Presentation
HE1 - 3D Technology Application in Pediatric Care: Lessons Learned from Customized Mask Development
DescriptionIntroduction
Medical device customization in healthcare utilizes 3D technologies within its end-to-end functional system to capture the individual complexity of patient forms. Currently, there is no process model in healthcare systems for individualized data capturing, despite this being arguably the most critical stage of customized medical device development (Luczak, Kabel, & Licht, 2006). As 3D scanning technologies become more and more accessible, it is necessary to integrate a seamless data collection process into the complex healthcare system to achieve a vision of customized medical product solutions for pediatric patients. Here, we propose a process that alleviates the burden of trial and error in data capturing for individualized medical devices. Without this process model, medical professionals, human factors engineers, and design teams are left repeating the same trial-and-error process, which can delay treatment and add unnecessary costs to the end product.
This research presents a process model informed by a case study applicable to the broader context of customized medical device development. Subsequently, this research aims to develop a repeatable 3D scanning process that can be used for pediatric patients in a hospital setting. The development of a repeatable scanning process hinges on a systematic, human factors approach of process modeling to acquire individualized data and apply it to products.
While 3D technologies offer a unique design opportunity for patients in a clinical environment, it is up to each provider to facilitate this process. 3D scanners and printers are becoming more common for various applications, from diagnosis to manufacturing personalized medical devices or implants. However, these technologies have not been widely implemented for pediatric patients due to specific barriers to pediatric medical device development, including clinical, technical, regulatory, and financial barriers (Espinoza, Shah et al., 2022). Notable challenges associated with 3D technologies include the inaccessibility of 3D data-capturing technologies, capturing high-quality data for children, and navigating data-capturing processes in the patient’s environment. The benefit of our process is that its flexibility allows for bringing the data-capturing process to the patient rather than depending on a specific environment for retrieving the patient's anatomical data. Our process can be customized to the provider's environment, eliminating the extraneous costs and treatment delays of a trial-and-error approach.
The primary considerations for creating a repeatable 3D scanning process for pediatric patients include portable technology, high-quality data output, the ability to manage unpredictable patient behavior, and the ability to adapt the scanning process to the patient’s environment (Amirav, Luder, Halamish, et al., 2014; Bockstedte, Xepapadeas, Spintzyk, et al., 2022; Kamath, Kamath, Ekici, et al., 2014; Willox, Metherall, Jeays-Ward, et al., 2020). Utilizing the redesign of a pediatric CPAP mask as a case study, a 3D scanning procedure for pediatric patients in a hospital environment was developed. After IRB approval, 12 pediatric patients ages 6 weeks to 17 years were scanned in a hospital setting. Based on the lessons learned during the scanning of the initial patients, scanning tools were developed, and a process model was created with stakeholder collaboration. The process presented in this paper improved the reliability and usability of 3D data captured in a Pediatric Intensive Care Unit (PICU) setting and enables future customized products to be developed and tested using this broadly applicable process model.
Knowledge Advancement
The objective of this research was to provide a process model recommendation on the utilization of 3D data-capturing technologies applicable beyond the presented case study of a dynamic, pediatric hospital setting. Capturing 3D data is a critical aspect of customized medical device development, with challenges that we hope can become foreseen using the human factors approach of process modeling. In the future, we hope to aid providers in the implementation of 3D data capturing technologies to develop customized medical devices, reducing treatment times and costs. The target audience for this research includes the stakeholders in the healthcare system relating to customized medical device development. This includes health providers in addition to human factors engineers, designers, and developers of medical devices. By furthering the development of 3D data-capturing methodology, manufacturing customized devices can become more accessible for patients that need them. With the advancement of new technologies such as handheld scanners with the ability to produce high-quality anthropometric data, it is now possible to easily scan patients in a variety of settings. By utilizing human factors principles to address these challenges, we hope to aid in future customized device development processes that rely on 3D data capturing technologies.
References
Amirav, I., Luder, A. S., Halamish, A., et al. (2014). Design of aerosol face masks for children using computerized 3D face analysis. Journal of aerosol medicine and pulmonary drug delivery, 27(4), 272–278. https://doi.org/10.1089/jamp.2013.1069
Bockstedte, M., Xepapadeas, A. B., Spintzyk, S., et al. (2022). Development of Personalized Non-Invasive Ventilation Interfaces for Neonatal and Pediatric Application Using Additive Manufacturing. Journal of personalized medicine, 12(4), 604. https://doi.org/10.3390/jpm12040604
Espinoza, J., Shah, P., Nagendra, G., et al. (2022). Pediatric Medical Device Development and Regulation: Current State, Barriers, and Opportunities. Pediatrics, 149(5). https://doi.org/10.1542/peds.2021-053390
Kamath, A. A., Kamath, M. J., Ekici, S., et al. (2014). Workflow to develop 3D designed personalized neonatal CPAP masks using iPhone structured light facial scanning. Journal of Aerosol Medicine and Pulmonary Drug Delivery, 27(4), 272-278. http://doi.org/10.1089/jamp.2013.1069
Luczak, H., Kabel, T., & Licht, T. (2006). Task design and motivation. In G., Salvendy (Ed.), Handbook of Human Factors and Ergonomics (3rd ed., pp. 384-427). John Wiley & Sons.
Willox, M., Metherall, P., Jeays-Ward, K., et al. (2020). Custom-made 3D printed masks for children using non-invasive ventilation: a feasibility study of production method and testing of outcomes in adult volunteers. Journal of Medical Engineering & Technology, 44(5), 213-223. https://doi.org/10.1080/03091902.2020.1769759
Medical device customization in healthcare utilizes 3D technologies within its end-to-end functional system to capture the individual complexity of patient forms. Currently, there is no process model in healthcare systems for individualized data capturing, despite this being arguably the most critical stage of customized medical device development (Luczak, Kabel, & Licht, 2006). As 3D scanning technologies become more and more accessible, it is necessary to integrate a seamless data collection process into the complex healthcare system to achieve a vision of customized medical product solutions for pediatric patients. Here, we propose a process that alleviates the burden of trial and error in data capturing for individualized medical devices. Without this process model, medical professionals, human factors engineers, and design teams are left repeating the same trial-and-error process, which can delay treatment and add unnecessary costs to the end product.
This research presents a process model informed by a case study applicable to the broader context of customized medical device development. Subsequently, this research aims to develop a repeatable 3D scanning process that can be used for pediatric patients in a hospital setting. The development of a repeatable scanning process hinges on a systematic, human factors approach of process modeling to acquire individualized data and apply it to products.
While 3D technologies offer a unique design opportunity for patients in a clinical environment, it is up to each provider to facilitate this process. 3D scanners and printers are becoming more common for various applications, from diagnosis to manufacturing personalized medical devices or implants. However, these technologies have not been widely implemented for pediatric patients due to specific barriers to pediatric medical device development, including clinical, technical, regulatory, and financial barriers (Espinoza, Shah et al., 2022). Notable challenges associated with 3D technologies include the inaccessibility of 3D data-capturing technologies, capturing high-quality data for children, and navigating data-capturing processes in the patient’s environment. The benefit of our process is that its flexibility allows for bringing the data-capturing process to the patient rather than depending on a specific environment for retrieving the patient's anatomical data. Our process can be customized to the provider's environment, eliminating the extraneous costs and treatment delays of a trial-and-error approach.
The primary considerations for creating a repeatable 3D scanning process for pediatric patients include portable technology, high-quality data output, the ability to manage unpredictable patient behavior, and the ability to adapt the scanning process to the patient’s environment (Amirav, Luder, Halamish, et al., 2014; Bockstedte, Xepapadeas, Spintzyk, et al., 2022; Kamath, Kamath, Ekici, et al., 2014; Willox, Metherall, Jeays-Ward, et al., 2020). Utilizing the redesign of a pediatric CPAP mask as a case study, a 3D scanning procedure for pediatric patients in a hospital environment was developed. After IRB approval, 12 pediatric patients ages 6 weeks to 17 years were scanned in a hospital setting. Based on the lessons learned during the scanning of the initial patients, scanning tools were developed, and a process model was created with stakeholder collaboration. The process presented in this paper improved the reliability and usability of 3D data captured in a Pediatric Intensive Care Unit (PICU) setting and enables future customized products to be developed and tested using this broadly applicable process model.
Knowledge Advancement
The objective of this research was to provide a process model recommendation on the utilization of 3D data-capturing technologies applicable beyond the presented case study of a dynamic, pediatric hospital setting. Capturing 3D data is a critical aspect of customized medical device development, with challenges that we hope can become foreseen using the human factors approach of process modeling. In the future, we hope to aid providers in the implementation of 3D data capturing technologies to develop customized medical devices, reducing treatment times and costs. The target audience for this research includes the stakeholders in the healthcare system relating to customized medical device development. This includes health providers in addition to human factors engineers, designers, and developers of medical devices. By furthering the development of 3D data-capturing methodology, manufacturing customized devices can become more accessible for patients that need them. With the advancement of new technologies such as handheld scanners with the ability to produce high-quality anthropometric data, it is now possible to easily scan patients in a variety of settings. By utilizing human factors principles to address these challenges, we hope to aid in future customized device development processes that rely on 3D data capturing technologies.
References
Amirav, I., Luder, A. S., Halamish, A., et al. (2014). Design of aerosol face masks for children using computerized 3D face analysis. Journal of aerosol medicine and pulmonary drug delivery, 27(4), 272–278. https://doi.org/10.1089/jamp.2013.1069
Bockstedte, M., Xepapadeas, A. B., Spintzyk, S., et al. (2022). Development of Personalized Non-Invasive Ventilation Interfaces for Neonatal and Pediatric Application Using Additive Manufacturing. Journal of personalized medicine, 12(4), 604. https://doi.org/10.3390/jpm12040604
Espinoza, J., Shah, P., Nagendra, G., et al. (2022). Pediatric Medical Device Development and Regulation: Current State, Barriers, and Opportunities. Pediatrics, 149(5). https://doi.org/10.1542/peds.2021-053390
Kamath, A. A., Kamath, M. J., Ekici, S., et al. (2014). Workflow to develop 3D designed personalized neonatal CPAP masks using iPhone structured light facial scanning. Journal of Aerosol Medicine and Pulmonary Drug Delivery, 27(4), 272-278. http://doi.org/10.1089/jamp.2013.1069
Luczak, H., Kabel, T., & Licht, T. (2006). Task design and motivation. In G., Salvendy (Ed.), Handbook of Human Factors and Ergonomics (3rd ed., pp. 384-427). John Wiley & Sons.
Willox, M., Metherall, P., Jeays-Ward, K., et al. (2020). Custom-made 3D printed masks for children using non-invasive ventilation: a feasibility study of production method and testing of outcomes in adult volunteers. Journal of Medical Engineering & Technology, 44(5), 213-223. https://doi.org/10.1080/03091902.2020.1769759
Event Type
Poster Presentation
TimeMonday, March 254:45pm - 6:15pm CDT
LocationSalon C
Digital Health
Simulation and Education
Hospital Environments
Medical and Drug Delivery Devices
Patient Safety Research and Initiatives