Register reference

Variable names for the most commonly used DST registers

Published

June 6, 2026

Warning

For DARTER: Check when cleaned-data was last updated before running the pipeline.

The registers in cleaned-data/ are not necessarily updated to today. Check the modification date on the DST server:

file.info("E:/workdata/[projectnumber]/cleaned-data/parquet-registers/")$mtime

Consider: when does your follow-up extend to, and are the registers updated up to that date? An outdated extraction cuts off censoring dates and outcomes too early — no error message, just silently wrong results. If the registers do not cover your study period, you need to order a new extraction from DST.

All column names on this page are confirmed on DST 2026-05-15 via colnames(). They are shown after rename_with(tolower) has been called. Key columns — the ones you actually use in the code — are marked in bold.

Note

Opening registers — two ways: The code examples on this page use open_dataset("path/to/register/") as a generic placeholder — replace with the path to your project’s parquet folder. DARTER users can use load_database("registername") — see DARTER — Register paths and datastores.

See Pitfalls for special quirks with each register. Column names apply after rename_with(tolower) — inspect your own register with colnames() if something does not match.

Tip

Looking for “which register contains X?” — start with the decision table in Phase 8 — Know your registers. This page is the deep reference with full column names, types and code examples.

Overview — all registers

Register	Register name	Join key	Period	Critical column
BEF	`"bef"`	`pnr`	All years	`koen`, `foed_dag`, `familie_id`
DODSAARS	`"dodsaars"`	`pnr`	See project guide	`d_dodsdto` (death date for censoring)
VNDS	`"vnds"`	`pnr`	All years	`indud_kode`, `haend_dato`
LPR2 contacts	`"lpr_adm"`	`recnum`	Up to March 2019	`d_inddto`, `c_pattype`
LPR2 diagnoses	`"lpr_diag"`	`recnum`	Up to March 2019	`c_diag`, `c_diagtype`
LPR2 SKS procedures	`"lpr_sksopr"`	`recnum`	Up to 2018	`c_opr`, `d_odto`
LPR2 psych contacts	`"t_psyk_adm"`	`k_recnum` → `recnum`	1995–March 2019	`v_cpr` → `pnr`
LPR2 psych diagnoses	`"t_psyk_diag"`	`v_recnum` → `recnum`	1995–March 2019	`c_diag`, `c_diagtype`
LPR3 contacts	`"lpr_a_kontakt"`	`dw_ek_kontakt`	March 2019+	`kont_starttidspunkt` (datetime)
LPR3 diagnoses	`"lpr_a_diagnose"`	`dw_ek_kontakt`	March 2019+	`diag_kode`, `diag_kode_type`, `senere_afkraeftet`
LPR3 SKS procedures	`"procedurer_kirurgi"`	`dw_ek_forloeb`	2019+	`procedurekode`, `dato_start`
LMDB	`"lmdb"`	`pnr`	Approx. 1994+	`atc`, `eksd`
UDDA	`"udda"`	`pnr`	All years	`hfaudd`, `aar`
FAIK	`"faik"`	`familie_id`	All years	`famaekvivadisp_13`
AKM	`"akm"`	`pnr`	All years	`socio13`, `aar`
Project-specific registers	See project guide	`pnr`	Varies	DARTER: see register paths →

1. Demographics and deaths

BEF — Population Register

Status register — one snapshot per person per reference time point (ultimo the period). Delivered quarterly since 2008 (March, June, September, December); before 2008 December only. Whether aar == 2020 corresponds to a particular reference time point depends on the project convention — confirm in your project guide. A person who dies during 2020 still appears in the 2020 snapshot — use DODSAARS to determine whether a person was alive on a specific date.

Column	Type	Contents
`pnr`	character	Personal identifier
`koen`	numeric	Sex: 1 = male, 2 = female
`foed_dag`	Date	Date of birth
`aar`	integer	Register year (one record per year)
`familie_id`	character	Household key — join to FAIK
`reg`	character	Region
`civst`	character	Marital status

Note

BEF does not contain date of death. Use DODSAARS (d_dodsdto) for censoring. See DST’s official BEF documentation: statistikdokumentation/befolkningen →

DODSAARS — Death Register

One row per deceased person.

Note

Coverage period and availability depends on your project’s cleaned-data. Check the modification date and ask your data manager about current coverage.

Column	Type	Contents
`pnr`	character	Personal identifier
`d_dodsdto`	Date	Date of death — use this for censoring
`fdato`	Date	Date of birth
`c_sex`	character	Sex
`v_alder`	numeric	Age at death
`year`	integer	Year of death
`c_dod1`	character	Underlying cause of death (ICD-10)
`c_dod2`–`c_dod4`	character	Contributing causes of death
`c_dodskom`	character	Manner/place of death
`c_bopkom`	character	Municipality of residence at death

Warning

dodsaasg is the classification register for causes of death — it is not the source for individual death dates. Always use dodsaars with the column d_dodsdto.

VNDS — Migration Register

One row per migration event per person.

Column	Type	Contents
`pnr`	character	Personal identifier
`indud_kode`	character	`"U"` = emigration (use for censoring), `"I"` = immigration
`haend_dato`	Date	Event date

Use: filter(indud_kode == "U") → min(haend_dato) per pnr for first emigration date. Non-emigrants do not appear in VNDS with a “U” event and get emigration_date = NA.

2. LPR2 — Somatic (up to March 2019)

Join: lpr_adm LEFT JOIN lpr_diag ON recnum.

lpr_adm — Contacts

Column	Type	Contents
`recnum`	character	Contact key — join to lpr_diag
`pnr`	character	Personal identifier
`d_inddto`	Date	Admission date — use as contact date
`c_pattype`	character	Contact type: `"0"` = inpatient, `"1"` = outpatient, `"2"` = emergency
`d_uddto`	Date	Discharge date
`c_adiag`	character	Action diagnosis (copy — use lpr_diag via join instead)
`c_spec`	character	Specialty code
`year`	integer	Year

lpr_diag — Diagnoses

Column	Type	Contents
`recnum`	character	Join key to lpr_adm
`c_diag`	character	ICD-10 code with D-prefix (e.g. `"DG30"`) — use `substr(c_diag, 2, 4)`
`c_diagtype`	character	`"A"` = action diagnosis, `"B"` = secondary diagnosis, `"G"` = underlying condition
`c_diagmod`	character	Diagnosis modifier
`year`	integer	Year

3. LPR2 — Psychiatric (1995 – March 2019)

Psychiatric contacts before March 2019 are in separate registers from somatic LPR2. From March 2019, LPR3 covers both in one table.

Warning

If you forget to query the psychiatric registers for the period 1995–2019, you miss all dementia diagnoses (F00–F03) recorded at geriatric psychiatry outpatient clinics and memory clinics. Those patients will appear dementia-free and remain in the cohort as false negatives.

t_psyk_adm — Psychiatric contacts

Column names differ from somatic LPR2 — rename at load:

psyk_adm <- open_dataset("path/to/t_psyk_adm/") %>%
  rename_with(tolower) %>%
  rename(pnr = v_cpr, recnum = k_recnum)

Raw column name	After rename	Type	Contents
`v_cpr`	→ `pnr`	character	Personal identifier
`k_recnum`	→ `recnum`	character	Contact key — join to t_psyk_diag
`d_inddto`	(unchanged)	Date	Contact date — same as lpr_adm
`c_pattype`	(unchanged)	character	Contact type

t_psyk_diag — Psychiatric diagnoses

psyk_diag <- open_dataset("path/to/t_psyk_diag/") %>%
  rename_with(tolower) %>%
  rename(recnum = v_recnum)

Raw column name	After rename	Type	Contents
`v_recnum`	→ `recnum`	character	Join key to t_psyk_adm
`c_diag`	(unchanged)	character	ICD-10 with D-prefix — use `substr(c_diag, 2, 4)`
`c_diagtype`	(unchanged)	character	`"A"` / `"B"` / `"G"` — same as lpr_diag

4. LPR3 (March 2019 and onwards)

LPR3 covers both somatic and psychiatric contacts in one table. Join: lpr_a_kontakt LEFT JOIN lpr_a_diagnose ON dw_ek_kontakt.

Note

The “a” in lpr_a_diagnose does not mean A-type diagnoses. It refers to the analysis model designation for the LPR3 series (LPR_A, introduced 2025). The table contains all types: A, B and G — you still need to filter on diag_kode_type.

lpr_a_kontakt — Contacts

Column	Type	Contents
`pnr`	character	Personal identifier
`dw_ek_kontakt`	character	Contact key — join to lpr_a_diagnose
`kont_starttidspunkt`	datetime	Contact start time — convert with `as.Date()`
`kont_type`	character	Contact type: `"ALCA00"` = inpatient
`kont_sluttidspunkt`	datetime	Contact end time
`kont_ans_hovedspec`	character	Specialty code
`borger_doedsdato`	Date	Date of death (copy from CPR)
`borger_foedselsdato`	Date	Date of birth (copy from CPR)
`borger_koen`	character	Sex (copy from CPR)
`year`	integer	Year

All confirmed columns in lpr_a_kontakt

pnr, dw_ek_kontakt, kont_starttidspunkt, kont_sluttidspunkt, kont_type, kont_type_tekst, kont_patient_type, kont_patient_type_tekst, kont_ans_hovedspec, kont_ans_hovedspec_shak, kont_ans_inst, kont_ans, kont_ans_geo_reg, kont_ans_geo_reg_tekst, kont_ans_org_reg, kont_ans_org_reg_tekst, borger_doedsdato, borger_foedselsdato, borger_koen, borger_alder_aar_ind, borger_alder_aar_ud, borger_bo_kom, borger_bo_kom_tekst, borger_bo_reg, borger_bo_reg_tekst, dw_sk_sygehusophold, dw_ek_helbredsforloeb, dw_ek_forloeb, dw_ek_borger, adiag, adiag_tekst, beh_starttidspunkt, flag_kont_afsluttet, kont_aarsag, kont_aarsag_tekst, kont_indb_tidspunkt, kont_fir_kode, kont_fir_tekst, kont_fritvalg, kont_fritvalg_tekst, kont_henv_aarsag, kont_henv_aarsag_tekst, kont_henv_instans, kont_henv_maade, kont_henv_maade_tekst, kont_henv_tidspunkt, kont_inst_ejertype, lprindberetningssystem, prioritet, prioritet_tekst, kont_lpr_entity_id, cprtjek, cprtype, year

lpr_a_diagnose — Diagnoses

Column	Type	Contents
`dw_ek_kontakt`	character	Join key to lpr_a_kontakt
`diag_kode`	character	ICD-10 with D-prefix (e.g. `"DG30"`) — use `substr(diag_kode, 2, 4)`
`diag_kode_type`	character	`"A"` = action diagnosis, `"B"` = secondary diagnosis, `"G"` = underlying condition
`senere_afkraeftet`	character	`"Ja"` = retracted (exclude), `"Nej"` = confirmed, `NA` = not recorded
`diag_kode_tekst`	character	ICD-10 code text
`diag_parent_kode`	character	Parent diagnosis code
`year`	integer	Year

Standard filter for senere_afkraeftet:

filter(is.na(senere_afkraeftet) | senere_afkraeftet != "Ja")

5. LPR — SKS procedure codes

SKS (Sundhedsvæsenets Klassifikations System — the Danish Health Classification System) is the Danish classification system for operations and procedures — equivalent to the NOMESCO codes used in the other Nordic countries. Bariatric surgery has e.g. codes KJDF10 (RYGB) and KJDF40 (sleeve gastrectomy).

SKS codes are split across two registers depending on period. For full coverage both must be queried and the results bound together.

Note

No pnr in the procedure tables. pnr is fetched via join to lpr_adm (LPR2) or lpr_a_kontakt (LPR3) respectively.

lpr_sksopr — LPR2 SKS procedures (up to 2018)

Location: parquet-registers/lpr_sksopr

lpr_sksopr <- open_dataset("path/to/lpr_sksopr/") %>%
  rename_with(tolower)

Column	Type	Contents
`recnum`	character	Join key to `lpr_adm`
`c_opr`	character	SKS procedure code — use this for matching (e.g. `"KJDF10"`)
`d_odto`	Date	Surgery date
`c_oprart`	character	Procedure type code
`c_osgh`	character	Operating hospital
`c_tilopr`	character	Supplementary procedure code
`year`	integer	Year (partition column)

procedurer_kirurgi — LPR3 SKS procedures (2019 and onwards)

Location: parquet-external/procedurer_kirurgi

proc_kirurgi <- open_dataset("path/to/procedurer_kirurgi/") %>%
  rename_with(tolower)

Column (after tolower)	Type	Contents
`dw_ek_forloeb`	character	Join key to `lpr_a_kontakt` — use this for pnr lookup
`dw_ek_kontakt`	character	NA for all rows in this parquet file on DARTER — use `dw_ek_forloeb` instead
`procedurekode`	character	SKS procedure code — use this for matching (e.g. `"KJDF10"`)
`dato_start`	Date	Procedure date
`proceduretype`	character	`"P"` = procedure, `"+"` = add-on code
`procedurekode_parent`	character	Parent procedure code
`proceduretype_parent`	character	Parent procedure type
`tidspunkt_start`	datetime	Procedure start time
`dato_slut`	Date	Procedure end date
`tidspunkt_slut`	datetime	Procedure end time
`lprindberetningssystem`	character	LPR reporting system
`sorenhed_pro`	character	SOR unit for the procedure
`procedureregistrering_id`	character	Internal registration ID

Warning

dw_ek_kontakt is NA for all rows in DARTER’s parquet version of procedurer_kirurgi (confirmed 2026-06-02). Join to lpr_a_kontakt via dw_ek_forloeb to fetch pnr. Applies to DARTER/project 708421 — check on your own project. Column names are mixed case in raw data — call rename_with(tolower) immediately after loading.

Combination across the full period

# Replace [projectnumber] with your own project number
# DARTER: use load_database("registername") instead of open_dataset("path")

# SKS from LPR2 (up to 2018)
surg_lpr2 <- open_dataset("path/to/lpr_sksopr/") %>%
  rename_with(tolower) %>%
  filter(toupper(c_opr) %in% !!SKS_CODES) %>%   # !! sends the local R vector to DuckDB
  left_join(
    open_dataset("path/to/lpr_adm/") %>%
      rename_with(tolower) %>%
      select(recnum, pnr, d_inddto),
    by = "recnum"
  ) %>%
  select(pnr, surgery_date = d_odto, surgery_code = c_opr) %>%
  collect()

# SKS from LPR3 (2019 and onwards) — join via dw_ek_forloeb
surg_lpr3 <- open_dataset("path/to/procedurer_kirurgi/") %>%
  rename_with(tolower) %>%
  filter(toupper(procedurekode) %in% !!SKS_CODES) %>%   # !! sends the local R vector to DuckDB
  left_join(
    open_dataset("path/to/lpr_a_kontakt/") %>%
      rename_with(tolower) %>%
      select(dw_ek_forloeb, pnr),
    by = "dw_ek_forloeb"
  ) %>%
  select(pnr, surgery_date = dato_start, surgery_code = procedurekode) %>%
  collect()

# Combined
surg_all <- bind_rows(surg_lpr2, surg_lpr3)

6. LMDB — Prescription Register

One row per dispensed prescription. Covers approximately 1994 onwards.

Column	Type	Contents
`pnr`	character	Personal identifier
`atc`	character	Full ATC code (e.g. `"N06D01"`)
`eksd`	Date	Dispensing date — use as prescription date
`atc1`–`atc4`	character	ATC levels 1–4
`indo`	character	Indication code
`vnr`	character	Item number
`apk`	numeric	Pack size
`aldr`	numeric	Age at dispensing
`year`	integer	Dispensing year

All confirmed columns in LMDB

pnr, eksd, ekst, atc, atc1, atc2, atc3, atc4, indo, vnr, apk, aldr, bald, eksp, korr, rinr, name, streng, packtext, volume, voltypecode, voltypetxt, dosform, strnum, strunit, packsize, cprtjek, cprtype, year, etid, ovnr, patt, doso, reca, abc

7. Socioeconomic registers

All three registers are used for SEP extraction following SEPLINE guidelines (Hjorth et al. 2025). No single combined SEP variable is calculated — three separate dimensions.

UDDA — Education Register

One record per person per year — updated when the education level changes.

Column	Type	Contents
`pnr`	character	Personal identifier
`hfaudd`	character	ISCED education code (e.g. `"35"` = vocational education)
`aar`	integer	Register year

Categorisation (SEPLINE): substr(as.character(hfaudd), 1, 2) → "10"/"15" = short, "20"–"35" = medium, "40"–"80" = long, "90" = unknown.

FAIK — Family Income

Household-equivalised disposable income per year. Link: join BEF (pnr, familie_id, aar) with FAIK (familie_id, aar).

Column	Type	Contents
`familie_id`	character	Household key — join to BEF
`famaekvivadisp_13`	numeric	Household-equivalised disposable income
`aar`	integer	Register year

Income quintiles are calculated as 3-year averages compared against Q20/Q40/Q60/Q80 cut-points from the full BEF population stratified by sex × 5-year age group × reference year.

AKM — Labour Classification Module

Labour market status per person per year.

Column	Type	Contents
`pnr`	character	Personal identifier
`socio13`	numeric	Employment code
`aar`	integer	Register year

SEPLINE categorisation of socio13: - Employed: 110–114, 120, 131–135, 139 - Student: 310 - Unemployed: 210, 410 - Outside labour market: 220, 321, 330 - Retired: 322, 323 - Unknown: 0, 420 or missing

8. Project-specific registers

Many projects have access to registers beyond the standard list above — e.g. quality registers from clinical databases or pre-computed classification files.

These are project-specific and not available in all projects on DST.

Tip

Working on DARTER / project 708421? The project uses among others DBSO (the Danish Obesity Treatment Database) and OSDC (Open Source Diabetes Classifier).

All applied-for variables and registers in a searchable table: steno-aarhus.github.io/darter-project →
Confirmed paths and column names: DARTER — Register paths and datastores →