Beyond Health Literacy

Park, Sun Young; Chen, Yunan; Raj, Shriti

doi:10.1145/2998181.2998357

Cited by 26 publications

(3 citation statements)

References 34 publications

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“…For instance, patients often have difficulties contacting their physicians and, thus, are not able to receive timely explanations of their laboratory test results [25]. Even during clinical visits, various barriers may hinder effective communication between patients and their physicians and, consequently, the questions the patients have are sometimes left unanswered [26][27][28].…”

Section: Patient-centered Communication Of Laboratory Test Resultsmentioning

confidence: 99%

User-Centered System Design for Communicating Clinical Laboratory Test Results: Design and Evaluation Study

Zhang¹,

Kmoth²,

Luo³

et al. 2021

JMIR Hum Factors

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Background Personal clinical data, such as laboratory test results, are increasingly being made available to patients via patient portals. However, laboratory test results are presented in a way that is difficult for patients to interpret and use. Furthermore, the indications of laboratory test results may vary among patients with different characteristics and from different medical contexts. To date, little is known about how to design patient-centered technology to facilitate the interpretation of laboratory test results. Objective The aim of this study is to explore design considerations for supporting patient-centered communication and comprehension of laboratory test results, as well as discussions between patients and health care providers. Methods We conducted a user-centered, multicomponent design research consisting of user studies, an iterative prototype design, and pilot user evaluations, to explore design concepts and considerations that are useful for supporting patients in not only viewing but also interpreting and acting upon laboratory test results. Results The user study results informed the iterative design of a system prototype, which had several interactive features: using graphical representations and clear takeaway messages to convey the concerning nature of the results; enabling users to annotate laboratory test reports; clarifying medical jargon using nontechnical verbiage and allowing users to interact with the medical terms (eg, saving, favoriting, or sorting); and providing pertinent and reliable information to help patients comprehend test results within their medical context. The results of a pilot user evaluation with 8 patients showed that the new patient-facing system was perceived as useful in not only presenting laboratory test results to patients in a meaningful way but also facilitating in situ patient-provider interactions. Conclusions We draw on our findings to discuss design implications for supporting patient-centered communication of laboratory test results and how to make technology support informative, trustworthy, and empathetic.

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Section: Patient-centered Communication Of Laboratory Test Resultsmentioning

confidence: 99%

User-Centered System Design for Communicating Clinical Laboratory Test Results: Design and Evaluation Study

Zhang¹,

Kmoth²,

Luo³

et al. 2021

JMIR Hum Factors

View full text Add to dashboard Cite

show abstract

“…As ED medical activities often depend on previous activities, the information patients need or want is usually delayed. Without having relevant information during the ED process, patients may experience communication challenges with ED providers, such as different perceptions of what information is critical to ED care [19]. Hence, as our participants suggested, interventions should provide ED patients with optimized information relevant to the current step of the care process or options to control the amount and timing of information they expect to receive.…”

Section: Design Implications For Patient-centered Interventions In Edmentioning

confidence: 99%

Designing Patient-Centered Interventions for Emergency Care: Participatory Design Study with Patients (Preprint)

Seo,

Jain,

et al. 2024

Preprint

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BACKGROUND Emergency departments (EDs) are high-pressure environments where a diagnosis is made in a resource-constrained context. These environments also require complicated interactions between patients, caregivers, and healthcare providers to make timely diagnoses. EDs, in consequence, predispose to suboptimal diagnostic outcomes, leading to potential errors and subsequent patient harm. Various interventions have been designed to improve the ED diagnostic process and patient safety. However, designing patient-centered interventions is challenging due to limited opportunities for engaging patients in intervention design processes. OBJECTIVE This study aims to invite ED patients to participatory design sessions, identify their challenges and needs during ED visits, and present design guidelines for patient-centered interventions. METHODS We conducted a participatory design study with ED patients to design patient-centered interventions to improve diagnostic safety. In total, 36 ED patients or caregivers participated in eight design sessions. We presented ten intervention ideas as storyboards to the participants. Through storyboards describing the use cases of each intervention idea, we assessed the participants’ needs and challenges during the ED care process. We also facilitated co-design activities with them to improve the intervention designs. We audio- and video-recorded the design sessions. We then analyzed session transcripts, field notes, and design sketches. RESULTS Based on ED patients’ feedback and evaluation of our intervention designs, we found the three most preferred intervention ideas that address the common challenges that ED patients experience. We also identified four themes of ED patients' needs: feeling of inclusion in the ED care process, access to sources for patient comprehension of medical information, need to address patient anxiety related to information overload and privacy concerns, and ensuring continuity in care and information. We interpreted them as insights for designing technological interventions for ED patients. Hence, based on the findings, we present five considerations for designing better patient-centered interventions in the ED care process: 1) technology-based interventions should address patients’ dynamic needs to promote continuity in care, 2) interventions should consider the amount and timing of information that patients receive, 3) interventions should empower patients to be more active for better patient safety and care quality, 4) interventions should optimize human resources, depending on patient’s needs, and 5) interventions should be designed with the consideration of patients’ perspectives on implementation. CONCLUSIONS This study provides unique insights for designing technological interventions to support ED diagnostic processes. By inviting ED patients into the design process, we present unique insights into the diagnostic process and design considerations for designing novel technological interventions to enhance patient safety. INTERNATIONAL REGISTERED REPORT RR2-10.2196/55357

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“…Researchers studying doctor-patient-computer interactions need to identify which interactions are taking place during the consultations. To do so, researchers have used qualitative methods such as taking notes during live observations [31,37], conducting interviews [37,38], administering questionnaires [39], and sending unannounced standardized patients to collect information [40] and quantitative methods such as videotaping consultations and manually coding the videos [36,41,42] or setting up complex mechanisms for automatic data collection and analysis inside the clinics [43]. Methods that include direct observations are likely to generate more accurate data than clinician or patient reports; however, direct observations are costly in terms of time and human resources, may be obtrusive in a clinical environment, and may cause the participants to knowingly or unknowingly alter their behavior (because of the presence of an observer) [44].…”

Section: Computational Ethnography Inside Clinicsmentioning

confidence: 99%

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

et al. 2021

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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.

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Beyond Health Literacy

Cited by 26 publications

References 34 publications

User-Centered System Design for Communicating Clinical Laboratory Test Results: Design and Evaluation Study

User-Centered System Design for Communicating Clinical Laboratory Test Results: Design and Evaluation Study

Designing Patient-Centered Interventions for Emergency Care: Participatory Design Study with Patients (Preprint)

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

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