Physicians in hospitals are expected to improve treatment outcome and reduce health care costs. Information systems have been widely adopted in hospitals but not been properly integrated to provide information for decision support. The objective of this research is trying to validate the feasibility of enhancing hospital resource planning system in decision support by utilizing data stored in multiple systems in the hospital with a deep reinforcement learning approach to assist medical practitioner making a more accurate and efficient decision. Following the Design Science Research Method, this research is going to build an artefact to utilize data from electronic health record (EHR) and hospital resource planning (HRP) to provide medical decision support in the emergency department setting.
{"title":"Enhancing Decision Making with Deep Reinforcement Learning in a Context of Novel Coronavirus Outbreak: an Example in Emergency Department","authors":"H. Jiang, William Yu Chung Wang, T. Goh, Jie Zhu","doi":"10.1145/3418094.3418137","DOIUrl":"https://doi.org/10.1145/3418094.3418137","url":null,"abstract":"Physicians in hospitals are expected to improve treatment outcome and reduce health care costs. Information systems have been widely adopted in hospitals but not been properly integrated to provide information for decision support. The objective of this research is trying to validate the feasibility of enhancing hospital resource planning system in decision support by utilizing data stored in multiple systems in the hospital with a deep reinforcement learning approach to assist medical practitioner making a more accurate and efficient decision. Following the Design Science Research Method, this research is going to build an artefact to utilize data from electronic health record (EHR) and hospital resource planning (HRP) to provide medical decision support in the emergency department setting.","PeriodicalId":192804,"journal":{"name":"Proceedings of the 4th International Conference on Medical and Health Informatics","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121981325","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}
Diagnosis-related groups(DRGs) is a payment system that can effectively solve the problem of excessive increases in health care costs. When DRGs was implemented in China, due to the complex medical environment, the design and update cost of traditional rules-based DRGs classifier became extremely high. In this paper, we proposed a low-cost method for designing and updating a DRGs classifier based on machine learning. This method first uses a rule-based classifier to classify cases roughly according to their major clinical features. With the assistance of the decision tree algorithm, this rule-based classifier can be easily designed and updated by experts. Then, an XGBoost(Extreme Gradient Boosting) classifier based on the one-vs-all(OVR) strategy is trained by a large number of cases labeled by experts or existing DRGs classifier, which will classify cases to each DRG. In the experiments, we proved that the method can utilize cases generated and labeled by China Healthcare Security Diagnosis Related Groups(CHS-DRG) classifier to design a classifier with the performance similar to the CHS-DRG classifier.Updated by low cost, the classifier performance can constantly improve after putting into use.
{"title":"A Low-Cost Method for Designing and Updating a DRGs Classifier Based on Machine Learning","authors":"Chenhao Fang, Zhenzhou Shao, Chao Wu","doi":"10.1145/3418094.3418111","DOIUrl":"https://doi.org/10.1145/3418094.3418111","url":null,"abstract":"Diagnosis-related groups(DRGs) is a payment system that can effectively solve the problem of excessive increases in health care costs. When DRGs was implemented in China, due to the complex medical environment, the design and update cost of traditional rules-based DRGs classifier became extremely high. In this paper, we proposed a low-cost method for designing and updating a DRGs classifier based on machine learning. This method first uses a rule-based classifier to classify cases roughly according to their major clinical features. With the assistance of the decision tree algorithm, this rule-based classifier can be easily designed and updated by experts. Then, an XGBoost(Extreme Gradient Boosting) classifier based on the one-vs-all(OVR) strategy is trained by a large number of cases labeled by experts or existing DRGs classifier, which will classify cases to each DRG. In the experiments, we proved that the method can utilize cases generated and labeled by China Healthcare Security Diagnosis Related Groups(CHS-DRG) classifier to design a classifier with the performance similar to the CHS-DRG classifier.Updated by low cost, the classifier performance can constantly improve after putting into use.","PeriodicalId":192804,"journal":{"name":"Proceedings of the 4th International Conference on Medical and Health Informatics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121746196","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}
Since the National Health Insurance system was implemented in Taiwan in 1995, fierce competition in the health care market has led to a shortage of front-line nurses. Such nurses are frequently tasked with an overwhelming amount of complex work, which causes them to experience constant mental stress that elicits anxiety, depression, and negative emotions. Art therapy and horticultural therapy are common stress alleviation methods. Therefore, this study explored the effectiveness of floricultural therapy on relieving the mental stress of nurses. The evaluation grid method of Miryoku engineering was employed in combination with in-depth interviews to compile the attractive factors of floricultural courses. Accordingly, this study examined the experiential cognition and preferences regarding floricultural courses and the perceived therapeutic effect of such courses in highly stressed nurses. The results can be a reference for designing future floricultural therapy courses and promotion.
{"title":"Exploring the Attractive Factors of Floricultural Therapy: A Case Study on Nurses","authors":"Wen-Hui Chen, Chun-Chin Chen, Shu-Ming Wu","doi":"10.1145/3418094.3418139","DOIUrl":"https://doi.org/10.1145/3418094.3418139","url":null,"abstract":"Since the National Health Insurance system was implemented in Taiwan in 1995, fierce competition in the health care market has led to a shortage of front-line nurses. Such nurses are frequently tasked with an overwhelming amount of complex work, which causes them to experience constant mental stress that elicits anxiety, depression, and negative emotions. Art therapy and horticultural therapy are common stress alleviation methods. Therefore, this study explored the effectiveness of floricultural therapy on relieving the mental stress of nurses. The evaluation grid method of Miryoku engineering was employed in combination with in-depth interviews to compile the attractive factors of floricultural courses. Accordingly, this study examined the experiential cognition and preferences regarding floricultural courses and the perceived therapeutic effect of such courses in highly stressed nurses. The results can be a reference for designing future floricultural therapy courses and promotion.","PeriodicalId":192804,"journal":{"name":"Proceedings of the 4th International Conference on Medical and Health Informatics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133953542","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}
M. Ferrer, V. Mancha, Melina I. Chumpitaz, Jaqueline Begazo, M. Chauca
Globally we are going through a difficult situation due to this pandemic due to COVID-19, one of the most effective measures implemented by most governments has been social isolation, which can cause psychosocial risk; The objective of this study is to evaluate the psychosocial well-being of the students of a Peruvian public university during the 90 days of social isolation; the method we have used is descriptive - cross-sectional, with a non-probability sample of 285 university students, who filled out an online survey to detect psychosocial symptoms, using the General Health Questionnaire (GHQ-28); finding that 72.6% of students exposed to a medium-high level of psychosocial risk. In conclusion, an association was found between a medium-high level of psychosocial risk and the variables: cohabiting with people at risk for COVID-19 (Xi2 = 9,661 and p <0.05); present symptoms compatible with COVID-19 19 (Xi2 = 28,957 and p <0.05) and cohabit with COVID-19 patients (Xi2 = 8,803 and p <0.05).
在全球范围内，由于COVID-19的大流行，我们正在经历一个困难的局面，大多数政府实施的最有效措施之一是社会隔离，这可能会导致社会心理风险;这项研究的目的是评估秘鲁一所公立大学学生在90天的社会隔离期间的心理健康状况;我们使用的方法是描述性的-横断面，以285名大学生为非概率样本，他们填写了一份在线调查，以检测心理社会症状，使用一般健康问卷(GHQ-28);发现72.6%的学生暴露于中高水平的社会心理风险。综上所述，中高水平的社会心理风险与以下变量之间存在关联:与COVID-19风险人群同居(Xi2 = 9661, p <0.05);出现与COVID-19相符的症状(Xi2 = 28,957, p <0.05)，并与COVID-19患者同居(Xi2 = 8,803, p <0.05)。
{"title":"Characterization of the Impact of Sars-Cov-2 Pandemic Social Isolation on the Psychosocial Well-Being of Public University Students, Based on the Ghq-28 Scale","authors":"M. Ferrer, V. Mancha, Melina I. Chumpitaz, Jaqueline Begazo, M. Chauca","doi":"10.1145/3418094.3418103","DOIUrl":"https://doi.org/10.1145/3418094.3418103","url":null,"abstract":"Globally we are going through a difficult situation due to this pandemic due to COVID-19, one of the most effective measures implemented by most governments has been social isolation, which can cause psychosocial risk; The objective of this study is to evaluate the psychosocial well-being of the students of a Peruvian public university during the 90 days of social isolation; the method we have used is descriptive - cross-sectional, with a non-probability sample of 285 university students, who filled out an online survey to detect psychosocial symptoms, using the General Health Questionnaire (GHQ-28); finding that 72.6% of students exposed to a medium-high level of psychosocial risk. In conclusion, an association was found between a medium-high level of psychosocial risk and the variables: cohabiting with people at risk for COVID-19 (Xi2 = 9,661 and p <0.05); present symptoms compatible with COVID-19 19 (Xi2 = 28,957 and p <0.05) and cohabit with COVID-19 patients (Xi2 = 8,803 and p <0.05).","PeriodicalId":192804,"journal":{"name":"Proceedings of the 4th International Conference on Medical and Health Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131143892","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}
Sleep is not only very important for physical health but also the mental health of human, that was addressed by many previous studies. Today, with the development of technology, which opens in the application for improving quality of sleep, such as wearable devices, artificial intelligence, neural network. In this study, we applied deep learning (DL) neural networks and smart wearable devices to predict the quality of sleep. The data was collected on students (mean age = 20.79) during 106 days by Fitbit Charge HR™ device. The results showed DL models could predict sleep quality base on physical activities in awake time.
{"title":"Applying Deep Learning for Prediction Sleep Quality from Wearable Data","authors":"Dinh-Van Phan, Chien-Lung Chan, Duc-Khanh Nguyen","doi":"10.1145/3418094.3418114","DOIUrl":"https://doi.org/10.1145/3418094.3418114","url":null,"abstract":"Sleep is not only very important for physical health but also the mental health of human, that was addressed by many previous studies. Today, with the development of technology, which opens in the application for improving quality of sleep, such as wearable devices, artificial intelligence, neural network. In this study, we applied deep learning (DL) neural networks and smart wearable devices to predict the quality of sleep. The data was collected on students (mean age = 20.79) during 106 days by Fitbit Charge HR™ device. The results showed DL models could predict sleep quality base on physical activities in awake time.","PeriodicalId":192804,"journal":{"name":"Proceedings of the 4th International Conference on Medical and Health Informatics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132663351","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}
Madurapperumage A. Erandathi, W. Wang, Michael Mayo
It is vital to estimate and predict the chronological risk rate of individuals of diabetes mellitus and its complications through non-invasive or minimally invasive methods. Data mining and machine learning techniques are applied to health data repositories to achieve this goal. Although past studies have used various combinations of technologies for the assessment and prediction of diabetes and its complications, there is a lack of attention to combining temporal data with a visual representation assessment technique, which can be widely accepted. Further, prediction of risk throughout the lifetime of an individual in a chronological manner by considering their future changes with respect to the characteristics of a similar cohort is something worth contemplating for accurate risk prediction models. We aim to introduce a simple, powerful visualization technique to self-monitoring, which will be highly beneficial in enhancing the health care management sector through empowering self-care management and policymaking. The system will effectively impact the progression of diabetes and its complications by early forecasting the risk without the aid of professional physician knowledge which would help to reduce the burden of the disease while saving the expenditures of diabetes mellitus.
{"title":"Predicting Diabetes Mellitus and its Complications through a Graph-Based Risk Scoring System","authors":"Madurapperumage A. Erandathi, W. Wang, Michael Mayo","doi":"10.1145/3418094.3418115","DOIUrl":"https://doi.org/10.1145/3418094.3418115","url":null,"abstract":"It is vital to estimate and predict the chronological risk rate of individuals of diabetes mellitus and its complications through non-invasive or minimally invasive methods. Data mining and machine learning techniques are applied to health data repositories to achieve this goal. Although past studies have used various combinations of technologies for the assessment and prediction of diabetes and its complications, there is a lack of attention to combining temporal data with a visual representation assessment technique, which can be widely accepted. Further, prediction of risk throughout the lifetime of an individual in a chronological manner by considering their future changes with respect to the characteristics of a similar cohort is something worth contemplating for accurate risk prediction models. We aim to introduce a simple, powerful visualization technique to self-monitoring, which will be highly beneficial in enhancing the health care management sector through empowering self-care management and policymaking. The system will effectively impact the progression of diabetes and its complications by early forecasting the risk without the aid of professional physician knowledge which would help to reduce the burden of the disease while saving the expenditures of diabetes mellitus.","PeriodicalId":192804,"journal":{"name":"Proceedings of the 4th International Conference on Medical and Health Informatics","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124244907","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}
The construction of medical infrastructure is a significant part of urban modernization. The accessibility of medical resources reflects the ability to respond and decentralize control in emergency management of public health emergencies. An improved gravity model is used to evaluate the accessibility of urban medical services based on the hospital and population distribution in a typical metropolis, and conducts a spatial analysis of control areas of urban public health emergency management, so as to identify risk points and propose improvements.
{"title":"Accessibility Analysis of Hospitals Medical Services in Urban Modernization","authors":"Tao Fan, Ying Sun, Xuhe Xie","doi":"10.1145/3418094.3418101","DOIUrl":"https://doi.org/10.1145/3418094.3418101","url":null,"abstract":"The construction of medical infrastructure is a significant part of urban modernization. The accessibility of medical resources reflects the ability to respond and decentralize control in emergency management of public health emergencies. An improved gravity model is used to evaluate the accessibility of urban medical services based on the hospital and population distribution in a typical metropolis, and conducts a spatial analysis of control areas of urban public health emergency management, so as to identify risk points and propose improvements.","PeriodicalId":192804,"journal":{"name":"Proceedings of the 4th International Conference on Medical and Health Informatics","volume":"615 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116076861","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}
The purpose of this study is to discuss the effect of peer education on the anxiety and depression of ostomy patients, so as to help guide and improve clinical nursing work. The method was to select 30 patients who underwent enterostomy surgery and peer education at the Changhai Hospital Affiliated to Shanghai Naval Military Medical University from December 2018 to March 2019, issue questionnaires before and after the patients received peer education, and then compare the changes of patients' anxiety and depression before and after the peer education.The results are shown below. After an ostomy patient received peer education, the anxiety and depression scores were lower than those before peer education, and the difference was statistically significant (p<0.05). It can be concluded that peer education can effectively improve the anxiety and depression of ostomy patients and improve the health status of ostomy patients.
{"title":"Study on the Effect of Peer Education on Anxiety and Depression of Ostomy Patients","authors":"Jiaojiao Gu, Hao Jianling","doi":"10.1145/3418094.3418147","DOIUrl":"https://doi.org/10.1145/3418094.3418147","url":null,"abstract":"The purpose of this study is to discuss the effect of peer education on the anxiety and depression of ostomy patients, so as to help guide and improve clinical nursing work. The method was to select 30 patients who underwent enterostomy surgery and peer education at the Changhai Hospital Affiliated to Shanghai Naval Military Medical University from December 2018 to March 2019, issue questionnaires before and after the patients received peer education, and then compare the changes of patients' anxiety and depression before and after the peer education.The results are shown below. After an ostomy patient received peer education, the anxiety and depression scores were lower than those before peer education, and the difference was statistically significant (p<0.05). It can be concluded that peer education can effectively improve the anxiety and depression of ostomy patients and improve the health status of ostomy patients.","PeriodicalId":192804,"journal":{"name":"Proceedings of the 4th International Conference on Medical and Health Informatics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134487981","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}
Digital security issues such as medical records, diagnostic certificates, medical images, etc. in the medical community have gradually been paid attention to. Nowadays, encrypting and signing electronic medical records including medical imaging records still have to rely on time-consuming exponential computations. Generally, medical image files are often larger and quite different from electronic medical text record file in characteristic, size and format. Recently, the chaotic map operation has been discovered to be superior to modular exponential or scalar multiplications on an elliptic curve. The extended chaotic maps also provide the characteristics of semigroup, commutative property, and the discrete logarithm problem, and thus are suitable for the development of asymmetric cryptosystems. This study develops a signature scheme based on extended chaotic maps that is suitable for medical imaging records. The proposed signature scheme not only provides the properties of digital signatures, including authentication, unforgeability and non-repudiation, but also is more efficient than the related signature mechanism used in medical institutions today.
{"title":"Efficient Signature Scheme Using Extended Chaotic Maps for Medical Imaging Records","authors":"Tian-Fu Lee, Ting-Shun Kung, I-Pin Chang","doi":"10.1145/3418094.3418144","DOIUrl":"https://doi.org/10.1145/3418094.3418144","url":null,"abstract":"Digital security issues such as medical records, diagnostic certificates, medical images, etc. in the medical community have gradually been paid attention to. Nowadays, encrypting and signing electronic medical records including medical imaging records still have to rely on time-consuming exponential computations. Generally, medical image files are often larger and quite different from electronic medical text record file in characteristic, size and format. Recently, the chaotic map operation has been discovered to be superior to modular exponential or scalar multiplications on an elliptic curve. The extended chaotic maps also provide the characteristics of semigroup, commutative property, and the discrete logarithm problem, and thus are suitable for the development of asymmetric cryptosystems. This study develops a signature scheme based on extended chaotic maps that is suitable for medical imaging records. The proposed signature scheme not only provides the properties of digital signatures, including authentication, unforgeability and non-repudiation, but also is more efficient than the related signature mechanism used in medical institutions today.","PeriodicalId":192804,"journal":{"name":"Proceedings of the 4th International Conference on Medical and Health Informatics","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114757745","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}
In the Philippine Health Insurance Company (PHIC) Advisory 04-2016, Primary Care Providers were given until the end of the year to adopt any of the certified electronic medical record providers for submission of patient profiling and patient consultations. With much emphasis on how electronic medical records can pave the way for better health care, this study presents finding on one year usage of a certified electronic medical record in selected areas in the Philippines. The study uses a novel approach in understanding technology adoption through process mining - technique often used in Business Process Analysis (BPA). A total of 8.8 million system-generated usage logs including: Session ID, Timestamp, URL Visited, URL Source, User ID were extracted as part of the dataset. Pre-processing techniques were performed on the data set prior to process mining. In using process mining to understand user behavior based on system-generated usage logs, one must consider: how to identify a case (i.e. how to group activities together), and how to structure your data in a way that allows the inference of real world activities and processes. Using standard adoption models shows us that adoption of early implementation of EMRs remain at basic usage with only a few users fully embracing the technology. However, use of process mining in understanding user behavior depicts actual workflow and presents adoption at a more advanced level.
{"title":"Understanding Adoption of Electronic Medical Records: Application of Process Mining for Health Worker Behavior Analysis","authors":"D. Villamor, Christian E. Pulmano, M. R. Estuar","doi":"10.1145/3418094.3418109","DOIUrl":"https://doi.org/10.1145/3418094.3418109","url":null,"abstract":"In the Philippine Health Insurance Company (PHIC) Advisory 04-2016, Primary Care Providers were given until the end of the year to adopt any of the certified electronic medical record providers for submission of patient profiling and patient consultations. With much emphasis on how electronic medical records can pave the way for better health care, this study presents finding on one year usage of a certified electronic medical record in selected areas in the Philippines. The study uses a novel approach in understanding technology adoption through process mining - technique often used in Business Process Analysis (BPA). A total of 8.8 million system-generated usage logs including: Session ID, Timestamp, URL Visited, URL Source, User ID were extracted as part of the dataset. Pre-processing techniques were performed on the data set prior to process mining. In using process mining to understand user behavior based on system-generated usage logs, one must consider: how to identify a case (i.e. how to group activities together), and how to structure your data in a way that allows the inference of real world activities and processes. Using standard adoption models shows us that adoption of early implementation of EMRs remain at basic usage with only a few users fully embracing the technology. However, use of process mining in understanding user behavior depicts actual workflow and presents adoption at a more advanced level.","PeriodicalId":192804,"journal":{"name":"Proceedings of the 4th International Conference on Medical and Health Informatics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125287187","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}
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