Approaches for Implementing App-Based Digital Treatments for Drug Use Disorders Into Primary Care: A Qualitative, User-Centered Design Study of Patient Perspectives.

BACKGROUND: Digital interventions, such as websites and smartphone apps, can be effective in treating drug use disorders (DUDs). However, their implementation in primary care is hindered, in part, by a lack of knowledge on how patients might like these treatments delivered to them. OBJECTIVE: This study aims to increase the understanding of how patients with DUDs prefer to receive app-based treatments to inform the implementation of these treatments in primary care. METHODS: The methods of user-centered design were combined with qualitative research methods to inform the design of workflows for offering app-based treatments in primary care. Adult patients (n=14) with past-year cannabis, stimulant, or opioid use disorder from 5 primary care clinics of Kaiser Permanente Washington in the Seattle area participated in this study. Semistructured interviews were recorded, transcribed, and analyzed using qualitative template analysis. The coding scheme included deductive codes based on interview topics, which primarily focused on workflow design. Inductive codes emerged from the data. RESULTS: Participants wanted to learn about apps during visits where drug use was discussed and felt that app-related conversations should be incorporated into the existing care whenever possible, as opposed to creating new health care visits to facilitate the use of the app. Nearly all participants preferred receiving clinician support for using apps over using them without support. They desired a trusting, supportive relationship with a clinician who could guide them as they used the app. Participants wanted follow-up support via phone calls or secure messaging because these modes of communication were perceived as a convenient and low burden (eg, no copays or appointment travel). CONCLUSIONS: A user-centered implementation of treatment apps for DUDs in primary care will require health systems to design workflows that account for patients' needs for structure, support in and outside of visits, and desire for convenience.

Capturing the patient voice: implementing patient-reported outcomes across the health system.

PURPOSE: Supporting the capture and use of patient-reported outcomes (PROs) at the point-of-care enriches information about important clinical and quality of life outcomes. Yet the ability to scale PROs across healthcare systems has been limited by knowledge gaps around how to manage the diversity of PRO uses and leverage health information technology. In this study, we report learnings and practice insights from UW Medicine's practice transformation efforts to incorporate patient voice into multiple areas of care. METHODS: Using a participatory, action research approach, we engaged with UW Medicine clinical and administrative stakeholders experienced with PRO implementation to inventory PRO implementations across the health system, characterize common clinical uses for PROs, and develop recommendations for system-wide governance and implementation of PROs. RESULTS: We identified a wide breadth of PRO implementations (n = 14) in practice and found that nearly half (47%) of employed PRO measures captured shared clinical domains (e.g., depression). We developed three vignettes (use cases) that illustrate how users interact with PROs, characterize common ways PRO implementations support clinical care across the health system (1) Preventive care, (2) Chronic/Specialty care, and (3) Surgical/Interventional care), and elucidate opportunities to enhance efficient PRO implementations through system-level standards and governance. CONCLUSIONS: Practice transformation efforts increasingly require integration of the patient voice into clinical care, often through the use of PROs. Learnings from our work highlight the importance of proactively considering how PROs will be used across the layers of healthcare organizations to optimize the design and governance of PROs.

Roles and Functions of Community Health Workers in Primary Care.

Community health workers have potential to enhance primary care access and quality, but remain underutilized. To provide guidance on their integration, we characterized roles and functions of community health workers in primary care through a literature review and synthesis. Analysis of 30 studies identified 12 functions (ie, care coordination, health coaching, social support, health assessment, resource linking, case management, medication management, remote care, follow-up, administration, health education, and literacy support) and 3 prominent roles representing clusters of functions: clinical services, community resource connections, and health education and coaching. We discuss implications for community health worker training and clinical support in primary care.

Understanding What Is Most Important to Individuals with Multiple Chronic Conditions: A Qualitative Study of Patients' Perspectives.

BACKGROUND: To improve care for individuals living with multiple chronic conditions, patients and providers must align care planning with what is most important to patients in their daily lives. We have a limited understanding of how to effectively encourage communication about patients' personal values during clinical care. OBJECTIVE: To identify what patients with multiple chronic conditions describe as most important to their well-being and health. DESIGN: We interviewed individuals with multiple chronic conditions in their homes and analyzed results qualitatively, guided by grounded theory. PARTICIPANTS: A total of 31 patients (mean age 68.7 years) participated in the study, 19 of which included the participation of family members. Participants were from Kaiser Permanente Washington, an integrated health care system in Washington state. APPROACH: Qualitative analysis of home visits, which consisted of semi-structured interviews aided by photo elicitation. KEY RESULTS: Analysis revealed six domains of what patients described as most important for their well-being and health: principles, relationships, emotions, activities, abilities, and possessions. Personal values were interrelated and rarely expressed as individual values in isolation. CONCLUSIONS: The domains describe the range and types of personal values multimorbid older adults deem important to well-being and health. Understanding patients' personal values across these domains may be useful for providers when developing, sharing, and following up on care plans.

"How Did We Get Here?": Topic Drift in Online Health Discussions.

BACKGROUND: Patients increasingly use online health communities to exchange health information and peer support. During the progression of health discussions, a change of topic-topic drift-can occur. Topic drift is a frequent phenomenon linked to incoherence and frustration in online communities and other forms of computer-mediated communication. For sensitive topics, such as health, such drift could have life-altering repercussions, yet topic drift has not been studied in these contexts. OBJECTIVE: Our goals were to understand topic drift in online health communities and then to develop and evaluate an automated approach to detect both topic drift and efforts of community members to counteract such drift. METHODS: We manually analyzed 721 posts from 184 threads from 7 online health communities within WebMD to understand topic drift, members' reaction towards topic drift, and their efforts to counteract topic drift. Then, we developed an automated approach to detect topic drift and counteraction efforts. We detected topic drift by calculating cosine similarity between 229,156 posts from 37,805 threads and measuring change of cosine similarity scores from the threads' first posts to their sequential posts. Using a similar approach, we detected counteractions to topic drift in threads by focusing on the irregular increase of similarity scores compared to the previous post in threads. Finally, we evaluated the performance of our automated approaches to detect topic drift and counteracting efforts by using a manually developed gold standard. RESULTS: Our qualitative analyses revealed that in threads of online health communities, topics change gradually, but usually stay within the global frame of topics for the specific community. Members showed frustration when topic drift occurred in the middle of threads but reacted positively to off-topic stories shared as separate threads. Although all types of members helped to counteract topic drift, original posters provided the most effort to keep threads on topic. Cosine similarity scores show promise for automatically detecting topical changes in online health discussions. In our manual evaluation, we achieved an F1 score of .71 and .73 for detecting topic drift and counteracting efforts to stay on topic, respectively. CONCLUSIONS: Our analyses expand our understanding of topic drift in a health context and highlight practical implications, such as promoting off-topic discussions as a function of building rapport in online health communities. Furthermore, the quantitative findings suggest that an automated tool could help detect topic drift, support counteraction efforts to bring the conversation back on topic, and improve communication in these important communities. Findings from this study have the potential to reduce topic drift and improve online health community members' experience of computer-mediated communication. Improved communication could enhance the personal health management of members who seek essential information and support during times of difficulty.

Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text.

BACKGROUND: The prevalence and value of patient-generated health text are increasing, but processing such text remains problematic. Although existing biomedical natural language processing (NLP) tools are appealing, most were developed to process clinician- or researcher-generated text, such as clinical notes or journal articles. In addition to being constructed for different types of text, other challenges of using existing NLP include constantly changing technologies, source vocabularies, and characteristics of text. These continuously evolving challenges warrant the need for applying low-cost systematic assessment. However, the primarily accepted evaluation method in NLP, manual annotation, requires tremendous effort and time. OBJECTIVE: The primary objective of this study is to explore an alternative approach-using low-cost, automated methods to detect failures (eg, incorrect boundaries, missed terms, mismapped concepts) when processing patient-generated text with existing biomedical NLP tools. We first characterize common failures that NLP tools can make in processing online community text. We then demonstrate the feasibility of our automated approach in detecting these common failures using one of the most popular biomedical NLP tools, MetaMap. METHODS: Using 9657 posts from an online cancer community, we explored our automated failure detection approach in two steps: (1) to characterize the failure types, we first manually reviewed MetaMap's commonly occurring failures, grouped the inaccurate mappings into failure types, and then identified causes of the failures through iterative rounds of manual review using open coding, and (2) to automatically detect these failure types, we then explored combinations of existing NLP techniques and dictionary-based matching for each failure cause. Finally, we manually evaluated the automatically detected failures. RESULTS: From our manual review, we characterized three types of failure: (1) boundary failures, (2) missed term failures, and (3) word ambiguity failures. Within these three failure types, we discovered 12 causes of inaccurate mappings of concepts. We used automated methods to detect almost half of 383,572 MetaMap's mappings as problematic. Word sense ambiguity failure was the most widely occurring, comprising 82.22% of failures. Boundary failure was the second most frequent, amounting to 15.90% of failures, while missed term failures were the least common, making up 1.88% of failures. The automated failure detection achieved precision, recall, accuracy, and F1 score of 83.00%, 92.57%, 88.17%, and 87.52%, respectively. CONCLUSIONS: We illustrate the challenges of processing patient-generated online health community text and characterize failures of NLP tools on this patient-generated health text, demonstrating the feasibility of our low-cost approach to automatically detect those failures. Our approach shows the potential for scalable and effective solutions to automatically assess the constantly evolving NLP tools and source vocabularies to process patient-generated text.

Improving Vaccine Equity: How Community Engagement and Informatics Facilitate Health System Outreach to Underrepresented Groups.

BACKGROUND: Given the inequities in access to health care resources like COVID-19 vaccination, health systems should carefully consider how to reach underrepresented groups. Reflecting on vaccine rollout efforts holds insight on the role of community engagement and informatics support in promoting health equity. OBJECTIVES: This study aimed to assess the effectiveness of four outreach strategies deployed by University of Washington (UW) Medicine in improving vaccine equity over traditional vaccine scheduling online or by phone, we report on appointment scheduling and completion of appointments (i.e., vaccine administration) through (1) automated outreach to individuals from underrepresented groups, (2) temporary "pop-up" clinics in neighborhoods highly impacted by COVID-19, (3) vulnerable population clinics, and (4) mobile vaccine vans. METHODS: We conducted a 6-month retrospective analysis of electronic health records (EHR) to describe the sociodemographic characteristics of individuals who scheduled appointments using the outreach strategies and characteristics associated with a greater likelihood of vaccine administration based on appointment completion. To help explain trends in the EHR data, we engaged 10 health system leaders and staff who spearheaded the outreach strategies in follow-up conversations to identify qualitative insights into what worked and why. RESULTS: Compared with traditional scheduling, all outreach strategies except vulnerable population clinics had higher vaccine appointment completion rates, including automated outreach (N = 3,734 [94.7%], p < 0.001), pop-up clinics (N = 4,391 [96.0%], p < 0.001), and mobile vans (N = 4,198 [99.1%], p < 0.001); and lower cancellation rates, including automated outreach (N = 166 [1.1%], p < 0.001), pop-up clinics (N = 155 [0.6%], p < 0.001), and mobile vans (N = 0 [0%], p < 0.001). Qualitative insights emphasized ongoing community partnerships and information resources in successful outreach. CONCLUSION: Vaccine equity outreach strategies improved the proportion of patients who scheduled and completed vaccination appointments among populations disproportionately impacted by COVID-19. Engaging community partners and equity-focused informatics tools can facilitate outreach. Lessons from these outreach strategies carry practical implications for health systems to amplify their health equity efforts.

Qualitative Analysis of Perspectives on Lung Transplant among People with Cystic Fibrosis.

Rationale: Lung transplant (LTx) is a potentially lifesaving treatment option for individuals with advanced cystic fibrosis (CF), but more people with CF (PwCF) and advanced lung disease die each year than undergo transplant in the United States. Little is known about these individuals' LTx information needs and factors influencing their decision-making process related to transplant. Objectives: To examine PwCF's experiences with and preferences for provision of LTx information and to identify transplant information needs that CF clinicians are well positioned to address. Methods: We performed semistructured qualitative interviews in two separate cohorts: PwCF without LTx and PwCF with LTx between July 2019 and June 2020. Questions focused on awareness and knowledge about LTx, perspectives related to communication about transplant in the CF clinic, and experiences with LTx. Thematic analysis was used to organize the qualitative data. Exemplar quotes were chosen to llustrate domains that emerged pertaining to the research objectives. Results: Fifty-five PwCF, including 35 without LTx and 20 with LTx, participated. One-third of PwCF without LTx had normal or near-normal lung function. Key common domains among PwCF with and without LTx were identified, including information needs, connections with LTx recipients, and conversations with CF clinicians. For PwCF with and without transplant, concrete information needs were identified: success or survival, social support, surgery, recovery/pain, and quality of life post-transplant. The importance of connecting with LTx recipients to hear their stories and experiences was emphasized by both PwCF with and without transplant. Important considerations for timing and content of discussions with CF clinicians were identified, including having information presented early (before LTx referral is needed) and in limited detail at first. PwCF without LTx wanted to understand how LTx was relevant to them, with a focus on the unique experience of CF. PwCF with LTx emphasized the need for a centralized resource for LTx information. Conclusions: The findings provide content areas for CF clinicians to focus on as they proactively initiate conversations about LTx and support the development of tools to aid in discussions about LTx for PwCF.

Validity and reliability of a smartphone application for the assessment of penile deformity in Peyronie's disease.

INTRODUCTION: Available methods to evaluate men with Peyronie's disease (PD) are limited by the inability to accurately and reproducibly measure penile deformity. AIM.: The study aims to evaluate the performance of a smartphone application for the measurement of penile curvature and narrowing. METHODS: A smartphone application, the University of Washington Peyronie's Examination Network (UWPEN), was developed for this purpose. To assess penile curvature, 15 single cylinders of malleable penile prostheses were molded to varying curvature angles. Three blinded observers nonsequentially measured the angle of curvature for each prosthetic cylinder using a protractor, goniometer, and UWPEN. To assess girth narrowing, six clay models of the penile shaft were constructed to represent conditions of normal, partial hourglass, circumferential hourglass, and pencil narrowing. Girth was measured using a ruler and UWPEN by the same blinded observers. MAIN OUTCOME MEASURES: Statistical analyses compared intertest, interobserver, and intraobserver reliability using the interclass correlation coefficient (ICC). An ICC above 0.75 indicates excellent reproducibility among measurements. RESULTS: Intertest reliability for angle measurements yielded an ICC for the three methods of 1.000. Separately, the ICC for UWPEN vs. the goniometer and protractor was 0.999 and 0.999, respectively. The interobserver ICC for UWPEN, goniometer, and protractor was 0.998, 0.999, and 1.000, respectively. Intertest reliability for girth narrowing measurements yielded an ICC of 0.991. The interobserver ICC for girth narrowing for UWPEN and the ruler was 0.978 and 0.986, respectively. Intraobserver ICC for angle measurements and girth narrowing showed high reliability for all observers and methods. CONCLUSIONS: The performance of UWPEN is comparable with and highly correlated with angle measurements obtained from the goniometer and protractor as well as with girth narrowing measurements obtained from a ruler. Measurements are reproducible among different observers. UWPEN may provide a noninvasive, accurate, reliable, and widely accessible method to characterize and track PD over time.

Integrating patient voices into the extraction of social determinants of health from clinical notes: ethical considerations and recommendations.

Identifying patients' social needs is a first critical step to address social determinants of health (SDoH)-the conditions in which people live, learn, work, and play that affect health. Addressing SDoH can improve health outcomes, population health, and health equity. Emerging SDoH reporting requirements call for health systems to implement efficient ways to identify and act on patients' social needs. Automatic extraction of SDoH from clinical notes within the electronic health record through natural language processing offers a promising approach. However, such automated SDoH systems could have unintended consequences for patients, related to stigma, privacy, confidentiality, and mistrust. Using Floridi et al's "AI4People" framework, we describe ethical considerations for system design and implementation that call attention to patient autonomy, beneficence, nonmaleficence, justice, and explicability. Based on our engagement of clinical and community champions in health equity work at University of Washington Medicine, we offer recommendations for integrating patient voices and needs into automated SDoH systems.

Geospatial divide in real-world EHR data: Analytical workflow to assess regional biases and potential impact on health equity.

Real-world data (RWD) like electronic health records (EHR) has great potential for secondary use by health systems and researchers. However, collected primarily for efficient health care, EHR data may not equitably represent local regions and populations, impacting the generalizability of insights learned from it. We assessed the geospatial representativeness of regions in a large health system EHR data using a spatial analysis workflow, which provides a data-driven way to quantify geospatial representation and identify adequately represented regions. We applied the workflow to investigate geospatial patterns of overweight/obesity and depression patients to find regional "hotspots" for potential targeted interventions. Our findings show the presence of geospatial bias in EHR and demonstrate the workflow to identify spatial clusters after adjusting for bias due to the geospatial representativeness. This work highlights the importance of evaluating geospatial representativeness in RWD to guide targeted deployment of limited healthcare resources and generate equitable real-world evidence.

Improving physical activity among prostate cancer survivors through a peer-based digital walking program.

Physical activity is important for prostate cancer survivors. Yet survivors face significant barriers to traditional structured exercise programs, limiting engagement and impact. Digital programs that incorporate fitness trackers and peer support via social media have potential to improve the reach and impact of traditional support. Using a digital walking program with prostate cancer survivors, we employed mixed methods to assess program outcomes, engagement, perceived utility, and social influence. After 6 weeks of program use, survivors and loved ones (n=18) significantly increased their average daily step count. Although engagement and perceived utility of using a fitness tracker and interacting with walking buddies was high, social media engagement and utility were limited. Group strategies associated with social influence were driven more by group attraction to the collective task of walking than by interpersonal bonds. Findings demonstrate the feasibility of a digital walking program to improve physical activity and extend the reach of traditional support.

Co-designing mind-body technologies for sleep with adolescents.

Sleep is critical for well-being, yet adolescents do not get enough sleep. Mind-body approaches can help. Despite the potential of technology to support mind-body approaches for sleep, there is a lack of research on adolescent preferences for digital mind-body technology. We use co-design to examine adolescent perspectives on mind-body technologies for sleep. From our analysis of design sessions with 16 adolescents, four major themes emerged: system behavior, modality, content, and context. In light of these key findings, we recommend that technology-based mind-body approaches to sleep for adolescents be designed to 1) serve multiple functions while avoiding distractions, 2) provide intelligent content while maintaining privacy and trust, 3) provide a variety of content with the ability to customize and personalize, 4) offer multiple modalities for interaction with technology, and 5) consider the context of adolescent and their families. Findings provide a foundation for designing mind-body technologies for adolescent sleep.

Imagining Improved Interactions: Patients' Designs To Address Implicit Bias.

Implicit biases may negatively influence healthcare providers' behaviors toward patients from historically marginalized communities, impacting providers' communication style, clinical decision-making, and delivery of quality care. Existing interventions to mitigate negative experiences of implicit biases are primarily designed to increase recognition and management of stereotypes and prejudices through provider-facing tools and resources. However, there is a gap in understanding and designing interventions from patient perspectives. We conducted seven participatory co-design workshops with 32 Black, Indigenous, People of Color (BIPOC), Lesbian, Gay, Bisexual, Transgender, Queer/Questioning (LGBTQ+), and Queer, Transgender, Black, Indigenous, People of Color (QTBIPOC) individuals to design patient-centered interventions that help them address and recover from provider implicit biases in primary care. Participants designed four types of solutions: accountability measures, real-time correction, patient enablement tools, and provider resources. These informatics interventions extend the research on implicit biases in healthcare through inclusion of valuable, firsthand patient perspectives and experiences.

Comparing Caregiving Needs in Asian And White Family Caregivers through a Journaling Exercise Delivered by a Conversational Agent.

Asian Americans are the fastest growing racial and ethnic group with nearly 1 in 5 self-identifying as a family caregiver. Understanding the needs of ethnic minority caregivers is needed to develop inclusive technology solutions that aim to support caregivers within these marginalized communities in managing their own health. This study aimed to describe and compare the common needs of Asian American (AA) and White caregivers through data collected using a short message service-based conversational agent. Caregivers (26 AA and 84 White) shared their daily experiences for 14 days, and the data were analyzed using directed content analysis to identify needs based on Maslow's Hierarchy of Needs. Overall, AA and White caregivers expressed different needs in physiological, safety, and esteem categories. Culturally tailored support and resources are needed for family caregivers from diverse cultural and ethnic backgrounds.

Battling Bias in Primary Care Encounters: Informatics Designs to Support Clinicians.

Although clinical training in implicit bias is essential for healthcare equity, major gaps remain both for effective educational strategies and for tools to help identify implicit bias. To understand the perspectives of clinicians on the design of these needed strategies and tools, we conducted 21 semi-structured interviews with primary care clinicians about their perspectives and design recommendations for tools to improve patient-centered communication and to help mitigate implicit bias. Participants generated three types of solutions to improve communication and raise awareness of implicit bias: digital nudges, guided reflection, and data-driven feedback. Given the nuance of implicit bias communication feedback, these findings illustrate innovative design directions for communication training strategies that clinicians may find acceptable. Improving communication skills through individual feedback designed by clinicians for clinicians has the potential to improve healthcare equity.

Exploring needs, interests and preferences for digital mind-body tools for adolescents.

Sleep problems are common among adolescents and research on mind-body interventions for sleep is promising. Although technology-based mind-body interventions have been shown to help early adolescents with practicing mind-body approaches, engagement and adherence has been a challenge. Using a Human-Centered Design framework with semi-structured interviews with parent-adolescent dyads, we describe exposure to, interest in, and preferences for digital mind-body technology for sleep. Identified challenges (e.g., 'establish routine', 'busy schedule) and preferences (e.g., age-appropriate content) reflect mind-body technology needs that impact engagement. Based on these findings, we recommend that a technology-based mind-body approach for early adolescents be designed to 1) provide content customized for adolescents 2) include functionalities that engage adolescents like games and rewards, and 3) allow for granular sharing controls. These recommendations provide a foundation for designing digital mind-body tools for adolescents.

Approaches for implementing digital interventions for alcohol use disorders in primary care: A qualitative, user-centered design study.

Background: Digital interventions, such as smartphone apps, can be effective in treating alcohol use disorders (AUD). However, efforts to integrate digital interventions into primary care have been challenging. To inform successful implementation, we sought to understand how patients and clinicians preferred to use apps in routine primary care. Methods: This study combined user-centered design and qualitative research methods, interviewing 18 primary care patients with AUD and nine primary care clinicians on topics such as prior experiences with digital tools, and design preferences regarding approaches for offering apps for AUD in primary care. Interviews were recorded and transcribed for template analysis whereby a priori codes were based on interview topics and refined through iterative coding. New codes and cross-cutting themes emerged from the data. Results: Patient participants with AUD indicated they would be more likely to engage in treatment if primary care team members were involved in their use of apps. They also preferred to see clinicians "invested" and recommended that clinicians ask about app use and progress during follow-up appointments or check-ins. Clinician participants valued the opportunity to offer apps to their patients but noted that workflows would need to be tailored to individual patient needs. Time pressures, implementation complexity, and lack of appropriate staffing were cited as barriers. Clinicians proposed concrete solutions (e.g., education, tools, and staffing models) that could improve their ability to use apps within the constraints of primary care and suggested that some patients could potentially use apps without clinician support. Conclusions: A user-centered approach to engaging patients in digital alcohol interventions in primary care may require personalized support for both initiation and follow-up. Meeting patients' needs likely require increased staffing and efficient workflows in primary care. Health systems should consider offering multiple pathways for enrolling patients in apps to accommodate individual preferences and contextual barriers. Plain Language Summary: Healthcare systems have begun using app-based treatments to help patients manage their health conditions, including alcohol use disorders. Some apps have been tested in research studies and appear to be effective. However, it is difficult for healthcare teams to offer apps to patients. Clinicians must engage in new activities that they have not done before, such as "teaching" patients to use apps and checking in on their use of the apps. Identifying how to use apps in routine healthcare is critical to their successful implementation. This study interviewed 27 people, including healthcare providers and patients in primary care, to uncover the most optimal ways to offer apps to patients with alcohol use disorders. The interviews combined the use of qualitative research methods and user-centered design. Results suggest that to use to address alcohol use disorders, primary care teams should be prepared to offer personalized support to patients. Both patient and clinician interviewees said that the steps required to use apps must be intuitive and simple. Patients could gain more benefits if clinicians introduced the apps and guided patients to use them, as opposed to making apps available for patients to download and use on their own. However, the exact approach to offering apps would depend on a given patient's preferences and the extent that staffing was available in the clinic to support patients. Health systems should be prepared to offer and support patients in their use of apps, which should accommodate patient preferences and the constraints of the clinic.

Usability preferences of people living with cystic fibrosis about a lung transplant education website.

People living with cystic fibrosis (CF) need educational resources about lung transplant prior to engaging in shared decision making with their medical providers. We conducted a usability study to elicit preferences of people living with CF about how didactic and experiential content could be used in an educational resource to learn about lung transplant. We created two prototypes with different design features that participants used in a scenario-based task and evaluated using the System Usability Scale. We interviewed participants and analyzed the data to understand their preferences for educational content and design. Study participants indicated that didactic resource articles were important to understanding their illness trajectory, while experiential patient stories supported fear reduction and knowledge discovery. When learning about lung transplant participants stated a preference to control the amount of information they receive and preferred a combination of didactic and experiential knowledge.

Maybe they had a bad day: how LGBTQ and BIPOC patients react to bias in healthcare and struggle to speak out.

OBJECTIVE: People who experience marginalization, including Black, Indigenous, People of Color (BIPOC) and Lesbian, Gay, Bisexual, Transgender, Queer, Plus (ie, all other marginalized genders and sexual orientations) people (LGBTQ+) experience discrimination during healthcare interactions, which negatively impacts patient-provider communication and care. Yet, scarce research examines the lived experience of unfair treatment among patients from marginalized groups to guide patient-centered tools that improve healthcare equity. MATERIALS AND METHODS: We interviewed 25 BIPOC and/or LGBTQ+ people about their experiences of unfair treatment and discrimination when visiting healthcare providers. Through thematic analysis, we describe participants' immediate reactions and longer-term consequences of those experiences. RESULTS: We identified 4 ways that participants reacted to discrimination in the moment: Fighting, Fleeing, Excusing, and Working Around Bias. Long-term consequences reflect 6 ways they coped: Delaying or Avoiding Care, Changing Healthcare Providers, Self-prescribing, Covering Behaviors, Experiencing Health Complications, and Mistrusting Healthcare Institutions. DISCUSSION: By describing how patients react to experiences of unfair treatment and discrimination, our findings enhance the understanding of health disparities as patients cope and struggle to speak out.To combat these problems, we identify 3 future directions for informatics interventions that improve provider behavior, support patient advocacy, and address power dynamics in healthcare. CONCLUSIONS: BIPOC and LGBTQ+ patients' perspectives on navigating unfair treatment and discrimination in healthcare offers critical insight into their experiences and long-term consequences of those experiences. Understanding the circumstances and consequences of unfair treatment, discrimination, and the impact of bias through this patient-centered lens is crucial to inform informatics technologies that promote health equity.