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The Healthcare Effectiveness Data and Information Set (HEDIS) is a widely used set of performance measures in the managed care industry, developed and maintained by the National Committee for Quality Assurance (NCQA). HEDIS was designed to allow consumers to compare health plan performance to other plans and to national or regional benchmarks.
Health plans seek accreditation and measure performance through the administration and submission of the Healthcare Effectiveness Data and Information Set (HEDIS) and Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey. The National Committee for Quality Assurance provides an evidence-based program for case-management ...
[4]: 19 The Healthcare Effectiveness Data and Information Set (HEDIS) is a prominent set of measurements and reporting on it is often mandated by states as well as Medicare; [4]: 19 as of 2017, HEDIS data was collected for plans covering 81% of the insured. [42]
Clinical Data Acquisition Standards Harmonization (CDASH) [6] Defines a minimal data collection set for sixteen safety SDTM Domains, harmonizing element names, definitions and metadata. The objective is to establish a standardized data collection baseline across all submissions. CDISC Terminology
The standard describes data formats and elements (known as "resources") and an application programming interface (API) for exchanging electronic health records (EHR). The standard was created by the Health Level Seven International (HL7) health-care standards organization.
Data element definitions are critical for external users of any data system. Good definitions can dramatically ease the process of mapping one set of data into another set of data. This is a core feature of distributed computing and intelligent agent development.
SOURCE: Integrated Postsecondary Education Data System, University of Alabama at Birmingham (2014, 2013, 2012, 2011, 2010). Read our methodology here. HuffPost and The Chronicle examined 201 public D-I schools from 2010-2014. Schools are ranked based on the percentage of their athletic budget that comes from subsidies.
Definition: Clear definitions should be provided so that current and future data users will know what the data mean. Each data element should have clear meaning and acceptable values. Granularity: The attributes and values of data should be defined at the correct level of detail.