16 research outputs found
Impact of a New Cost-Effectiveness Threshold Implementation on Cancer Formulary Decisions in Jordan
No full textRising prices of novel cancer medications are increasing the economic burden from cancer in Jordan, risking the ability of cancer patients to access lifesaving and life-extending treatments. Furthermore, in the absence of a national health technology assessment (HTA) framework, medication prices in Jordan are set based on manufacturers’ pricing considerations and not a value proposition. In response to these challenges, King Hussein Cancer Center (KHCC), the de facto national cancer institute, developed a first-in-country, cancer-specific, cost-effectiveness threshold (CET) to aid institutional decision makers in approving only cost-effective medications. Over the past 10 years, cost-effectiveness analyses based on this CET have led to the introduction of > 70% of requested novel cancer medications after manufacturers agreed to lower prices, beyond registration prices, to meet the CET. Future work is warranted to empirically derive a CET for Jordan to better guide reimbursement decisions.Full Tex
Form-Finding Framework for FRP Shells: A Multi-Step Structural Optimization Tool for Preliminary FRP designs
No full textFibre reinforced polymers, or FRP, are increasingly used in structural engineering applications. Permeating the construction field from the aerospace industry, FRP are applied in both the rehabilitation of existing degrading structures as well as the conception of new projects such as pedestrian and traffic bridges or building facades. The increase of interest and use in FRP in recent decades is driven by the material’s advantageous properties. Its tailorable mechanical properties, long-term durability, customizable free-form design, and its light-weight feature have engrained FRP as a noteworthy alternative to traditional construction materials such as concrete, steel, or timber. This is of paramount importance in light of the climate change challenge facing structural engineers today. While the material properties have been extensively investigated over the past decades, the structural use in FRP have remained limited to specific applications. As such, FRP, material of the future, has fallen short of its aspirations, disappointing its most ardent proponents. A rift is identified between the academic setting of laboratory testing and the pragmatic essence of the construction industry. This research situates itself as part of the efforts interrogating the industry limits and attempting to bridge these two spheres. It proposes to answer the following research question: What strategies capitalize on FRP’s favorable mechanical properties in order to promote formal exploration with the material in the preliminary phase of a design considering its durable and sustainable potential? This research proposes then a tool that capitalizes on the advantageous mechanical properties of FRP and encourages formal exploration in FRP at the conception phase of a design. Considering the climate change threat, the stakes of such a catalyst framework are high. The Wilhelminaberg Viewpoint, a landmark project in Landgraaf (NL) designed by Ney & Partners, is used as case-study to implement the proposed framework. It also allows to draw a contrast between what is structurally feasible in FRP and what is realistically buildable in FRP. A multi-step single-objective optimization is developed. First, stiffness for a certain design boundary is maximized. Using a brute force algorithm, the first level iterates through all the possible laminate layup combinations to find the combination which generates the stiffest structure. The second level of the optimization finds the lightest geometries using a genetic algorithm. This suggested framework offers an answer to the research question, mentioned hereinabove. Completely integrated in one interface (Grasshopper 3D), the developed tool stimulates formal exploration in FRP structures exhibiting shell-like behavior. The user defines the design boundaries, design constraints, load-cases, and material properties and implements the framework.Civil Engineering | Building Engineerin
Development and implementation of a method for characterizing clinical pharmacy interventions and medication use in a cancer center
No full textPurpose: Develop and implement a method to characterize clinical pharmacy activities and the associated medication use in a comprehensive cancer center. A standard characterization of clinical pharmacy services facilitates benchmarking and informs continuous development. Methods: A set of quantifiable parameters to describe clinical pharmacy activities and the associated medication use was proposed and validated by peer review. For implementation, clinical pharmacy interventions for six clinical pharmacy services at the King Hussein Cancer Center in 2008 were prospectively documented and the numbers of patients and medications dispensed for the same period were obtained from the admission office and pharmacy database respectively. Results: The method comprised four main aspects: (1) number of interventions, (2) type of interventions, (3) number of doses dispensed, and (4) the NNI which is the number of doses dispensed for one intervention to occur. A total of 8552 interventions were recorded for 37,784 patient days. Interventions were highest in the pediatric oncology and ICU with 2612 (31%) and 1867 (22%) respectively, followed by medical oncology 1563 (18%), BMT 998 (12%), palliative care 792 (9%), and surgery 720 (8%). Interventions per 1000 patient days were: ICU 555, pediatric oncology 326, BMT 319, palliative care 244, medical oncology 137, and surgery 83. Main intervention categories for all services: therapeutic 3055 (36%), safety 2195 (26%), quality assurance 2376 (28%), and education-information 925 (10%). The number of doses dispensed per 1000 patient days was: BMT 19,404, palliative care 17,272, ICU 12,290, medical oncology 13,182, pediatric oncology 12,093, and surgery 8976. Finally, NNI was as follows: ICU 22, pediatric oncology 39, BMT 60, palliative care 71, medical oncology 96, and surgery 109. Conclusion: A method for characterizing clinical pharmacy interventions and medication use was developed and used to compare different oncology clinical pharmacy services. Further work is warranted to refine and validate the parameters proposed.No Full Tex
Comparative Cost Utility Analysis of Plerixafor Plus GCSF Versus Cyclophosphamide Plus GCSF as Salvage Mobilization Regimens in Multiple Myeloma Patients
No full textDevelopment and implementation of a method for characterizing clinical pharmacy interventions and medication use in a cancer center
No full text Purpose: Develop and implement a method to characterize clinical pharmacy activities and the associated medication use in a comprehensive cancer center. A standard characterization of clinical pharmacy services facilitates benchmarking and informs continuous development. Methods: A set of quantifiable parameters to describe clinical pharmacy activities and the associated medication use was proposed and validated by peer review. For implementation, clinical pharmacy interventions for six clinical pharmacy services at the King Hussein Cancer Center in 2008 were prospectively documented and the numbers of patients and medications dispensed for the same period were obtained from the admission office and pharmacy database respectively. Results: The method comprised four main aspects: (1) number of interventions, (2) type of interventions, (3) number of doses dispensed, and (4) the NNI which is the number of doses dispensed for one intervention to occur. A total of 8552 interventions were recorded for 37,784 patient days. Interventions were highest in the pediatric oncology and ICU with 2612 (31%) and 1867 (22%) respectively, followed by medical oncology 1563 (18%), BMT 998 (12%), palliative care 792 (9%), and surgery 720 (8%). Interventions per 1000 patient days were: ICU 555, pediatric oncology 326, BMT 319, palliative care 244, medical oncology 137, and surgery 83. Main intervention categories for all services: therapeutic 3055 (36%), safety 2195 (26%), quality assurance 2376 (28%), and education-information 925 (10%). The number of doses dispensed per 1000 patient days was: BMT 19,404, palliative care 17,272, ICU 12,290, medical oncology 13,182, pediatric oncology 12,093, and surgery 8976. Finally, NNI was as follows: ICU 22, pediatric oncology 39, BMT 60, palliative care 71, medical oncology 96, and surgery 109. Conclusion: A method for characterizing clinical pharmacy interventions and medication use was developed and used to compare different oncology clinical pharmacy services. Further work is warranted to refine and validate the parameters proposed. </jats:p
Corrigendum to 'Multidisciplinary strategies to treat painful mononeuropathies in the upper extremity: from lab to bedside’(J Hand Surg Eur., 10.1177/17531934241240389)
No full textThe name of the author J. Henk Coert was incorrect in the original paper. The name has now been corrected in the paper
Adoption Factors of Artificial intelligence in Human Resource Management
No full textTesis por compendio[ES] El mundo es testigo de nuevos avances tecnológicos que afectan significativamente a las organizaciones en diferentes departamentos. La inteligencia artificial (IA) es uno de estos avances, visto como una tecnología revolucionaria en la gestión de recursos humanos (RRHH). Profesionales y académicos han discutido el brillante papel de la IA en RRHH. Sin embargo, el análisis profundo de esta tecnología en el proceso de RRHH es aún escaso. Con todo ello, el objetivo principal de esta tesis es investigar el estado de la IA en RRHH y así identificar factores clave de implementación concretos. Primero, construyendo un marco académico para la IA en RRHH; segundo, analizar las aplicaciones de IA más utilizada en los procesos de RRHH; tercero, identificar las formas óptimas de transferir el conocimiento en los procesos de implementación de IA.
La metodología utilizada para la investigación combina la revisión sistemática de la literatura y técnicas de investigación cualitativa. Como base y medida preparatoria para abordar las preguntas de investigación, se llevó a cabo un extenso análisis de la literatura en el campo AI-RRHH, con un enfoque particular en las publicaciones de algoritmos de IA en HRM, análisis de HR-Big data, aplicaciones/soluciones de IA en HRM e implementación de IA. En la misma línea, el autor publicó artículos en varias conferencias que contribuyeron a mejorar la madurez de las preguntas de investigación. Con base en este conocimiento, los estudios publicados ilustraron la brecha entre la promesa y la realidad de la IA en RRHH, teniendo en cuenta los requisitos técnicos de la implementación de la IA, así como las aplicaciones y limitaciones. Posteriormente, se entrevistó a expertos en recursos humanos y consultores de IA que ya habían adquirido experiencia de primera mano con los procesos de recursos humanos en un entorno de IA para descubrir la verdad de la aplicación de la IA dominante en el proceso de RRHH.
Los principales hallazgos de esta tesis incluyen la derivación de una definición completa de IA en RRHH, así como el estado de las estrategias de adopción de aplicaciones de IA en RRHH. Como resultado adicional, se explora la utilidad y las limitaciones de los chatbots en el proceso de contratación en la India. Además, factores clave para transferir el conocimiento del proceso de implementación de IA a los gerentes y empleados de recursos humanos. Finalmente, se concluye identificando desafíos asociados con la implementación de IA en el proceso de recursos humanos y el impacto de COVID-19 en la implementación de IA.[CA] El món és testimoni de nous avanços tecnològics, que afecten significativament les organitzacions en diferents departaments. La intel·ligència artificial (IA) és un d'aquests avanços que s'anuncia àmpliament com una tecnologia revolucionària en la gestió de recursos humans (HRM). Professionals i acadèmics han discutit el brillant paper de la IA en HRM. No obstant això, encara és escàs l'anàlisi profund d'aquesta tecnologia en el procés de HRM. Per tant, l'objectiu principal d'aquesta tesi és investigar l'estat de la IA en HRM i derivar factors clau d'implementació concrets. Primer, construint un marc acadèmic per a la IA en HRM; segon, analitzar l'aplicació de IA més utilitzada en el procés de recursos humans; tercer, identificar les formes òptimes de transferir el coneixement dels processos d'implementació de IA.
La metodologia utilitzada per a la investigació es combina entre una revisió sistemàtica de la literatura i una tècnica d'investigació qualitativa. Com a base i mesura preparatòria per a abordar les preguntes d'investigació, es va dur a terme una extensa anàlisi de la literatura en el camp IA-HRM, amb un enfocament particular en les publicacions d'algorismes de IA en HRM, anàlisis de HR-Big data, aplicacions/soluciones de IA en HRM i implementació de IA. En la mateixa línia, l'autor va publicar articles en diverses conferències que van procedir a millorar la maduresa de les preguntes d'investigació. Amb base en aquest coneixement, els estudis publicats van illustrar la bretxa entre la promesa i la realitat de la IA en HRM, tenint en compte els requisits tècnics de la implementació de la IA, així com les aplicacions i limitacions. Posteriorment, es va entrevistar experts en recursos humans i consultors de IA que ja havien adquirit experiència de primera mà amb els processos de recursos humans en un entorn de IA per a descobrir la veritat de l'aplicació de la IA dominant en el procés de recursos humans.
Les principals troballes d'aquesta tesi són la derivació d'una definició completa de IA en HRM, així com l'estat de les estratègies d'adopció d'aplicacions de IA en HRM. Com a resultat addicional, explore la utilitat i les limitacions dels chatbots en el procés de contractació a l'Índia. A més, factors clau per a transferir el coneixement del procés d'implementació de IA als gerents i empleats de recursos humans. També es van concloure els desafiaments associats amb la implementació de IA en el procés de recursos humans i l'impacte de COVID-19 en la implementació de IA.[EN] The world is witnessing new technological advancements, which significantly impacts organizations across different departments. Artificial intelligence (AI) is one of these advancements that is widely heralded as a revolutionary technology in Human Resource Management (HRM). Professionals and scholars have discussed the bright role of AI in HRM. However, deep analysis of this technology in the HR process is still scarce.
Therefore, the main goal of this thesis is to investigate the status of AI in HRM and derive concrete implementation key factors. Through, first, building an academic framework for AI in HRM; second, analyzing the most commonly used AI applications in HR process; third, identifying the optimal ways to transfer the knowledge of AI implementation processes.
The methodology used for the investigation combines a systematic literature review and a qualitative research technique. As a basis and preparatory measure to address the research questions, an extensive literature analysis in the AI-HRM field was carried out, with a particular focus on publications of AI in HRM, HR-Big data analysis, AI applications/solutions in HRM and AI implementation. Along similar lines, the author published papers in several conference proceedings to improve the maturity of research questions.
Based on this work, the published studies illustrate the gap between the promise and reality of AI in HRM, taking into account the requirements of AI implementation as well as the applications and limitations. Subsequently, HR experts and AI consultants, who had already gained first-hand experience with HR processes in an AI environment, were interviewed to find out the truth of the dominant AI's application in HR process.
The main findings of this thesis are the derivation of a complete definition of AI in HRM as well as the status of the adoption strategies of AI applications in HRM. As a further result, it explores the usefulness and limitations of chatbots in the recruitment processes in India. In addition, derived the key factors to transfer the knowledge of AI implementation process to HR managers and employees. Challenges associated with AI implementation in the HR process and the impact of COVID-19 on AI implementation were also concluded.Tuffaha, M. (2022). Adoption Factors of Artificial intelligence in Human Resource Management [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/185909TESISCompendi
GCSF with or without chemotherapy compared to Plerixafor with GCSF as salvage mobilization regimen in patients with multiple myeloma and lymphoma: Collection effectiveness and cost effectiveness analysis
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The Effectiveness and Cost Effectiveness of Plerixafor + GCSF Versus GCSF ± Chemotherapy as Salvage Mobilization Regimens in Lymphoma and Multiple Myeloma Patients
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