Improving Patient Wait Times on the First Day of Radiotherapy Treatment

Abstract

Long wait times on starting day of radiotherapy (day 1) can cause dissatisfaction among both patients and healthcare providers. Reducing these wait times will decrease stress and decongest hospital facilities especially in current coronavirus disease 2019 times. A multidisciplinary core team was formed during the Stanford-India Collaborative Quality Improvement training to reduce the median wait times on day 1 of treatment from 6 to 4.5 hours (a 25% reduction). Several factors were identified on the fishbone diagram, and key causes were identified using a Pareto chart and action prioritization matrix. The Plan-Do-Study-Act Cycle strategy was undertaken for the identified interventions. The outcome measure was time from arrival at the hospital to entry into a treatment room. Data were obtained from time charts at various stations and electronic records. The secondary measures were visual analog scale (VAS) scores, 80th percentile wait times, and the day-2 delay percentage. The balancing measure was “new errors” due to interventions. The interventions included the completion of all administrative tasks not needing patients' presence on the day before day 1. Baseline data from 198 patients and postintervention data from 160 patients were compared and analyzed. The median wait time at baseline, which was 6 hours, was reduced to 4.2 hours. The VAS score showed 70.4, 67.7, and 71.9% satisfaction for the resident physician, therapists, and patients, respectively. The 80th percentile wait times reduced from 8 to 5.7 hours; and the day 2 starting rate decreased from 22.5 to 2.04%, with no new errors reported. Radiotherapy day 1 wait times can be safely decreased, leading to improved satisfaction among patients and healthcare providers, by utilizing classic quality improvement methods and tools.

Keywords

EQuIP - patient care - Quality Training Program - radiotherapy - wait times

Publication History

Article published online:
14 October 2024

• References

• 1 Accessed July 10, 2023 at: https://tmc.gov.in/PDF/Annual_Report/AR_2019E.pdf
• 2 Agazaryan N, Chow P, Lamb J. et al. The timeliness initiative: continuous process improvement for prompt initiation of radiation therapy treatment. Adv Radiat Oncol 2020; 5 (05) 1014-1021
• 3 Ho AS, Kim S, Tighiouart M. et al. Quantitative survival impact of composite treatment delays in head and neck cancer. Cancer 2018; 124 (15) 3154-3162
• 4 Gomez DR, Liao KP, Swisher SG. et al. Time to treatment as a quality metric in lung cancer: staging studies, time to treatment, and patient survival. Radiother Oncol 2015; 115 (02) 257-263
• 5 Agarwal JP, Krishnatry R, Panda G. et al. An audit for radiotherapy planning and treatment errors from a low-middle-income country centre. Clin Oncol (R Coll Radiol) 2019; 31 (01) e67-e74
• 6 Yeung AWK. The “As Low As Reasonably Achievable” (ALARA) principle: a brief historical overview and a bibliometric analysis of the most cited publications. Radioprotection 2019; 54 (02) 103-109
• 7 Maitre P, Krishnatry R, Chopra S. et al. Modern radiotherapy technology: obstacles and opportunities to access in low- and middle-income countries. JCO Glob Oncol 2022; 8: e2100376
• 8 Manjali JJ, Krishnatry R, Palta JR, Agarwal JP. Quality and safety with technological advancements in radiotherapy: an overview and journey narrative from a low- and middle-income country institution. JCO Glob Oncol 2022; 8: e2100367
• 9 Krishnatry R, Johnny C, Tahmeed T. et al. Quality improvement process with incident learning program helped reducing transcriptional errors on telecobalt due to mismatched parameters in different generations. J Med Phys 2022; 47 (04) 367-373