DML
Description:
Data warehouse stores patient Lab results since October 2009. Primarily used for management of the laboratory.
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.)? | All records are linked to patient identifiers. Approximately 90% are linked to an NHI |
Volume of data (e.g. how many records) Since when? | There are records of 1.6 million patient encounters |
Purpose and governance including ethics committee/patient consent mechanisms. Q: How do you get around ethics/privacy issues with your data sources? Esp. DHBs? | We have an in house privacy committee to review external requests for information. The only sharing of information we allow is de-personalised, with the exception of projects that have sought and received their own ethics approval . |
Scope | Provider |
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? | Some test results lead to diagnoses, but generally the diagnosis is left up to the attending physician.No clinical outcomes are recorded.The dataset has no details of procedures,device information or medication.The data set has a base price associated with each test performed. (Originating from a MOH schedule for community laboratory testing) |
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.) | There is no data dictionary as such. Data query tools analyse the data structure on the fly. |
Linked (or linkable) to other datasets within your organisation or across the Sector | There is no linkage to other data sets. |
How often does this data set get updated? Daily? Weekly? Monthly? Quarterly? Yearly? | The data is updated nightly. |
Indication of data quality (e.g. missing values, duplications, inconsistencies etc.). Q: Audits? How do you ensure the data is valid and correct? | Auditing is only at the row count level. Ie. Everything is accounted for at a database level. The consistency or quality of the data reecived is not formally checked. |
Brief info about the systems and processes used to collect/manage data. Q: Where the data is collected, in what form, and accessibility? | The data all originates from our laboratory information system. This data is manually collected from the referrers "request for tests form ". Test results data comes from the laboratory staff and analysers. |
Data format, e.g., data structure, data types, and storage form (relational database, Excel, csv, etc.). | The data is held in a normalised relational database. |
How well the data is structured, e.g. free text VS coded text VS pick-list (drop-down list) | The data type depends on the information stored. Some is structured, some text, some numeric. |