• Values, value conflict and stress the prediction of stress by values and value conflict

      Bouckenooghe, Dave; Buelens, Marc; Fontaine, J.; Vanderheyden, Karlien (2004)
      The aim of this paper was to investigate the relationship between stress, values, and value conflict. Data collected from 400 people working in a wide variety of companies in Flanders indicated that the values openness to change, conservation, self-transcendence, self-enhancement, and value conflict were important predictors of stress. Participants open to change reported less stress, while respondents scoring high on conservation, self-enhancement, and self-transcendence perceived more stress. People reporting high value conflict also experienced more stress. Separate analyses for the male and female subsamples demonstrated that sex differences regarding the relationship between the four value types and stress cast new light on the findings for the total sample. The article concludes with a discussion of the results and future research directions.
    • Van bancassurance en assurfinance naar all finance

      Van den Berghe, Lutgart; Verweire, Kurt (Bank- en Financiewezen, 1998)
    • Van de velde case - The challenge of implementing SA8000

      Louche, Céline; Van Liedekerke, Luc (2006)
    • Van loopbaanladders naar zig-zag carrières

      Willemse, Ine; Meganck, Annelies; De Vos, Ans (2009)
    • Van verzorgingsstaat naar verzekeringsstaat

      Van den Berghe, Lutgart (Inversie, 1996)
    • Variability in hospital costs of adult spinal deformity care

      Jacobs, Karel; Dewilde, Thibault; Vandoren, Cindy; Cardoen, Brecht; Vansteenkiste, Nancy; Scheys, Lennart; Roodhooft, Filip; Moke, Lieven; Kesteloot, Katrien (Spine, 2020)
      Objective: To calculate the total clinical hospital cost of the Adult Spinal Deformity (ASD) care trajectory, to explain cost variability by patient and surgery characteristics, and to identify areas of process improvement opportunities. Summary of background data: ASD is associated with a high financial and clinical burden on society. ASD care thus requires improved insights in costs and its drivers as a critical step toward the improvement of value, i.e., the ratio between delivered health outcome and associated costs. Methods: Patient characteristics and surgical variables were collected following ethical approval in a cohort of 139 ASD patients, treated between December, 2014 and January, 2018. Clinical hospital costs were calculated, including all care activities, from initial consultation to 1 year after initial surgery (excl. overhead) in a university hospital setting. Multiple linear regression analysis was performed to analyze the impact of patient and surgical characteristics on clinical costs. Results: 75.5% of the total clinical hospital cost (€27,865) was incurred during initial surgery with costs related to the operating theatre (80.3%), nursing units (11.9%), and intensive care (2.9%) being the largest contributors. 57.5% of the variation in total cost could be explained in order of importance by surgical invasiveness, age, coronary disease, single or multiple-staged surgery, and mobility status. Revision surgery, unplanned surgery due to complications, was found to increase average costs by 87.6% compared with elective surgeries (€ 44,907 (± € 23,429) vs. € 23,944 (± € 7302)). Conclusion: This study identified opportunities for process improvement by calculating the total clinical hospital costs. In addition, it identified patient and treatment characteristics that predict 57.5% of cost variation, which could be taken into account when developing a payment system. Future research should include outcome data to assess variation in value.
    • Variability in hospital treatment costs: A time-driven activity-based costing approach for early-stage invasive breast cancer patients

      Roman, Erin (2020)
      Objectives: 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 $29,780 relative 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.
    • Variability in hospital treatment costs: A time-driven activity-based costing approach for early-stage invasive breast cancer patients

      Roman, Erin; Cardoen, Brecht; Decloedt, Jan; Roodhooft, Filip (BMJ Open, 2020)
      Objectives: 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 US$29 780 relative to US$11 208 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.
    • Vast, voltijds en levenslang. Het onwrikbare eenbaanskarakter van de loopbaan

      Buyens, Dirk; De Vos, Ans; Heylen, Leen; Mortelmans, Dimitri; Soens, Nele (Tijdschrift voor HRM, 2006)
    • Vendor Selection and Evaluation: An Activity Based Costing Approach

      Roodhooft, Filip; Konings, Jozef (European Journal of Operational Research, 1997)
    • Venture capital

      Manigart, Sophie; Baeyens, Katleen (Praktijkgids Waardebepaling en Strategische Reorganisaties, 2002)
    • Venture capital

      Manigart, Sophie; Baeyens, Katleen (2002)
    • Venture capital

      Vanacker, Tom; Manigart, Sophie (2013)
    • Venture capital firms and equity investment appraisal in the US, UK, France, Belgium and Holland

      Wright, Mike; Manigart, Sophie; Desbrières, Philippe; Sapienza, Harry J. (Management Buy-Outs, 1997)
    • Venture capital gids en Belgique

      Manigart, Sophie; Witmeur, Olivier (2009)
    • Venture capital gids in België

      Manigart, Sophie; Witmeur, Olivier (2009)