Description:

Growing Up in New Zealand longitudinal dataset

Additional information:

Have_(encrypted)_NHI Yes
Personally identifiable (e.g. linked to NHI numbers) and longitudinal or aggregated (e.g. for planning, clinical research etc.)? longitudinal, internal working dataset has a created family ID, external working dataset further anonymised
Volume of data (e.g. how many records) Since when? data from different data collection waves from antenatal to when the children are 45 months old
Purpose and governance including ethics committee/patient consent mechanisms. Q: How do you get around ethics/privacy issues with your data sources? Esp. DHBs? consent forms, ethics approval, secure processes
Scope Cohort
Does the data contain diagnoses and clinical outcomes? Does the data contain procedures, device information and medication for therapy? Does this data set have cost / price data? information from participants across the themes of the study - family & whanau, societal context, education, health & wellbeing, pyschsocial & cognitive development, culture & identity
Presence of Data dictionary? Column headings in Excel or any kind of data model if residing in a relational database (e.g. Access, SQL Server, Oracle etc.) data dictionary, held in relational database http://www.growingup.co.nz/data.shtml
Linked (or linkable) to other datasets within your organisation or across the Sector linked to routine datasets that consent has been obtained for eg NMDS, perinatal information, NIR
How often does this data set get updated? Daily? Weekly? Monthly? Quarterly? Yearly? updated at each data collection wave
Indication of data quality (e.g. missing values, duplications, inconsistencies etc.). Q: Audits? How do you ensure the data is valid and correct? detalied work to ensure quality data is collected, data is cleaned after collection, peer review and checking undertaken
Brief info about the systems and processes used to collect/manage data. Q: Where the data is collected, in what form, and accessibility? data is collected using a CAPI or CATI, identifiable data kept separate, secure and robust systems and processes used throughout process, data transfered to research data, stored in relational databases, strong security at all stages, limited access
Data format, e.g., data structure, data types, and storage form (relational database, Excel, csv, etc.). relational database
How well the data is structured, e.g. free text VS coded text VS pick-list (drop-down list) extensive data collected
How quickly can the data be made available from time of request and how old is the data once it is made available availability internally and externally differs, managed through a strong data access protocol and data access committe, availability timing depends on the data collection waves and funding availability