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Background <p>Efficient pre-anesthesia check-up (PAC) clearance is essential for timely cancer surgery; however, delays are common in high-volume oncology centres, where complex comorbidities, fragmented workflows, and logistical barriers create process bottlenecks. Evidence quantifying the combined impact of these factors—particularly the burden of repeated visits and long travel distances—remains limited.</p> Methods <p>This retrospective observational study included adults (≥ 18 years) attending the PAC clinic of a tertiary cancer centre in North India between December 2023 and May 2024. Of 1,016 attendees, 33 were excluded due to incomplete PAC documentation, yielding 983 patients for analysis. Time to PAC fitness was recorded in days; delayed PAC fitness was defined a priori as &gt; 4 days (upper quartile). Travel distance was calculated as the one-way road distance from the registered residential address to the hospital using Google Maps. The Visit Burden Index (VBI) was defined as: (number of PAC visits) × log₁₀ (distance in km + 1). Predictors of delayed PAC fitness were evaluated using multivariable logistic regression with bootstrap internal validation (1,000 iterations). A Cox proportional hazards model (PAC fitness as the event) was additionally performed due to right-skewed clearance times.</p> Results <p>The mean age was 50.2 ± 14.1 years, and 533 patients (54.2%) were male. The median time to PAC fitness was 1&#xa0;day (IQR 1–4), while the mean was 5.4 days. Known comorbidities were present in 409 patients (42.6%), and newly detected medical conditions were identified in 170 (17.7%). PAC fitness was achieved in one visit by 401 patients (40.8%), two visits by 503 (51.2%), and three or more visits by 79 (8.0%). Among those requiring multiple visits, the predominant reasons were pending investigations (<i>n</i> = 415, 71.4%) and uncontrolled medical illness (<i>n</i> = 167, 28.6%). Delay rates increased across VBI tertiles (4.8%, 26.5%, and 41.4%). In multivariable analysis, known comorbidity (aOR 2.98, 95% CI 2.08–4.26), newly detected medical conditions (aOR 3.52, 95% CI 2.39–5.19), and VBI (aOR 1.23 per unit, 95% CI 1.17–1.29) independently predicted delayed PAC fitness (all <i>p</i> &lt; 0.001). Model discrimination was good (AUC 0.807; optimism-adjusted AUC 0.77). In Cox analysis, higher VBI (HR 0.88 per unit, 95% CI 0.84–0.92), known comorbidity (HR 0.72, 95% CI 0.61–0.83), and newly detected medical conditions (HR 0.71, 95% CI 0.59–0.85) were independently associated with longer time to PAC fitness (all <i>p</i> &lt; 0.001).</p> Conclusion <p>Delayed PAC fitness reflects both comorbidity burden—including newly detected conditions—and modifiable system-level factors, particularly incomplete investigations. The Visit Burden Index quantifies combined visit–travel burden, demonstrates a dose–response relationship with delay, and independently predicts prolonged PAC clearance; its role in workflow optimization warrants multicentre validation.</p> Trial Registration <p>CTRI Registration: CTRI/2024/11/076616 [Registered on: 11/11/2024] - Trial Registered Prospectively in Clinical Trial Registry – India</p>

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Evaluating PAC visits and time to fitness in a tertiary care cancer hospital: a retrospective observational study

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  • 发表日期：

    2026年3月6日

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  • Pradeepika Gangwar,
  • Uddalak Chattopadhyay,
  • Nikhil Kumar Singh

摘要

Background

Efficient pre-anesthesia check-up (PAC) clearance is essential for timely cancer surgery; however, delays are common in high-volume oncology centres, where complex comorbidities, fragmented workflows, and logistical barriers create process bottlenecks. Evidence quantifying the combined impact of these factors—particularly the burden of repeated visits and long travel distances—remains limited.

Methods

This retrospective observational study included adults (≥ 18 years) attending the PAC clinic of a tertiary cancer centre in North India between December 2023 and May 2024. Of 1,016 attendees, 33 were excluded due to incomplete PAC documentation, yielding 983 patients for analysis. Time to PAC fitness was recorded in days; delayed PAC fitness was defined a priori as > 4 days (upper quartile). Travel distance was calculated as the one-way road distance from the registered residential address to the hospital using Google Maps. The Visit Burden Index (VBI) was defined as: (number of PAC visits) × log₁₀ (distance in km + 1). Predictors of delayed PAC fitness were evaluated using multivariable logistic regression with bootstrap internal validation (1,000 iterations). A Cox proportional hazards model (PAC fitness as the event) was additionally performed due to right-skewed clearance times.

Results

The mean age was 50.2 ± 14.1 years, and 533 patients (54.2%) were male. The median time to PAC fitness was 1 day (IQR 1–4), while the mean was 5.4 days. Known comorbidities were present in 409 patients (42.6%), and newly detected medical conditions were identified in 170 (17.7%). PAC fitness was achieved in one visit by 401 patients (40.8%), two visits by 503 (51.2%), and three or more visits by 79 (8.0%). Among those requiring multiple visits, the predominant reasons were pending investigations (n = 415, 71.4%) and uncontrolled medical illness (n = 167, 28.6%). Delay rates increased across VBI tertiles (4.8%, 26.5%, and 41.4%). In multivariable analysis, known comorbidity (aOR 2.98, 95% CI 2.08–4.26), newly detected medical conditions (aOR 3.52, 95% CI 2.39–5.19), and VBI (aOR 1.23 per unit, 95% CI 1.17–1.29) independently predicted delayed PAC fitness (all p < 0.001). Model discrimination was good (AUC 0.807; optimism-adjusted AUC 0.77). In Cox analysis, higher VBI (HR 0.88 per unit, 95% CI 0.84–0.92), known comorbidity (HR 0.72, 95% CI 0.61–0.83), and newly detected medical conditions (HR 0.71, 95% CI 0.59–0.85) were independently associated with longer time to PAC fitness (all p < 0.001).

Conclusion

Delayed PAC fitness reflects both comorbidity burden—including newly detected conditions—and modifiable system-level factors, particularly incomplete investigations. The Visit Burden Index quantifies combined visit–travel burden, demonstrates a dose–response relationship with delay, and independently predicts prolonged PAC clearance; its role in workflow optimization warrants multicentre validation.

Trial Registration

CTRI Registration: CTRI/2024/11/076616 [Registered on: 11/11/2024] - Trial Registered Prospectively in Clinical Trial Registry – India