Health Information System - Data Quality and Assessment

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What is Data Quality?

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The overall utility of a dataset as a function of its ability to be processed easily and analyzed for a database, data warehouse, or data analytics system.

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What is the difference between a database and a data warehouse?

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A database is like a USB (smaller), while a data warehouse is like a hard drive (larger).

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List the aspects of Data Quality.

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Accuracy, Completeness, Update Status, Relevance, Consistency, Reliability, Accessibility, Appropriate Presentation.

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What are the outcomes of Data Quality?

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Low Data Quality or High Data Quality.

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What are the consequences of Low Data Quality?

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Generates costs, affects customer satisfaction, company reputation, and strategic decisions.

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What are the benefits of High Data Quality?

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Useful and consistent data; data cleansing can raise the quality of available data.

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What is Lot Quality Assessment Sampling (LQAS)?

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A tool that uses small random samples to distinguish between different groups of data elements with high and low data quality.

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What is the purpose of LQAS in health management?

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Makes conducting surveys or supervision more efficient.

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What are the steps in applying LQAS?

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Define the service to be assessed, identify the unit of interest, define performance thresholds, determine acceptable error, and observe errors.

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What is the Routine Data Quality Assessment (RDQA) Tool?

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A simplified version of the Data Quality Audit (DQA) that verifies and assesses the quality of reported data.