Digital radiograph rejection analysis during “Coronavirus disease 2019 (COVID-19) pandemic” in a tertiary care public sector hospital in Khyber Pakhtunkhwa Province of Pakistan

Abstract

Background Evaluation of X-ray reject analysis is an important quality parameter in diagnostic facility. The aim of this study was to find out the radiograph rejection and its causes during the coronavirus disease 2019 (COVID-19) pandemics as there was fear of coronavirus disease infection among the technical staff from the incoming patients in a busy, high volume public sector tertiary care hospital. Materials and method This descriptive study was conducted at Radiology Department, Lady Reading Hospital, Peshawar from August to November, 2020. The rejected radiographs and their causes were analyzed. Results A total of 15,000 X-ray procedures were conducted during study period out of which 2550 cases were repeated making the total rejection 17%. Rejection in male and female were 74.3 and 25.7%, respectively, while rejection in adults was (80.1%) and (19.9%) in pediatric age group of the total rejection. The main cause of rejection was positioning (30.5%) followed by artifacts (22.4%), motion (12.1%), improper collimation (10%), wrong labeling (8.4%), exposure errors (6.9%), detector errors (3.7%), machine faults (2.8%), re-request from referring physician (1.7%), and PACS issues (1.5%). In terms of body anatomical parts, the highest rejection was observed in extremities (44.1%), followed by chest radiography (23.3%), spine (11.4%), abdomen (6.4%), skull (5.9%), pelvis (4.7%), KUB (3.7%), and neck (0.6%), respectively. Conclusion Radiograph rejection is common problem in every diagnostic facility but significant reduction can be achieved by implementing rejection analysis as basic quality indicator, and conducting technologist/s specific training programs for their knowledge and skill enhancement.

Digital radiography reject analysis: A comparison between two radiology departments in New Zealand

“…Firstly, the data were collected during a period that included lockdown restrictions due to the COVID‐19 pandemic, which may have impacted the normal workflow of the radiology departments. It is possible that the lockdown periods due to the COVID‐19 pandemic may have influenced the duration of examinations and the technique used by the MITs, which could have impacted the rate of positioning errors 24,25 …”

“…It is possible that the lockdown periods due to the COVID‐19 pandemic may have influenced the duration of examinations and the technique used by the MITs, which could have impacted the rate of positioning errors. 24 , 25 …”

“…It is possible that the lockdown periods due to the COVID-19 pandemic may have influenced the duration of examinations and the technique used by the MITs, which could have impacted the rate of positioning errors. 24,25 Additionally, this study was conducted between radiology departments that had different patient populations; RAD 1 provided radiology services to inpatient and trauma patients while RAD 2 provided outpatient examinations. A repeat of this image RA at the individual radiology departments following interventions would allow for the comparison of image RRs and selection of image rejection reasons that reflect the specific department variations.…”

Suboptimal Chest Radiography and Artificial Intelligence: The Problem and the Solution

“…Several publications have reported on the reject rate for radiographs [12][13][14][15][16][17][18][19][20][21]. Reject rate refers to suboptimal radiographs that are rejected or discarded, and often require repeat radiographs to obtain a diagnostic quality radiograph.…”

“…Reject rate refers to suboptimal radiographs that are rejected or discarded, and often require repeat radiographs to obtain a diagnostic quality radiograph. For CXRs, prior research reported the reject rates varying between 4% and 15% (Table 2) [14][15][16][17][18][19][20][21]. Jabbari et al evaluated 5695 radiographs in Iran and reported an 11% repeat or reject rate.…”