1. Dependent sampling and clerical matching of survey and admin data to support the production of admin-based population estimates NSDEC(24)12

1. Debbie Curtis, from the ONS Surveys team, and Amy Large, from the Methodology and Quality division, presented this item to the Committee for their feedback.
2. The paper covered the proposal to develop a dependent sampling and clerical matching methodology to support the production of population estimates.
3. The Committee discussed the project, and raised points on the following:
   1. How identification risk would be mitigated
   2. The importance of informed consent for participants
   3. The necessity of public engagement around using administrative data
   4. How alternative approaches suggested would differ from the main option proposed in practice

Action:

The research team to provide assurance via the Secretariat and discuss the points raised in 1.3 with the Committee at the NSDEC April meeting.

2. Health Insights Study NSDEC(24)13

1. Caroline Youell and Maria Ledgeway from the ONS Winter CIS team submitted this item via correspondence.
2. The HIS follows on from the Coronavirus Infection Survey (CIS) and the Winter Coronavirus Infection Survey (Winter CIS), engaging participants of those surveys in new questions about their access to primary care such as GP services. Key differences from the Winter CIS, which has previously been brought to NSDEC, include that the questionnaire will not include bio-sampling, focuses on a different health topic than the original study, and relies on implied consent through filling out an online questionnaire.
3. The Committee raised the following points via correspondence:
   1. They acknowledged the clear public good of this project.
   2. They asked the research team to clarify their approach to participant consent, the accessibility of the survey, the representation of the sample surveyed and respondent burden.

Action:

The research team to follow up on points raised via the Secretariat and provide an update to the Committee.