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Patient-generated health data (PGHD) encompass health-related information created, recorded, and gathered by patients in their daily lives, and are distinct from data collected in clinical settings. PGHD can offer insight into patients’ everyday health behaviors and conditions, supporting health management and clinical decision-making. The Veterans Health Administration (VHA) has developed a robust infrastructure to collect PGHD, including automatically collected data from digital sensors and patient-entered data. This effort is guided by comprehensive policy and strategy documents to ensure the secure storage and effective use of PGHD. This paper describes the development and implementation of an infrastructure to support PGHD within the VHA and highlights envisioned clinical and research uses of PGHD to advance health care for US veterans. The PGHD database was built to Fast Healthcare Interoperability Resources standards, facilitating secure data storage and exchange of PGHD. Clinical tools, such as the provider-facing dashboards, make PGHD accessible from the electronic health records. Research and evaluation efforts focus on evaluating PGHD’s impact on patient engagement, clinical outcomes, and health care equity. The VHA’s comprehensive PGHD infrastructure represents a significant advancement in personalized health care and patient engagement. The integration of PGHD into clinical practice can enhance shared decision-making and self-management, while research and evaluation efforts can address how to maximize the benefits of PGHD for veterans. The VHA’s approach sets a benchmark for other US health care systems in leveraging PGHD to achieve the broad aims of enhancing stakeholder health care experiences, improving population health and health equity, and reducing costs.

The integration of patient-generated health data (PGHD) into health care has the potential to significantly transform patient care and clinical practice. PGHD includes health-related data created by patients, enabling the collection of health data beyond traditional health care settings. The Veterans Health Administration (VA) has taken proactive steps to incorporate PGHD into health care through its Share My Health Data (SMHD) mobile app. Launched in 2023, the SMHD app allows veterans to securely share data from their personal digital health devices with the VA for clinical and research use. However, data characterizing patients who use such tools in real-world health care systems are lacking, creating an evidence gap for implementing PGHD-informed care equitably. This study aimed to identify the characteristics of patients using the VA SMHD mobile app, which allows veterans to share PGHD with the VA. We conducted a cross-sectional analysis of veterans who began using SMHD between October 2023 and September 2024 (n=3157, \"SMHD users\"). We collected demographic information, including age, sex, race/ethnicity, and rurality, and clinical information, including physiological and mental health conditions, from VA administrative data. We compared characteristics of SMHD users to a 10% random sample of veterans from the same underlying administrative data cohort that had never used the app (n=632,187, \"nonusers\"). Statistical analyses were performed using chi-square tests, independent t tests, and multivariable regression to assess the relationship between use and key characteristics. Middle-aged veterans were more likely to be SMHD users (40-49 years: odds ratio [OR] 1.55, P<.001; 50-59 years: OR 1.37, P<.001), while veterans aged 60 years and over were less likely (60-69 years: OR 0.72, P<.001; ≥70 years: OR 0.24, P<.001). Female (OR 1.23, P<.001) and married (OR 1.31, P<.001) veterans were more likely to be SMHD users than male and unmarried veterans. In contrast, Black or African American (OR 0.62, P<.001) and rural (OR 0.82, P<.001) veterans were less likely to be SMHD users than White and urban veterans. Veterans in higher-income zip codes (OR 1.36, P<.001) were more likely to have used the app than those in lower-income zip codes. Clinically, SMHD users were more likely to have a service-connected disability (OR 1.81, P<.001), multiple physiological conditions (OR 1.86, P<.001), and multiple mental health diagnoses (OR 1.35, P<.001) versus none. Veterans who used the SMHD app differed significantly from nonusers across several demographic and clinical characteristics. These insights identify specific demographic and clinical subgroups with higher and lower app adoption, providing an evidence base to inform targeted implementation and outreach and support strategies to promote enhanced engagement in PGHD-informed care.

Designing proteins that bind with high affinity to hydrophilic protein target sites remains a challenging problem. Here we show that RFdiffusion can be conditioned to generate protein scaffolds that form geometrically matched extended β-sheets with target protein edge β-strands in which polar groups on the target are complemented with hydrogen bonding groups on the design. We use this approach to design binders against edge-strand target sites on KIT, PDGFRɑ, ALK-2, ALK-3, FCRL5, NRP1, and α-CTX, and obtain higher (pM to mid nM) affinities and success rates than unconditioned RFdiffusion. Despite sharing β-strand interactions, designs have high specificity, reflecting the precise customization of interacting β-strand geometry and additional designed binder-target interactions. A binder-KIT co-crystal structure is nearly identical to the design model, confirming the accuracy of the design approach. The ability to robustly generate binders to the hydrophilic interaction surfaces of exposed β-strands considerably increases the range of computational binder design. This study demonstrates the capability of deep learning protein design models in generating functionally validated β-strand pairing interfaces, expanding the structural diversity of de novo binding proteins and accessible target surfaces.

There has been increased incentivization to develop remote exercise training programs for those living with chronic respiratory diseases, such as chronic obstructive pulmonary disease (COPD). Remote programs offer patients an opportunity to overcome barriers to accessing traditional in-person programs, such as pulmonary rehabilitation (PR). Methods to deliver exercise training remotely range in complexity and types of technological modalities, including phone calls, real-time video conferencing, web- and app-based platforms, video games, and virtual reality (VR). There are a number of studies demonstrating the effectiveness of these programs on exercise capacity, dyspnea, and health-related quality of life (HRQL). However, there is great variation in these programs, making it difficult to assess findings across studies. Other aspects that contribute to the effectiveness of these programs include stakeholder perceptions, such as motivation and willingness to engage, and adherence. Finally, while the intent of these remote programs is to overcome barriers to access, they may inadvertently exacerbate access disparities. Future program development efforts should focus on standardizing how remote exercise training is delivered, engaging stakeholders early on to develop patient-centered programs that patients will want to use, and understanding the heterogeneous preferences and needs of those living with chronic respiratory disease in order to facilitate engagement with these programs.

The Veterans Health Administration (VHA) is the largest integrated healthcare system in the United States (US) providing healthcare to an increasing number of middle-aged and older adults who remain at greater risk for chronic obstructive pulmonary disease (COPD) compared to their civilian counterparts. The VHA has obligated research funds, drafted clinical guidelines, and built programmatic infrastructure to support the diagnosis, treatment, and care management of Veterans with COPD. Despite these efforts, COPD remains a leading cause of morbidity and mortality in Veterans. This paper provides a narrative review of research conducted with US Veteran samples targeting improvement in COPD outcomes. We review key physiological, physical, and psychological health outcomes and intervention research that included US Veteran samples. We conclude with a discussion of directions for future research to continue advancing the treatment of COPD in Veterans and inform advancements in COPD research within and outside the VHA.

There is an increasingly diverse range of mobile apps and digital health devices available to help patients manage their health. Despite evidence for the effectiveness of such technologies, their potential has not been fully realized because adoption remains low. Such limited uptake can have direct implications for the intended benefits of these technologies. This study aimed to understand what matters most to US military veterans when deciding whether to use digital health technologies (DHTs) such as mobile health apps or devices to manage their health and compare these factors between veterans with and without prevalent chronic physical and mental health conditions. We conducted a cross-sectional analysis of survey data collected from a national sample of veterans who receive care from the Veterans Health Administration (VHA), which was predominantly gathered as part of the last wave of a larger longitudinal data collection effort. Among respondents (n=857), 86.7% (736/849) reported currently using or having previously used ≥1 devices to manage their health, and 78.4% (639/815) also reported using either VHA or non-VHA health apps. Considerations most frequently endorsed as \"very important\" by veterans when deciding whether to use DHTs included receiving secure messages from their health care team about DHTs, knowing data from DHTs would be used to inform their care, and receiving recommendations from providers to use DHTs. Conversely, considerations most frequently endorsed as \"not at all important\" included seeing information about DHTs on social media, having community support to use DHTs, and receiving encouragement from peers to use DHTs. Considerations did not significantly differ between veterans with or without prevalent chronic health conditions; however, a greater proportion of veterans with prevalent mental health conditions reported the following considerations to be \"very important:\" seeing information about DHTs on social media, having community support to use DHTs, having other veterans encourage DHT use, and having help from family, friends, or other important people to use DHTs. Understanding what matters most to patients when they are deciding to adopt a technology for their health can, and should, inform implementation strategies and other approaches to enhance health-related technology use. Our results suggest that, for veterans, recommendations from health care team members and knowing that the data from DHTs will be used in clinical care are more important than information from social media, community sources, or peers when deciding to use DHTs, although perceptions of importance regarding the latter may differ among patients with different conditions. Our findings suggest that communication from health care team members to patients, perhaps either in-person or electronically, could help encourage DHT adoption and use.

CRISPR-suppressor scanning reveals potential resistance mechanisms of cancer cells to molecular glue degraders via neosubstrate alteration.

Uncontrolled diabetes contributes to serious comorbidities and mortality. Effective self-management can improve outcomes, though barriers such as limited education and support often prevent patients from engaging in such behaviors. Automated texting systems show promise to deliver diabetes self-management education as they are accessible and scalable. Furthermore, customizing these systems may further enhance patient engagement compared to standard, one-size-fits-all approaches. However, such customization is more resource-intensive, and it remains unclear whether the added effort meaningfully enhances diabetes self-management and outcomes. This study aimed to describe the development of 2 versions of an automated texting system intervention for diabetes self-management: (1) a standard, education-only intervention (Diabetes Self-Management Support; DSMS) and (2) an interactive, customizable intervention (Diabetes Self-Management Support + Interactive and Customizable Messages; DSMS+). Two versions of an automated texting system intervention were developed using a participatory design approach that incorporated input from veterans and expert clinicians. Message content was refined through feedback from a multidisciplinary team, veteran coinvestigators, national surveys, interviews, clinical expert panel reviews, and beta testing. Surveys were mailed to 1000 potential participants, oversampling rural, low-income, minority, and female participants. Respondents rated message relevance and provided preferences for content, timing, and frequency. Interviews provided customization preferences. A clinical expert panel reviewed all messages for safety and appropriateness. Beta testing informed final refinements. Ninety-two surveys were completed (9.2% response rate). Respondents rated 62% of the messages as personally relevant and 61% confidence-enhancing. Interviews with 23 respondents revealed a preference for 1-2 texts per day, emphasizing topics such as healthy eating and weight management. The clinical expert panel reviewed 536 messages, flagging 81 for revision. Beta testing confirmed feasibility and informed refinements to clarity and timing. The 2 resulting interventions were built in the US Department of Veterans Affairs' automated texting system, Annie. Two text messaging interventions, DSMS and DSMS+, were developed to support diabetes self-management among US veterans. DSMS delivers standard educational content, while DSMS+ incorporates interactive features and personalization. The subsequent clinical trial will assess whether customization enhances engagement and improves diabetes outcomes, providing insights into the potential of tailored mobile health interventions for chronic disease management.

Background Pain is a common but underappreciated symptom experienced by people with Chronic Obstructive Pulmonary Disease (COPD). The relationships between pain and physical activity (PA) and exercise capacity are poorly understood. Methods This retrospective secondary analysis includes three cohorts of Veterans with COPD who participated in longitudinal studies evaluating PA and exercise capacity with objective measures of daily step counts and 6-min walk test (6MWT) distance, respectively. Pain was assessed using the bodily pain domain of the Veterans RAND-36. In two cohorts, participants were randomly assigned to a web-based, pedometer-mediated PA intervention which has previously been demonstrated to improve PA. Results Three-hundred and seventy-three (373) unique study participants were included in this analysis. Eighty-three percent (n = 311) of the population reported at least mild pain and/or at least a little bit of interference due to pain at baseline. Cross-sectionally, greater bodily pain was associated with lower 6MWT distance (β = 0.51; 95% CI 0.20, 0.82; p = 0.0013). Longitudinally, worsening bodily pain was associated with a decline in 6MWT distance (β = 0.30; 95% CI 0.03, 0.58; p = 0.0312). There was no association between baseline bodily pain and baseline daily step counts, baseline bodily pain and change in PA, or change in bodily pain and change in PA. Compared to usual care, our PA intervention improved bodily pain scores (β = 6.17; 95% CI 1.84, 10.45; p = 0.0054). Bodily pain scores did not affect the impact of the intervention on daily step counts. Conclusion Pain is highly prevalent and significantly associated with lower exercise capacity among Veterans with COPD. Worsening pain co-occurred with decline in exercise capacity but not PA. Our intervention reduced pain, although pain did not affect the impact of the intervention on PA.

Secure messaging use is associated with improved diabetes-related outcomes. However, it is less clear how secure messaging supports diabetes management. We examined secure message topics between patients and clinical team members in a national sample of veterans with type 2 diabetes to understand use of secure messaging for diabetes management and potential associations with glycemic control. We surveyed and analyzed the content of secure messages between 448 US Veterans Health Administration patients with type 2 diabetes and their clinical teams. We also explored the relationship between secure messaging content and glycemic control. Explicit diabetes-related content was the most frequent topic (72.1% of participants), followed by blood pressure (31.7% of participants). Among diabetes-related conversations, 90.7% of patients discussed medication renewals or refills. More patients with good glycemic control engaged in 1 or more threads about blood pressure compared to those with poor control (37.5% vs 27.2%, P=.02). More patients with good glycemic control engaged in 1 more threads intended to share information with their clinical team about an aspect of their diabetes management compared to those with poor control (23.7% vs 12.4%, P=.009). There were few differences in secure messaging topics between patients in good versus poor glycemic control. Those in good control were more likely to engage in informational messages to their team and send messages related to blood pressure. It may be that the specific topic content of the secure messages may not be that important for glycemic control. Simply making it easier for patients to communicate with their clinical teams may be the driving influence between associations previously reported in the literature between secure messaging and positive clinical outcomes in diabetes.