Analysis of workload generated in the two years following first consultation by each new cancer patient: studying the past to plan the future of cancer care

Introduction

Prevalence of cancer patients is dramatically increasing. We aimed at quantifying the oncology workload generated by each new cancer patient in the two years following first consultation.

Methods

In this record-based retrospective study, we retrieved data of all newly diagnosed patients treated at the Oncology Department of Udine Academic Hospital between 01.01.2012 and 31.12.2017. We calculated mean number and standard deviation of the activity type generated by each new cancer patient during the following 2 years.

Results

Seven thousand four hundred fifty-two cancer patients generated a total of 85,338 clinical episodes. The two-years mean number of oncology episodes generated was 11.31 (i.e., for every 1,000 new cancer patients, 11,310 oncology activities are generated overall in the following two-year lapse). Patients with advanced disease generated the highest workload (24.3; SD 18.8) with a statistically significant difference compared to adjuvant and follow-up patients (p < 0.001). The workload generated in the period 0–6 and 0–12 months was significantly higher than in the following months (p < 0.001) and it was also higher for patients initially designated to treatment (p < 0.001).

Conclusion

This is the first study reporting on the mean oncology workload generated during the 2 years following first consultation. Workload is the highest for patient with advanced disease, especially in the first months and in patients in active treatment. A detailed analysis of workloads in oncology is feasible and could be crucial for planning a sustainable framework for cancer care in the next future.

The impact of COVID-19 pandemic on oncology workload: The experience of an Italian Reference Cancer Center

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Background: Since its outbreak in January 2020, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic dramatically affected health systems worldwide and a prompt realignment of clinical activities had to be thought. International Oncology guidelines recommended that routine oncology care continued to be delivered, ensuring triage procedures to prevent COVID-19 diffusion alongside treatments prioritization. Aim of this study was to assess the variation of activity volumes due to COVID-19 pandemic in the Oncology Department of the Academic Reference Cancer Center of Udine, Italy. Methods: We extracted activity volumes from the electronic “Data Warehouse” accountability system and compared activity in 2020 with historical activity in 2019. We then narrowed the analysis to the peak of COVID-19 pandemic, comparing data of a four-months period (February-May 2020 vs 2019). In accordance with the Italian Association of Medical Oncology guidelines, the activities analyzed included: new patients referrals, first consultations, new therapy assignments, treatment prescriptions and therapy administrations, disease re-assessments, follow-up visits, tele-examinations, unplanned visits and ward discharges. Results: Overall, throughout COVID-19 pandemic a negligible reduction in the number of first consultations (-5%) and new patients referrals to our Oncology Department (-10%) was detected. Of note, a significant reduction in the number of unplanned oncologic visits was observed (-23%). The replacement of follow up visits with telephonic interviews with the interpretation of laboratory and radiologic examinations (tele-examinations) led to a substantial reduction in follow-up visits throughout 2020 (-25%). Conversely, treatment-related activities, including new therapy assignments (+1%), treatment prescriptions and therapy administrations (+2% and +3%, respectively), confirmed the increasing trend of the previous year. Interestingly, similar trends were observed in the four-months peak period with a substantially higher decrease in follow-up visits in 2020 vs 2019 (-51%), whereas treatment-related activities remained stable. Conclusions: In the context of COVID-19 pandemic, our Oncology Department maintained stable performances on critical oncology activities. Strict triage procedures, serial swabs for patients and healthcare professionals and strategic follow-up visits remodulation were crucial. Notwithstanding the significant decrease in cancer treatments observed in several published reports, our experience demonstrates that the reorganization of oncology departments during a global pandemic is feasible and it should be pursued to preserve patients’ safety without compromising the continuum of care.

Impact of 12 months of immunotherapy for metastatic cancer patients on oncology workload

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Background: In the last years, the introduction of immune checkpoint inhibitors (ICI) in clinical practice translated into major changes in oncology workload. We conducted a study aimed to estimate the shift in workload generated, within 1 year of first consultation, by any new metastatic cancer patient receiving ICI at the Oncology Department of the Academic Hospital of Udine, Italy. Methods: We collected from our electronic accountability system data all new cases of metastatic cancer between 01.01.2017 and 31.12.2018, leading to at least a second clinical episode (treatment sessions, unplanned presentations, hospitalizations, re-evaluations, follow-up, and inpatient oncology advices) during the following year. Patients (pts) were divided into those receiving ICI (anti-CTLA4/PD1/PDL1) versus pts receiving other treatments. Mean number per patient and standard deviation were calculated for clinical episodes, and the mean numbers in each group were compared using Student’s t-test (significance p<0.05). Follow-up continued until 31.12.2019. Results: 969 pts were included: 115 were treated with ICI, 854 received other treatments. In the first group a greater number of treatment sessions, re-evaluations and unplanned presentations was generated, with a statistically significant increased workload. On the other hand, pts receiving other treatments generated a greater workload in terms of follow-up. In detail, data are reported in Table. Conclusions: ICI have transformed the oncology landscape, leading to longer lasting treatment period with emerging toxicities. Estimating the workload generated by ICI is crucial for the implementation of more sustainable systems and for planning clinical activities. Mean number of clinical episodes in the first year of treatment with ICI for metastatic disease. Mean number per patient is represented by mean value and standard deviation (SD). Total number of clinical episodes is shown (N=). Data are reported for ICI versus other treatments group. [Table: see text]

Incremental oncology workload generated by immunotherapy in the first-year of treatment

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Background: The rapid development of immunotherapy (IO) has transformed the cancer therapy landscape with growing impact on oncology workload. Given the few data on this topic, we conducted a study to estimate the shift in workload generated by any new metastatic cancer patient treated with IO and referred to the Oncology Department of the Academic Academic Cancer Center of Udine, Italy, within the 12 months of first consultation. Methods: We collected from our “Data Warehouse” electronic accountability system all new diagnosis of metastatic cancer between 01.01.2017 and 31.12.2018, resulting in a first consultation and leading to a second clinical episode during the following year, in order to assess the oncology workload. The population was divided into patients that received IO (anti-CTLA-4/PD-1/PDL1) versus patients treated with “other treatments”. Mean number per patient and standard deviation were calculated for clinical episodes (first consultations, treatment sessions, unplanned presentations, hospitalizations, re-evaluations, follow-up and inpatient oncology advices). The total number of patients treated and the number of episodes were recorded. Mean numbers of episodes in the IO group and “other treatments” group were compared using Student’s t-test (significance p < 0.005). Follow-up data was collected up to 31.12.2019. Results: A total number of 969 patients were considered (854 “other treatments” group and 115 IO group), resulting in a total of 12407 clinical episodes over the period of 12 months (first consultations excluded). Compared to “other treatments” group, patients in the IO group generated a greater workload in terms of treatment sessions (9.59 vs 6.83 per patient, p < 0.0001), re-evaluations (2.55 vs 1.88, p = 0.0002), and unplanned presentations (2.19 vs 1.51, p = 0.08). On the other hand, follow-up visits workload was greater for “other treatments” group (0.83 vs 0.63, p = 0.0002). No differences were found regarding hospitalizations and inpatient oncology advices. Further analysis will be presented. Conclusions: IO represents a new frontier in oncology landscape, leading to outcome’s improvement and longer lasting treatment periods. The estimate of oncology workload generated by new diagnosis of metastatic cancer requiring IO, is crucial for implementing more sustainable systems and for planning clinical activities.

Effects of the growing prevalence in oncology: A real-world study on the estimated workload

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Background: The increasing prevalence of cancer patients due to new effective treatments is leading to a growing demand in oncology activities, thus requiring a re-modelling towards more sustainable systems. The aim of this study is to estimate the workload generated by each new cancer patient referred to the Oncology Department of the Academic Cancer Center of Udine, Italy, within the two years from first consultation. Methods: We have utilised our electronic “Data Warehouse” accountability system to retrieve anonymous aggregate data of the 2-year oncology workload generated by each new diagnosis, leading to an initial consultation, occurring between 01.01.2012 and 31.12.2017. Initial consultations with no clinical episode in the following 12 months were excluded. Mean value per patient and standard deviations were calculated for the following clinical activities: treatment sessions, unplanned presentations, hospitalisations, re-assessments, follow-up visits and inpatient oncology advices. The total number of patients treated and of episodes were recorded. Follow-up data was collected up to 31.12.2019. Results: During the observation period, 7,454 newly diagnosed patients were referred to our Oncology Unit, resulting in a total of 92,830 clinical activities occurring over an 8-year period. In 1,788 pts (24.0%) only follow-up was needed; 3,152 pts (42.3%) were referred for adjuvant treatment and 2,514 (33.7%) for advanced disease management. Overall, the mean number of clinical activities per patient within the first 2 years was: 6.04 pre-treatment evaluations (52.9%; SD 8.81; 45,003 total episodes), 2.00 follow-up visits (17.5%; SD 1.89; 14,922 total episodes), 0.42 hospitalisations (3.7%; SD 1.21; 3,141 total episodes), 0.36 inpatient oncology advices (3.2%; SD 0.83; 2,705 total episodes), 1.57 re-assessments (13.8%; SD 2.28; 11,723 total episodes) and 1.02 unplanned presentations (8.9%; SD 2.17; 7,601 total episodes). Subgroup analysis in the different tumors and settings are ongoing. Conclusions: The landscape of cancer care is changing due to the growing prevalence of cancer patients that experience longer overall survival. Trying to estimate the amount of clinical activities generated by any new diagnosis is crucial for implementing new models of oncology management and for programming an adequate workforce supply.