Predicting No-Shows in Radiology Using Regression Modeling of Data Available in the Electronic Medical Record

Harvey, H. Benjamin; Liu, Catherine; Ai, Jing; Jaworsky, Cristina; Guerrier, Claude E; Flores, Efrén J.; Pianykh, Oleg S.

doi:10.1016/j.jacr.2017.05.007

Cited by 83 publications

(103 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…An attitude of self‐reliance and a reluctance to seek help are traits frequently observed in male patients in regional and rural healthcare settings and may partially explain this finding . This finding agreed with results of most other medical imaging non‐attendance studies . However, a Saudi Arabian study of MRI appointment non‐attendance found that females were significantly less likely to attend .…”

Section: Discussionsupporting

confidence: 90%

“…In this study of medical imaging department non‐attendance, the rate of non‐attendance was 5.4%, which was similar to that reported by previous publications This study appears to be the only analysis of medical imaging non‐attendance in the Australian context, as well as the first to address this subject in the regional setting.…”

Section: Discussionsupporting

confidence: 88%

“…Patients aged 45–54 were the only group shown to be significantly less likely to attend. This result agrees with a recent study of non‐attendance in medical imaging but is at odds with the findings of other medical imaging studies that suggest that patients under 18 or over 65, respectively, are at greater incidence of non‐attendance …”

Section: Discussionsupporting

confidence: 86%

“…27 This finding agreed with results of most other medical imaging non-attendance studies. 21,22,24 However, a Saudi Arabian study of MRI appointment nonattendance found that females were significantly less likely to attend. 25 Disparate cultural factors may account for this disagreement.…”

Section: Discussionmentioning

confidence: 99%

“…This result agrees with a recent study of non-attendance in medical imaging but is at odds with the findings of other medical imaging studies that suggest that patients under 18 or over 65, respectively, are at greater incidence of nonattendance. 21,22,26 The main strengths of this study were the large patient cohort allowing for a strong statistical correlation of outcomes. The study highlights the need for medical imaging departments to monitor non-attendance and consider implementing strategies to mitigate this.…”

Section: Discussionmentioning

confidence: 99%

See 4 more Smart Citations

Factors associated with appointment non‐attendance at a medical imaging department in regional Australia: a retrospective cohort analysis

Mander

Reynolds

Cook

et al. 2018

J of Medical Radiation Sci

View full text Add to dashboard Cite

IntroductionAppointment non‐attendance contributes added cost to the healthcare sector through wasted resource allocations. Medical imaging departments commonly schedule appointments for most modalities; however, no study has quantified patient attendance rates in the Australian regional setting. This is despite evidence that regional, rural and remote Australians tend to demonstrate poorer health than metropolitan counterparts. This study aims to identify the factors that influence appointment non‐attendance at a teaching hospital in regional Australia.MethodsCategories restricted to age, gender, indigenous status, distance from investigation site, referral source and imaging modality were collected for all appointments (N = 13,458) referred to the medical imaging department in 2015. The likelihood of each of these factors correlating with a patient not attending a scheduled appointment was calculated using the chi‐squared analysis and binary logistic regression.ResultsGender, indigenous status as well as specific imaging modalities, referral sources and age categories were significantly associated with non‐attendance. Overall, male patients were 1.57 (P < 0.001) times more likely to miss a scheduled appointment than female patients. Patients who identified as Aboriginal and Torres Strait Islander were 2.66 (P < 0.001) times more likely to miss a scheduled appointment than patients who did not identify as Aboriginal and Torres Strait Islander.ConclusionsSeveral key factors appear to affect medical imaging appointment non‐attendance. Key factors include indigenous status, gender, image modality, referral source and age. Further improvement is required to better meet the needs of underrepresented patient demographics.

show abstract

Section: Discussionsupporting

confidence: 90%

Section: Discussionsupporting

confidence: 88%

Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 3 more Smart Citations

Factors associated with appointment non‐attendance at a medical imaging department in regional Australia: a retrospective cohort analysis

Mander

Reynolds

Cook

et al. 2018

J of Medical Radiation Sci

View full text Add to dashboard Cite

show abstract

Racial differences in no‐show rates for screening mammography

Hensing

Poplack

Herman

et al. 2021

Cancer

View full text Add to dashboard Cite

Background Differences in utilization of screening mammography partly explain the increased breast cancer mortality observed in African American (AA) women compared with non‐Hispanic White women. However, the contribution of noncompliance from women who do not come for their scheduled screening mammography appointment (ie, no‐shows) is unknown. The purpose of this study was to investigate racial differences in no‐show rates for screening mammography. Methods Women scheduled for routine screening mammograms between January 2018 and March 2018 were identified from the Joanne Knight Breast Health Center at Siteman Cancer Center in St. Louis, Missouri. Using a case‐control design, this study retrospectively identified patients who no‐showed for their mammograms (cases) and randomly sampled an equal number of patients who completed their mammograms (controls). These participants were compared by race. The main outcome measure was whether AA race was associated with no‐shows for screening mammography. Results During the study period, 5060 women were scheduled for screening mammography, and 316 (6.2%) did not keep their appointment (ie, they no‐showed). Women who no‐showed were more likely to be AA than women who kept their appointment (odds ratio, 2.64; 95% confidence interval, 1.90‐3.67). Even after adjustments for marital status, insurance type, and place of residence, AA race was still significantly associated with no‐shows for screening mammography. Conclusions This study identified a no‐show rate of 6.2% for screening mammography at the authors' institution. Women who no‐showed were more likely to be AA than women who completed their mammogram even after adjustments for multiple factors. These data can be leveraged for future studies aimed at improving mammography attendance rates among AA women.

show abstract

Association between missed appointment and related factors of patients with cancer in a tertiary hospital

Lee

Kim

2018

Health Planning & Management

View full text Add to dashboard Cite

For the hospital administration, 1 major responsibility is to prevent the outflow of existing patients and minimize losses because of the failure of patients with cancer to attend appointments. We analyzed the association between no-show rates and characteristics of patients with cancer at a tertiary hospital in Seoul using patient affair data. Among the 680 190 patients, no-show rates were 4.39% and 3.37% for males and females, respectively. Male patients with colon and rectum, pancreas, and liver cancer had higher no-show rates (5.81%, 5.8%, and 5.1%). Among females, pancreas, colon and rectum, and liver cancer were associated with high no-show rates (5.65%, 5.44%, and 4.92%). For both males and females, liver (males: OR = 2.02; 95% CI: 1.68-2.44; females: OR = 1.91; 95% CI: 1.60-2.28) and pancreas (males: OR = 1.98; 95% CI: 1.57-2.50; females: OR = 1.97; 95% CI: 1.61-2.42) cancer were associated with high no-show rates. To reduce the rate of no-shows, hospitals should establish and enforce "missed appointment" policies as well as its effect upon health outcome.

show abstract

Predicting No-Shows in Radiology Using Regression Modeling of Data Available in the Electronic Medical Record

Cited by 83 publications

References 20 publications

Factors associated with appointment non‐attendance at a medical imaging department in regional Australia: a retrospective cohort analysis

Factors associated with appointment non‐attendance at a medical imaging department in regional Australia: a retrospective cohort analysis

Racial differences in no‐show rates for screening mammography

Association between missed appointment and related factors of patients with cancer in a tertiary hospital

Contact Info

Product

Resources

About