Collaborative sharing of health and social housing data in a population health management (PHM) platform to prioritise repair work for damp and mould (DM).
<bold>Background:</bold> Detrimental effects of DM on respiratory health are well known and impact on clinically vulnerable (CV) individuals of all ages. Guidance states UK landlords must address DM hazards. PHM platforms offer new opportunities for data sharing between NHS (national health service; UK) organisations and councils to systematically prioritise DM repair work in council owned social housing (SH) according to health-related factors for the first time. <bold>Aim:</bold> To identify households whose health is at risk when exposed to DM and develop risk stratification modelling. <bold>Methods:</bold> A vulnerability dataset created for a cohort of SH households using national guidance on CV, refined by consultation with respiratory clinicians, to search clinical records linked to each property. Number of households and vulnerabilities identified were compared using different methods depending on the inclusion of children and elderly. <bold>Results:</bold> Figure 1: Comparison of vulnerabilities identified in SH. Method 1: 99% of households had at least one vulnerability; 23% having four or more. Method 2: 90% had at least one vulnerability; 10% having four or more. <bold>Conclusion:</bold> Health data can identify households vulnerable to DM. Next steps are to evaluate how this could support systematic prioritisation of DM repairs in SH and refine the model to develop a weighted vulnerability risk score.
Authors
- Jessica Sheringham (ORCID: https://orcid.org/0000-0003-3468-129X)
- Kalyan Roy
- M. Salman Shaukat
- Harriet North
- Gayathri Balasubramaniam
Institutions
- University College London Hospitals NHS Foundation Trust (GB)
- London Borough of Islington (GB)
- Sequenom (United Kingdom) (GB)
- University College London (GB)
Publication Details
- Published
- 2024-09-14
- DOI
- https://doi.org/10.1183/13993003.congress-2024.pa1322
- Primary Topic
- BIM and Construction Integration
- Type
- article
- Field-Weighted Citation Impact
- 0.00