Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Viewers also liked
Viewers also liked (15)
Similar to Knowledge from health registries, cohorts, and biobanks stein emilvollset
Similar to Knowledge from health registries, cohorts, and biobanks stein emilvollset (20)
More from EPINOR
More from EPINOR (20)
Recently uploaded
Recently uploaded (20)
Knowledge from health registries, cohorts, and biobanks stein emilvollset
- 1. 06.10.2016 1 Knowledge from health registries, cohorts, and biobanks Professor Stein Emil Vollset, MD, DrPH Centre for Disease Burden, Norwegian Institute of Public Health Department of Global Public Health and Primary Care, University of Bergen Affiliate professor, Institute for Health Metrics and Evaluation, University of Washington, Seattle Scandic Bergen City Register epidemiology – the research area where Norway has an advantage Can registries help ?
- 2. 06.10.2016 2 Why engage with register research? A short introduction to the different registries What are the challenges? ‐ Scientific ‐ Bureaucratic Presentation of national research infrastructures ‐ Health registries for research (HRR) HRR WP: Biostatistics support Issues* to consider in registry research • Norway is famous for our health registries. From a research point of view their aim is to say something about causality. Why? Because, if you find a causal effect, then maybe you can intervene and prevent disease or treat people. • But to which extent is there causal information in the registries? You could have the most excellent biobank, and it could be virtually useless if data are not collected according to a statistical design that allows causal inference. Or if there are numerous unmeasured confounders. Do the registry data really contain a lot of gold that can be mined? • Following Judea Pearl's fundamental distinction between seeing and doing: Registry data are about seeing while the interventions they shall support are about doing. How to bridge the gap? • The two pillars of epidemiology are the great data sources, represented by cohorts, registries and other data collections, and the extensive and deep methodological thinking. * Raised by professor Odd Aalen motivating a meeting on causal inference in December 2015
- 3. 06.10.2016 3 Another perspective ‐ descriptive • Epidemiology not only etiologic/causal research • Also: describe determinants and health status of the population • Global burden of disease project • Registries underused for such descriptive purposes
- 4. 06.10.2016 4 Global Burden of Disease Study: Levealder – begge kjønn Norge 2013 81.4 år 15. plass 83.7 år 79.1 år Data fra Global Burden of Disease Study 2013 – www.healthdata.org 48 50 55 60 65 70 75 80 84 www.healthdata.org • Global Burden of Disease (GBD) 1993 prosjekt ved Verdensbanken og Verdens helseorganisasjon (WHO) • WHO perioden 1998‐2003: World Health Report 2002 • GBD 2010 Studien startet i 2007 ved Institute for Health Metrics and Evaluation (IHME) ved University of Washington i Seattle • GBD 2013 ‐ første gang for 188 land. Publisert i Lancet 2014‐15. • GBD 2015 pågår med et ekspertnettverk på over 1000 forskere fra over 100 land. • Resultater fra GBD 2013 på nett: www.healthdata.org 2014‐15
- 6. 06.10.2016 6 Kreft Hjertekar Psykiske lidelser Muskel‐skjelett Selvmord Overdoser Trafikkdød GBD 2013 Mortality and causes of death, Years of life lost (YLL) Non‐fastal health loss, Years lived with disability (YLD) DALY (YLL+YLD) Disease burden attributable to risk factors Lancet 2015
- 7. 06.10.2016 7 GBD 2013 – deaths attributable to major risk factors – Norway 2013 Blood Pressure Diet Tobacco BMI Cholesterol Fasting glucose Physical activity Kidney function Alcohol/drugs BMD Occupation Other envir Air pollution Unsafe sex Sexual abuse Malnutrition WaSH Cardiovascular disease Cancer COPD Diabetes GBD 2013 results ‐ http://vizhub.healthdata.org/gbd‐compare/ Data needed on population distribution of major risk factors; Confounders/mediators in studies of chronic diseases and population health 0 2000 4000 6000 8000 www.healthdata.org • Burden of disease for 195 countries and terriotories, 1990‐2015 • Deaths, years of life lost (YLL), non‐fatal health loss (YLD), DALYs (=YLL+YLD) • and burden (above metrics) attributable to 79 risk factors • With GBD 2015 soon to be released also prevalence and incidence
- 8. 06.10.2016 8 registries Electronic nationwide Nordic health registries with national id‐number Registry Denmark Finland Norway Sweden Cause of death 1943 1969 1951 1952 Medical birth 1973 1987 1967 1973 Hospital discharge 1967 (1977*) 1969 2008 1964 (1987*) Cancer 1943 1953 1952 1958 Prescription 1995 1994 2004 2005 * Nationwide from the year in parenthesis From Vollset & Cappelen. Registerepidemiologi. I Laake et al. Epidemiologiske og kliniske forskningsmetoder. Gyldendal Akademisk 2007 [some corrections made to the original table]
- 9. 06.10.2016 9 Some reasons registries are important • Give overview of the population’s health status and use of resources in the health care system • Provide outcomes/events for cohorts and biobanks • Often RCTs (randomised clinical trials) cannot be used to advance knowledge • RCTs rarely done in many medical areas where legal regulations do not require them (medical devices: eg. hip/knee‐prostheses, and others) • Because drug trials do not have sufficient sample size to detect side effects Norway Health registries – gold mine? • There is gold – but it may be hard to find ! • Often gold is made from combining many data sources • Sometimes gold may be found within one register alone
- 10. 06.10.2016 10 Papers in New England Journal of Medicine with first author from a Norwegian institution 1990‐2015 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 0.00.51.01.52.02.53.0 3 2 1 Registry based/linkage studies = 13 Randomised clinical trial = 9 Observational clinical study = 2 Basic medical sciences study = 2 Papers in New England Journal of Medicine with first author from Norway 1990‐2014 • Search in Pub Med: norway[Affiliation] AND n‐engl‐j‐med[Journal] • 35 hits 1990‐2015 (1 later «retracted», 2 er «sounding board» / commentary without human data, 6 first author from non‐ Norwegian institution) • 26 original‐articles remain – 1 study of NMR for cancer detection, 1 is clinical study of hepC infection in patients receiving immunglobuliner, 1 er en studie av assay for troponin T i et materiale fra en randomisert studie blant hjertekar‐pasienter, 1 is description of novel dominant genetic disease – 9 are randomised clinical trials, (7 in cardiovascular area) – 13 of 26 articles are based on Medical birth registry, Cancer registry, Cause of death registry or other data sources (cohorts, biobanks) linked to these registries for outcome measures
- 11. 06.10.2016 11 On causal information • None of the registries we are famous for were designed for causal inference, neither for etiological nor for identifying best treatments • They are event registries and say little about causes of the event or factors that may improve the outcome after the event (treatment) • However, many clinical quality registries are designed for causal inference (identify best treatment), as are cohort studies and biobanks linked to cohorts (identify causes of disease, prevention opportunities) Typology of Health Registry data 1. (see) Health care system or population events 2. (see) Population risk factors (etiologic factors; behavioral, metabolic, environmental/occupational), population gene data 3. (see) Clinical information: diagnosis with prognostic factors, severity of disease, functional level associated with a disease, stage of disease, genetic/metabolic disease markers. Repeated information over time. 4. (do‐factors) Treatments, interventions, preventive measures, screening programs, risk factors
- 12. 06.10.2016 12 Registry, cohort/biobank information (see) Health care system or population events Nation‐wide population‐based mandatory registries (14) • Cause of death registry • Cancer registry • Population registry • Medical Birth Registry • Prescription registry • Patient registry • Cardiovascular disease registry • Vaccination registry • Infectious disease registries • Primary care data [all contacts] – not registry status yet • Unsystematic and sparse information on risk factors, prognostic factors, treatments (dose, duration, surgery, devices), functional status. • Limited use for causal inference alone (see/do) COHORTS/BIOBANKS Population risk factors (etiologic factors; behavioral, metabolic, environmental /occupational), population gene data Mother &Child Cohort Cardiovascular Screening Programs JANUS Biobank Tromsø and HUNT cohorts Gain value with follow‐up Loss of value without regular updating of exposure and confounder information need regular updating(see) Clinical quality registries (58 with national status) Clinical information: diagnosis with prognostic factors, severity of disease, functional level associated with a disease, stage of disease, genetic/metabolic disease markers (do‐factors) Treatments, interventions, preventive measures, screening programs, risk factors Need great detail, many events with duration, dose, type of intervention and intermediate results May be found in good Clinical quality i Sentrale/lovhjemlede helseregistre › Lovhjemmel i helseregisterloven - juridisk definisjon › Etablert av den sentrale helseforvaltningen › Landsdekkende – Meldeplikt › Registerformer › Anonyme/avidentifiserte › Pseudonyme › Personidentifiserbare › Samtykke
- 13. 06.10.2016 13 Sentrale/lovhjemlede helseregistre 1. Dødsårsaksregisteret 2. Medisinsk fødselsregister 3. Hjerte- og karregisteret 4. Meldingssystem for smittsomme sykdommer (MSIS) 5. Nasjonalt vaksinasjonsregister 6. Resistensregistrene (NORM, RAVN) 7. Norsk overvåkingssystem for infeksjoner i sykehustjenesten (NOIS) 8. Reseptbasert legemiddelregister 9. Register over svangerskapsavbrudd 10. Kreftregisteret 11. Genetisk masseundersøkelse av nyfødte 12. Norsk pasientregister 13. Informasjonssystem for pleie og omsorgssektoren (IPLOS) 14. Forsvarets helseregister Under etablering 1. Helsearkivregisteret 2. System for bivirkningsrapportering Sentrale helseregistre per februar 2015 Register Etablert Owner/ ID 1. Dødsårsaksregisteret / Cause of death Registry 1925 FHI Pid. 2. Medisinsk fødselsregister / Medical Birth Registry 1967 FHI Pid. 3. Register for svangerskapsavbrudd / Registry for abortions 1979 FHI deid. 4. Nasjonalt register over hjerte‐ og karlidelser / Cardiovascular disease registry 2012 FHI Pid. 5. Meldingssystem for smittsomme sykdommer (MSIS) / Surveillance system infectious diseases 1977 FHI Pid/deid 6. Nasjonalt vaksinasjonsregister (SYSVAK) / Vaccination registry 1995 FHI Pid. 7. Resistensregistrene (NORM, RAVN) / Registries for antibiotic resistance 2000 FHI deid. 8. Norsk overvåkingssystem for infeksjoner i sykehustjenesten (NOIS) / Hospital infections registry 2005 FHI deid. 9. Reseptbasert legemiddelregister / Prescription registry 2004 FHI Pseudo 10. Kreftregisteret / Cancer Registry 1951 Kreftregisteret Pid. 11. Norsk pasientregister (NPR) / Patient registry (hospitalisations and outpatient visits) 1997/2008Helsedir. Pid. 12. IPLOS‐registeret 2006 Helsedir. Pseudo 13. Forsvarets helseregister / Norwegian defence health registry 2005 Forsvarsdep. Pid. 14. Genetisk masseundersøkelse av nyfødte / Genetic mass‐screening of newborns 2012 OUS Pid. https://ehelse.no/helseregistre National health registries 2015
- 14. 06.10.2016 14 › Helse Nord RHF › Nordisk register for hidradenitis suppurativa - HISREG › Norsk Nakke- og Ryggregister › Nasjonalt kvalitetsregister for ryggkirurgi › Norsk register for arvelige og medfødte nevromuskulære › sykdommer › Norsk register for analinkontinens › Norsk Register for Gastrokirurgi - NoRGast › Norsk kvalitetsregister for behandling av spiseforstyrrelser › - NORSPIS › Helse Vest RHF › Norsk kvalitetsregister for artrittsykdommer (NorArtritt) › Det Norske Nyrebiopsiregisteret › Nasjonalt register for organspesifikke autoimmune sykdommer › (ROAS) › Nasjonalt register for langtids mekanisk ventilasjon (LTMV) Nasjonalt register for invasiv kardiologi Nasjonalt register for ablasjonsbehandling og elektrofysiologi › Norsk porfyriregister › Norsk MS Register og biobank › Nasjonalt korsbåndregister › Nasjonalt hoftebruddregister › Nasjonalt Barnehofteregister › Nasjonalt register for leddproteser › Nasjonalt register for kronisk obstruktiv lungesykdom (KOLS) › Norsk kvalitetsregister for leppe- kjeve- ganespalte › Norsk Intensivregister (NIR) › Norsk diabetesregister for voksne › Norsk kvalitetsregister for fedmekirurgi › Nasjonalt Kvalitetsregister for Smertebehandling 27 52 nasjonale medisinske kvalitetsregistre (2015) › Helse Midt RHF › Norsk ryggmargsskaderegister - NorSCIR Norsk hjertesviktregister Norsk hjerneslagregister Norsk Karkirurgisk register - NORKAR Norsk hjerteinfarktregister › Helse Sør-Øst RHF Nasjonalt register for brystkreft Nasjonalt register for føflekkreft Nasjonalt register for barnekreft Nasjonalt register for gynekologisk kreft Nasjonalt register for malignt lymfom og kronisk lymfatisk leukemi Nasjonalt register for lungekreft Nasjonalt register for prostatakreft (NPPC) Nasjonalt register for tykk- og endetarmskreft › Norsk kvinnelig inkontinensregister (NKIR) › Kvalitetsregister for demens Nasjonalt hjertestansregister Norsk Pacemaker og ICD-register › Norsk kvalitetsregister for hiv (NORHIV) › Norsk gynekologisk endoskopiregister (NGER) › Norsk Nefrologiregister Det norske hjertekirurgiregisteret › Gastronet › Nasjonalt kvalitetsregister for døvblindhet › Nasjonalt traumeregister › Cerebral pareseregisteret i Norge (CPRN) › Norsk Nyfødtmedisinsk Kvalitetsregister (NNK) › Nasjonalt medisinsk kvalitetsregister for barne- og › ungdomsdiabetes Andre datasamlinger › Fagsystemet KUHR (Kontroll og utbetaling av helserefusjoner, HELFO) - Primærhelsetjenesten › Forløpsdatabasen trygd (FD-trygd, SSB) › Sosioøkonomiske og økonomiske individdata i SSB (inntekt, utdanning, sysselsetting, fødeland m.m.) › Folkeregisteret (Skatteetaten)
- 15. 06.10.2016 15 Norwegian arthroplasty register • Hip replacement registry • Treatment registry – type of hip prosthesis • Narrow range of diagnoses: Osteoarthritis • Follow‐up till failure (reoperation prosthesis) • Norway register from 1987 • 164 000 primary hip prostheses followed • 27 000 reoperations with replacements • In 2014 more than 40 treatment combinations (semented, uncemented, hybrid, different brands and designs) – 17 cement types Journal Bone Joint Surg Br 1995
- 16. 06.10.2016 16 Journal Bone Joint Surg Br 1995 Why does the arthroplasty registers work [i.e. give good guidance to selecting best treatment] • Very heterogenous treatment options, hundreds of brands/types, brand/type combinations, cements in use over time • Relatively homogeneous patient group (moderate variation in prognosis) • Little clinical knowledge or clinical beliefs of choice of treatment options according to prognosis of the patient • Therefore clinical reality approximately allocates treatments unrelated to prognosis (except may be age, that is easily controlled for) • Treatment choice is often made at the institutional level
- 17. 06.10.2016 17 Questions that registry data can answer [alone or in combination with other data sources] • Trends in still births, perinatal and infant mortality • Trends in maternal/gestational diabetes • Trends in use of cesarean sections • Which drugs cause congenital malformations • Long term prognosis of low‐birth weight/prematurity • Is assisted reproductive technology safe ? • Sleeping position and sudden infant death syndrome vollset ‐ health registries in norway ‐ isar – bergen – 20‐22 May 2012 slide 34
- 18. 06.10.2016 18 Research question How will prematurely born manage the competitive adult society? Is it possible to design a study answering this question, including all gestational ages and not only the most immature? Moster et al. New Engl J Med 2008 vollset ‐ health registries in norway ‐ isar – bergen – 20‐22 May 2012 slide 35 9 Norwegian registries that provided outcomes for the study • The Medical Birth Registry • The Cause of Death Register • The National Insurance Scheme (disabilities, ICD codes) • The Norwegian Population Database (demography) • The National Education Database (education, mother and father; proxy for social class) • The Norwegian Tax Administration’s register (income) • The National Employment Service’s register (employment status) • The Register of Social Services (social benefits) • The Central Criminal and Police Information Register Moster et al. New Engl J Med 2008 vollset ‐ health registries in norway ‐ isar – bergen – 20‐22 May 2012 slide 36
- 19. 06.10.2016 19 • Year of birth 1967‐1983 • 903,402 livebirths without congenital anomalies 1 822 born at 23 to 27 weeks of gestation 2 805 at 28 to 30 weeks 7 424 at 31 to 33 weeks 32 945 at 34 to 36 weeks 858 406 at 37 weeks or later • Follow‐up through 2003 (34 years of data collection) The Medical Birth Registry – Selection of study population Moster et al. New Engl J Med 2008 vollset ‐ health registries in norway ‐ isar – bergen – 20‐22 May 2012 slide 37 Conclusion: • There was a highly significant association between reduced gestational age at birth and medical disabilities (e.g. cerebral palsy or mental retardation) • For those without disabilities, there was a weaker, but still significant association between preterm birth and level of education, income, need for social security benefits, establishing a family and having own children, but not for unemployment or criminality. • There was a striking dose-response relationship between reduced gestational age and most outcomes studied. • Most premature children who survived without medical disabilities functioned well as adults. Moster et al. New Engl J Med 2008 vollset ‐ health registries in norway ‐ isar – bergen – 20‐22 May 2012 slide 38
- 20. 06.10.2016 20 Factors considered: birth weight, gestational age, growth retardation, perinatal mortality in 2546 women who had conceived both naturally and by assisted fertilisation The Lancet 2008 Question: Does assisted fertilisation harm the baby ? Key idea: compare pregnancy outcomes in women who had singleton pregnancies conceived both spontaneously and after assisted fertilisation 2546 such women identified in Medical Birth Registry Irgens LM, Markestad T, Baste V, Schreuder P, Skjærven R, Øyen N. Sleeping position and sudden infant death syndrome in Norway 1967‐91. Arch Dis Child 1995;72:478‐82. Sudden infant death syndrome (SIDS) and sleeping position Data: • Time trend in SIDS from Medical Birth Registry • Exposure from ad hoc survey in 1992 • Time trend in retrospectively reported sleeping position i 1992 for the years 1970, 75, 80, 85, 89, 90, 91 by 24438 mothers (70% response rate) sampled from 20 largest maternity institutions. • For each year and institution 250 mothers were randomly selected 7x20x250=35000 • One page questionnaire • 92.5% stated the were certain about the babies sleeping position at 3 months of age
- 21. 06.10.2016 21 3. august 2011 Half the Norwegian population were Vaccinated with Pandemrix against «swine‐flu» H1N1 influenza A ‐ Narcolepsy ? ‐ Pregnancy complications? vollset ‐ health registries in norway ‐ isar – bergen – 20‐22 May 2012 slide 41
- 22. 06.10.2016 22 Population Registry of Norway Surveillance System of Infectious Diseases (MSIS) •Positive H1N1 tests Medical Birth Registry of Norway (MBRN) •Pregnancy outcomes •Chronic conditions in pregnant women Immunzation Registry (SYSVAK) •Vaccination status •Date of vaksination 43 HELFO‐data Reimbursement of doctors (KUHR ) •Primary care consultations •Influensa (R80)
- 23. 06.10.2016 23 Conclusion • The natiowide population‐based (central) registries we are famous for (Cancer registry, Medical birth registry, Cause of death registry, Prescription registry, Patient registry and others) are not designed to contain causal information • Quality registries, cohorts, biobanks associated with cohorts are designed to study causes of diseases and to identify best treatments • We need to establish data collection that can enrich the central registries (determinants of population health, diet, smoking, blood pressure, cholesterol, BMI, alcohol/drugs, occupational exposure, environmental exposure and others). These factors are also often prognostic factors • Regular updates is needed and best done in large representative cohorts or dedicated risk factor data collection systems • Case‐control design is sometimes used in registry data collection to provide population data on risk factors (for each event – identify 1 or more similar persons from population) Conclusion (cont.) • Without large cohorts and biobanks the central registries are of limited value for causal analysis • Clinical Quality registries have a great potential for analysis of treatments and prognostic factors. They need to be adequately sized, have sufficient follow‐up time and detailed information both on treatment (type, dose, duration, detailed information on procedures and devices) and general risk factors / prognostic factors. • Information on national risk factor distributions are necessary to compute population attributable numbers from universal RR estimates and observed event numbers in the population. • In short, we lack a risk factor registry (e.g. large living national cohort, or system for regular risk factor data collection)
- 26. 06.10.2016 26 Dagens medisin 9. april 2015 … Tilgang til helsedata for forsknings‐formål er en slik skandale: En stille skandale som skaper få overskrifter, men som man med enkle midler kunne ha rettet opp. Problemet er at dagens regelverk gjør det svært tidkrevende og kostbart å få tilgang til koblet infor‐masjon fra ulike register. Det betyr at slike koblinger i praksis gjøres langt sjeldnere og tregere enn man ellers kunne. Institutt for global helse og samfunnsmedisin Gråsoner • Forskning – kvalitetssikring – helseanalyse ‐ infrastruktur – REK avviser 25 % av søknadene med begrunnelse «faller utenfor Helseforskningsloven» • Når blir et registerforskningsprosjekt et helseregister som krever konsesjon fra Datatilsynet • Hvordan håndteres behovet for koplede filer i produksjon av helsestatistikk eller helseanalyse (versus forskning) • Anonyme data versus indirekte personidentifiserbare • SSBs rolle i helseforskning som forvalter av sosioøkonomiske data og innvandrerbakgrunn • Multippel saksbehandling av koplede filer Institutt for global helse og samfunnsmedisin
- 27. 06.10.2016 27 Utfordring – prosjekter som krever kopling av mange registre, datakilder • Det er de store prosjektene med et stort antall datakilder som gir internasjonalt forskningsfortrinn • Eksempel: Helseundersøkelser, Dødsårsaksregister, Kreftregister, Norsk pasientregister, Medisinsk fødselsregister, Hjertekarregister, Reseptregister, KUHR‐ database, utdannelse (SSB), innvandrerbakgrunn (SSB) • Krever selvstendig saksbehandling og forvaltningsvedtak i REK, SSB, hvert enkelt register, Datatilsyn • Kopling av to pseudonyme registre – lovlig men i dag i praksis umulig (manglende tekniske løsninger) – eksempel på årevis med saksbehandling Institutt for global helse og samfunnsmedisin