Abstract
Background
Timeliness of care is an important metric for lung cancer patients, and care delays
in the safety-net setting have been described. Timeliness from the point of the suspicious
image is not well-studied. Herein, we evaluate time intervals in the workup of lung
cancer at an urban, safety net hospital and assess for disparities by demographic
and clinical factors.
Patients and Methods
We performed a retrospective analysis of lung cancer patients receiving some portion
of their care at Boston Medical Center between 2015 and 2020. A total of 687 patients
were included in the final analysis. Median times from suspicious image to first treatment
(SIT), suspicious image to diagnosis (SID), and diagnosis to treatment (DT) were calculated.
Nonparametric tests were applied to assess for intergroup differences in time intervals.
Results
SIT, SID, and DT for the entire cohort was 78, 34, and 32 days, respectively. SIT
intervals were 87 days for females and 72 days for males (p < .01). SIT intervals were 106, 110, 81, and 41 days for stages I, II, III, and IV,
respectively (p < .01). SID intervals differed between black (40.5) and Hispanic (45) patients compared
to white (28) and Asian (23) patients (p < .05).
Conclusion
Advanced stage at presentation and male gender were associated with more timely treatment
from the point of suspicious imaging while white and Asian were associated with more
timely lung cancer diagnosis. Future analyses should seek to elucidate drivers of
timeliness differences and assess for the impact of timeliness disparities on patient
outcomes in the safety net setting.
Keywords
Abbreviations:
(SIT) (suspicious image to first treatment), (SID) (suspicious image to diagnosis), (DT) (diagnosis to treatment), (NSCLC) (non-small cell lung cancer), (SCLC) (small cell lung cancer), (BTS) (British Thoracic Society), (RAND) (Research and Development), (VA) (Veterans Affairs)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: December 24, 2022
Accepted:
December 8,
2022
Received in revised form:
December 3,
2022
Received:
October 7,
2022
Identification
Copyright
© 2022 Elsevier Inc. All rights reserved.
