title: Method for identifying eligible individuals for a prevalence survey in the absence of a disease register or population register.
abstract: BACKGROUND
  Identifying eligible individuals for a prevalence survey is difficult in the absence of a disease register or a national population register.
  
  
  OBJECTIVE
  To develop a method to identify and invite eligible individuals to participate in a national prevalence survey while maintaining confidentiality and complying with privacy legislation.
  
  
  METHODS
  A unique identifier (based on date of birth, sex and initials) was developed so that database holders could identify eligible individuals, notify us and invite them on our behalf to participate in a national multiple sclerosis prevalence survey while maintaining confidentiality and complying with privacy legislation.
  
  
  RESULTS
  Several organisations (including central government, health and non-governmental organisations) used the method described to assign unique identifiers to individuals listed on their databases and to forward invitations and consent forms to them. The use of a unique identifier allowed us to recognise and record all the sources of identification for each individual. This prevented double counting or approaching the same individual more than once and facilitated the use of capture-recapture methods to improve the prevalence estimate. Capture-recapture analysis estimated that the method identified over 96% of eligible individuals in this prevalence survey.
  
  
  CONCLUSIONS
  This method was developed and used successfully in a national prevalence survey of multiple sclerosis in New Zealand. The method may be useful for prevalence surveys of other diseases in New Zealand and for prevalence surveys in other countries with similar privacy legislation and lack of disease registers and population registers.
authors.affiliation: Health Sciences Centre, University of Canterbury, Christchurch, New Zealand. ann.richardson@canterbury.ac.nz
authors.forename: A K
authors.initials: AK
authors.lastname: Richardson
authors.forename: G
authors.initials: G
authors.lastname: Clarke
authors.forename: C E
authors.initials: CE
authors.lastname: Sabel
authors.forename: J F
authors.initials: JF
authors.lastname: Pearson
authors.forename: D F
authors.initials: DF
authors.lastname: Mason
authors.forename: B V
authors.initials: BV
authors.lastname: Taylor
mesh_terms: D003219:Confidentiality / Q000331:legislation & jurisprudence; D003430:Cross-Sectional Studies / Q000941:ethics / Q000379:methods*; D016208:Databases, Factual; D006306:Health Surveys / Q000941:ethics / Q000379:methods*; D006801:Humans; D008499:Medical Records; D009103:Multiple Sclerosis / Q000453:epidemiology; D009520:New Zealand / Q000453:epidemiology; D010355:Patient Identification Systems / Q000941:ethics / Q000379:methods*; D015995:Prevalence; D018907:Privacy; D011795:Surveys and Questionnaires