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ABSTRACT: Objective
To evaluate whether medical event charges are associated with uninsured patients' probability of medical payment default and whether there exist racial/ethnic disparity gaps in medical payment defaults.Design
We use logistic regression models to analyse medical payment defaults. Our adjusted estimates further control for a rich set of patient and medical visit characteristics, region and time fixed effects.Setting
Uninsured US adult (non-elderly) population from 2002 to 2017.Participants
We use four nationally representative samples of uninsured patients from the Medical Expenditure Panel Survey across office-based (n=39 967), emergency (n=3269), outpatient (n=1739) and inpatient (n=340) events.Primary and secondary outcome measures
Payment default, medical event charges and medical event payments.Results
Relative to uninsured non-Hispanic white (NHW) patients, uninsured non-Hispanic black (NHB) patients are 142% (p<0.01) more likely to default on medical payments for office-based visits, 27% (p<0.05) more likely to default on emergency department visit payments and 82% (p<0.1) more likely to default on an outpatient visit bill. Hispanic patients are 46% (p<0.01) more likely to default on an office-based visit, but 25% less likely to default on emergency department visit payments than NHW patients. Within our fully adjusted model, we find that racial/ethnic disparities persist for office-based visits. Our results further suggest that the probabilities of payment defaults for office-based, emergency and outpatient visits are all significantly (p<0.01) and positively associated with the medical event charges billed.Conclusions
Medical event charges are found to be broadly associated with payment defaults, and we further note disproportionate payment default disparities among NHB patients.
SUBMITTER: Linde S
PROVIDER: S-EPMC9125734 | biostudies-literature | 2022 May
REPOSITORIES: biostudies-literature
Linde Sebastian S Egede Leonard E LE
BMJ open 20220525 5
<h4>Objective</h4>To evaluate whether medical event charges are associated with uninsured patients' probability of medical payment default and whether there exist racial/ethnic disparity gaps in medical payment defaults.<h4>Design</h4>We use logistic regression models to analyse medical payment defaults. Our adjusted estimates further control for a rich set of patient and medical visit characteristics, region and time fixed effects.<h4>Setting</h4>Uninsured US adult (non-elderly) population from ...[more]