Participant's warning: "Do not let the best be the enemy of the good!"


  • Validated and 'clean' data
  • Universal Coding Standards and comparability issues
  • Weighting of various data sets in developing performance measures (beyond Macleans) incl. conceptual design
  • National (not federal or provincial) organization of data
  • Better and free access to publicly AND privately owned databases (also need scan of current policy practices and information around access/privacy issues)
  • Ethics protocols for collecting and using data
  • Research repository/clearing house on what has been done
  • More expertise in data analysis-
    theoretical models for data interpretation (models drive what data we use or not)
    how to use large data sets-
    use mixed methodologies (quantitative AND qualitative approaches)
  • Clearly distinguish the databases for medical record-keeping and insurance record-keeping
  • Multi-level, integrated and multi-sectoral data
  • Link administrative data to health status
  • Need to provide decision support systems
  • Sustain longitudinal tracing
  • Use patient 'smart cards'
  • Remuneration systems other than fee for services and privatization of the system present problems for data collection
  • At what level of management should data from different regions get shared?


  • Data sets that accurately capture determinants of health (need measures of 'chronically good health'); these need to be person-specific and linkable
  • Need to extend data capturing such that databases represent the entirety of the health system (e.g., using databases to track resources)
  • Data on first line (première ligne)
  • Sufficient clinical data to make comparisons across groups
  • Performance indicators for organizations and individuals at ALL levels of the system
  • Administrative data to address emerging priorities
  • More data to relate inputs to outcomes adjusted
    'Real time' data for time sensitive issues (quick collect, quick analysis)
  • Databases on best practices or best evidence (at program and structural level, not just clinical)
    More sophisticated and comprehensive human resource data sets (to improve recruitment/retention strategies)
  • Data on actual/future public expectations/preferences, and their shaping process
    Services used by patients
  • Data on use of the system by marginal populations
  • Role of the family in health care