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Most HEDIS data is collected through surveys, medical charts and insurance claims for hospitalizations, medical office visits and procedures. Survey measures must be conducted by an NCQA-approved external survey organization. Clinical measures use the administrative or hybrid data collection methodology, as specified by NCQA.
HCUP Logo. The Healthcare Cost and Utilization Project (HCUP, pronounced "H-Cup") is a family of healthcare databases and related software tools and products from the United States that is developed through a Federal-State-Industry partnership and sponsored by the Agency for Healthcare Research and Quality (AHRQ).
Mobile data collection or mobile surveys is an increasingly popular method of data collection. Over 50% of surveys today are opened on mobile devices. [6] The survey, form, app or collection tool is on a mobile device such as a smart phone or a tablet.
The Minimum Data Set (MDS) is part of the U.S. federally mandated process for clinical assessment of all residents in Medicare or Medicaid certified nursing homes and non-critical access hospitals with Medicare swing bed agreements.
Survey methodology is "the study of survey methods". [1] As a field of applied statistics concentrating on human-research surveys, survey methodology studies the sampling of individual units from a population and associated techniques of survey data collection, such as questionnaire construction and methods for improving the number and accuracy of responses to surveys.
The data management plan describes the activities to be conducted in the course of processing data. Key topics to cover include the SOPs to be followed, the clinical data management system (CDMS) to be used, description of data sources, data handling processes, data transfer formats and process, and quality control procedure
Analysis: the process of translating data into information utilized for an application. Each aspect is analyzed with 10 different data characteristics: Accuracy: Data are the correct values and are valid. Accessibility: Data items should be easily obtainable and legal to collect. Comprehensiveness: All required data items are included. Ensure ...
Barriers to the widespread adoption of effective data standards include: inconsistency in and poor understanding of the concepts and language used in clinical practice, for example compared to those in chemistry or accounting; rival systems of standards; the cost of implementation or change to better standards; avoidance of commercial competition.