Literature DB >> 25018076

A multiobserver study of the effects of including point-of-care patient photographs with portable radiography: a means to detect wrong-patient errors.

Srini Tridandapani1, Senthil Ramamurthy2, James Provenzale3, Nancy A Obuchowski4, Michael G Evanoff5, Pamela Bhatti6.   

Abstract

RATIONALE AND
OBJECTIVES: To evaluate whether the presence of facial photographs obtained at the point-of-care of portable radiography leads to increased detection of wrong-patient errors.
MATERIALS AND METHODS: In this institutional review board-approved study, 166 radiograph-photograph combinations were obtained from 30 patients. Consecutive radiographs from the same patients resulted in 83 unique pairs (ie, a new radiograph and prior, comparison radiograph) for interpretation. To simulate wrong-patient errors, mismatched pairs were generated by pairing radiographs from different patients chosen randomly from the sample. Ninety radiologists each interpreted a unique randomly chosen set of 10 radiographic pairs, containing up to 10% mismatches (ie, error pairs). Radiologists were randomly assigned to interpret radiographs with or without photographs. The number of mismatches was identified, and interpretation times were recorded.
RESULTS: Ninety radiologists with 21 ± 10 (mean ± standard deviation) years of experience were recruited to participate in this observer study. With the introduction of photographs, the proportion of errors detected increased from 31% (9 of 29) to 77% (23 of 30; P = .006). The odds ratio for detection of error with photographs to detection without photographs was 7.3 (95% confidence interval: 2.29-23.18). Observer qualifications, training, or practice in cardiothoracic radiology did not influence sensitivity for error detection. There is no significant difference in interpretation time for studies without photographs and those with photographs (60 ± 22 vs. 61 ± 25 seconds; P = .77).
CONCLUSIONS: In this observer study, facial photographs obtained simultaneously with portable chest radiographs increased the identification of any wrong-patient errors, without substantial increase in interpretation time. This technique offers a potential means to increase patient safety through correct patient identification.
Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  DICOM; PACS; Patient identification; digital photography; medical errors

Mesh:

Year:  2014        PMID: 25018076      PMCID: PMC4100078          DOI: 10.1016/j.acra.2014.03.006

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  8 in total

1.  An automated patient recognition method based on an image-matching technique using previous chest radiographs in the picture archiving and communication system environment.

Authors:  J Morishita; S Katsuragawa; K Kondo; K Doi
Journal:  Med Phys       Date:  2001-06       Impact factor: 4.071

2.  Automated patient identity recognition by analysis of chest radiograph features.

Authors:  E-Fong Kao; Wei-Chen Lin; Twei-Shiun Jaw; Gin-Chung Liu; Jain-Shing Wu; Chung-Nan Lee
Journal:  Acad Radiol       Date:  2013-08       Impact factor: 3.173

3.  Receiver operating characteristic analysis of chest image interpretation with conventional, laser-printed, and high-resolution workstation images.

Authors:  B S Slasky; D Gur; W F Good; M A Costa-Greco; K M Harris; L A Cooperstein; H E Rockette
Journal:  Radiology       Date:  1990-03       Impact factor: 11.105

4.  Making the most of patient safety I.T.

Authors:  Neil Versel
Journal:  Health Data Manag       Date:  2011-08

5.  Patient safety event reporting in a large radiology department.

Authors:  Stacy R Schultz; Robert E Watson; Sherrie L Prescott; Karl N Krecke; Kenneth T Aakre; Mohammad N Islam; Anthony W Stanson
Journal:  AJR Am J Roentgenol       Date:  2011-09       Impact factor: 3.959

6.  Investigation of misfiled cases in the PACS environment and a solution to prevent filing errors for chest radiographs.

Authors:  Junji Morishita; Hideyuki Watanabe; Shigehiko Katsuragawa; Nobuhiro Oda; Yoshiharu Sukenobu; Hiroko Okazaki; Hajime Nakata; Kunio Doi
Journal:  Acad Radiol       Date:  2005-01       Impact factor: 3.173

7.  Increasing rate of detection of wrong-patient radiographs: use of photographs obtained at time of radiography.

Authors:  Srini Tridandapani; Senthil Ramamurthy; Samuel J Galgano; James M Provenzale
Journal:  AJR Am J Roentgenol       Date:  2013-04       Impact factor: 3.959

Review 8.  Integrating patient digital photographs with medical imaging examinations.

Authors:  Senthil Ramamurthy; Pamela Bhatti; Chesnal D Arepalli; Mohamed Salama; James M Provenzale; Srini Tridandapani
Journal:  J Digit Imaging       Date:  2013-10       Impact factor: 4.056

  8 in total
  5 in total

1.  A novel technology for automatically obtaining digital facial photographs near-simultaneously with portable radiographs.

Authors:  Senthil Ramamurthy; Pamela Bhatti; Farasat Munir; Timothy Ng; Kimberly Applegate; Srini Tridandapani
Journal:  J Digit Imaging       Date:  2015-06       Impact factor: 4.056

2.  Impact of Patient Photos on Detection Accuracy, Decision Confidence and Eye-Tracking Parameters in Chest and Abdomen Images with Tubes and Lines.

Authors:  Elizabeth A Krupinski
Journal:  J Digit Imaging       Date:  2019-10       Impact factor: 4.056

3.  Stakeholders' Perceptions Regarding the Use of Patient Photographs Integrated with Medical Imaging Studies.

Authors:  Gelareh Sadigh; Kimberly E Applegate; Timothy W Ng; Kamilah A Hendrix; Srini Tridandapani
Journal:  J Digit Imaging       Date:  2016-06       Impact factor: 4.056

4.  Improvement in Detection of Wrong-Patient Errors When Radiologists Include Patient Photographs in Their Interpretation of Portable Chest Radiographs.

Authors:  Srini Tridandapani; Kevin Olsen; Pamela Bhatti
Journal:  J Digit Imaging       Date:  2015-12       Impact factor: 4.056

5.  A Facial Recognition Mobile App for Patient Safety and Biometric Identification: Design, Development, and Validation.

Authors:  Byoungjun Jeon; Boseong Jeong; Seunghoon Jee; Yan Huang; Youngmin Kim; Gee Ho Park; Jungah Kim; Maierdanjiang Wufuer; Xian Jin; Sang Wha Kim; Tae Hyun Choi
Journal:  JMIR Mhealth Uhealth       Date:  2019-04-08       Impact factor: 4.773

  5 in total

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