Big Data technology is one of the most promising organizational processes within the Healthcare and Pharmaceutical industry and crucial for any company that wants to preserve the competitive advantage in the market, where most of the organizational structures are already struggling with the right skills and knowledge to fully support existing business needs for storing and processing and even analyzing information. This paper aims to examine the extent to which new Big Data technology and data-related processes are developing different professionals skills and competencies within the Healthcare and Pharmaceutical industries, and creating sustainable development in addressing critical organizational challenges in recruiting, retaining, and discover professional skills that can fully support the advances and exponential growth of Big Data technology benefits. This research paper also highlights the significant aspects of Big Data in professional technical and process oriented skills development, and the influence it has on organizational business processes including how various internal functions will need to adapt to new circumstances with renewed competency and skills development programs for departments that are strongly connected to the business and analytical needs. We conducted a focus group with twenty-five industry based professionals' ranges from analysts to executive directors to better assess the necessary knowledge to answer the proposed research questions: (1) which professional skills can big data influence in employee development and (2) how can organizations adapt their employee skills to big data. Regarding the key research limitations/implications most of the article and research was built on the foundation of the literature review and the performed focus group. The conceptual recommendations and observations presented provide solid empirical evidence but should be subjected to more comprehensive, large-scale empirical testing and validation. It's recommended for future research a more extensive sample of companies, organizations, and interviewees. Studying a broader set of similar research questions in more homogeneous organizations could provide deeper insights into the process, governance, and stakeholder dimensions of Big Data within specific contexts. Therefore this study contributes to explore in-depth and systematically to what extent Big Data technology and processes are currently influencing the healthcare and pharmaceuticals industries where to the best of the authors' knowledge, it is the first focus group dealing with the presented research questions.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7544557 | PMC |
http://dx.doi.org/10.1007/s10916-020-01665-9 | DOI Listing |
Int J Med Inform
December 2024
Chongqing Cancer Multiomics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing 400030, China. Electronic address:
Background: With advancements in healthcare, traditional VTE risk assessment tools are increasingly insufficient to meet the demands of high-quality care, underscoring the need for innovative and specialized assessment methods.
Objective: Owing to the remarkable success of machine learning in supervised learning and disease prediction, our objective is to develop a reliable and efficient model for assessing VTE risk by leveraging the fundamental data and clinical characteristics of colorectal cancer patients within our medical facility.
Methods: Six commonly used machine learning algorithms were utilized in our study to predict the occurrence of VTE in patients with rectal cancer.
J Anxiety Disord
December 2024
Institut für Psychologie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany.
Background: This paper reports on the outcomes of a proof-of-principle study for the Exposure Therapy Consortium, a global network of researchers and clinicians who work to improve the effectiveness and uptake of exposure therapy. The study aimed to test the feasibility of the consortium's big-team science approach and test the hypothesis that adding post-exposure processing focused on enhancing threat reappraisal would enhance the efficacy of a one-session large-group interoceptive exposure therapy protocol for reducing anxiety sensitivity.
Methods: The study involved a multi-site cluster-randomized controlled trial comparing exposure with post-processing (ENHANCED), exposure without post-processing (STANDARD), and a stress management intervention (CONTROL) in students with elevated anxiety sensitivity.
J Food Sci
December 2024
College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, China.
As consumers increasingly prioritize food safety and nutritional value, the dairy industry faces a pressing need for rapid and accurate methods to detect essential nutritional components in milk, such as fat, protein, and lactose. Hyperspectral imaging (HSI) technology, known for its non-destructive, fast, and precise nature, shows great promise in food quality assessment. However, the high dimensionality of HSI data poses challenges for effective band selection and model optimization.
View Article and Find Full Text PDFMed Sci Monit
December 2024
Department of Neurosurgery, China Medical University Hospital, Taichung, Taiwan.
BACKGROUND Ventriculoperitoneal (VP) shunt surgery is a widely used procedure for managing hydrocephalus; however, postoperative infections remain a serious complication, increasing morbidity and mortality. Known risk factors include prior surgeries, steroid use, and concurrent procedures. However, the role of liver cirrhosis, a condition that compromises immune function and predisposes patients to infections, has not been fully investigated in the context of neurosurgery.
View Article and Find Full Text PDFNutr J
December 2024
Department of Nutrition, Center for Big Data and Population Health of IHM, School of Public Health, Anhui Medical University, Hefei, Anhui, China.
Background: Although emerging evidence suggests that indole derivatives, microbial metabolites of tryptophan, may improve cardiometabolic health, the effective metabolites remain unclear. Also, the gut microbiota that involved in producing indole derivatives are less studied. We identified microbial taxa that can predict serum concentrations of the key indole metabolite indole-3-propionic acid (IPA) at population level and investigated the associations of indole derivatives and IPA-predicting microbial genera with cardiometabolic risk markers.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!