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Our Data Quality Program is recognized internationally for its comprehensiveness and high standards in health information management.

Improving data and information quality is a collaborative effort. CIHI works with its data suppliers and users to ensure we continue to be a trusted source of health information that meets the broadening needs of our stakeholders.

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Data Quality by Data Holding

Narrow the search results below by using the drop-down menu to choose a data holding, or use the search bar for more freedom. You can also sort results by year.

Click a title for pricing and eligibility information. Some restrictions may apply. 

Data Holding Title Year Description
Provincial/Territorial Data Quality Report: Indicators and Contextual Measures 2016

CIHI produces annual data quality reports to assess the contribution of each province and territory to 11 of CIHI's databases.

CJRR Data Quality Documentation for Users: Canadian Joint Replacement Registry, 2015-2016 Data 2015-2016

Information on coverage, non-response, collection processes, data quality control, methodological changes and revision history.

CORR Data Quality Documentation for Users: Canadian Organ Replacement Register, 2006 to 2015 Data 2016

Data Quality Documentation for Users: Canadian Organ Replacement Register, 2006 to 2015 Data

CORR Canadian Organ Replacement Register Data Quality Documentation, 2005 to 2014 Data 2016

Data quality documentation for users.

CPCD MIS Patient Cost Database Methodology 2017

This document is a comprehensive methodology that describes allocation and cost distribution per patient visit for comparisons and decision-making on resource consumption and performance.

DAD Data Quality Study of the 2015–2016 Discharge Abstract Database: A Focus on Hospital Harm 2015–2016

A summary of results from a reabstraction study on DAD data, providing an assessment of coding quality, with a particular focus on data used to measure patient safety.

DAD Discharge Abstract Database Open-Year Data Quality Test Specifications, 2015–2016 2015–2016

Open-year data quality tests performed on the DAD in 2015–2016, along with the rules, selection criteria and data elements used.

DAD Job Aid: Alternate Level of Care Diagnosis List: Clarification of Use, 2016 2016

The importance of getting ALC data right and how to resolve problems related to medical facilities and health care.

DAD Job Aid: Changes to Z-Codes Allowable With Alternate Level of Care Service 99 — 2016 2016

Z-code changes to coding and abstracting within the context of ALC.

DAD Data Quality Documentation, Hospital Morbidity Database — Current-Year Information, 2015–2016 2015–2016

Information on the quality of the data file for the relevant fiscal year.

DAD Data Quality Documentation, Discharge Abstract Database — Current-Year Information, 2015–2016 2015–2016

Current-Year Information is produced on a yearly basis and provides information on the quality of the data file for the relevant fiscal year.

HMDB Job Aid: Alternate Level of Care Diagnosis List: Clarification of Use, 2016 2016

The importance of getting ALC data right and how to resolve problems related to medical facilities and health care.

HMDB Job Aid: Changes to Z-Codes Allowable With Alternate Level of Care Service 99 — 2016 2016

Z-code changes to coding and abstracting within the context of ALC.

HMDB Data Quality Documentation, Hospital Morbidity Database — Current-Year Information, 2015–2016 2015–2016

Information on the quality of the data file for the relevant fiscal year.

HMDB Data Quality Documentation, Discharge Abstract Database — Current-Year Information, 2015–2016 2015–2016

Current-Year Information is produced on a yearly basis and provides information on the quality of the data file for the relevant fiscal year.

HMHDB HMHDB Hospital Mental Health Database, 2015-2016: User Documentation 2015-2016

Describes the composition of the Hospital Mental Health Database (HMHDB), data quality and other information relevant to data users.

NACRS National Ambulatory Care Reporting System Open-Year Data Quality Test Specifications, 2015–2016 2015–2016

Open-year data quality tests performed on NACRS in 2015–2016, including the rules, patient care types, submission levels, selection criteria and data elements used.

NACRS Data Quality Documentation, National Ambulatory Care Reporting System— Current-Year Information, 2015–2016 2015–2016

Current-Year Information is produced on a yearly basis and provides information on the quality of the data file for the relevant fiscal year.

NRS National Rehabilitation Reporting System Data Quality Documentation, 2015–2016 2015–2016

Information on the fitness of National Rehabilitation Reporting System (NRS) data for various uses.

OMHRS System for Classification of In-Patient Psychiatry (SCIPP) Grouping Methodology: Flow Charts and SAS Code, OMHRS Version 2016–2017 2016-2017

This product describes the System for Classification of In-Patient Psychiatry (SCIPP) grouping methodology through flowcharts and SAS code. This grouping methodology is meant for use with all Ontario Mental Health Reporting System (OMHRS) data. 

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Data quality framework

CIHI’s Data Quality Framework sets out an approach to systematically assess, document and improve data quality for all of our data holdings. Applying the framework helps us identify both strengths and limitations in our data and identify how it can be improved. We provide documentation to help users determine whether the data meets their needs and, if so, how to use it appropriately.

Provincial and territorial data quality reports

CIHI produces annual data quality reports to assess the contribution of each province and territory to 11 of CIHI’s databases. These reports are shared with deputy ministers of health and key jurisdictional representatives across the country in order to raise awareness of data quality at the highest level of government.

The reports have helped to enhance the coverage and the quality of our data. An executive summary highlights each jurisdiction’s most significant data quality findings, areas of best practice and improvement, and areas that may require particular attention.

Discharge Abstract Database reabstraction studies

CIHI conducts regular reabstraction studies of the Discharge Abstract Database (DAD) as part of its comprehensive Data Quality Program. These studies are designed to evaluate the quality of abstract coding, identify systemic issues and assess the impact of any coding issues on CIHI’s products. They involve health information coding specialists performing a chart review of acute care diagnostic, intervention and other selected data elements that were previously collected and submitted to CIHI.

The most recent reabstraction study was carried out on open-year (preliminary) 2015–2016 DAD data and provides an assessment of overall coding quality, with a primary focus on data used to measure patient safety.