Diabetes Cohort Study
Description:
The Diabetes Cohort Study (DCS) is a prospective open cohort using routinely collected data from a national primary-care annual review program called “Get Checked,” which commenced in New Zealand in 2000. Funded by the Ministry of Health, nearly all the reviews were undertaken by general medical practitioners or practice nurses. With informed consent, astandard template of clinical and demographic data was completed and submitted, usually electronically, to local primary care organizations around the country to provide regional statistics on diabetes and clinical management. Almost all data were collected by 26 organizations around the country, all of whom were invited to provide data for this study.
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.)? | Yes - NHI |
Volume of data (e.g. how many records) Since when? | Data were collected from 71,570 people with type 2 diabetes between January 2000 and December 2006. |
Purpose and governance including ethics committee/patient consent mechanisms. Q: How do you get around ethics/privacy issues with your data sources? Esp. DHBs? | National programme - based on individual patient consent |
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? | Very comprehensive; diagnoses, labs, procedures and diabetic assessments. Through linkages outcomes and costing information can be obtained. |
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 collected from integration with GP Practice Management Systems (PMS). Data schema is present. |
Linked (or linkable) to other datasets within your organisation or across the Sector | Yes - Each patient was identified by an encrypted unique identifier that maintained their anonymity but allowed linkage of their records to the national collections of hospital discharge and mortality |
How often does this data set get updated? Daily? Weekly? Monthly? Quarterly? Yearly? | real-time but data collection has ceased since 2006 |
Indication of data quality (e.g. missing values, duplications, inconsistencies etc.). Q: Audits? How do you ensure the data is valid and correct? | variable (according to a study covering the Waikato region: the coverage of the “Get Checked” programme (62%-80%) varied depending on practice IT systems, data handling procedures and patient characteristics) |
Brief info about the systems and processes used to collect/manage data. Q: Where the data is collected, in what form, and accessibility? | Data collected using advanced forms within Medtech32 PMS. |
Data format, e.g., data structure, data types, and storage form (relational database, Excel, csv, etc.). | Data stored in PMS in a RDMS |
How well the data is structured, e.g. free text VS coded text VS pick-list (drop-down list) | mostly structured. |