Literature DB >> 19892342

Colposcopy audit for improving quality of service in areas with a high incidence of cervical cancer.

Manatsawee Manopunya1, Prapaporn Suprasert, Jatupol Srisomboon, Chumnan Kietpeerakool.   

Abstract

OBJECTIVE: To audit routine colposcopy performance using 8 standard requirements of the National Health Service Cervical Screening Programme (NHSCSP).
METHODS: Records of women who underwent colposcopy for abnormal cervical cytology between January and December 2008 at Chiang Mai University Hospital, Thailand, were reviewed.
RESULTS: The standard requirements were not achieved in 2 practices: (1) the proportion of women who had recordings of visibility of the transformation zone (96.6%) did not achieve the NHSCSP requirement of 100%; and (2) the rate of excisional biopsy (87.8%) was lower than the 95% minimum required.
CONCLUSION: Colposcopic performance at Chiang Mai University Hospital was generally favorable. However, re-audit is necessary to ensure that unmet standards of performance are improved and achieved standards are maintained.

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Year:  2010        PMID: 19892342     DOI: 10.1016/j.ijgo.2009.07.042

Source DB:  PubMed          Journal:  Int J Gynaecol Obstet        ISSN: 0020-7292            Impact factor:   3.561


  3 in total

1.  Rationale and development of an on-line quality assurance programme for colposcopy in a population-based cervical screening setting in Italy.

Authors:  Lauro Bucchi; Paolo Cristiani; Silvano Costa; Patrizia Schincaglia; Paola Garutti; Priscilla Sassoli de Bianchi; Carlo Naldoni; Oswaldo Olea; Mario Sideri
Journal:  BMC Health Serv Res       Date:  2013-06-28       Impact factor: 2.655

2.  Classification of images acquired with colposcopy using artificial neural networks.

Authors:  Priscyla W Simões; Narjara B Izumi; Ramon S Casagrande; Ramon Venson; Carlos D Veronezi; Gustavo P Moretti; Edroaldo L da Rocha; Cristian Cechinel; Luciane B Ceretta; Eros Comunello; Paulo J Martins; Rogério A Casagrande; Maria L Snoeyer; Sandra A Manenti
Journal:  Cancer Inform       Date:  2014-10-31

3.  Development of a prognostic prediction support system for cervical intraepithelial neoplasia using artificial intelligence-based diagnosis.

Authors:  Takayuki Takahashi; Hikaru Matsuoka; Rieko Sakurai; Jun Akatsuka; Yusuke Kobayashi; Masaru Nakamura; Takashi Iwata; Kouji Banno; Motomichi Matsuzaki; Jun Takayama; Daisuke Aoki; Yoichiro Yamamoto; Gen Tamiya
Journal:  J Gynecol Oncol       Date:  2022-05-16       Impact factor: 4.756

  3 in total

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