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[Extra Quality] Project 2 Third Edition Tests

November 21, 2022

[Extra Quality] Project 2 Third Edition Tests



 
 
 
 
 
 
 

[Extra Quality] Project 2 Third Edition Tests

To ensure the greatest possible representativeness, the index of learning opportunities uses schools’ self-reported data on the number of support staff available at the school. These figures are based on the Minimum Education Data Set (MEDS), a joint programme of the European Statistical Office (Eurostat) and the OECD’s Centre for Educational and Vocational Statistics (CEVS). To compute the number of support staff, the figures needed for each country are pooled across all schools in the EU. The raw numbers are then converted into a per country ratio according to categories of the number of support staff per school that have been agreed between the OECD and Eurostat. In the table below, these ratios are shown. The ratios are not estimated weights. They are necessary to provide comparable measures across countries. They should be interpreted in the context of the information that the Education at a Glance 2014 report provides on teaching personnel and institutional characteristics of schools that report on the number of staff (EC 2016: 7.4.5). As the number of support staff in a school is only a partial indicator of the degree of support that a school can provide to its students, the final outcome from these two components (treatment and control) will serve as an indicator of the overall quality of education at a country level. These indicators are included in the Learning Opportunity Index in the same way that they have been included in the previous editions of the Index.

The rapid transition to digital health records over the past decade has caused tensions in the cross-sector health data community, including tensions between record-keepers and information-providers, access to health records by third parties, and sharing of health records between providers, health researchers, payers, patients, and regulators. Thus, the re-evaluation of data quality has been at the forefront of the reform of health care in Canada.

The purpose of the 2nd edition of the project 2 data quality workbook is to further define the data quality limitations of non-representative education data, to provide examples of how to test the quality of data and to demonstrate an approach to test-driven data quality improvement projects.
The 2nd edition of the project 2 data quality workbook is a ready-to-use template for establishing a data quality system for education-related data. The workbook is based on the Project 2 literature review and on the results of several assessments of the quality of non-representative education data collected in the Data Quality Initiative. The workbook provides background information on how data are typically collected in educational research, gives an overview of the four common data quality themes, and provides the “how to” details of conducting a test. The focus of the workbook is to demonstrate the process of data quality improvement using an iterative approach.
The first step in the clinical content evaluation process is to define the clinical content categories in which registry data elements will be collected. The registry’s clinical content category approach will vary depending on its purpose. The reasons for this vary depending on the purpose of the registry, e.g., clinical research or quality improvement. For example, a registry for clinical research or patient safety or harm reduction purposes may need to collect a relatively large number of registry data elements, whereas registries focused on providing patient information and providing feedback to clinicians or patient for quality improvement purposes may be more focused on extra quality a few data elements.
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