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Variability in hospital treatment costs: a time-driven activity-based costing approach for early-stage invasive breast cancer patients
Get PDFOBJECTIVES: Using a standardised diagnostic and generic treatment path for breast cancer, and the molecular subtype perspective, we aim to measure the impact of several patient and disease characteristics on the overall treatment cost for patients. Additionally, we aim to generate insights into the drivers of cost variability within one medical domain.
DESIGN, SETTING AND PARTICIPANTS: We conducted a retrospective study at a breast clinic in Belgium. We used 14 anonymous patient files for conducting our analysis.
RESULTS: Significant cost variations within each molecular subtype and across molecular subtypes were found. For the luminal A classification, the cost differential amounts to roughly 166%, with the greatest treatment cost amounting to US11 208 for a patient requiring fewer medical activities. The major driver for these cost variations relates to disease characteristics. For the luminal B classification, a cost difference of roughly 242% exists due to both disease-related and patient-related factors. The average treatment cost for triple negative patients amounted to US$26 923, this is considered to be a more aggressive type of cancer. The overall cost for HER2-enriched is driven by the inclusion of Herceptin, thus this subtype is impacted by disease characteristics. Cost variability across molecular classifications is impacted by the severity of the disease, thus disease-related factors are the major drivers of cost.
CONCLUSIONS: Given the cost challenge in healthcare, the need for greater cost transparency has become imperative. Through our analysis, we generate initial insights into the drivers of cost variability for breast cancer. We found evidence that disease characteristics such as severity and more aggressive cancer forms such as HER2-enriched and triple negative have a significant impact on treatment cost across the different subtypes. Similarly, patient factors such as age and presence of gene mutation contribute to differences in treatment cost variability within molecular subtypes.Co--funded by an unconditional grant provided by Xperthis in Belgium, but no conflict of interest to be reported
The effect of traffic-light labels and time pressure on estimating kilocalories and carbon footprint of food
No full textFood consumption decisions require consumers to evaluate the characteristics of products. However, the literature has given limited attention to how consumers determine the impact of food on health (e.g., kilocalories) and on the environment (e.g., carbon footprint). In this exercise, 1511 consumers categorised 43 food products as healthy/unhealthy and good/bad for the environment, and estimated their kilocalories and carbon footprint, which were known to the investigator. The task was performed either with no stimuli (a control group), under time pressure only, with traffic-light labels only, or both. Results show that traffic-light labels: 1) operate through improvements in knowledge, rather than facilitating information processing under pressure; 2) improve the ability to rank products by both kilocalories and carbon footprint, rather than the ability to use the metric; 3) reduce the threshold used to categorise products as unhealthy/bad for the environment, whilst raising the threshold used to classify products as good for the environment (but not healthy). Notably, traffic-light increase accuracy by reducing the response compression of the metric scale. The benefits of labels are particularly evident for carbon footprint. Overall, these results indicate that consumers struggle to estimate numerical information, and labels are crucial to ensure consumers make sustainable decisions, particularly for unfamiliar metrics like carbon footprint
Variability in hospital treatment costs: A time-driven activity-based costing approach for early-stage invasive breast cancer patients
No full textObjectives: Using a generic treatment path for breast cancer, and the molecular subtype perspective, we aim to measure the impact of several patient and disease characteristics on the overall treatment cost for patients. We aim to generate insights into the drivers of cost variability within one medical domain. Methods - A generic treatment pathway was developed, process maps were constructed identifying all relevant activities, medical personnel, direct medical materials and facilities used for treating patients. Through face-to-face interviews with the medical staff and direct observations, time estimates were captured for each activity. The cost of resources were obtained from the financial database of the hospital. The per unit cost of supplying the resources were calculated by dividing the financial cost and the practical capacity rate. The per unit cost was then multiplied by the time spent per activity to obtain the full cost for each step in the treatment process. Results - Significant cost variations within each molecular subtype and across molecular subtypes were found. Typically for luminal A the cost differential amounts to roughly 166%, with the greatest treatment cost amounting to 11,208 for a patient requiring less medical activities. The major driver for these cost variations relate to disease characteristics. For the luminal B classification a cost difference of roughly 242% exists due to both disease and patient related factors. The average treatment cost for triple negative patients amounted to $26,923, this is considered to be a more aggressive type of cancer. The overall cost for HER2-enriched is driven by the inclusion of Herceptin, thus this subtype is impacted by disease characteristics. Cost variability across molecular classifications is impacted by the severity of the disease, thus disease related factors are the major drivers of cost. Conclusions - Given the cost challenge in health care, the need for greater cost transparency has become imperative. Through our analysis we generate initial insights into the drivers of cost variability for breast cancer. We found evidence that disease characteristics such as severity and more aggressive cancer forms like HER2-enriched and triple negative have a significant impact on treatment cost across the different subtypes. Similarly, patient factors such as age and presence of gene mutation contribute to differences in treatment cost variability within molecular subtypes
Academy of Management Proceedings
No full textWith the increasing pressure for organizations to digitalize, many companies are complementing their top management teams (TMT) with new members, chief informational and digital officers (CIOs and CDOs). As members of top management teams, CIOs and CDOs are expected to fulfill essential roles in the digital transformation strategy and its implementation. By making decisions on digitalization, they also influence business model development, innovation, and business strategy. While research on digital transformation is growing steadily, we lack a coherent understanding of the extent and nature of these top management roles and their relationships and the specific tasks involved. Based on the literature on management, information systems, and related fields, this paper discusses the evolving CIO and CDO roles and their interrelationships. Our key contribution is to conceptualize the role split, the emergence of the CDO, the nature of organizational roles and relationships by drawing on concepts of organizational ambidexterity, transactive memory systems (TMS), and shared understanding. We find that despite the separation of roles and potentially overlapping responsibilities, a collaborative relationship can be beneficial due to the complementary nature of the roles particularly to drive the digital transformation. We conclude with a future research agenda.
The Evolution of Electricity Markets in Europe
No full textBridging theory and practice, this book offers insights into how Europe has experienced the evolution of modern electricity markets from the end of the 1990s to the present day. It explores defining moments in the process, including the four waves of European legislative packages, landmark court cases, and the impact of climate strikes and marches
Evaluation of precision medicine assessment reports of the Belgian healthcare payer to inform reimbursement decisions
No full textINTRODUCTION: Precision medicines rely on companion diagnostics to identify patient subgroups eligible for receiving the pharmaceutical product. Until recently, the Belgian public health payer, RIZIV-INAMI, assessed precision medicines and companion diagnostics separately for reimbursement decisions. As both components are considered co-dependent technologies, their assessment should be conducted jointly from a health technology assessment (HTA) perspective. As of July 2019, a novel procedure was implemented accommodating for this joint assessment practice. The aim of this research was to formulate recommendations to improve the assessment in the novel procedure.
METHODS: This study evaluated the precision medicine assessment reports of RIZIV-INAMI of the last 5 years under the former assessment procedure. The HTA framework for co-dependent technologies developed by Merlin et al. for the Australian healthcare system was used as a reference standard in this evaluation. Criteria were scored as either present or not present.
RESULTS: Thirteen assessment reports were evaluated. Varying scores between reports were obtained for the domain establishing the co-dependent relationship between diagnostic and pharmaceutical. Domains evaluating the clinical utility of the biomarker and the cost-effectiveness performed poorly, whereas the budget impact and the transfer of trial data to the local setting performed well.
RECOMMENDATIONS: Based on these results we recommend three amendments for the novel procedure. (i) The implementation of the linked evidence approach when direct evidence of clinical utility is not present, (ii) incorporation of a bias assessment tool, and (iii) further specify guidelines for submission and assessment to decrease the variability of reported evidence between assessment reports.Research Foundation Flanders funded this research through means of a doctoral scholarship
A project buffer and resource management model in energy sector; a case study in construction of a wind farm project
No full textPurpose This study aims to introduce an efficient project buffer and resource management (PBRM) model for project resource leveling and project buffer sizing and controlling of project buffer consumption of a wind power plant project to achieve a more realistic project duration. Design/methodology/approach The methodology of this research consists of three main phases. In the first phase of the research methodology, resource leveling is done in the project and resource conflicts of activities are identified. In the second phase, the project critical chain is determined, and the appropriate size of the project buffer is specified. In the third phase of the methodology, buffer consumption is controlled and monitored during the project implementation. After using the PBRM method, the results of this project were compared with those of the previous projects. Findings According to the obtained results, it can be concluded that using PBRM model in this wind turbine project construction, the project duration became 25 per cent shorter than the scheduled duration and also 29 per cent shorter than average duration of previous similar projects. Research limitations/implications One of the major problems with projects is that they are not completed according to schedule, and this creates time delays and losses in the implementation of projects. Today, as projects in the energy sector, especially renewable projects, are on the increase and also we are facing resource constraint in the implementation of projects, using scheduling techniques to minimize delays and obtain more realistic project duration is necessary. Practical implications This research was carried out in a wind farm project. In spite of the initial plan duration of 142 days and average duration of previous similar projects of 146 days, the project was completed in 113 days. Originality/value This paper introduces a practical project buffer and resource management model for project resource leveling, project buffer sizing and buffer consumption monitoring to reach a more realistic schedule in energy sector. This study adds to the literature by proposing the PBRM model in renewable energy sector
The digital future of internal staffing: A vision for transformational electronic human resource management
No full textSummary Through an international Delphi study, this article explores the new electronic human resource management regimes that are expected to transform internal staffing. Our focus is on three types of information systems: human resource management systems, job portals, and talent marketplaces. We explore the future potential of these new systems and identify the key challenges for their implementation in governments, such as inadequate regulations and funding priorities, a lack of leadership and strategic vision, together with rigid work policies and practices and a change‐resistant culture. Tied to this vision, we identify several areas of future inquiry that bridge the divide between theory and practice.Belgian Federal Public Service of Policy and Support - We want to extend our special thanks to Chris Van der Auwera, Chief of Staff in charge of Public Administration in the cabinet of Belgian federal minister Steven Vandeput, and Daniel Gerson, project manager at the Observatory of Public Sector Innovation at the Organisation for Economic Co-operation and Development for enabling the study and providing introductions to the experts. This work was supported by the Belgian Federal Public Service of Policy and Support
