1. Right Here Right Now (RHRN) Pilot Study: Testing a Method of Near-Real-Time Data Collection on the Social Determinants of Health
- Author
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Naven, Lynn, Inglis, Greig, Harris, Rachel, Fergie, Gillian, Teal, Gemma, Phipps, Rebecca, Stewart, Sally, Kelly, Lorna, Hilton, Shona, Smith, Madeline, McCartney, Gerry, Walsh, David, Tolan, Matthew, and Egan, James
- 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.
- Published
- 2018
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