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Daily waiting and treatment times at an advanced radiation oncology setup: A 4-year audit of consecutive patients from single institution


 Department of Radiation Oncology, Fortis Memorial Research Institute, Gurgaon, Haryana, India

Date of Submission02-Sep-2019
Date of Acceptance07-Jan-2020
Date of Web Publication22-Oct-2020

Correspondence Address:
Anusheel Munshi,
Department of Radiation Oncology, Manipal Hospital, Dwarka, New Delhi - 110 075
India
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jcrt.JCRT_685_19

 > Abstract 


Purpose: We present our data for every single fraction for every patient treated at our center for the past 4 years, analyzing the waiting and treatment times.
Materials and Methods: Between January 2014 and February 2018, all patients and their corresponding recorded measurements of waiting time and machine treatment time were analyzed. Times recorded included actual arrival time, designated arrival time, linac entry time, and last beam treatment time. The complete waiting time information was divided into two categories (1) first day treatments and (2) subsequent day treatments. SPSS version 18 was used for statistical calculations, correlations, and assessing significance.
Results:First day treatments - of 1982 patients following treatments were carried out; 1557 volumetric-modulated arc therapy (78.6%), 88 three-dimensional conformal radiotherapy (RT) (4.4%), 14 electron (0.7%), 10 intensity-modulated RT (0.5%), 264 stereotactic irradiation (13.3%), 17 stereotactic body RT (0.7%), and 32 total body irradiation (1.6%). The mean (± standard deviation) times for early/late time, total spent time (TST), wait time gross (WTG), and wait time net (WTN) were 11.0 ± 49.6 min, 74.7 ± 44.8 min, 47.46 ± 43.9 min, and 24.1 ± 44.4 min, respectively. Subsequent day treatments - a total of 34,438 sessions of treatment delivery were recorded. Overall average WTG was 37.4 ± 32.7 min. Overall WTN was 12.1 ± 62.7 min. Overall mean total spent time (TST) was 52.4 ± 33.0 min, overall mean setup and treatment time was 15.1 ± 10.9 min.
Conclusion: We have presented our results of patient-related times during RT. Our study covers the daily waiting times before RT as well as the actual treatment times during modern-day RT. This consecutive patient data from a large series shall be an important resource tool for future planners and policymakers.

Keywords: Advanced radiation oncology setup, daily waiting time, treatment times



How to cite this URL:
Munshi A, Krishnakutty S, Sarkar B, Ganesh T, Mohanti BK. Daily waiting and treatment times at an advanced radiation oncology setup: A 4-year audit of consecutive patients from single institution. J Can Res Ther [Epub ahead of print] [cited 2020 Dec 2]. Available from: https://www.cancerjournal.net/preprintarticle.asp?id=298865




 > Introduction Top


Radiotherapy (RT) is an essential component of cancer management. It is used either alone or in combination with surgery and chemotherapy. RT is used both for curative as well as palliative goals.[1],[2],[3] Of all the cancer patients cured, it is estimated that approximately 80% are cured by combined modality treatment while nearly 20% are cured by RT alone.[4] Overall, nearly 60%–70% of all cancer patients require RT at some point during their treatment course.

RT has steadily evolved from simple two-dimensional techniques to three-dimensional conformal radiotherapy (3DCRT), intensity-modulated radiotherapy (IMRT), image-guided RT, and volumetric-modulated arc-based therapies (VMAT). Typically, patients who are advised RT have to undergo daily visits to the RT department. The frequency could vary from a single-session treatment (stereotactic radiosurgery [SRS] and palliative treatments) to fractionated treatments having durations of 6–7 weeks.[5]

During single or fractionated treatments, patients experience a certain waiting time in the department, before being taken inside the treatment machine. In addition, after being taken inside the machine, pretreatment setup, image guidance, and subsequent treatment delivery all require certain periods.[6] This waiting time in the department as well as the treatment time in the machine can have a significant impact on the daily activities of the patient as well as the immediate family.[7],[8]

Further, while modern-day RT is presumed to be time-efficient, there is a paucity of objective data in this regard. No large data set of patients analyzing the waiting and treatment times encountered by patients in a modern setup has been reported so far. Our hospital has an advanced radiation oncology setup, using IMRT and VMAT treatments coupled with image guidance for most patients. We hereby present our data for every single fraction for every patient treated at our center for the past 4 years.


 > Materials and Methods Top


Between January 2014 and February 2018, 1982 new patients were taken for RT treatment at our center. The treatment of these patients resulted in 34,438 recorded measurements of waiting time and machine treatment time.

Our department has MOSAIQ (Elekta, Sunnyvale, CA, USA) RT networking solution (V2.64). Since the department has an existing paperless environment, all the specified time points were recorded digitally in the system. Our department has two non-identical, non-beam matched linear accelerators Elekta Axesse (M1) (Elekta AB, Stockholm, Sweden) and Elekta Synergy (M2) (Elekta AB, Stockholm, Sweden).[9] Post simulation, a date and time of appointment is given to the patients for the start of the therapy as per the available timing in one of the linear accelerators.

Before the first session, all patients are provided with a radiation card along with an individualized barcode. For all the sessions, the patient punched the barcode on a stationary barcode scanner placed in the helpdesk, and this time was automatically registered in MOSAIQ as the patient arrival time. [Figure 1] shows a typical scheduling in M-2 linear accelerator. This process was called queuing of the patients in the desired accelerator. After the patient was taken in the radiation therapy area, the treating technologist made an entry in the patient file so that the MOSAIQ sequencer status changed from queuing to “on treatment.” Finally, MOSAIQ recorded the “end treatment” on completion of the last beam delivery.{Figure 1}

We defined the following times for the purpose of this study:

  1. Actual arrival time (AAT) was the time when the patient actually punched the radiation card barcode in the system
  2. Designated arrival time (DAT) was the time allotted to the patient for reporting for treatment
  3. Linac entry time (LET) was the time when the patient entered the linear accelerator area
  4. Last beam treatment (LBT) was the time when the last treatment beam got completed
  5. Wait time gross (WTG) was defined as LET minus AAT
  6. Wait time (net) (WTN) was defined as LET minus DAT (WTN was independent of actual patient arrival in the department)
  7. Wait time net corrected for late arrival cWTN
  8. Setup and treatment time (STT) was defined as LBT minus LET
  9. Total spent time (TST) was defined as LBT minus AAT
  10. Early (+)/late (−) arrival time (time patient reported before or after DAT): early/late time (ELT).


[Figure 2] Scenario I depicts the WTG and WTN for the case where the patient AAT is earlier than the DAT. However, in case, the patient's actual arrival was later than the scheduled appointment time, WTN becomes larger than the WTG [Figure 2], Scenario II]. In such scenario, the WTN was corrected for the late arrival (cWTN) by replacing WTN by WTG. This is because in such scenario of patient is arriving later than the schedule time, patient's actual waiting time is equal to the calculated WTG.
Figure 1: A typical color coded workflow and patient queuing in the MOSAIQ for M-2 linear accelerator

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The complete waiting time information was divided into two categories (1) first day treatments and (2) subsequent day treatments. All the above-mentioned parameters were evaluated for both the categories.

For the purpose of this study, data for each day of treatment for every patient were procured from the MOSAIQ system. This was the master sheet on which all calculations were done. For statistical calculations, correlations, and assessing significance Statistical Package for the Social Sciences (SPSS version 18, New York, United Sates) was used.


 > Results Top


First-day treatments

Of 1982 patients following treatments were carried out 1557 VMAT (78.6%), 88 3DCRT (4.4%), 14 electron (0.7%), 10 IMRT (0.5%), 264 stereotactic irradiation (13.3%), 17 stereotactic body radiotherapy (SBRT) (0.7%), and 32 total body irradiation (TBI) (1.6%). [Figure 3] shows the frequency plot of the (a) ELT, (b) WTG, (c) cWTN, and (d) STT. ELT and STT show a typical Gaussian, where (b) and (c) shows a positive biased distribution terminating at zero.
Figure 3: Day 1 therapy: Frequency distribution of (a) Early (+)/Late (−) arrival (b) Wait Time Gross (c) Wait Time Net and (d) Setup and Treatment Time corrected for late arrival of the patients. Gross and net wait time corrected for late arrival shows a positive biasness as waiting time cannot be negative

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sThe mean (± standard deviation [SD]) times for ELT, TST, WTG, and WTN were 11.0 ± 49.6 min, 74.7 ± 44.8 min, 47.46 ± 43.9 min, and 24.1 ± 44.4 min, respectively. The corresponding values for cWTN and STT were 33.5 ± 35.2 min, 27.4 ± 20.3 min, respectively [Table 1]. Minimum cWTN was offered by the TBI 16.5 ± 18.4 min. Electron therapy offers the maximum delayed arrival corrected net wait time (WT) of 50.2 ± 49.2 min. Maximum gross waiting time is offered for SBRT technique, 65.9 ± 46.7 min because patients are called earlier for acclimatization. Pearson correlation coefficient analysis shows a correlation of 35.7% for < ELT || WTG>, -24.9% for < ELT || WTN>, and 9.8% < ELT || cWTN > calculated using the. However, <WTG || cWTN>< WTN || cWTN > shows a correlation of 84.2% and 79.2%, respectively.
Table 1: Day 1 analysis: Time analysis of different parameters as a function of different techniques categorized as per the linear accelerators early (+)/late (-) timing gross waiting time (on treatment - arrival) net wait time net waiting time corrected for late arrival total time (time out-arrived) setup and therapy time

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Subsequent day treatments

A total of 34,438 sessions of treatment delivery were recorded. These included 1250 (3.6%) sessions of 3DCRT, 254 Sessions (0.7%) of IMRT, 31626 sessions (91.8%) of VMAT 225 sessions (0.6%) of electron treatments, 90 sessions (0.2%) of SBRT, 890 sessions (2.5%) of SRS/stereotactic radiotherapy, and 103 sessions (0.3%) of TBI.

[Figure 3] shows the frequency plot of the Day 1 therapy in (a) ELT (b) WTG (c) cWTN and (d) (STT). [Figure 4] shows the corresponding parameters for rest of days(except Day 1).
Figure 4: Rest of the days: Analysis of (a) early/late (arrival time-appointment time) timing, (b) Wait time Gross (time out-arrival time), (c) Wait Time Net (on treatment-arrival time), and (d) Setup and Treatment Time for overall and another eight different subsets (three-dimensional conformal radiotherapy, volumetric-modulated arc therapy, electron, boost, dynamic intensity-modulated radiotherapy, step and shoot intensity-modulated radiotherapy, stereotactic body radiotherapy, total body irradiation, and cranial stereotaxy) as a function of individual machine and combination of both the machines

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Overall analysis of different calculated times are presented in [Table 2]. Overall average WTG was 37.4 ± 32.7 min. Overall net waiting time was 12.1 ± 62.7 min; cWTN was 34.4 ± 46.3 min. Overall mean total time (TST) was 52.4 ± 33.0 min, overall mean STT was 15.1 ± 10.9 min. For TBI with per patient average STT was 47.9 ± 15.4 min, while the corresponding figure for SBRT setup and delivery was 38.4 ± 18.0 min. Electron recorded setup and treatment time of 8.6 ± 5.9 min. Among the multiple field/arc treatment times, the STT offered by VMAT treatment was 14.8 ± 10.2 min, followed by 3DCRT technique with 16.7 ± 20.0 min. SBRT shows WTG of 54.9 ± 57.1 min. STT shown by TBI technique was 47.9 ± 15.4 min. Pearson correlation coefficient analysis revealed a correlation of 24.4% for < ELT || WTG>, 86.3% for < ELT || WTN>, and 50.8% < ELT || cWTN > calculated using the. However, <WTG || cWTN> < WTN || cWTN > shows a correlation of 38.4% and 70.3%, respectively.
Table 2: Rest of the day analysis: Time analysis of different parameters as a function of different techniques categorised as per the linear accelerators [A] Early(+)/Late(-) timing [B] Gross waiting time (on treatment - arrival) [C] Net wait time [ D] Net waiting time corrected for late arrival [E] Total time (Time out-Arrived) [F] Set up and therapy time

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 > Discussion Top


Patient satisfaction and related parameters play an important role in ensuring holistic health care. Waiting times for daily RT is one of the parameters that can have a significant impact on patient satisfaction. More than expected WT can make patients irritable and lead to loss of quality time for the patient as well as the attendants.[10]

Similarly, the on-treatment time can be an important factor both for the treating facility as well as the patient. Furthermore, there are reports suggesting that modern techniques such as IMRT, VMAT, and flattening filter-free treatments are faster and time-efficient.[11]

The strengths of our data are: (1) the large number of observations, (2) all consecutive patients for 4 years and (3) all individual patient timings for all days during the RT course. This makes our data a real-life scenario, unlike a typical trial setting where selected patients are taken. Limited studies are present in literature to study the question being asked in our analysis. A study aimed to investigate the cause of identified delays by analyzing and quantifying WTs associated with daily RT. It included 128 outpatients that were scheduled on different linear accelerators.[12] The entry time (which was defined as the time patient entered the treatment room) was recorded for each appointment over 10 consecutive treatment days. Subsequently, the authors calculated WTs (defined as the difference between the scheduled appointment time and the entry time). In this study, the mean WT ± SD was 7.2 ± 27 min for 866 outpatient appointments (OPAs). A total of 382/866 (44%) (OPAs) were early or on time (−12 ± 21 min.); however, 484/866 (56%) were delayed (22 ± 20 min). The authors attributed the delays primarily to an indirect cause of ripple effect of delay in previous appointments (73%). The WT was ≤20 min for 693/866 OPAs (80.0%). Interestingly, the mean WT ± SD was the longest for midday appointments (10:30 AM–2:30 PM) at 9.5 ± 29 min (P < 0.020). Site-wise analysis revealed that pelvis site (of which majority were prostate cancer patients) experiencing the longest WT ± SD at 11 ± 22 min (P < .0001), and this was because of the specific RT treatment protocol.

In this article, we were keen to find the physical waiting time of the patients in a department where the standard daily workload per machine lies between 25 and 30 patients with a complete paperless environment and significant number of special technique such as cranial and extracranial stereotaxy and TBI. We have reported first day and rest of days' results separately since first-day treatments intuitively take a longer time since patients take time to get accustomed to the treatment schedule.

In our department, we do weekly audits to evaluate the reasons for the delays of patient treatments. In decreasing order of frequency, following were the reasons identified: (1) the patient arrived late, (2) patient arrived in the right time but did not bring the radiosensitizer drug (temozolomide), (3) patients on bladder protocol for pelvic irradiation, (4) bladder/rectum volume not matching after setup imaging, (5) apprehensions about the treatment, (6) claustrophobic patient, and (7) interpreter not available at the time of setup/treatment.

Around 25% of our patients are international patients from countries such as Iraq, Afghanistan, Commonwealth of Independent States countries, East/Central Africa such as Kenya, Morocco, Mozambique, and Zimbabwe. A good majority of these patients are non-English speaking and require interpreter assistance. This dependence on interpreters is a significant reason for increased waiting/treatment times in such patients.

Many factors could have influenced patient waiting times including the seasonal weather, concurrent chemotherapy schedules, communication issues with foreign patients, and bladder filling protocols for pelvic RT patients. It is to be noted that all our patients underwent daily assessment of vitals (blood pressure, temperature, and pulse) by the designated sister and were then taken to the treatment area. This activity could lead to some increase in TST. However, the analysis of these is beyond the scope of this study.

In another relevant study, the researchers conducted a survey by patient questionnaire of all outpatients receiving RT in the West of Scotland on a single day in 1990.[13] A total of 216 outpatients were taken in the study with a 92% response rate to the questionnaire. The authors reported median values (and ranges) were as follows: age 58 (4–85) years, daily treatment sessions 20 (4–33), distance traveled 10 (1–60) miles, total traveling time 45 (5–130) minutes, and waiting time in the department before treatment 60 (0–200) min. The total time away from home was 2 h 50 min (35 min-7 h). About 16% of the patients had a relative who lost time from work because of attending to the transportation needs of the patient. Only 12 of 60 patients who were away from home over a mealtime were offered a hospital meal. Sixteen percent of patients came by ambulance and 73% by car. The study concluded that long traveling distances, traveling times, and treatment waiting times for many patients required revision in the facilities of transportation, a more strict appointment system, more treatment machine units, and hostel accommodation for patients/attendants whenever needed.

In another relevant study, the authors measured time taken to integrate image guidance with the cone-beam CTs (CBCTs) in routine clinical practice for patients treated for 3 years.[6] 117,301 CBCTs from 4592 patients across 13 disease sites were included. The mean image assessment decision time was 79 s. The authors found that the decision time was correlated with setup displacement magnitude.

A factor that is likely to influence treatment time is the technique of RT being used.[14] Most of our patients in the present study have been treated with VMAT. Our result suggested this technique is faster as compared to multiple static field IMRT or 3DCRT. (VMAT: 28.7±21.9; 3D CRT: 32.1±20.0; IMRT: 43.3±60.9 minutes, [Table 1]).

We used multiple time definitions for the purpose of this study such as gross wait timing, net wait timing, and net WT corrected for delayed arrival. We feel that a more robust indicator is the net WT corrected for delayed arrival, which reflects the true waiting time. For example, if patient arrived well in advance from scheduled appointment and due to already occupied patients it was not possible to accommodate the patient earlier than their schedule time, the calculated gross waiting time became high. This problem was overcome in the delay corrected net waiting time calculation.

It is to be noted that our waiting times did not correlate significantly with the late/delayed arrival. A possible reason for this could be that the concerned technologist made all possible efforts to accommodate the patients, as soon as possible even after early/delayed arrivals.

Our data suffer from some pitfalls as well. It is possible that there might be some site dependence or fraction size dependence for RT time taken. For example, RT times could be larger for patients for SRS where a large dose is given in a single fraction. However, such radiosurgery patients constitute <5% of our overall patients and have limited ability to influence the overall data. Mis-timings in punching by the patient and the technologist too can lead to errors in data. However, we believe that such errors would be miniscule in number.


 > Conclusion Top


To summarize, we have presented our results of patient-related times during RT. Our study covers the daily waiting times before RT as well as the actual treatment times during modern-day RT. This consecutive patient data from a large series shall be an important resource tool for future planners and policymakers.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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Chan K, Li W, Medlam G, Higgins J, Bolderston A, Yi Q, et al. Investigating patient wait times for daily outpatient radiotherapy appointments (A Single-Centre Study). J Med Imaging Radiat Sci 2010;41:145-51.  Back to cited text no. 12
    
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Junor EJ, Macbeth FR, Barrett A. An audit of travel and waiting times for outpatient radiotherapy. Clin Oncol (R Coll Radiol) 1992;4:174-6.  Back to cited text no. 13
    
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Ballhausen H, Li M, Ganswindt U, Belka C. Shorter treatment times reduce the impact of intra-fractional motion: A real-time 4DUS study comparing VMAT vs. step-and-shoot IMRT for prostate cancer. Strahlenther Onkol 2018;194:664-74.  Back to cited text no. 14
    


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