Alma Pedersen - Danmark som registerland

Danmark som registerland
Alma B. Pedersen, Afdelingslæge, ph.d., klinisk lektor
Klinisk Epidemiologisk Afdeling Aarhus Universitetshospital
Agenda
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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
PROM
Laboratory
Social
Services
GP
Hospital
Data
Pharmacy
Clinical
databases
Purpose
Built
Other
Record-Linked Data
Completing the Jigsaw
Purpose
Built
Pharmacy
Laboratory
PROM
GP
Social
Services
Other
Hospital
Clinical
databases
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
CPR Number
Hospital department
Admission and discharge data
Some tests and treatments
ICD 8 1977 – 1993
ICD 10 1994 –
Surgical procedures NOMESCO classification
Variables
Diagnoses
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-0-1:19782003, 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)
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Period
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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
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Dokumentation af Sygesikringsregisteret
since 1990
Principper for udlevering af data fra SSI
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Du skal altid søge via det elektroniske ansøgningsskema på
Sundhedsstyrelsens hjemmeside (forskerservice)
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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
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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
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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
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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
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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
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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)
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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
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Organisatoriske
Sundhedsfaglige
Informatiske
Basiskrav vedr. afrapportering og offentliggørelse
Basiskrav til nationale kompetencecentre
Organisatoriske krav
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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
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 struktur-,
proces- og resultatindikatorer
Indikatorer - Hoftenær
Indikatorområde
lårbensbrud
Type
Standard
Hurtig udredning og behandling af patienter med symptomer på Hoftenær lårbensbrud
Præoperativ
optimering
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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
Tidlig
mobilisering
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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 %
3
Andelen af patienter, der efter operationen mobiliseres inden for 24 timer
Proces
Mindst 90%
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%
Proces
Mindst 90%
Basismobilitet
Andelen af patienter, hvor ernæringsplan er udarbejdet
Ernæring
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Profylakse
Osteoporose
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Andelen af patienter, hvor der udover behandling med calcium og vitamin D,
er taget stilling til medicinsk osteoporoseprofylakse.
Proces
Mindst 90%
Profylakse Fald
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Andelen af patienter, hvor der er taget stilling til faldprofylakse
Proces
Mindst 90%
Overlevelse
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Andelen af patienter, som er i live 30 dage efter operationsdato
Resultat
Mindst 90%
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Andelen af patienter, der udskrives med almen genoptræningsplan, hvor der
påbegyndes genoptræning i kommunalt regi
Proces
Sættes ved
audit
Ventetid til
kommunal
genoptræning
Indikatorområde
Indikatorer - Hoftenær
Genindlæggelse
Andelen af patienter der genindlægges akut – uanset
årsag – inden for 30 dage efter udskrivelse fra sygehuse
med diagnosen hoftenær lårbensbrud.
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Reoperation
Osteosyntese pga.
medial fraktur af
lårbenshals
lårbensbrud
Andelen af patienter med osteosynteret medial fraktur
uanset frakturstilling, der inden for 2 år reopereres
Type
Resultat
Standard
Højst 20%
Højst 15%
Resultat
Højst 10%
11a
Andelen af patienter med osteosynteret uforskudt medial
fraktur, der inden for 2 år reopereres
11b
Andelen af patienter med osteosynteret forskudt medial
fraktur, der inden for 2 år reopereres
Resultat
Reoperation,
Osteosyntese pga.
per-/subtrochantær
femurfraktur
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Andelen af patienter med osteosynteret pertrochantær /
subtrochantær femurfraktur der inden for 2 år reopereres
Resultat
Højst 5%
Reoperation pga.
Hemi- eller
totalalloplastik
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Andelen af patienter med en hemi- eller totalalloplastik
uanset frakturtype, der inden for 2 år reopereres
Resultat
Højst 10%
Reoperation
Dyb infektion
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Andelen af patienter, der reopereres pga. dyb infektion
inden for 2 år
Resultat
Højest 2%
Resultat
Højst 20%
Ansøgning om data fra kvalitetsdatabaser
 Protokol
 (Forskningsmiljø)
 Tilladelse
fra Datatilsynet til at lave projekt
 Anmodning om dataudtræk fremsendes til
Databasernes Fællessekretariat ([email protected])
 Betaling - Nej
Eksempler på kvalitetsdatabaser
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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
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Dansk Transfusions Database (DTDB)
Dansk Intensiv Database (DID)
Dansk Anæstesi Database (DAD)
Dansk Reumatologisk Database (DANBIO)
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www.sundhed.dk eller www.rkkp.dk
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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 shock
Crohn's disease
Diabetes
Ulcerative colitis
Myocardial infarction
Herniated lumbal disc
Meningococcal disease
Liver cirrhosis
Cancer diagnoses
Essential 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
Primary arthrosis
Fresh fracture of proximal
femur
Sequelae after trauma
Atraumatic necrosis of
femoral head
Inflammatory diseases
Hip disorders in childhood
PPV (%)
95% CI (%)
84.6
74.7 – 91.8
30.1
19.9 – 42.0
95.0
87.7 – 98.6
98.7
93.2 – 99.9
100
94.9 – 100
89.7
80.8 – 95.5
Eksempel 3
Validation of DHR cont. - Gundtoft PH et al. 2015
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The "true" incidence of surgically treated deep prosthetic joint infection
(PJI) after 32,896 primary total hip arthroplasties: a prospective cohort
study.
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Using algorithm incorporating data from microbiological, prescription,
and clinical biochemistry databases and clinical findings from the
medical records.
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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
Adjusted RR
VTE following primary THA: comparison with general population
20
18
16
14
12
10
8
6
4
2
0
The risk of VTE was elevated irrespective of
the gender, age or level of comorbidity
VTE
DVT
PE
0-90 days
91-365 days
Days after THA surgery
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
• All primary THA
57,575 patients with a first primary THR
in the DHR
• Hospitalization at all Danish
Danish 3,278
National
(5.7%) patients
had diabetes
hospitals
with ICD-10 codes
Registry of
for diagnoses of type 1 or
Patients
andtype 2 diabetes
DHR
54,297 (94.3%) were
non-diabetic
Danish National
• Prescription
for insulin or an
Drug Prescription
oral antidiabetic drug before
Database
surgery
Revision risk in THA with diabetes mellitus
National Registry of Patients
hospitalization with diagnoses of
type 1 or type 2 diabetes
Danish Hip Arthroplasty
Registry (DHR)
National Drug Prescription
Database
prescription for insulin or an oral
antidiabetic drug before surgery
National Registry of Patients
Comorbidity level before surgery
National Drug Prescription
Database
prescription for other drugs
related to diabetes and revision
risk (f.eks. NSAID, statins)
Civil Registration System
Vital status, complete follow up
Integrated Database for Labour
Market Research
Socioeconomic status
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
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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
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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
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Tak for jeres opmærksomhed
ALMA B. PEDERSEN
[email protected]
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.