Right here right now (RHRN) pilot study: testing a method of near-real-time data collection on the social determinants of health

  • Lynn Naven*
  • , Greig Inglis
  • , Rachel Harris
  • , Gillian Fergie
  • , Gemma Teal
  • , Rebecca Phipps
  • , Sally Stewart
  • , Lorna Kelly
  • , Shona Hilton
  • , Madeline Smith
  • , Gerry McCartney
  • , David Walsh
  • , Matthew Tolan
  • , James Egan
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Background
    Informing policy and practice with up-to-date evidence on the social determinants of health is an ongoing challenge. One limitation of traditional approaches is the time-lag between identification of a policy or practice need and availability of results. The Right Here Right Now (RHRN) study piloted a near-real-time data-collection process to investigate whether this gap could be bridged.

    Methods
    A website was developed to facilitate the issue of questions, data capture and presentation of findings. Respondents were recruited using two distinct methods - a clustered random probability sample, and a quota sample from street stalls. Weekly four-part questions were issued by email, Short Messaging Service (SMS or text) or post. Quantitative data were descriptively summarised, qualitative data thematically analysed, and a summary report circulated two weeks after each question was issued. The pilot spanned 26 weeks.

    Results
    It proved possible to recruit and retain a panel of respondents providing quantitative and qualitative data on a range of issues. The samples were subject to similar recruitment and response biases as more traditional data-collection approaches. Participants valued the potential to influence change, and stakeholders were enthusiastic about the findings generated, despite reservations about the lack of sample representativeness. Stakeholders acknowledged that decision-making processes are not flexible enough to respond to weekly evidence.

    Conclusion
    RHRN produced a process for collecting near-real-time data for policy-relevant topics, although obtaining and maintaining representative samples was problematic. Adaptations were identified to inform a more sustainable model of near-real-time data collection and dissemination in the future.

    Key messages

    RHRN aimed to capture people’s everyday experiences to provide timely insights for policy-makers.

    It proved feasible to run a multi-mode weekly data-collection process to inform decision-makers.

    Difficulties recruiting a representative sample limited the utility of the quantitative data.

    Decision-making processes were not flexible enough to respond to rapid weekly evidence generation.
    Original languageEnglish
    Pages (from-to)301-321
    Number of pages21
    JournalEvidence & Policy
    Volume14
    Issue number2
    Early online date18 Jul 2017
    DOIs
    Publication statusPublished - 31 May 2018

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • Evidence
    • Policy
    • Real-time
    • Technology

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