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A Database is not what you think and different designs serve different purposes.
 

A Database is not what you think and different designs serve different purposes.

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Lecture given at Eular Vienna 2005.

Lecture given at Eular Vienna 2005.

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    A Database is not what you think and different designs serve different purposes. A Database is not what you think and different designs serve different purposes. Presentation Transcript

    • Different designs of longitudinal observational studies (databases, regist ries , cohort studies) serve different purposes Loreto Carmona Research Unit Spanish Society of Rheumatology
    • Why this talk?
      • Sometimes the only point in which investigators agree in a given project is about the need to collect data .
      • T here is indeed much misunderstanding about databases.
      • T he first principle of data collection : We should not collect data just for the sake of it, without explicit and specified objectives .
    • What is a database?
      • NOT:
        • Any set of data entered into a computer
      • YES:
        • A tool to organize the data in a study
    • What is not a database? A dataset
    • Other uses
    • What is a database?
      • Organizing
      • Hierarchical
      • Relational
    • Structure patient treatment treatment treatment treatment AE AE AE AE AE AE
    • Structure patient visit visit visit visit outcome outcome outcome outcome outcome outcome
    • Time and databases Medical databases time Longitudinal Observational Studies
    • Can we analyse data directly from a DB? wide long
    • wide
    • long
    • Types of databases
      • Depend on the purpose and design of the study they serve .
    • Types of databases
      • Registries
      • Cohorts
      • Administrative databases
      • Clinical databases
    • Registries
      • The introduction of new elements is not pre-planned (no schedule).
        • relate to the pace of patients entry
        • events entry
      • The purpose of the registry defines the types of registry:
        • Disease registry
        • Drug registry
    • Registries
      • Disease registry :
        • to estimate incidence of diseases
        • pace of new entries = occurrence of new cases
      • Drug registry :
        • The main purpose of such registries is the identification of adverse events
        • pace of entry = initiation of new treatments, of a target drug or therapeutic group, in patients who meet the inclusion criteria
    • Cohorts
      • Studies set up for testing hypotheses .
        • Sensu strictu aetiological hypotheses
        • they can also be assembled to test prognosis, or to test resource use hypothesis
      • Subjects in a cohort must be sampled in a probabilistic way ( to be representative ) .
      • Timing of data entry pre-established in visits or examinations at a given interval ( periodical ).
    • Cohorts (concepts)
      • Inception cohort
        • all new cases
        • or early
      • Nested case-control studies
        • advantage: cases and controls selected equally
    • Cohorts (concepts)
      • Open cohorts
        • Permanent incorporation
        • allow the study of the simultaneous influence of calendar time, age (duration) and cohort (onset) in demography, epidemiology, and clinical follow-up
    • Cohorts (concepts)
    • Cohorts (concepts)
      • Closed cohorts
        • specific research objective ( sample size )
        • recruitment period
        • subjects become older with follow-up
      • Permanent surveys
        • examination over time is established in repeated cross-sectional surveys
        •  large open cohorts which are monitored over such a long time ( Framingham study )
    • Cohorts (concepts)
      • Randomised controlled trials
        • cohorts in which the hypothesis is the efficacy of an intervention
        • Not a LOS ( planned intervention )
    • Cohorts (concepts)
      • Aren’t prognosis or resource use studies cohorts?
        • OK if the sample is selected in a probabilistic way
        • and the hypothesis is pre-established before the launch of the cohort :
          • link between exposure to prognostic factors (i.e. determinants) and rate of occurrence of outcome
          • link between determinants and rate of use or cost
    • Types of databases
      • Registries
      • Cohorts
      • Administrative databases
      • Clinical databases
    • Administrative databases
      • S pecific purpose : managing the economic and organization aspects
      • They allow to assess and preview :
        • the need of workforce
        • allocation of resources
        • logistic needs
        • insurance monitoring
        • costs, etc.
    • Administrative databases as surrogates
      • PROS
      • rapid response (availability)
      • large sets of population ( increases statistical power )
      • CONS
      • severe selection bias
    • Administrative databases ’ best use
      • To cross-check data in clinical databases :
        • to confirm death ,
        • work status ,
        • drug consumption ...
    • Clinical databases
      • Quite often physicians record patients characteristic and variables directly from their practice in an intent to monitor health care practices.
      • The resulting clinical databases are useful to :
        • retrieve patients’ reports
        • Retrieve individual clinical histories
        • assess the individual practice composition of a department or a clinic
    • Clinical databases ’ bias
      • The patients included have not been selected in a probabilistic way , what precludes the use of formal hypothesis testing statistical instruments.
      • Representativity
      • D ifficult y to record all variables with the expected quality of a main outcome variable if one does not know ahead of time what the main outcome variable will be ( study protocol )
    • Clinical databases ’ best use
      • To monitor practice
      • T o identify patients with a given characteristic, and to use them to draw a random sample, better if multicentre, and to test prospectively a research hypothesis
    • Conclusions
      • We should bear in mind the meaning and use of databases.
      • Different types of databases serve very different purposes .
      • A clear understanding of the different investigation designs sh ould avoid many of the databases we launch be just a lot of work and very little of science.