Literature DB >> 15738736

Development of the Society of Gastroenterology Nurses and Associates Minimum Data Set: an evidence-based resource.

Kathy B Bean.   

Abstract

The Society for Gastroenterology Nurses and Associates (SGNA) has developed a Minimum Data Set identifying the essential elements necessary to document delivery of patient care in the gastrointestinal endoscopic setting. Standardized information, such as a minimum data set, for facilitating communication among practitioners is believed to enhance patient outcomes. The SGNA Minimum Data Set was developed for "public" use to facilitate quality patient outcomes and to enhance the education, research, and clinical practice of GI nurses. Data were collected from a cross-sectional representation of geographic locations and settings (major medical centers, community hospitals, and free-standing clinics) in order to establish a broad evidence-based perspective for the data set. Data for the four primary endoscopic procedures: esophagogastroduodenoscopy (EGD), colonoscopy, endoscopic retrograde cholangiopancreatography (ERCP), and flexible sigmoidoscopy; as well as the most common therapeutic procedures (biopsy, polypectomy, dilation, endoscopic ultrasound [EUS], and manometry/motility) were analyzed to establish the key elements of the Minimum Data Set. Focus groups with members from around the U.S. verified the validity of the Minimum Data Set. The SGNA Minimum Data Set can be used by healthcare institutions, industry, and individuals to facilitate the capture and analysis of standardized data for the purpose of improving GI patient outcomes and enhancing delivery of nursing care.

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Year:  2005        PMID: 15738736     DOI: 10.1097/00001610-200501000-00014

Source DB:  PubMed          Journal:  Gastroenterol Nurs        ISSN: 1042-895X            Impact factor:   0.978


  3 in total

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2.  Evaluating clinical stop-smoking services globally: towards a minimum data set.

Authors:  Andrew L Skinner; Robert West; Martin Raw; Emma Anderson; Marcus R Munafò
Journal:  Addiction       Date:  2017-11-26       Impact factor: 6.526

Review 3.  Identification of data elements for blood gas analysis dataset: a base for developing registries and artificial intelligence-based systems.

Authors:  Sahar Zare; Zahra Meidani; Maryam Ouhadian; Hosein Akbari; Farid Zand; Esmaeil Fakharian; Roxana Sharifian
Journal:  BMC Health Serv Res       Date:  2022-03-08       Impact factor: 2.655

  3 in total

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