Factors Related to Personal Health Data Sharing: Data Usefulness, Sensitivity and Anonymity.

Using an online survey, we examined the relationships between the perceived usefulness, sensitivity, and anonymity of personal health data and people's willingness to share it with researchers. An analysis of 112 responses showed that people's willingness and perceptions are related to the type of the data, their trust in the data's anonymity, and their personal sociodemographic characteristics. In general, we found that people do not completely trust that their identities remain anonymous when sharing data anonymously with researchers. We also found that they are more willing to share personal health data with researchers if they perceive it as useful for public health research, not sensitive, and if they trust that their identity will remain anonymous after sharing it. We also found that people's age, gender, occupation, and region of residence may be related to their perceptions regarding the sharing of personal health data.

Automatic Classification of Screen Gaze and Dialogue in Doctor-Patient-Computer Interactions: Computational Ethnography Algorithm Development and Validation.

BACKGROUND: The study of doctor-patient-computer interactions is a key research area for examining doctor-patient relationships; however, studying these interactions is costly and obtrusive as researchers usually set up complex mechanisms or intrude on consultations to collect, then manually analyze the data. OBJECTIVE: We aimed to facilitate human-computer and human-human interaction research in clinics by providing a computational ethnography tool: an unobtrusive automatic classifier of screen gaze and dialogue combinations in doctor-patient-computer interactions. METHODS: The classifier's input is video taken by doctors using their computers' internal camera and microphone. By estimating the key points of the doctor's face and the presence of voice activity, we estimate the type of interaction that is taking place. The classification output of each video segment is 1 of 4 interaction classes: (1) screen gaze and dialogue, wherein the doctor is gazing at the computer screen while conversing with the patient; (2) dialogue, wherein the doctor is gazing away from the computer screen while conversing with the patient; (3) screen gaze, wherein the doctor is gazing at the computer screen without conversing with the patient; and (4) other, wherein no screen gaze or dialogue are detected. We evaluated the classifier using 30 minutes of video provided by 5 doctors simulating consultations in their clinics both in semi- and fully inclusive layouts. RESULTS: The classifier achieved an overall accuracy of 0.83, a performance similar to that of a human coder. Similar to the human coder, the classifier was more accurate in fully inclusive layouts than in semi-inclusive layouts. CONCLUSIONS: The proposed classifier can be used by researchers, care providers, designers, medical educators, and others who are interested in exploring and answering questions related to screen gaze and dialogue in doctor-patient-computer interactions.

The Effect of the COVID-19 Pandemic on Physicians' Use and Perception of Telehealth: The Case of Lebanon.

The COVID-19 pandemic forced physicians to quickly adapt and find ways to provide their usual offline services by using online tools. We aimed to understand how physicians adapted to the sudden need for telehealth and if their perception of telehealth changed due to their experience during the COVID-19 pandemic. We conducted an exploratory sequential mixed-methods study. We interviewed five Lebanese physicians and thematically analyzed the interviews. We developed a questionnaire based on the analysis results and administered it online to physicians in Lebanon. In total, 140 responses were collected. We found that, during the COVID-19 pandemic, physicians engaged in more telehealth activities in the realms of telemedicine, public awareness, continuing medical education, research, administration, and teaching. They also expanded their repertoire of information-technology tools. Our results also show that there was a significant shift in the physicians' perceptions, indicating greater openness and willingness to adopt telehealth services. However, a significant amount of skepticism and uncertainty regarding telemedicine remains, especially concerning its efficiency, safety, and the adequacy of existing regulations. Based on our findings, we offer recommendations for health IT policy makers, developers, and researchers, to sustain the continuity of telehealth activities beyond the COVID-19 pandemic.

Visualizing the Cascade Effect of Redesigning Features in an EMR System.

Electronic Medical Record (EMR) systems are complex systems with interdependent features. Redesigning one feature of the system can create a cascade effect affecting the other features. By calculating the cascade effect, the designers can understand how each individual feature could be affected. This understanding allows them to maximize the positive effects and avoid negative consequences of their redesign activities. To understand the cascade effect, the designers can look at their computations' results; a task that becomes more difficult when the number of features grows. To reduce their task load, we propose a tool for visualizing the cascade effect of redesigning features in an EMR system. Our preliminary evaluation with six graduate students shows that visualizing the cascade effect reduces the task load and slightly improves their performance when analyzing the cascade effect. Ways for improving the tool include (i) showing the computation results within the visualization, and (ii) allowing the designers to compare the cascade effect generated by redesigning different features.

Prioritizing Features to Redesign in an EMR System.

Redesigning Electronic Medical Record (EMR) systems is needed to improve their usefulness and usability. For user-centered redesign, designers should consider which EMR features are the most important to the users. However, prioritizing the EMR features is complicated because: (i) EMR systems involve multiple users with different, and sometimes conflicting, priorities and (ii) targeting one feature will affect other features of the EMR system. In this work, we propose a method for prioritizing the features to target when redesigning an EMR system. The method takes into consideration the different priorities of the users and the relationships between the different features. We illustrate the method through a case study on redesigning EMR systems in Japanese antenatal care settings. Our results show the importance of considering the different types of EMR users and the relationships between different EMR features. Designers could use the proposed method as a decision-aid tool in EMR redesign projects.

Understanding the Situated Roles of Electronic Medical Record Systems to Enable Redesign: Mixed Methods Study.

BACKGROUND: Redesigning electronic medical record (EMR) systems is needed to improve their usability and usefulness. Similar to other artifacts, EMR systems can evolve with time and exhibit situated roles. Situated roles refer to the ways in which a system is appropriated by its users, that is, the unintended ways the users engage with, relate to, and perceive the system in its context of use. These situated roles are usually unknown to the designers as they emerge and evolve as a response by the users to a contextual need or constraint. Understanding the system's situated roles can expose the unarticulated needs of the users and enable redesign opportunities. OBJECTIVE: This study aimed to find EMR redesign opportunities by understanding the situated roles of EMR systems in prenatal care settings. METHODS: We conducted a field-based observational study at a Japanese prenatal care clinic. We observed 3 obstetricians and 6 midwives providing prenatal care to 37 pregnant women. We looked at how the EMR system is used during the checkups. We analyzed the observational data following a thematic analysis approach and identified the situated roles of the EMR system. Finally, we administered a survey to 5 obstetricians and 10 midwives to validate our results and understand the attitudes of the prenatal care staff regarding the situated roles of the EMR system. RESULTS: We identified 10 distinct situated roles that EMR systems play in prenatal care settings. Among them, 4 roles were regarded as favorable as most users wanted to experience them more frequently, and 4 roles were regarded as unfavorable as most users wanted to experience them less frequently; 2 ambivalent roles highlighted the providers' reluctance to document sensitive psychosocial information in the EMR and their use of the EMR system as an accomplice to pause communication during the checkups. To improve the usability and usefulness of EMR systems, designers can amplify the favorable roles and minimize the unfavorable roles. Our results also showed that obstetricians and midwives may have different experiences, wants, and priorities regarding the use of the EMR system. CONCLUSIONS: Currently, EMR systems are mainly viewed as tools that support the clinical workflow. Redesigning EMR systems is needed to amplify their roles as communication support tools. Our results provided multiple EMR redesign opportunities to improve the usability and usefulness of EMR systems in prenatal care. Designers can use the results to guide their EMR redesign activities and align them with the users' wants and priorities. The biggest challenge is to redesign EMR systems in a way that amplifies their favorable roles for all the stakeholders concurrently.