• Job stress among middle-aged health care workers and its relation to sickness absence

      Verhaeghe, Rik; Mak, R.; Van Maele, G.; Kornitzer, M.; De Backer, G. (Stress and Health, 2003)
    • Knowledge-flows and firm performance

      Erden, Zeynep; Klang, David; Sydler, Renato; von Krogh, Georg (Journal of Business Research, 2014)
      This study advances the understanding of how knowledge-flows impact on firm performance. Incorporating recent research on the knowledge-based view of the firm, this paper tests and extends the knowledge flow model by using more fine-grained measures and by proposing a nonlinear effect. This study tests the predicted effects in a longitudinal research design with data on a global sample of public biopharmaceutical firms. The results largely support the expectation that knowledge-flows largely have a nonlinear impact on firm performance. However, one traditional measure of knowledge-flows, geographical location, turns out to have no significant influence in the extended model. The paper explains the implications of these findings for practice and research.
    • Kostenbeheer in de Healthcare Supply Chain

      Krols, Krist'l (Healthcare Executive, 2012)
    • Kostenkennis in de zorgsector: onbekend is onbemind

      Krols, Krist'l; Van Steendam, Tom (Logistics Management, 2012)
    • Marketing of the life sciences: A new framework and research agenda for a nascent field

      Stremersch, Stefan; Van Dyck, Walter (Journal of Marketing, 2009)
    • Nearest neighbour propensity score matching and bootstrapping for estimating binary patient response in oncology: A Monte Carlo simulation

      Geldof, Tine; Dusan, Popovic; Van Damme, Nancy; Huys, Isabelle; Van Dyck, Walter (Scientific Reports: A Nature Research Journal, 2020)
      Nearest Neighbour (NN) propensity score (PS) matching methods are commonly used in pharmacoepidemiology to estimate treatment response using observational data. Unfortunately, there is limited evidence on the optimal approach for accurately estimating binary treatment response and, more so, to estimate its variance. Bootstrapping, although commonly used to accurately estimate variance, is rarely used together with PS matching. In this Monte Carlo simulation-based study, we examined the performance of bootstrapping used in conjunction with PS matching, as opposed to diferent NN matching techniques, on a simulated dataset exhibiting varying levels of real world complexity. Thus, an experimental design was set up that independently varied the proportion of patients treated, the proportion of outcomes censored and the amount of PS matches used. Simulation results were externally validated on a real observational dataset obtained from the Belgian Cancer Registry. We found all investigated PS methods to be stable and concordant, with k-NN matching to be optimally dealing with the censoring problem, typically present in chronic cancer-related datasets, whilst being the least computationally expensive. In contrast, bootstrapping used in conjunction with PS matching, being the most computationally expensive, only showed superior results in small patient populations with long-term largely unobserved treatment efects.
    • On the use of planning models in the operating theatre: Results of a survey in Flanders

      Cardoen, Brecht; Demeulemeester, Erik; Van der Hoeven, J. (International Journal of Health Planning and Management, 2010)
    • Operating room planning and scheduling problems: a classification scheme

      Cardoen, Brecht; Demeulemeester, Erik; Beliën, Jeroen (International Journal of Health Management and Information, 2010)
    • Operating room planning and scheduling: A literature review

      Cardoen, Brecht; Demeulemeester, Erik; Beliën, Jeroen (European Journal of Operational Research, 2010)
    • Operating room planning and scheduling: Solving a surgical case sequencing problem

      Cardoen, Brecht (4OR - A quarterly Journal of Operations Research, 2010)
    • Patient co-creation activities in healthcare service delivery at the Micro level: The influence of online access to healthcare information

      Osei-Frimpong, K.; Wilson, A.; Lemke, Fred (Technological forecasting and social change, 2018)
      The healthcare sector has undergone a number of transformations in recent years, partly due to recent advances in technology. This triggered our study to examine patients' desire to seek health information largely driven by increased access via the Internet and the cumulative impacts on value co-creation. We employed a sequential exploratory design involving a phenomenological approach in the qualitative phase, followed by a quantitative survey design to further our understanding of the influence of technology in co-creating value in healthcare at the micro level. Advances in technology have empowered patients to be informed, which enabled them to play an active role in clinical encounters with the doctor. The findings suggest pre-encounter information search impacts positively on improved service engagement and commitment to compliance with medical instructions. It does this by shaping the nature of interactions, enhancing provider-patient orientation, and increasing their involvement in a shared decision-making process. From a theoretical perspective, our study integrates multiple research perspectives (e.g., access to information, online information seeking and knowledge creation, healthcare consultation models, etc.) and extends research on patient integration, participation, and co-creation of value. The conceptualization of value co-creation activities in this study suggests a need for service providers to adopt delivery approaches that would effectively integrate patient resources to co-create value.
    • Patient preferences to assess value in gene therapies: Protocol development for the paving study in Hemophilia

      van Overbeeke, Eline; Hauber, Brett; Michelsen, Sissel; Goldman, Michel; Simoens, Steven; Huys, Isabelle (Frontiers in Medicine, 2021)
      Introduction: Gene therapies are innovative therapies that are increasingly being developed. However, health technology assessment (HTA) and payer decision making on these therapies is impeded by uncertainties, especially regarding long-term outcomes. Through measuring patient preferences regarding gene therapies, the importance of unique elements that go beyond health gain can be quantified and inform value assessments. We designed a study, namely the Patient preferences to Assess Value IN Gene therapies (PAVING) study, that can inform HTA and payers by investigating trade-offs that adult Belgian hemophilia A and B patients are willing to make when asked to choose between a standard of care and gene therapy. Methods and Analysis: An eight-step approach was taken to establish the protocol for this study: (1) stated preference method selection, (2) initial attributes identification, (3) stakeholder (HTA and payer) needs identification, (4) patient relevant attributes and information needs identification, (5) level identification and choice task construction, (6) educational tool design, (7) survey integration, and (8) piloting and pretesting. In the end, a threshold technique survey was designed using the attributes "Annual bleeding rate," "Chance to stop prophylaxis," "Time that side effects have been studied," and "Quality of Life." Ethics and Dissemination: The Medical Ethics Committee of UZ KU Leuven/Research approved the study. Results from the study will be presented to stakeholders and patients at conferences and in peer-reviewed journals. We hope that results from the PAVING study can inform decision makers on the acceptability of uncertainties and the value of gene therapies to patients.
    • Patient-level effectiveness prediction modeling for glioblastoma using classification trees

      Geldof, Tine; Van Damme, Nancy; Huys, Isabelle; Van Dyck, Walter (Frontiers in Pharmacology, 2020)
      Little research has been done in pharmacoepidemiology on the use of machine learning for exploring medicinal treatment effectiveness in oncology. Therefore, the aim of this study was to explore the added value of machine learning methods to investigate individual treatment responses for glioblastoma patients treated with temozolomide.
    • Patients' perceptions of service quality and patient satisfaction in nuclear medicine

      De Man, Stefanie; Gemmel, Paul; Vlerick, Peter; Van Rijk, P.; Dierckx, Rudi (European Journal of Nuclear Medicine, 2002)
    • Personalized medicine: Time to invest more in our health

      Van Dyck, Walter; Cardoen, Brecht; Neels, Leo (The Clinical Services Journal, 2015)
      Healthcare is on the verge of a revolution, especially as miniaturised digital technology, more powerful computing and an attitude change converse and reshape the way we deal with health issues.
    • Real-world evidence gathering in oncology: The need for a biomedical big data insight-providing federated network

      Geldof, Tine; Huys, Isabelle; Van Dyck, Walter (Frontiers in Medicine, 2019)
      Moving towards new adaptive pathways for the development and access to innovative medicines implies that real-world data (RWD) collected throughout the medicinal product life cycle is becoming increasingly important. Big data analytics on RWD can obtain new and powerful insights into medicines’ effectiveness. However, the healthcare ecosystem still faces many sector-specific challenges that hamper the use of big data analytics delivering real world evidence (RWE). We distinguish between exploratory (ExTE) and hypotheses-evaluating (HETE) studies testing treatment effectiveness in the real world. From our experience and in the context of the four V’s of data management, we show that to get meaningful results data Variety and Veracity are needed regardless of the type of study conducted. More so, for ExTE studies high data Volume is needed while for HETE studies high Velocity becomes essential. Next, we highlight what are needed within the biomedical big data ecosystem, being: (a) international data reusability; (b) real-time RWD processing information systems; and (c) longitudinal RWD. Finally, in an effort to manage the four V’s whilst respecting patient privacy laws we argue for the development of an underlying federated RWD infrastructure on a common data model, capable of bringing the centrally-conducted big data analysis to the de-centrally kept biomedical data.
    • Recurrent changes in the work environment, job resources and distress among nurses: a comparative cross-sectional survey

      Verhaeghe, Rik; Vlerick, Peter; De Backer, G.; Van Maele, G.; Gemmel, Paul (International Journal of Nursing Studies, 2008)
    • Samenwerking in de zorgsector

      Krols, Krist'l; Van Steendam, Tom (Zorgmagazine, 2013)
      The present study aims to unravel the relationship between competency development, employability and career success. To do so, we tested a model wherein associations between employee participation in competency development initiatives, perceived support for competency development, self-perceived employability, and two indicators of subjective career success (i.e. career satisfaction and perceived marketability) have been specified. A survey was conducted among a sample of 561 employees of a large financial services organization. The results support the idea that employee participation in competency development initiatives as well as perceived support for competency development is positively associated with workers' perceptions of employability. Moreover, self-perceived employability appeared to be positively related with career satisfaction and perceived marketability. A full mediation effect was found for the relationship between participation in competency development initiatives and both career satisfaction and perceived marketability, while a partial mediation effect was found in case perceived support for competency development was the predictor variable. The implications of our findings for understanding the process through which individuals and organizations can affect subjective career success are discussed.