Development Of Health Technology Methodologies: An Indepth Study Based On Medical Devices
DOI:
https://doi.org/10.48047/xbv9jt14Keywords:
Healthcare efficiency, medical equipment effectiveness, health information technology, healthcare system performance, patient treatment results.Abstract
Finding methods by which current medical technology may enhance healthcare delivery by enabling treatment that is more targeted, accurate, and efficient is the major objective of the project. It is imperative that the researcher incorporate these technologies into the researcher’s operational and clinical processes if the researcher want to achieve improved outcomes for everyone in the healthcare system. The reason for this initiative is that, over the course of the next several years, the advancement of medical technology will continue to proceed at a tremendous speed. This study investigates a wide range of medical equipment, including diagnostic, monitoring, and therapeutic tools, to name just a few of the many distinct categories of medical apparatus. To evaluate the influence that various kinds of medical equipment have on the development and enhancement of health technology practices, the purpose of this study is to investigate the repercussions of the many effects that are created by these practices. It is important to consider how the technology may enhance patient care and clinical decision-making, as well as how simple it is to use and how effectively it handles the integration of data. It is the objective of this research project to assess medical devices based on three criteria: the degree to which they are able to expedite operations, the frequency with which they eliminate medical errors, and the degree to which they properly prescribe medicines. To do this, the researcher have relied on methods that are part of quantitative research. Within the scope of the researcher’s investigation, the researcher used both qualitative and quantitative methods to accomplish this goal. They argue for improved interoperability, real-time monitoring, and individualised treatment; they also stress the strategic use of medical equipment. This approach is a significant advance in the field of health technology techniques
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References
Mbunge, e., batani, j., gaobotse, g., & muchemwa, b. (2022). Virtual healthcare services and digital health technologies deployed during coronavirus disease 2019 (covid-19) pandemic in south africa: a systematic review. Global health journal, 6(2), 102-113.
Ming, j., he, y., yang, y., hu, m., zhao, x., liu, j., ... & chen, y. (2022). Health technology assessment of medical devices: current landscape, challenges, and a way forward. Cost effectiveness and resource allocation, 20(1), 54.
Rahman, a., hossain, m. S., muhammad, g., kundu, d., debnath, t., rahman, m., ... & band, s. S. (2023). Federated learning-based ai approaches in smart healthcare: concepts, taxonomies, challenges and open issues. Cluster computing, 26(4), 2271-2311.
Rehman, a., abbas, s., khan, m. A., ghazal, t. M., adnan, k. M., & mosavi, a. (2022). A secure healthcare 5.0 system based on blockchain technology entangled with federated learning technique. Computers in biology and medicine, 150, 106019.
Shahrubudin, n., koshy, p., alipal, j., kadir, m. H. A., & lee, t. C. (2020). Challenges of 3d printing technology for manufacturing biomedical products: a case study of malaysian manufacturing firms. Heliyon, 6(4).
Soekhai, v., whichello, c., levitan, b., veldwijk, j., pinto, c. A., donkers, b., ... & de bekker-grob, e. W. (2019). Methods for exploring and eliciting patient preferences in the medical product lifecycle: a literature review. Drug discovery today, 24(7), 1324-1331.
Stoumpos, a. I., kitsios, f., & talias, m. A. (2023). Digital transformation in healthcare: technology acceptance and its applications. International journal of environmental research and public health, 20(4), 3407.
Tareq, m. S., rahman, t., hossain, m., & dorrington, p. (2021). Additive manufacturing and the covid-19 challenges: an in-depth study. Journal of manufacturing systems, 60, 787-798.
Viceconti, m., pappalardo, f., rodriguez, b., horner, m., bischoff, j., & tshinanu, f. M. (2021). In silico trials: verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products. Methods, 185, 120-127.
World health organization. (2025). Health technology assessment of medical devices. World health organization.
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