Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare最新文献
Pub Date : 2023-03-01DOI: 10.1177/2327857923121027
N. Patel, Arianne Gleiser, Yalda Khashe
This research seeks to build on previous efforts to serve the needs of expectant mothers in terms of providing effective digital healthcare. The first task in accomplishing this was to determine a list of basic features needed to completely satisfy all key performance indicators and needs of a maternal healthcare website. Once this was completed and each category of the established hierarchy had been addressed, the second task could be approached. This was to ensure the platform’s usability by designing sub features with the Nielsen Heuristics in mind. The result of these tasks is a complete framework for an all-in-one platform powerful enough to assist women through pregnancy. This research is intended for doctors, specifically those interested in the evolving virtual landscape, and other healthcare professionals. We believe these people have a significant stake in the development of virtual platforms and welcome their interest and criticism. The significance of this research lies in its future potential: the actualization of the platform. A sound framework for the feature set has been established, so what follows is the implementation, which will prove useful to doctors and expectant mothers alike.
{"title":"Creating A Reliable Digital Maternal Health Platform Using Maslow's Hierarchy and Nielsen Heuristics","authors":"N. Patel, Arianne Gleiser, Yalda Khashe","doi":"10.1177/2327857923121027","DOIUrl":"https://doi.org/10.1177/2327857923121027","url":null,"abstract":"This research seeks to build on previous efforts to serve the needs of expectant mothers in terms of providing effective digital healthcare. The first task in accomplishing this was to determine a list of basic features needed to completely satisfy all key performance indicators and needs of a maternal healthcare website. Once this was completed and each category of the established hierarchy had been addressed, the second task could be approached. This was to ensure the platform’s usability by designing sub features with the Nielsen Heuristics in mind. The result of these tasks is a complete framework for an all-in-one platform powerful enough to assist women through pregnancy. This research is intended for doctors, specifically those interested in the evolving virtual landscape, and other healthcare professionals. We believe these people have a significant stake in the development of virtual platforms and welcome their interest and criticism. The significance of this research lies in its future potential: the actualization of the platform. A sound framework for the feature set has been established, so what follows is the implementation, which will prove useful to doctors and expectant mothers alike.","PeriodicalId":74550,"journal":{"name":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","volume":"12 1","pages":"111 - 116"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45139297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1177/2327857923121023
Joseph M. Gerard, A. Stuebe, Alison Sweeney, Theodore T. Allen, M. Brunette, C. Gill, K. Umstead, E. Patterson
All newborns experience low blood glucose levels when they first initiate carbohydrate metabolism. Some levels remain low, with potential seizures and severe brain injury. Predicting newborns at higher risk is clinically useful because newborns can have their blood sugar raised with breastfeeding, donor milk, formula, or oral dextrose gels. Additionally, informing parents of this higher risk can enhance shared decision-making in the first 48 hours after birth. To address this, we propose three predictive models using binary logistic regression for newborns receiving treatment with oral dextrose gels for hypoglycemia. The first is a parsimonious model, where a high-risk newborn's first blood glucose value is highly predictive of requiring an oral dextrose gel treatment. The second model can be used earlier in the clinical workflow. It is based on the most predictive variables that are also electronically available for all newborns and do not change much in the electronic health record. The third model explores the most predictive variables based on a conceptual model of factors associated with health disparities. These three models are informed from insights gleaned by an exploratory analysis of alternative outcome measures, variables, and threshold cutoffs using a standard heuristic of greedily finding the highest average difference for records on both sides of partitions. We discuss how the dynamics of when data are available during a hospital stay in the postnatal care unit for all patients impact the selection of useful variables for electronically-based decision support. We plan to modify handouts for postnatal care nurses that detail treatment guidance and support shared decision-making. We plan to embed stratified guidance, recommended scripts for high and low-risk cohorts, orientation materials for float and junior nurses, and patient-facing educational materials.
{"title":"Using Machine Learning to Develop a Predictive Model of Infant Hypoglycemia Based on Maternal and Infant Variables in an Electronic Health Record","authors":"Joseph M. Gerard, A. Stuebe, Alison Sweeney, Theodore T. Allen, M. Brunette, C. Gill, K. Umstead, E. Patterson","doi":"10.1177/2327857923121023","DOIUrl":"https://doi.org/10.1177/2327857923121023","url":null,"abstract":"All newborns experience low blood glucose levels when they first initiate carbohydrate metabolism. Some levels remain low, with potential seizures and severe brain injury. Predicting newborns at higher risk is clinically useful because newborns can have their blood sugar raised with breastfeeding, donor milk, formula, or oral dextrose gels. Additionally, informing parents of this higher risk can enhance shared decision-making in the first 48 hours after birth. To address this, we propose three predictive models using binary logistic regression for newborns receiving treatment with oral dextrose gels for hypoglycemia. The first is a parsimonious model, where a high-risk newborn's first blood glucose value is highly predictive of requiring an oral dextrose gel treatment. The second model can be used earlier in the clinical workflow. It is based on the most predictive variables that are also electronically available for all newborns and do not change much in the electronic health record. The third model explores the most predictive variables based on a conceptual model of factors associated with health disparities. These three models are informed from insights gleaned by an exploratory analysis of alternative outcome measures, variables, and threshold cutoffs using a standard heuristic of greedily finding the highest average difference for records on both sides of partitions. We discuss how the dynamics of when data are available during a hospital stay in the postnatal care unit for all patients impact the selection of useful variables for electronically-based decision support. We plan to modify handouts for postnatal care nurses that detail treatment guidance and support shared decision-making. We plan to embed stratified guidance, recommended scripts for high and low-risk cohorts, orientation materials for float and junior nurses, and patient-facing educational materials.","PeriodicalId":74550,"journal":{"name":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","volume":"12 1","pages":"94 - 100"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46569593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1177/2327857923121035
Renee Jones, F. Montalvo, J. Sasser, J. Smither, Daniel S. McConnell
Research on patient experiences within healthcare systems tend to report a variety negative encounters. This can be especially observed in food distribution systems within nursing homes. While nursing homes have various practices and structures that affect a resident’s physical and mental health, the process of food distribution considerably relates to issues of autonomy. Because loss of independence may lead to increased rates of elderly loneliness and depression, mealtimes and the process of food distribution are an integral part of improving a resident’s quality of life and encouraging socialization and self-sufficiency. Moreover, developing patient experiences within food distribution systems, whether centralized or decentralized, will likely improve resident’s autonomy and self-efficacy, reduce frustration, and enhance their overall mental and physical health. The present study utilizes Arhippainen’s User Experience heuristics to identify manners of augmenting patient experiences relating to food distribution in nursing homes by addressing patients’ needs, values, and desires. By utilizing these heuristics, patient experiences and assessments of healthcare systems would become more personalized and fulfilling to the individuals.
{"title":"Applying user Experience Principles to Food Distribution in Nursing Homes","authors":"Renee Jones, F. Montalvo, J. Sasser, J. Smither, Daniel S. McConnell","doi":"10.1177/2327857923121035","DOIUrl":"https://doi.org/10.1177/2327857923121035","url":null,"abstract":"Research on patient experiences within healthcare systems tend to report a variety negative encounters. This can be especially observed in food distribution systems within nursing homes. While nursing homes have various practices and structures that affect a resident’s physical and mental health, the process of food distribution considerably relates to issues of autonomy. Because loss of independence may lead to increased rates of elderly loneliness and depression, mealtimes and the process of food distribution are an integral part of improving a resident’s quality of life and encouraging socialization and self-sufficiency. Moreover, developing patient experiences within food distribution systems, whether centralized or decentralized, will likely improve resident’s autonomy and self-efficacy, reduce frustration, and enhance their overall mental and physical health. The present study utilizes Arhippainen’s User Experience heuristics to identify manners of augmenting patient experiences relating to food distribution in nursing homes by addressing patients’ needs, values, and desires. By utilizing these heuristics, patient experiences and assessments of healthcare systems would become more personalized and fulfilling to the individuals.","PeriodicalId":74550,"journal":{"name":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","volume":"12 1","pages":"151 - 155"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45719975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1177/2327857923121013
Shannon K. T. Bailey, A. Hughes, J. Ray, G. Miller, Samreen Vora, M. Scerbo
As educators seek to optimize the utility of distance simulation for healthcare education, several challenges are present in the design, delivery, and evaluation of simulation-based training (SBT) that align with best practices in human factors. The planned outcome of this panel is a strengthening of the collaboration between human factors/ergonomics (HF/E) and healthcare simulation communities with practical tools that can be used to optimize distance healthcare training. Content proposed as part of the current effort should inform the development of strategic partnerships between simulationists, medical education, and HF/E professionals. We anticipate that the panel will be of interest to scientists and practitioners alike who perform work within the medical simulation space. Although the panel is formed with a focus on the needs identified for distance simulation training, panelists will be asked how human factors techniques can be beneficial to simulation in healthcare more broadly.
{"title":"Human factors’ role in distance healthcare simulation","authors":"Shannon K. T. Bailey, A. Hughes, J. Ray, G. Miller, Samreen Vora, M. Scerbo","doi":"10.1177/2327857923121013","DOIUrl":"https://doi.org/10.1177/2327857923121013","url":null,"abstract":"As educators seek to optimize the utility of distance simulation for healthcare education, several challenges are present in the design, delivery, and evaluation of simulation-based training (SBT) that align with best practices in human factors. The planned outcome of this panel is a strengthening of the collaboration between human factors/ergonomics (HF/E) and healthcare simulation communities with practical tools that can be used to optimize distance healthcare training. Content proposed as part of the current effort should inform the development of strategic partnerships between simulationists, medical education, and HF/E professionals. We anticipate that the panel will be of interest to scientists and practitioners alike who perform work within the medical simulation space. Although the panel is formed with a focus on the needs identified for distance simulation training, panelists will be asked how human factors techniques can be beneficial to simulation in healthcare more broadly.","PeriodicalId":74550,"journal":{"name":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","volume":"12 1","pages":"50 - 52"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45688948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1177/2327857923121029
D. Dicostanzo, A. Ayan, S. Jhawar, T. Allen, E. Patterson
The use of artificial intelligence continues to increase. In healthcare, there has been a recent increase in AI applications to real-time individual patient clinical care, as opposed to population-based research or quality improvement efforts. However, the expertise to evaluate and implement these solutions is limited and often congregates in academic medical centers, creating barriers to adoption for smaller community and rural centers. Lowering the barrier to entry for innovative tools can help address disparities in patient outcomes due to access and other urban/rural contributors. We describe a strategy for evaluating commercially available machine learning models to disseminate lessons learned from developing, validating, and implementing machine learning-based models in clinical care in radiation therapy. In addition, we share an end-to-end data pipeline as open-source code with the tools necessary to identify, extract, organize, and process the data for use in machine-learning applications. We illustrate the application of this data pipeline to the use of brachytherapy to treat female cervical cancer patients. The example will show how we used the proposed pipeline to extract 708 potential participants and applied the developed methods and visualizations to clean the data providing 144 study participants for inclusion in our study. Finally, we discuss the anticipated challenges in implementing machine learning models in commercially available FDA-approved devices and suggest solutions using discrete tools built in different programming languages.
{"title":"Machine Learning Data Pipeline for the Democratization of AI","authors":"D. Dicostanzo, A. Ayan, S. Jhawar, T. Allen, E. Patterson","doi":"10.1177/2327857923121029","DOIUrl":"https://doi.org/10.1177/2327857923121029","url":null,"abstract":"The use of artificial intelligence continues to increase. In healthcare, there has been a recent increase in AI applications to real-time individual patient clinical care, as opposed to population-based research or quality improvement efforts. However, the expertise to evaluate and implement these solutions is limited and often congregates in academic medical centers, creating barriers to adoption for smaller community and rural centers. Lowering the barrier to entry for innovative tools can help address disparities in patient outcomes due to access and other urban/rural contributors. We describe a strategy for evaluating commercially available machine learning models to disseminate lessons learned from developing, validating, and implementing machine learning-based models in clinical care in radiation therapy. In addition, we share an end-to-end data pipeline as open-source code with the tools necessary to identify, extract, organize, and process the data for use in machine-learning applications. We illustrate the application of this data pipeline to the use of brachytherapy to treat female cervical cancer patients. The example will show how we used the proposed pipeline to extract 708 potential participants and applied the developed methods and visualizations to clean the data providing 144 study participants for inclusion in our study. Finally, we discuss the anticipated challenges in implementing machine learning models in commercially available FDA-approved devices and suggest solutions using discrete tools built in different programming languages.","PeriodicalId":74550,"journal":{"name":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","volume":"12 1","pages":"120 - 124"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41799186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1177/2327857923121014
E. Patterson, Jennifer Winner, M. Patterson, Michael F. Rayo, Ellen Deutsch
In this panel, we present perspectives on how to incorporate fundamental concepts in resilience engineering into health care human-in-the-loop simulations. Our panelists have successfully implemented concepts, but also continue to experience challenges with convincing colleagues of the importance and value of doing so for simulations that have other training, technology evaluation, or quality improvement objectives.
{"title":"Incorporating resilience engineering into simulation for health care education and training","authors":"E. Patterson, Jennifer Winner, M. Patterson, Michael F. Rayo, Ellen Deutsch","doi":"10.1177/2327857923121014","DOIUrl":"https://doi.org/10.1177/2327857923121014","url":null,"abstract":"In this panel, we present perspectives on how to incorporate fundamental concepts in resilience engineering into health care human-in-the-loop simulations. Our panelists have successfully implemented concepts, but also continue to experience challenges with convincing colleagues of the importance and value of doing so for simulations that have other training, technology evaluation, or quality improvement objectives.","PeriodicalId":74550,"journal":{"name":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","volume":"12 1","pages":"53 - 56"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43020270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1177/2327857923121032
Kailyn Henderson, Trevor Hall, Nataly Farshait, M. Chignell
Canada is currently facing a critical healthcare worker (HCW) shortage, in part resulting from absenteeism due to healthcare-associated infection (HAI). HCWs are at greater risk of infection and are among the most common sources of HAI transmission. Face touching is a behaviour that HCWs engage in on average 20-23 times per hour, and is one way for HCWs to infect themselves. While personal protective equipment (e.g., face masks) has been found to decrease face touching, the behaviour still occurs. We conducted a literature review on face touching, previously proposed solutions for addressing face touching, and the applications of human factors in mitigating face touching behaviours. We also conducted a pilot study of semi-structured interviews with three HCWs using the Lead User method to understand their needs and explore how best to decrease face touching, which resulted in several suggested interventions for reducing face touching.
{"title":"Applying Human Factors to Reduce Healthcare-Associated Infections Caused by Face Touching","authors":"Kailyn Henderson, Trevor Hall, Nataly Farshait, M. Chignell","doi":"10.1177/2327857923121032","DOIUrl":"https://doi.org/10.1177/2327857923121032","url":null,"abstract":"Canada is currently facing a critical healthcare worker (HCW) shortage, in part resulting from absenteeism due to healthcare-associated infection (HAI). HCWs are at greater risk of infection and are among the most common sources of HAI transmission. Face touching is a behaviour that HCWs engage in on average 20-23 times per hour, and is one way for HCWs to infect themselves. While personal protective equipment (e.g., face masks) has been found to decrease face touching, the behaviour still occurs. We conducted a literature review on face touching, previously proposed solutions for addressing face touching, and the applications of human factors in mitigating face touching behaviours. We also conducted a pilot study of semi-structured interviews with three HCWs using the Lead User method to understand their needs and explore how best to decrease face touching, which resulted in several suggested interventions for reducing face touching.","PeriodicalId":74550,"journal":{"name":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","volume":"12 1","pages":"136 - 141"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43649103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1177/2327857923121030
Prameet Ranjan Jha, Xiaoyu Chen, Xiaomei Wang
Portable medical devices have been playing an important role in improving health outcomes across the socio-economic spectrum. In the recent decades, substantial population have started using such devices to monitor important vital signs. Significant proportion of these users are older patients with chronic diseases, declined physical and/or cognitive capabilities. Furthermore, these portable devices are often used in unguided environments, that can present unpredictable use contexts. In this preliminary study, we conducted usability inspection on five portable medical devices. Cognitive walkthrough followed by Nielson’s ten Usability Heuristic evaluation method were utilized for the purpose of usability inspection. Sixteen usability concerns were uncovered in such evaluation study. We also recorded the elapsed time of measuring vital signs with all five devices on a daily basis in a month. The average total completion time after familiarization (after the first week) was 5.17 minutes. Results suggest that ‘non-expert’, independent users may face challenges when using portable medical devices in home care settings. Further, the study results also indicate that unsatisfactory usability of portable medical devices could pose hinderances in technology adoption among low eHealth literate users.
{"title":"Preliminary Usability Evaluation of Personal Medical Devices towards Better Home Healthcare","authors":"Prameet Ranjan Jha, Xiaoyu Chen, Xiaomei Wang","doi":"10.1177/2327857923121030","DOIUrl":"https://doi.org/10.1177/2327857923121030","url":null,"abstract":"Portable medical devices have been playing an important role in improving health outcomes across the socio-economic spectrum. In the recent decades, substantial population have started using such devices to monitor important vital signs. Significant proportion of these users are older patients with chronic diseases, declined physical and/or cognitive capabilities. Furthermore, these portable devices are often used in unguided environments, that can present unpredictable use contexts. In this preliminary study, we conducted usability inspection on five portable medical devices. Cognitive walkthrough followed by Nielson’s ten Usability Heuristic evaluation method were utilized for the purpose of usability inspection. Sixteen usability concerns were uncovered in such evaluation study. We also recorded the elapsed time of measuring vital signs with all five devices on a daily basis in a month. The average total completion time after familiarization (after the first week) was 5.17 minutes. Results suggest that ‘non-expert’, independent users may face challenges when using portable medical devices in home care settings. Further, the study results also indicate that unsatisfactory usability of portable medical devices could pose hinderances in technology adoption among low eHealth literate users.","PeriodicalId":74550,"journal":{"name":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","volume":"12 1","pages":"125 - 129"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46518744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1177/2327857923121022
Tim Arnold, Helen J. A. Fuller, D. Wilson
This paper describes a set of approaches for evaluating and designing healthcare policy content. These approaches draw from multiple viewpoints in human factors, systems thinking, safety science, and human-centered design (HCD). Six groupings of approaches drawing from different viewpoints are included that address philosophical underpinnings, policy networks and information systems, embedded references to available expertise, customizable modular elements, usability and HCD, and linguistic considerations. For each grouping, an example is provided along with lessons learned and limitations of each approach. Because these approaches emphasize different vantage points and flexibility in design, they can be useful for inquiring into a variety of policy design considerations. Viewing bodies of policy through these perspectives can help us to address questions about how they support healthcare work and how they may work as a system of policies together towards positive outcomes.
{"title":"Weaving viewpoints into healthcare policy","authors":"Tim Arnold, Helen J. A. Fuller, D. Wilson","doi":"10.1177/2327857923121022","DOIUrl":"https://doi.org/10.1177/2327857923121022","url":null,"abstract":"This paper describes a set of approaches for evaluating and designing healthcare policy content. These approaches draw from multiple viewpoints in human factors, systems thinking, safety science, and human-centered design (HCD). Six groupings of approaches drawing from different viewpoints are included that address philosophical underpinnings, policy networks and information systems, embedded references to available expertise, customizable modular elements, usability and HCD, and linguistic considerations. For each grouping, an example is provided along with lessons learned and limitations of each approach. Because these approaches emphasize different vantage points and flexibility in design, they can be useful for inquiring into a variety of policy design considerations. Viewing bodies of policy through these perspectives can help us to address questions about how they support healthcare work and how they may work as a system of policies together towards positive outcomes.","PeriodicalId":74550,"journal":{"name":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","volume":"12 1","pages":"89 - 93"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42137626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1177/2327857923121000
M. Ebnali, Nima Ahmadi, Ehsan Nabiyouni, H. Karimi
When patients are unwilling to speak openly, therapists miss valuable information and may not be able to provide best possible care. This study investigated the idea of human Digital Twins (DT) of patients and therapists as a novel solution to encourage them to speak openly. We proposed a methodology to create highly realistic human DT using computer vision, 3D scanning, Metahumans tool, and Unreal game engine. Based on this methodology, we created two versions of virtual therapeutic session: a) video-based virtual sessions with real human and b) virtual sessions with DT of patients and therapists. Twelve therapists then were asked to evaluate technology acceptance of each virtual session. Participants reported significantly lower trust to virtual sessions with highly realistic digital human compared to video-based one. Findings from this study may provide insights regarding opportunities and challenges of virtual therapy using highly realistic digital human technologies. This work also contributes to the virtual therapeutic research field by proposing an AI-powered methodology to create human DT of patients and therapists. Further studies are needed to provide more validation of the efficiency of this approach in virtual sessions for mental health support.
{"title":"AI-powered Human Digital Twins in Virtual Therapeutic Sessions","authors":"M. Ebnali, Nima Ahmadi, Ehsan Nabiyouni, H. Karimi","doi":"10.1177/2327857923121000","DOIUrl":"https://doi.org/10.1177/2327857923121000","url":null,"abstract":"When patients are unwilling to speak openly, therapists miss valuable information and may not be able to provide best possible care. This study investigated the idea of human Digital Twins (DT) of patients and therapists as a novel solution to encourage them to speak openly. We proposed a methodology to create highly realistic human DT using computer vision, 3D scanning, Metahumans tool, and Unreal game engine. Based on this methodology, we created two versions of virtual therapeutic session: a) video-based virtual sessions with real human and b) virtual sessions with DT of patients and therapists. Twelve therapists then were asked to evaluate technology acceptance of each virtual session. Participants reported significantly lower trust to virtual sessions with highly realistic digital human compared to video-based one. Findings from this study may provide insights regarding opportunities and challenges of virtual therapy using highly realistic digital human technologies. This work also contributes to the virtual therapeutic research field by proposing an AI-powered methodology to create human DT of patients and therapists. Further studies are needed to provide more validation of the efficiency of this approach in virtual sessions for mental health support.","PeriodicalId":74550,"journal":{"name":"Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare","volume":"12 1","pages":"1 - 4"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48191161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare
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