Data quality and information quality are fundamental to CIHI’s mandate to
- Inform public policy
- Support health care management
- Build public awareness about the factors that affect health
Our data quality program is recognized nationally and internationally for its comprehensiveness and high standards. Its goal is to continuously improve data and information quality within CIHI and the broader health sector.
Our strategy for data quality is based on a six-point plan designed to
- Foster a data quality culture
- Strengthen data quality infrastructure and capacity
- Cultivate the data supply chain
- Enhance external data quality collaboration
- Initiate fast-track priority projects
- Promote communication and provide consultation
Improving data and information quality is a collaborative effort. CIHI works with its data suppliers and users to support each of these activities. All staff play some role in helping to manage the quality of our data. This collaborative effort is designed to meet the changing and expanding user requirements and expectations of CIHI’s data holdings.
We welcome your feedback and questions
- Contact us at communications@cihi.ca
Have a data inquiry or research question? Make a custom data request.
Data quality information
Data quality in action
Data quality in action
Each program area at CIHI regularly performs a number of data quality activities to help prevent, detect, monitor and resolve data issues, including
- Developing and implementing standards, including diagnosis and intervention coding standards for coding in ICD-10-CA and CCI and standards for financial reporting (MIS)
- Providing educational sessions to data providers on data requirements and data quality issues
- Offering a Coding Query service to health information management professionals and other data collectors
- Publishing edit specifications for vendors’ abstracting software
- Building systems that automatically check for data quality issues and providing feedback to data suppliers
- Performing data analyses and additional checks on the data to identify other potential quality issues
- Assessing and documenting the quality of data and providing this information to suppliers and users of the data
- Preparing annual jurisdictional reports on the status of data quality to provincial/territorial deputy ministers
Reports and analyses about data quality
- Earning Trust: Key Findings and Proposed Action Plan From the Data Quality Strategies Study (June 2003) (PDF, 290 KB)
- Earning Trust—3 Years Later (Dec. 2006) (PDF, 98 KB)
Data Quality Framework
CIHI’s Data Quality Framework (2009) sets out an approach to systematically assess, document and improve data quality for all of our data holdings. This framework is based on the five dimensions of quality and helps us identify both strengths and limitations in our data. After the assessment, we identify how to improve the data, and we provide documentation to help users determine whether the data meets their needs and, if so, how to use it appropriately.
Dimensions of data quality
CIHI uses five dimensions to define data and information quality:
- Accuracy—How well information from a data holding reflects the reality it was designed to measure
- Timeliness—How current the data is at the time of release
- Comparability—The extent to which a data holding is consistent over time and collects data in a way similar to other data holdings
- Usability—The ease with which data can be accessed and understood
- Relevance—The degree to which a data holding meets users’ current and potential future needs
Special studies about data quality
CIHI also performs special data quality studies to check the accuracy of the data supplied to us. For data holdings that are based on data extracted from patients’ medical records or charts, we perform reabstraction studies. In these studies, we visit a sample of submitting health care organizations to review a sample of the original patient charts and compare this information with what exists in CIHI’s data holding. To date, we have conducted studies on the following databases:
- Discharge Abstract Database
- National Ambulatory Care Reporting System
- Canadian Organ Replacement Register
