Literature DB >> 22161431

Computer-assisted versus oral-and-written family history taking for identifying people with elevated risk of type 2 diabetes mellitus.

Yannis Pappas1, Igor Wei, Josip Car, Azeem Majeed, Aziz Sheikh.   

Abstract

BACKGROUND: Diabetes is a chronic illness characterised by insulin resistance or deficiency, resulting in elevated glycosylated haemoglobin A1c (HbA1c) levels. Because diabetes tends to run in families, the collection of data is an important tool for identifying people with elevated risk of type2 diabetes. Traditionally, oral-and-written data collection methods are employed but computer-assisted history taking systems (CAHTS) are increasingly used. Although CAHTS were first described in the 1960s, there remains uncertainty about the impact of these methods on family history taking, clinical care and patient outcomes such as health-related quality of life.
OBJECTIVES: To assess the effectiveness of computer-assisted versus oral-and-written family history taking for identifying people with elevated risk of developing type 2 diabetes mellitus. SEARCH
METHODS: We searched The Cochrane Library (issue 6, 2011), MEDLINE (January 1985 to June 2011), EMBASE (January 1980 to June 2011) and CINAHL (January 1981 to June 2011). Reference lists of obtained articles were also pursued further and no limits were imposed on languages and publication status. SELECTION CRITERIA: Randomised controlled trials of computer-assisted versus oral-and-written history taking in adult participants (16 years and older). DATA COLLECTION AND ANALYSIS: Two authors independently scanned the title and abstract of retrieved articles. Potentially relevant articles were investigated as full text. Studies that met the inclusion criteria were abstracted for relevant population and intervention characteristics with any disagreements resolved by discussion, or by a third party. Risk of bias was similarly assessed independently. MAIN
RESULTS: We found no controlled trials on computer-assisted versus oral-and-written family history taking for identifying people with elevated risk of type 2 diabetes mellitus. AUTHORS'
CONCLUSIONS: There is a need to develop an evidence base to support the effective development and use of computer-assisted history taking systems in this area of practice. In the absence of evidence on effectiveness, the implementation of computer-assisted family history taking for identifying people with elevated risk of type 2 diabetes may only rely on the clinicians' tacit knowledge, published monographs and viewpoint articles.

Entities:  

Mesh:

Year:  2011        PMID: 22161431     DOI: 10.1002/14651858.CD008489.pub2

Source DB:  PubMed          Journal:  Cochrane Database Syst Rev        ISSN: 1361-6137


  5 in total

1.  Constructing data-derived family histories using electronic health records from a single healthcare delivery system.

Authors:  Maya Leventer-Roberts; Ilan Gofer; Yuval Barak Corren; Ben Y Reis; Ran Balicer
Journal:  Eur J Public Health       Date:  2020-04-01       Impact factor: 3.367

Review 2.  Improving the Primary Care Consultation for Diabetes and Depression Through Digital Medical Interview Assistant Systems: Narrative Review.

Authors:  Geronimo Jimenez; Shilpa Tyagi; Tarig Osman; Pier Spinazze; Rianne van der Kleij; Niels H Chavannes; Josip Car
Journal:  J Med Internet Res       Date:  2020-08-28       Impact factor: 5.428

3.  Development of an Algorithm for Determining of Genetic Risk at the Primary Healthcare Level - A New Tool for Primary Prevention: A Study Protocol.

Authors:  Polona Selič; Zalika Klemenc-Ketiš; Erika Zelko; Andrej Kravos; Janez Rifel; Irena Makivić; Antonija Poplas Susič; Špela Tevžič; Metka Cerovič; Borut Peterlin; Nena Kopčavar Guček
Journal:  Zdr Varst       Date:  2019-12-13

4.  The Computer Will See You Now: Overcoming Barriers to Adoption of Computer-Assisted History Taking (CAHT) in Primary Care.

Authors:  Pier Spinazze; Jiska Aardoom; Niels Chavannes; Marise Kasteleyn
Journal:  J Med Internet Res       Date:  2021-02-24       Impact factor: 5.428

5.  Increasing the HIV testing among MSM through HIV test result exchange mechanism: study protocol for a cluster randomized controlled trial.

Authors:  Yuning Shi; Jialing Qiu; Qingling Yang; Tailin Chen; Yongheng Lu; Sha Chen; Xiaoru Fan; Zhiye Lin; Zhigang Han; Jie Lu; Haobing Qian; Jing Gu; Dong Roman Xu; Yuzhou Gu; Chun Hao
Journal:  BMC Infect Dis       Date:  2021-08-06       Impact factor: 3.090

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.