Danmark som registerland

Alma B. Pedersen, Afdelingslæge, ph.d., klinisk lektor

Klinisk Epidemiologisk Afdeling Aarhus Universitetshospital

Agenda

• Præsentation af danske register data

• Adgang til data

• Fordele og ulemper ved register forskning

• Eksempler på register forskning

Secondary data - a historical view

1645 Church files

1769 The First Census

1856 The First Disease Registry -The Leprosy Registry in Norway

1924 National Population Registry

1925 The Registry of Cerebral Paresis

1937 The Registry of Tuberculosis

1943 The Cancer Registry

1943 The Registry of Causes of Death

1953 The Central Psychiatric Registry

1968 The Civil Registration System

1973 The Medical Birth Registry

1977 The National Registry of Patients

1989/90 Regional Prescription Database

1995 The National Prescription Registry

The Civil Registration System

• Period: 1 April 1968 (Greenland 1972)

• All persons who are born in DK or live or work in DK

• Main variables:

• Civil Registration Number (CPR)

• Civil status

• Civil Registration Number of father/mother/children

• Immigration / Emigration

• Current and historical addresses

• Current and historical marriages

• Updated daily

• The civil registration number is used in all Danish registries

Data, Data everywhere

But not much of it linked

Purpose Built

Hospital Data

GP

Other

PROM

Pharmacy Social

Services

Laboratory

Clinical databases

Record-Linked Data

Completing the Jigsaw

GP Hospital

Social Services

Pharmacy

PROM Purpose Built

Laboratory Clinical databases

Other

Type af registre

• Sundhedsregistre (administrative)

• Kliniske kvalitetsdatabaser

• Regionale databaser

SSI

• Statens Serum Institut er ansvarlig for en række

sundhedsregistre som anvendes til centrale og lokale

myndighedsopgaver og forskning.

• http://www.ssi.dk/Sundhedsdataogit/Registre.aspx

• De mest efterspurgte registre:

– Landspatientregisteret

– Dødsårsagsregisteret

– Det Psykiatriske Centralregister

– Cancerregisteret

– Fødselsregisteret

– Sygesikringsregisteret

The Danish National Registry of Patients (DNRP)

Period 1 January 1977 –

Population All persons hospitalized in Denmark

Outpatients since 1994

Emergency room visit since 1994

Variables CPR Number

Hospital department

Admission and discharge data

Some tests and treatments

Diagnoses ICD 8 1977 – 1993

ICD 10 1994 –

Surgical procedures NOMESCO classification

Dokumentation af Landspatientregisteret (Excel), opdateret data

The Danish Cancer Registry

Period: 1 January 1943 –

Population: All incident cases of cancer

Main Variables: CPR Number

Diagnosis (ICD-7:1943-1977, ICD-10: since 1978)

Extend of spread of the tumor (TNM)

Treatment: Surgery, Chemo-, Anti-hormone therapy

Topography and histology codes (ICD-0-1:1978-

2003, ICD-0-3 since 2004

Vital status

Registration electronically since 2004

Dokumentation af Cancerregisteret (Excel), forsinket data

The Danish Registry of Causes of Death

Established: 1 January 1943, Registration in the present form since

1970 in DK (Greenland and Faroe Islands since 1983)

Population: All deaths, death certificate must be filled for every

Danish decedent

Main variables: CPR number

Place of death

Causes of death (one underlying cause and up to three

additional immediate causes)

Autopsy (yes/no)

Registration electronically since 2007

Dokumentation af Dødsårsagsregisteret 1970-2001, 2002-2011

Health Insurance Register (Sygesikringsregister)

• Period since 1990

• Contains information about the settlement of health insurance benefits

between regions and providers in health insurance, i.e. general

practitioners, specialists, dentists, physiotherapists, psychologists and

others

• Dokumentation af Sygesikringsregisteret

Principper for udlevering af data fra SSI

• Du skal altid søge via det elektroniske ansøgningsskema på

Sundhedsstyrelsens hjemmeside (forskerservice)

• Til det elektroniske ansøgningsskema skal du vedhæfte følgende:

– Tilladelse fra Datatilsynet om at lave projekt

– Projektbeskrivelse (PDF)

– Udtræksbeskrivelse (PDF) (the need to know princippet)

– Betaling- JA

Danmark Statistik (DST)

Eksempler på registre i DST

• Integrated Database for Labour Market Research

– Contains information on each Danish citizen’s socioeconomic status

including data on gross income, education, employment status and

marital status since 1980

– Update once a year

• Lægemiddelstatistikregister

– Outpatient drug prescriptions since 1995, nationwide

– information on cpr number, on the dispensed drug (ATC-code,

name, package size, formulation and quantity), date of transaction,

price, code identifying the prescribing physician

– Update once a year from the SSI

Principles for use of data in DST

1. Analysis must be done in Statistics Denmark

2. Statistics Denmark links the registries and deletes the civil registration number

3. No access to the civil registration number and paper records an thus no possibilities for validation

4. The procedure for getting access to the data might take up to six months

Acces to the data in DST

• Projektansøgning til Danmarks Statistiks Forskerserviceenhed (www.dst.dk/forskning)

• Projektbeskrivelse

• Godkendelse fra Lægemiddelstyrelsen (ved brug af Lægemiddeldatabase)

• Godkendelse fra Datatilsynet for at lave projekt

• Betaling- JA

The Danish National Database of Reimbursed Prescriptions

• Established by Danish Regions and Aarhus University in 2004

• a prescription at a community pharmacy or a hospital-based

outpatient pharmacy

• Cpr number, the prescriber, ATC code, item number, date of

redemption, quantity of the item, strength, pack size, 24 hour

dose, unit (related to strength), name on the packaging, form of

dosis, manufacturer, drug ID and unit (related to pack size)

• Access available after application

http://www.kea.au.dk/da/forskning/dansk-receptdatabase2.html

The North Denmark Regional Microbiological

Bacteremia Research Database

• All hospitalized patients with bacteremia in the former North Jutland

County

• Since 1981

• Main variables:

– cpr number

– Date and department of admission

– Focus of infection

– Blood cultures

– Microbiological species

– Differnetiation between community- from hospital-acquired episodes

• Maintained by the Department of Clnical Microbiology at Aalborg

Hospital

The Laboratory Information System (LABKA)

• records test results from every blood sample taken in any public or

private hospital or by any general practitioner

• submitted to any clinical chemistry department located in the Central or

North Denmark Region,

• starting in early 1990

• Main variables:

– CPR number, measurement units, dates of ordering and carrying

out the analysis, and a unique ID identifier of hospital department or

general practitioner who ordered the test

• Data are recorded according to Nomenclature for Properties and Units

(NPU) codes

Introduktion til Kliniske kvalitetsdatabaser

Hvad er en klinisk kvalitetsdatabase?

Et register, der indeholder udvalgte kvantificerbare indikatorer, som kan belyse dele af eller den samlede kvalitet af sundhedsvæsnets indsats og resultater for en afgrænset patientgruppe med udgangspunkt i det enkelte patientforløb.

Kort sagt:

Et offentligt register, der etableres som led i kvalitetsudvikling.

Kvalitetsudvikling i Sundhedsvæsnet, Kjærgaard m.fl.,

2001

Formelle krav til kvalitetsdatabaser

Basiskrav for Kliniske kvalitetsdatabaser, 2007.

Bekendtgørelse nr. 459 om godkendelse af

landsdækkende og regionale kliniske kvalitetsdatabaser,

2006.

Anmeldt jf. Persondataloven til Datatilsynet

Godkendes af Sundhedsstyrelsen

Basiskrav for Kliniske kvalitetsdatabaser

• Organisatoriske

• Sundhedsfaglige

• Informatiske

• Basiskrav vedr. afrapportering og offentliggørelse

• Basiskrav til nationale kompetencecentre

Organisatoriske krav

• Målsætning, >90% dækningsgrad i sekundær sektoren

• Målsætning, >90% komplethedsgrad af patient

registrering

• Dette sikrer validiteten af de data, der indsamles, og

dermed validiteten af de konklusioner og anbefalinger

Kvalitetsindikatorer

• Defineres som målbare variabler, der anvendes til at

overvåge og evaluere behandlingskvaliteten

• Alment accepteret og evidensbaserede

• Veldefineret

• Indikatorspecifikationer og Indikatoralgoritmer

• 5-10 veldefinerede kvalitetsindikatorer

Kategoriseres som struktur-, proces- og resultatindikatorer

Indikatorområde Indikatorer - Hoftenær lårbensbrud Type Standard

Hurtig udredning og behandling af patienter med symptomer på Hoftenær lårbensbrud

Præoperativ

optimering 1

Andelen at patienter der er set og vurderet af speciallæge eller af læge i

hoveduddannelses forløbets sidste år mhp. at få lagt en præoperativ

optimeringsplan senest 4 timer efter ankomst til sygehuset.

Proces Mindst 80 %

Behandling af patienter med Hoftenær lårbensbrud

Operationsdelay

2 Andel af patienter der opereres senest 24 timer efter ankomst til sygehuset Proces Mindst 75 %

2a Andel af patienter der opereres senest 36 timer efter ankomst til sygehuset Proces Mindst 90 %

Tidlig

mobilisering 3 Andelen af patienter, der efter operationen mobiliseres inden for 24 timer Proces Mindst 90%

Basismobilitet

4a Andelen af patienter, der får vurderet og indberettet score for basismobilitet

med Cumulated Ambulation Score (CAS) forud for aktuelle fraktur Proces Mindst 90%

4b Andelen af patienter, der får vurderet og indberettet score for basismobilitet

med CAS ved udskrivelsen Proces Mindst 90%

Ernæring 5 Andelen af patienter, hvor ernæringsplan er udarbejdet

Proces Mindst 90%

Profylakse

Osteoporose 6

Andelen af patienter, hvor der udover behandling med calcium og vitamin D,

er taget stilling til medicinsk osteoporoseprofylakse.

Proces Mindst 90%

Profylakse Fald 7 Andelen af patienter, hvor der er taget stilling til faldprofylakse Proces Mindst 90%

Overlevelse 8 Andelen af patienter, som er i live 30 dage efter operationsdato Resultat Mindst 90%

Ventetid til

kommunal

genoptræning

9 Andelen af patienter, der udskrives med almen genoptræningsplan, hvor der

påbegyndes genoptræning i kommunalt regi Proces

Sættes ved

audit

Indikatorområde Indikatorer - Hoftenær lårbensbrud Type Standard

Genindlæggelse

10

Andelen af patienter der genindlægges akut – uanset

årsag – inden for 30 dage efter udskrivelse fra sygehuse

med diagnosen hoftenær lårbensbrud.

Resultat Højst 20%

Reoperation

Osteosyntese pga.

medial fraktur af

lårbenshals

11

Andelen af patienter med osteosynteret medial fraktur

uanset frakturstilling, der inden for 2 år reopereres

Resultat

Højst 15%

11a Andelen af patienter med osteosynteret uforskudt medial

fraktur, der inden for 2 år reopereres Resultat

Højst 10%

11b Andelen af patienter med osteosynteret forskudt medial

fraktur, der inden for 2 år reopereres Resultat

Højst 20%

Reoperation,

Osteosyntese pga.

per-/subtrochantær

femurfraktur

12 Andelen af patienter med osteosynteret pertrochantær /

subtrochantær femurfraktur der inden for 2 år reopereres Resultat Højst 5%

Reoperation pga.

Hemi- eller

totalalloplastik

13 Andelen af patienter med en hemi- eller totalalloplastik

uanset frakturtype, der inden for 2 år reopereres Resultat Højst 10%

Reoperation

Dyb infektion 14

Andelen af patienter, der reopereres pga. dyb infektion

inden for 2 år Resultat Højest 2%

Ansøgning om data fra kvalitetsdatabaser

Protokol

(Forskningsmiljø)

Tilladelse fra Datatilsynet til at lave projekt

Anmodning om dataudtræk fremsendes til

Databasernes Fællessekretariat (fagligkvalitet@rm.dk)

Betaling - Nej

Eksempler på kvalitetsdatabaser

• Dansk Hoftealloplastik Register (DHR)- siden 1995

• Dansk Knæalloplastik Register (DKR)- siden 1997

• Dansk Skulderalloplastik Register (DSR)- siden 2005

• Dansk Korsbåndsrekonstruktion Register (DKRR)- siden 2005

• Dansk Tværfagligt Register for Hoftenære Lårbensbrud- siden 2003

• Dansk Transfusions Database (DTDB)

• Dansk Intensiv Database (DID)

• Dansk Anæstesi Database (DAD)

• Dansk Reumatologisk Database (DANBIO)

• www.sundhed.dk eller www.rkkp.dk

Registry studies- Advantages

1) Data already exist, reducing costs

2) Large sample size, usually population based

3) Data collected for administrative or other purposes

unrelated to research objectives

4) More likely to reflect daily usual clinical practice

5) Much more feasible to rare outcomes, long term

outcomes, and prognosis studies

6) Nearly complete follow-up

Registry studies- Limitations

1) Information on potential confounders may not have been

collected

• Smoking

• Alcohol intake

• Diet

• Physical activity

• Obesity

• Severity of the underlying disease

• Comorbidity

• Socioeconomic status

HRT and coronary heart disease

BMJ 2004; 329:868-869

Registry studies- Limitations

1) Information on potential confounders may not have been

collected

2) Temptation to post hoc analyses

3) Related to data quality

Use of registries

Requires knowledge about the data validity:

• Completeness of patient registration

• Completeness of registered data

• Quality of registered data

Eksempel 1

Validity of different diagnosis codes in the National

Registry of Patients

Anafylactic shockCrohn's disease

Diabetes Ulcerative colitis

Myocardial infarction Herniated lumbal disc

Meningococcal disease Liver cirrhosis

Cancer diagnosesEssential hypertension

Rheumatic fever Conn's syndrome

Traumatic hip luxation Uterine rupture

0 10 20 30 40 50 60 70 80 90 100

Eksempel 2

Validation in DHR - Registration completeness

% 95% CI (%)

Overall 94.1 93.9 – 94.4

Primary THAs 93.9 93.6 - 94.2

Revisions 81.4 80.2 – 82.6

Revisions (-hemi) 90.1 89.1 - 91.0

Pedersen AB et al. Acta

Orthop 2004

Validity of the registered diagnoses in DHR

Diagnosis PPV (%) 95% CI (%)

Primary arthrosis 84.6 74.7 – 91.8

Fresh fracture of proximal

femur 30.1 19.9 – 42.0

Sequelae after trauma 95.0 87.7 – 98.6

Atraumatic necrosis of

femoral head 98.7 93.2 – 99.9

Inflammatory diseases 100 94.9 – 100

Hip disorders in childhood 89.7 80.8 – 95.5

Eksempel 3

Validation of DHR cont. - Gundtoft PH et al. 2015

• The "true" incidence of surgically treated deep prosthetic joint infection

(PJI) after 32,896 primary total hip arthroplasties: a prospective cohort

study.

• Using algorithm incorporating data from microbiological, prescription,

and clinical biochemistry databases and clinical findings from the

medical records.

• Conclusion: The incidences of PJI based on the DHR and the NRP were

consistently 40% lower than those estimated using the algorithm

covering several data sources.

Eksempel 4

Death following hip arthroplasty

Danish Hip Arthroplasty register DHR

• All primary THA

CPR registry

• Each THA patient was matched according to gender and age at the time of surgery with 3 persons from the general population

• Outcome: death

Pedersen AB et al. JBJS Br 2011

Death following hip arthroplasty using Cause of death registry

Pedersen AB et al. JBJS Br 2011

Eksempel 5

VTE following hip arthroplasty- comparison with general population

DHR • All primary THA, n=85,965

CPR registry

• Comparison cohort without THA from the general population (n=257,895). Matched on gender and age.

Danish National Registry of patients

• Confounding: comorbiditet

• Outcome: VTE

Pedersen AB et al. JBJS Br 2012

VTE following primary THA: comparison with general population

0

2

4

6

8

10

12

14

16

18

20

0-90 days 91-365 days

VTE

DVT

PE

Days after THA surgery

Adju

ste

d R

R

The risk of VTE was elevated irrespective of

the gender, age or level of comorbidity

Pedersen AB et al. JBJS Br 2012

Eksempel 6

Revision risk in THA with diabetes mellitus

DHR • All primary THA

Danish National Registry of Patients

• Hospitalization at all Danish hospitals with ICD-10 codes for diagnoses of type 1 or type 2 diabetes

Danish National Drug Prescription Database

• Prescription for insulin or an oral antidiabetic drug before surgery

Pedersen AB et al. JBJS Br 2009

Example 6 - Revision risk in THA with diabetes mellitus

DHR • All primary THA

Danish National Registry of Patients

• Hospitalization at all Danish hospitals with ICD-10 codes for diagnoses of type 1 or type 2 diabetes

Danish National Drug Prescription Database

• Prescription for insulin or an oral antidiabetic drug before surgery

57,575 patients with a first primary THR in the DHR

3,278 (5.7%) patients had diabetes

and

54,297 (94.3%) were non-diabetic

Revision risk in THA with diabetes mellitus

Danish Hip Arthroplasty

Registry (DHR)

National Registry of Patients

hospitalization with diagnoses of

type 1 or type 2 diabetes

National Registry of Patients

Comorbidity level before surgery

National Drug Prescription

Database

prescription for insulin or an oral

antidiabetic drug before surgery

Civil Registration System

Vital status, complete follow up

Integrated Database for Labour

Market Research

Socioeconomic status

National Drug Prescription

Database

prescription for other drugs

related to diabetes and revision

risk (f.eks. NSAID, statins)

Revision risk in THA with diabetes mellitus

Revision risk in THA with diabetes mellitus

• Revision risk due to deep infection

– RR=1.01 (95% CI: 0.33-3.12) in THR pt. with type 1 diabetes

– RR=1.49 (95% CI: 1.02-2.18) in THR pt. with type 2 diabetes

• This elevated risk is particularly present among THR patients

– Who have had diabetes for less than five years

– Those with diabetes-related complications

– Those with presence of cardiovascular comorbidites prior to surgery

Eksempel 7

International samarbejde - For eksempel NARA (Nordic

Arthroplasty Register Association)

• Pedersen AB et al. Association between fixation technique and

revision risk in total hip arthroplasty patients younger than 55 years of

age. Results from the Nordic Arthroplasty Register Association.

Osteoarthritis and Cartilage 2014.

• Mäkelä KT et al. Failure rate of cemented and uncemented total hip

arthroplasty: a register study of combined Nordic database of four

nations. BMJ 2014

• Glassou EN et al. Hospital procedure volume and risk of implant

revision surgery after total hip arthroplasty: A study within the Nordic

Arthroplasty Register Association. Osteoarthritis and Cartilage 2015.

• Varnum C et al. Risk and Causes for Revision of Cementless

Stemmed Total Hip Arthroplasties with Metal-on-Metal Bearings. 19,588

Patients from the Nordic Arthroplasty Registry Association. Acta Orthop

2015

Conclusions

• Hvis man har en veldefineret forsknings hypotese:

– Undersøg om du kan bruge allerede indsamlede data fra danske

sundhedsregistre eller kliniske kvalitetsdatabaser til formålet,

– Undersøg validiteten af data,

– Overvej samarbejde med en epidemiolog og biostatistikker, som har

erfaring i at arbejde med register data,

– To do list over de forskellige tilladelser og ansøgninger

• Husk: det kan tage lige så lang tid til at opnå alle tilladelser og få data,

end at lave efterfølgende data management og statistiske analyser.

• START I GOD TID

ALMA B. PEDERSEN

ABP@CLIN.AU.DK

Tak for jeres opmærksomhed

Factors to consider when planning or interpreting

the results of observational studies

1. Does the database fit the research question?

2. Does the study population fit to the research question?

3. Is the size of the study population adequate to answer the

question?

4. Does the study design fit to the research question?

Hepatology, 2006: 1075-1082.

Factors to consider when planning or interpreting

the results of observational studies- cont.

5. Is the exposure determined accurately? Was the exposure

assessed before the outcome occurred? Bias?

6. Is the outcome measured accurately and is it relevant for clinical

practice? Bias?

7. Are confounding factors measured accurately? Unmeasured

confounding?

8. Are the patients followed for a long enough time to let the

outcome occur? Is there any loss to follow-up?

9. Are the statistical methods suitable for the research question?

Hepatology, 2006: 1075-1082.