ℹ 28 more rows
#> # ℹ 2 more variables: danish_description <chr>, english_description <chr>

Let’s convert that to a nicer format to show the list as a table.

variable_description |> 
  select(register_name, register_abbrev, variable_name, english_description) |> 
  knitr::kable()

register_name	register_abbrev	variable_name	english_description
CPR-registerets befolkningstabel	bef	pnr	pseudonymised social security number
CPR-registerets befolkningstabel	bef	koen	sex
CPR-registerets befolkningstabel	bef	foed_dato	date of birth
Laegemiddelstatistikregisteret	lmdb	pnr	pseudonymised social security number
Laegemiddelstatistikregisteret	lmdb	eksd	date of purchase
Laegemiddelstatistikregisteret	lmdb	atc	ATC code (fully specified)
Laegemiddelstatistikregisteret	lmdb	volume	number of daily standard doses (DDD) in package
Laegemiddelstatistikregisteret	lmdb	apk	number of packages purchased
Laegemiddelstatistikregisteret	lmdb	indo	indication code
Laegemiddelstatistikregisteret	lmdb	name	drug retail name
Laegemiddelstatistikregisteret	lmdb	vnr	item code
Landspatientregisterets administrationstabel (LPR2)	lpr_adm	pnr	pseudonymised social security number
Landspatientregisterets administrationstabel (LPR2)	lpr_adm	recnum	record id number
Landspatientregisterets administrationstabel (LPR2)	lpr_adm	d_inddto	date of admission or initial contact
Landspatientregisterets administrationstabel (LPR2)	lpr_adm	c_spec	specialty code of department
Landspatientregisterets diagnosetabel (LPR2)	lpr_diag	recnum	record id number
Landspatientregisterets diagnosetabel (LPR2)	lpr_diag	c_diag	diagnosis code
Landspatientregisterets diagnosetabel (LPR2)	lpr_diag	c_diagtype	diagnosis type
Landspatientregisterets kontakttabel (LPR3)	kontakter	cpr	pseudonymised social security number
Landspatientregisterets kontakttabel (LPR3)	kontakter	dw_ek_kontakt	record id number
Landspatientregisterets kontakttabel (LPR3)	kontakter	dato_start	date of admission or initial contact
Landspatientregisterets kontakttabel (LPR3)	kontakter	hovedspeciale_ans	specialty of department
Landspatientregisterets diagnosetabel (LPR3)	diagnoser	dw_ek_kontakt	record id number
Landspatientregisterets diagnosetabel (LPR3)	diagnoser	diagnosekode	diagnosis code
Landspatientregisterets diagnosetabel (LPR3)	diagnoser	diagnosetype	diagnosis type
Landspatientregisterets diagnosetabel (LPR3)	diagnoser	senere_afkraeftet	was the diagnosis retracted later?
Sygesikringsregisteret	sysi	pnr	pseudonymised social security number
Sygesikringsregisteret	sysi	barnmak	was the service provided to the patient’s child?
Sygesikringsregisteret	sysi	speciale	billing code of the service (fully specified)
Sygesikringsregisteret	sysi	honuge	week and year of service
Sygesikringsregisteret	sssy	pnr	pseudonymised social security number
Sygesikringsregisteret	sssy	barnmak	was the service provided to the patient’s child?
Sygesikringsregisteret	sssy	speciale	billing code of the service (fully specified)
Sygesikringsregisteret	sssy	honuge	week and year of service
Laboratoriedatabasens forskertabel	lab_forsker	patient_cpr	pseudonymised social security number
Laboratoriedatabasens forskertabel	lab_forsker	samplingdate	date of sampling
Laboratoriedatabasens forskertabel	lab_forsker	analysiscode	NPU code of analysis
Laboratoriedatabasens forskertabel	lab_forsker	value	numerical result of analysis