Time-driven activity-based costing of a novel form of CT-guided high-dose-rate brachytherapy intraoperative radiation therapy compared with conventional breast intraoperative radiation therapy for early stage breast cancer

The Application of Time-Driven Activity-Based Costing in Oncology: A Systematic Review

OBJECTIVES

Time-driven activity-based costing (TD-ABC) holds promise to control costs and enhance value in oncology, but the current landscape of its applications remains uncharted. This study aimed to: (1) document the applications of TD-ABC in oncology and unveil its strengths and limitations, (2) assess the extent to which studies adhere to Kaplan and Porter's method, and (3) appraise study quality.

METHODS

A systematic review was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines. To be eligible for inclusion, studies had to provide an empirical application of TD-ABC within oncology. Structured data extraction included key characteristics such as cancer type, perspective, and analysis setting. Quality was assessed using the TD-ABC Healthcare Consortium Consensus Statement checklist.

RESULTS

A total of 59 studies met the inclusion criteria, two-thirds of which were published within the last 5 years. Most studies were conducted in high-income countries and analyzed common cancer types. The provider's perspective (85%) dominated, and studies typically relied on single-institution data (76%). No study assessed costs over a complete cycle of care and most focused on the costs of radiotherapy (56%) or surgery (20%). Articles generally did not adhere to the seven-step method, and average study quality was low (52%), particularly because of inadequate content in methods and results.

CONCLUSIONS

Oncology has emerged as a productive field for TD-ABC analyses, showcasing the effectiveness of TD-ABC in capturing the costs of healthcare processes in which medical devices are integral to care delivery. Nevertheless, concerns arise because of the low overall study quality and the lack of a consistent methodology.

Deep learning for high-resolution dose prediction in high dose rate brachytherapy for breast cancer treatment

Objective.Monte Carlo (MC) simulations are the benchmark for accurate radiotherapy dose calculations, notably in patient-specific high dose rate brachytherapy (HDR BT), in cases where considering tissue heterogeneities is critical. However, the lengthy computational time limits the practical application of MC simulations. Prior research used deep learning (DL) for dose prediction as an alternative to MC simulations. While accurate dose predictions akin to MC were attained, graphics processing unit limitations constrained these predictions to large voxels of 3 mm × 3 mm × 3 mm. This study aimed to enable dose predictions as accurate as MC simulations in 1 mm × 1 mm × 1 mm voxels within a clinically acceptable timeframe.Approach.Computed tomography scans of 98 breast cancer patients treated with Iridium-192-based HDR BT were used: 70 for training, 14 for validation, and 14 for testing. A new cropping strategy based on the distance to the seed was devised to reduce the volume size, enabling efficient training of 3D DL models using 1 mm × 1 mm × 1 mm dose grids. Additionally, novel DL architecture with layer-level fusion were proposed to predict MC simulated dose to medium-in-medium (Dm,m). These architectures fuse information from TG-43 dose to water-in-water (Dw,w) with patient tissue composition at the layer-level. Different inputs describing patient body composition were investigated.Main results.The proposed approach demonstrated state-of-the-art performance, on par with the MCDm,mmaps, but 300 times faster. The mean absolute percent error for dosimetric indices between the MC and DL-predicted complete treatment plans was 0.17% ± 0.15% for the planning target volumeV100, 0.30% ± 0.32% for the skinD2cc, 0.82% ± 0.79% for the lungD2cc, 0.34% ± 0.29% for the chest wallD2ccand 1.08% ± 0.98% for the heartD2cc.Significance.Unlike the time-consuming MC simulations, the proposed novel strategy efficiently converts TG-43Dw,wmaps into preciseDm,mmaps at high resolution, enabling clinical integration.

Is it possible to automate the discovery of process maps for the time-driven activity-based costing method? A systematic review

OBJECTIVES

The main objective of this manuscript was to identify the methods used to create process maps for care pathways that utilized the time-driven activity-based costing method.

METHODS

This is a systematic mapping review. Searches were performed in the Embase, PubMed, CINAHL, Scopus, and Web of Science electronic literature databases from 2004 to September 25, 2022. The included studies reported practical cases from healthcare institutions in all medical fields as long as the time-driven activity-based costing method was employed. We used the time-driven activity-based costing method and analyzed the created process maps and a qualitative approach to identify the main fields.

RESULTS

A total of 412 studies were retrieved, and 70 articles were included. Most of the articles are related to the fields of orthopedics and childbirth-related to hospital surgical procedures. We also identified various studies in the field of oncology and telemedicine services. The main methods for creating the process maps were direct observational practices, complemented by the involvement of multidisciplinary teams through surveys and interviews. Only 33% of the studies used hospital documents or healthcare data records to integrate with the process maps, and in 67% of the studies, the created maps were not validated by specialists.

CONCLUSIONS

The application of process mining techniques effectively automates models generated through clinical pathways. They are applied to the time-driven activity-based costing method, making the process more agile and contributing to the visualization of high degrees of variations encountered in processes, thereby making it possible to enhance and achieve continual improvements in processes.

Time-Driven, Activity-Based Costing to Reduce Interventional Radiology Suite Idle Time

Background With the ever-increasing complexity of today's healthcare environment, it is evident that there is a higher demand to deliver high-quality, accessible, efficient, and affordable healthcare. At the same time, these changes are accompanied by decreasing rates of reimbursement. This can be attributed to the shift from fee-for-service to value-based payment methods in the industry. The reception of such changes in the appropriate manner is crucial to improvement and the much-demanded reform in our healthcare system. To adapt to this changing landscape, hospitals and healthcare systems must incorporate proper measures to identify extraneous spending, control costs, and streamline patient care. Our goal in this study was to use the time-driven, activity-based costing (TDABC) model to quantify the costs at every step as an inpatient goes through the care process in an interventional radiology department. Methodology After identification and mapping of all the steps involved from interventional radiology (IR) consult placement to patient transport to the postoperative recovery area, time data were collected for each step of the process. One of the steps was then selected for intervention. Our focus was on the time interval between one patient leaving after a completed procedure and the next scheduled patient entering the IR suite (heretofore referred to as idle time). To decrease the idle room time between patients, the interventional radiologists, IR administrations, nurse manager, transportation manager, and charge nurse first met as a group to set a realistic initial goal. Pre-intervention data were collected. Results After the collection of pre-intervention data, the average idle time of the IR suite was found to be 40 minutes. After a multidisciplinary discussion, our goal was to reduce this time to 25 minutes. Post-intervention data found the average time decreased to 24 minutes. Calculation of average costs per unit time for staff, IR room, and equipment yielded an approximate cost of $57 per minute of time in the IR suite. Conclusions Considering the near 40% decrease in suite idle time as well as the cost per minute of material, equipment, and staff (at ~80% capacity), this study proves that the TDABC system is a viable method of targeting bottlenecks in operations and streamlining patient care by reducing costs while optimizing the process patients go through during care continuum.

Process, resource and success factors associated with chimeric antigen receptor T-cell therapy for multiple myeloma

Background: Chimeric antigen receptor T-cell (CAR-T) therapy represents a new frontier in multiple myeloma. It is important to understand critical success factors (CSFs) that may optimize its use in this therapeutic area. Methods: We estimated the CAR-T process using time-driven activity-based costing. Information was obtained through interviews at four US oncology centers and with payer representatives, and through publicly available data. Results: The CAR-T process comprises 13 steps which take 177 days; it was estimated to include 46 professionals and ten care settings. CSFs included proactive collaboration, streamlined reimbursement and CAR-T administration in alternative settings when possible. Implementing CSFs may reduce episode time and costs by 14.4 and 13.2%, respectively. Conclusion: Our research provides a blueprint for improving efficiencies in CAR-T therapy, thereby increasing its sustainability for multiple myeloma.

A comparative study using time-driven activity-based costing in single-fraction breast high-dose rate brachytherapy: An integrated brachytherapy suite vs. decentralized workflow

INTRODUCTION

Precision breast intraoperative radiation therapy (PB-IORT) is a novel approach to adjuvant radiation therapy for early-stage breast cancer performed as part of a phase II clinical trial at two institutions. One institution performs the entire procedure in an integrated brachytherapy suite which contains a CT-on-rails imaging unit and full anesthesia capabilities. At the other, breast conserving surgery and radiation therapy take place in two separate locations. Here, we utilize time-driven activity-based costing (TDABC) to compare these two models for the delivery of PB-IORT.

METHODS

Process maps were created to describe each step required to deliver PB-IORT at each institution, including personnel, equipment, and supplies. Time investment was estimated for each step. The capacity cost rate was determined for each resource, and total costs of care were then calculated by multiplying the capacity cost rates by the time estimate for the process step and adding any additional product costs.

RESULTS

PB-IORT costs less to deliver at a distributed facility, as is more commonly available, than an integrated brachytherapy suite ($3,262.22 vs. $3,996.01). The largest source of costs in both settings ($2,400) was consumable supplies, including the brachytherapy balloon applicator. The difference in costs for the two facility types was driven by personnel costs ($1,263.41 vs. $764.89). In the integrated facility, increased time required by radiation oncology nursing and the anesthesia attending translated to the greatest increases in cost. Equipment costs were also slightly higher in the integrated suite setting ($332.60 vs. $97.33).

CONCLUSIONS

The overall cost of care is higher when utilizing an integrated brachytherapy suite to deliver PB-IORT. This was primarily driven by additional personnel costs from nursing and anesthesia, although the greatest cost of delivery in both settings was the disposable brachytherapy applicator. These differences in cost must be balanced against the potential impact on patient experience with these approaches.

A primer on time-driven activity-based costing in brachytherapy

Emphasis on value-based healthcare has led to increasing use of time-driven activity-based costing (TDABC) across medical departments. When applied to brachytherapy, TDABC provides insight into differences in costs across various modes of therapy, the nuances that drive cost including institutional factors and involved personnel, and discrepancies in reimbursement which influence clinical practice. This is especially important with the new alternative payment model (APM) in radiation oncology which offers fixed reimbursement per 90-day episode of care. The TDABC model can thus be utilized to improve efficiency, optimize the role of ancillary staff in treatment planning and care delivery, and implement shorter fraction schedules when clinically appropriate to promote value-based care. Ultimately, application of this methodology could potentiate changes to practice and incentives to improve patient care. In this review, we discuss the utility and limitations of TDABC in the context of existing studies in brachytherapy which have utilized this methodology.

Examining the Financial Impact of Altered Fractionation in Breast Cancer: An Analysis Using Time-Driven Activity-Based Costing

PURPOSE

Value-based care is increasingly informing treatment decisions in radiation oncology. Although reimbursement differences have been examined for accelerated whole breast irradiation (AWBI) and conventional whole breast irradiation (CWBI), the cost of care delivery is poorly understood. This article describes our experience evaluating costs for altered fractionation in early-stage breast cancer using a time-driven activity-based costing (TDABC) model.

METHODS AND MATERIALS

Process maps were developed for 2 treatment regimens, AWBI (42.5 Gy in 16 fractions + 10 Gy in 4 fractions boost) and CWBI (50 Gy in 25 fractions + 10 Gy in 5 fractions boost). Cost was determined based on aggregate cost of personnel, materials, equipment, space, and utilities per unit time and based on the relative proportion of capacity used. The total reimbursement for each regimen was calculated as the aggregate of all billable events during a course of radiation therapy, based on the 2019 Centers for Medicare & Medicaid Services physician fee schedule database.

RESULTS

The total cost of delivering courses of AWBI and CWBI was $6965 and $9267, respectively, a difference of $2302 (25%). Eighty-six percent of this difference was related to a lower cost of delivering daily treatments. The total reimbursement for AWBI or CWBI was $9665 or $12,908, respectively, a difference of $3243 (25%). Overall, 55% to 60% of total costs were related to personnel, with the remainder related to materials, utilities, space, and equipment.

CONCLUSIONS

This analysis shows how TDABC can be used to evaluate resource requirements for different radiation therapy fractionation schedules. We found a substantially lower cost for AWBI compared with CWBI, primarily resulting from fewer daily treatments. As the emphasis in health care shifts toward value-based care, TDABC can help identify opportunities to reduce costs and increase clinical efficiency.