Research Priorities to Expand Virtual Care Access for Patients in the Veterans Affairs Health Care System.

The rapid expansion of virtual care is driving demand for equitable, high-quality access to technologies that are required to utilize these services. While the Department of Veterans Affairs (VA) is seen as a national leader in the implementation of telehealth, there remain gaps in evidence about the most promising strategies to expand access to virtual care. To address these gaps, in 2022, the VA's Health Services Research and Development service and Office of Connected Care held a "state-of-the-art" (SOTA) conference to develop research priorities for advancing the science, clinical practice, and implementation of virtual care. One workgroup within the SOTA focused on access to virtual care and addressed three questions: (1) Based on the existing evidence about barriers that impede virtual care access in digitally vulnerable populations, what additional research is needed to understand these factors? (2) Based on the existing evidence about digital inclusion strategies, what additional research is needed to identify the most promising strategies? and (3) What additional research beyond barriers and strategies is needed to address disparities in virtual care access? Here, we report on the workgroup's discussions and recommendations for future research to improve and optimize access to virtual care. Effective implementation of these recommendations will require collaboration among VA operational leadership, researchers, Human Factors Engineering experts and front-line clinicians as they develop, implement, and evaluate the spread of virtual care access strategies.

Incorporating TechQuity in Virtual Care Within the Veterans Health Administration: Identifying Future Research and Operations Priorities.

BACKGROUND: The Covid-19 pandemic dramatically changed healthcare delivery, driving rapid expansion of synchronous (i.e., real-time) audio-only and video telehealth, otherwise known as virtual care. Yet evidence describes significant inequities in virtual care utilization, with certain populations more dependent on audio-only virtual care than video-based care. Research is needed to inform virtual care policies and processes to counteract current inequities in access and health outcomes. OBJECTIVE: Given the importance of incorporating equity into virtual care within the Veterans Health Administration (VHA), we convened a Think Tank to identify priorities for future research and virtual care operations focused on achieving equitable implementation of virtual care within the VHA. METHODS: We used participatory activities to engage clinicians, researchers, and operational partners from across the VHA to develop priorities for equitable implementation of virtual care. We refined priorities through group discussion and force-ranked prioritization and outlined next steps for selected priorities. KEY RESULTS: Think Tank participants included 43 individuals from the VHA who represented diverse geographical regions, offices, and backgrounds. Attendees self-identified their associations primarily as operations (n = 9), research (n = 28), or both (n = 6). We identified an initial list of 63 potential priorities for future research and virtual care operations. Following discussion, we narrowed the list to four priority areas: (1) measure inequities in virtual care, (2) address emerging inequities in virtual care, (3) deploy virtual care equitably to accommodate differently abled veterans, and (4) measure and address potential adverse consequences of expanded virtual care. We discuss related information, data, key partners, and outline potential next steps. CONCLUSIONS: This Think Tank of research and operational partners from across the VHA identified promising opportunities to incorporate equity into the design and implementation of virtual care. Although much work remains, the priorities identified represent important steps toward achieving this vital goal.

Barriers and facilitators to the implementation and adoption of improvement coaching: A qualitative evidence synthesis.

BACKGROUND: Healthcare organisations and teams perform improvement activities to facilitate high-quality healthcare. The use of an improvement coach who provides support and guidance to the healthcare team may facilitate improvement activities; however, no systematic review exists on the facilitators and barriers to implementing an improvement coach. AIMS: We conducted a qualitative evidence synthesis to examine the facilitators and barriers to the implementation of improvement coaching. METHODS: We searched MEDLINE® , Embase and CINAHL. The final search was in March 2021. The screening eligibility criteria included the following: interdisciplinary team receiving the coaching, improvement coaching, designs with a qualitative component and primary purpose of evaluating practice facilitation in OECD countries. An ecologically-informed consolidated framework for implementation research (CFIR) served as the framework for coding. Patterns of barriers and facilitators across domains were identified through matrix analysis. Risk of bias was assessed using Critical Appraisal Skills Program. PRISMA reporting guidelines served as a guide for reporting this review. RESULTS: Nineteen studies with a qualitative component met the inclusion criteria. Four themes of barriers and facilitators crossed multiple CFIR domains: adaptability (e.g. making adjustments to the project; process, or approach); knowledge and skills (e.g. understanding of content and process for the project); engagement (e.g. willingness to be involved in the process) and resources (e.g. assets required to complete the improvement process). CONCLUSION: Improvement coaching is a complex intervention that influences the context, healthcare team being coached and improvement activities. Improvement coaches should understand how to minimise barriers and promote facilitators that are unique to each improvement project across the domains. Limitations of the study are related to the nature of the intervention including potential publication bias given quality improvement focus; the variety of terms similar to improvement coaching or selection of framework.

Effectiveness of Quality Improvement Coaching on Process Outcomes in Health Care Settings: A Systematic Review.

BACKGROUND: A culture of improvement is an important feature of high-quality health care systems. However, health care teams often need support to translate quality improvement (QI) activities into practice. One method of support is consultation from a QI coach. The literature suggests that coaching interventions have a positive impact on clinical outcomes. However, the impact of coaching on specific process outcomes, like adoption of clinical care activities, is unknown. Identifying the process outcomes for which QI coaching is most effective could provide specific guidance on when to employ this strategy. METHODS: We searched multiple databases from inception through July 2021. Studies that addressed the effects of QI coaching on process of care outcomes were included. Two reviewers independently extracted study characteristics and assessed risk of bias. Certainty of evidence was assessed using GRADE. RESULTS: We identified 1983 articles, of which 23 cluster-randomized trials met eligibility criteria. All but two took place in a primary care setting. Overall, interventions typically targeted multiple simultaneous processes of care activities. We found that coaching probably has a beneficial effect on composite process of care outcomes (n = 9) and ordering of labs and vital signs (n = 6), and possibly has a beneficial effect on changes in organizational process of care (n = 5), appropriate documentation (n = 5), and delivery of appropriate counseling (n = 3). We did not perform meta-analyses because of conceptual heterogeneity around intervention design and outcomes; rather, we synthesized the data narratively. Due to imprecision, inconsistency, and high risk of bias of the included studies, we judged the certainty of these results as low or very low. CONCLUSION: QI coaching interventions may affect certain processes of care activities such as ordering of labs and vital signs. Future research that advances the identification of when QI coaching is most beneficial for health care teams seeking to implement improvement processes in pursuit of high-quality care will support efficient use of QI resources. PROTOCOL REGISTRATION: This study was registered and followed a published protocol (PROSPERO: CRD42020165069).

Implementation of an Intensive Telehealth Intervention for Rural Patients with Clinic-Refractory Diabetes.

BACKGROUND: Rural patients with type 2 diabetes (T2D) may experience poor glycemic control due to limited access to T2D specialty care and self-management support. Telehealth can facilitate delivery of comprehensive T2D care to rural patients, but implementation in clinical practice is challenging. OBJECTIVE: To examine the implementation of Advanced Comprehensive Diabetes Care (ACDC), an evidence-based, comprehensive telehealth intervention for clinic-refractory, uncontrolled T2D. ACDC leverages existing Veterans Health Administration (VHA) Home Telehealth (HT) infrastructure, making delivery practical in rural areas. DESIGN: Mixed-methods implementation study. PARTICIPANTS: 230 patients with clinic-refractory, uncontrolled T2D. INTERVENTION: ACDC bundles telemonitoring, self-management support, and specialist-guided medication management, and is delivered over 6 months using existing VHA HT clinical staffing/equipment. Patients may continue in a maintenance protocol after the initial 6-month intervention period. MAIN MEASURES: Implementation was evaluated using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. The primary effectiveness outcome was hemoglobin A1c (HbA1c). KEY RESULTS: From 2017 to 2020, ACDC was delivered to 230 patients across seven geographically diverse VHA sites; on average, patients were 59 years of age, 95% male, 80% white, and 14% Hispanic/Latinx. Patients completed an average of 10.1 of 12 scheduled encounters during the 6-month intervention period. Model-estimated mean baseline HbA1c was 9.56% and improved to 8.14% at 6 months (- 1.43%, 95% CI: - 1.64, - 1.21; P < .001). Benefits persisted at 12 (- 1.26%, 95% CI: - 1.48, - 1.05; P < .001) and 18 months (- 1.08%, 95% CI - 1.35, - 0.81; P < .001). Patients reported increased engagement in self-management and awareness of glycemic control, while clinicians and HT nurses reported a moderate workload increase. As of this submission, some sites have maintained delivery of ACDC for up to 4 years. CONCLUSIONS: When strategically designed to leverage existing infrastructure, comprehensive telehealth interventions can be implemented successfully, even in rural areas. ACDC produced sustained improvements in glycemic control in a previously refractory population.

Addressing Hypertension Outcomes Using Telehealth and Population Health Managers: Adaptations and Implementation Considerations.

PURPOSE OF REVIEW: There is a growing evidence base describing population health approaches to improve blood pressure control. We reviewed emerging trends in hypertension population health management and present implementation considerations from an intervention called Team-supported, Electronic health record-leveraged, Active Management (TEAM). By doing so, we highlight the role of population health managers, practitioners who use population level data and to proactively engage at-risk patients, in improving blood pressure control. RECENT FINDINGS: Within a population health paradigm, we discuss telehealth-delivered approaches to equitably improve hypertension care delivery. Additionally, we explore implementation considerations and complementary features of team-based, telehealth-delivered, population health management. By leveraging the unique role and expertise of a population health manager as core member of team-based telehealth, health systems can implement a cost-effective and scalable intervention that addresses multi-level barriers to hypertension care delivery. We describe the literature of telehealth-based population health management for patients with hypertension. Using the TEAM intervention as a case study, we then present implementation considerations and intervention adaptations to integrate a population health manager within the health care team and effectively manage hypertension for a defined patient population. We emphasize practical considerations to inform implementation, scaling, and sustainability. We highlight future research directions to advance the field and support translational efforts in diverse clinical and community contexts.

Telehealth for the Longitudinal Management of Chronic Conditions: Systematic Review.

BACKGROUND: Extensive literature support telehealth as a supplement or adjunct to in-person care for the management of chronic conditions such as congestive heart failure (CHF) and type 2 diabetes mellitus (T2DM). Evidence is needed to support the use of telehealth as an equivalent and equitable replacement for in-person care and to assess potential adverse effects. OBJECTIVE: We conducted a systematic review to address the following question: among adults, what is the effect of synchronous telehealth (real-time response among individuals via phone or phone and video) compared with in-person care (or compared with phone, if synchronous video care) for chronic management of CHF, chronic obstructive pulmonary disease, and T2DM on key disease-specific clinical outcomes and health care use? METHODS: We followed systematic review methodologies and searched two databases (MEDLINE and Embase). We included randomized or quasi-experimental studies that evaluated the effect of synchronously delivered telehealth for relevant chronic conditions that occurred over ≥2 encounters and in which some or all in-person care was supplanted by care delivered via phone or video. We assessed the bias using the Cochrane Effective Practice and Organization of Care risk of bias (ROB) tool and the certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation. We described the findings narratively and did not conduct meta-analysis owing to the small number of studies and the conceptual heterogeneity of the identified interventions. RESULTS: We identified 8662 studies, and 129 (1.49%) were reviewed at the full-text stage. In total, 3.9% (5/129) of the articles were retained for data extraction, all of which (5/5, 100%) were randomized controlled trials. The CHF study (1/5, 20%) was found to have high ROB and randomized patients (n=210) to receive quarterly automated asynchronous web-based review and follow-up of telemetry data versus synchronous personal follow-up (in-person vs phone-based) for 1 year. A 3-way comparison across study arms found no significant differences in clinical outcomes. Overall, 80% (4/5) of the studies (n=466) evaluated synchronous care for patients with T2DM (ROB was judged to be low for 2, 50% of studies and high for 2, 50% of studies). In total, 20% (1/5) of the studies were adequately powered to assess the difference in glycosylated hemoglobin level between groups; however, no significant difference was found. Intervention design varied greatly from remote monitoring of blood glucose combined with video versus in-person visits to an endocrinology clinic to a brief, 3-week remote intervention to stabilize uncontrolled diabetes. No articles were identified for chronic obstructive pulmonary disease. CONCLUSIONS: This review found few studies with a variety of designs and interventions that used telehealth as a replacement for in-person care. Future research should consider including observational studies and studies on additional highly prevalent chronic diseases.

eConsults' Impact on Care Access and Wait Times in Rheumatology.

BACKGROUND/OBJECTIVE: A growing number of health systems have implemented eConsults to improve access to specialty advice, but few studies have described their use in rheumatology or impact on visit wait times. We evaluated the uptake of an eConsult program and its impact on wait times for in-person rheumatology visits. METHODS: In this quality improvement project, we analyzed electronic health record data from 4 intervention clinics and 4 comparison clinics, 12 months before and after implementation of an eConsult program. We compared median wait time for rheumatology appointments using a pre-post difference-in-differences analysis and quantile regression, adjusting for patient age, race, sex, clinic pair, and primary insurance payer. We also interviewed 11 primary care providers from the intervention clinics and conducted a rheumatology provider focus group (n = 4) to elucidate experiences with the program. RESULTS: Rheumatologists recommended management in primary care or referral to another specialty for 41% of eConsults, reducing initial demand for in-person visits. The median wait times dropped in the intervention and the comparison clinics (42 and 25 days, respectively). Intervention clinic median wait time dropped 17 days more than comparison clinics, and this was nonstatistically significant (p = 0.089). eConsults fit provider care tasks best for triage or initial workup for diagnosis, and less well when tests required interpretation, or when back and forth communication was needed to manage the patient's condition. CONCLUSIONS: Implementation of eConsults for rheumatology was associated with reduced wait times for rheumatology appointments and supported primary care providers in the triage and workup for a substantial portion of patients.

Applied Rapid Qualitative Analysis to Develop a Contextually Appropriate Intervention and Increase the Likelihood of Uptake.

BACKGROUND: Rapid approaches to collecting and analyzing qualitative interview data can accelerate discovery timelines and intervention development while maintaining scientific rigor. We describe the application of these methods to a program designed to improve care coordination between the Veterans Health Administration (VHA) and community providers. METHODS: Care coordination between VHA and community providers can be challenging in rural areas. The Telehealth-based Coordination of Non-VHA Care (TECNO Care) intervention was designed to improve care coordination among VHA and community providers. To ensure contextually appropriate implementation of TECNO Care, we conducted preimplementation interviews with veterans, VHA administrators, and VHA and community providers involved in community care. Using both a rapid approach and qualitative analysis, an interviewer and 1-2 note-taker(s) conducted interviews. RESULTS: Over 5 months, 18 stakeholders were interviewed and we analyzed these data to identify how best to deliver TECNO Care. Responses relevant to improving care coordination include health system characteristics; target population; metrics and outcomes; challenges with the current system; and core components. Veterans who frequently visit VHA or community providers and are referred for additional services are at risk for poor outcomes and may benefit from additional care coordination. Using these data, we designed TECNO Care to include information on VHA services and processes, assist in the timely completion of referrals, and facilitate record sharing. CONCLUSION: Rapid qualitative analysis can inform near real-time intervention development and ensure relevant content creation while setting the stage for stakeholder buy-in. Rigorous and timely analyses support the delivery of contextually appropriate, efficient, high-value patient care.

Accelerating Implementation of Virtual Care in an Integrated Health Care System: Future Research and Operations Priorities.

BACKGROUND: Virtual care is critical to Veterans Health Administration (VHA) efforts to expand veterans' access to care. Health care policies such as the Veterans Access, Choice, and Accountability (CHOICE) Act and the Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act impact how the VHA provides care. Research on ways to refine virtual care delivery models to meet the needs of veterans, clinicians, and VHA stakeholders is needed. OBJECTIVE: Given the importance of virtual approaches for increasing access to high-quality VHA care, in December 2019, we convened a Think Tank, Accelerating Implementation of Virtual Care in VHA Practice, to consider challenges to virtual care research and practice across the VHA, discuss novel approaches to using and evaluating virtual care, assess perspectives on virtual care, and develop priorities to enhance virtual care in the VHA. METHODS: We used a participatory approach to develop potential priorities for virtual care research and activities at the VHA. We refined these priorities through force-ranked prioritization and group discussion, and developed solutions for selected priorities. RESULTS: Think Tank attendees (n = 18) consisted of VHA stakeholders, including operations partners (e.g., Office of Rural Health, Office of Nursing Services, Health Services Research and Development), clinicians (e.g., physicians, nurses, psychologists, physician assistants), and health services researchers. We identified an initial list of fifteen potential priorities and narrowed these down to four. The four priorities were (1) scaling evidence-based practices, (2) centralizing virtual care, (3) creating high-value care within the VHA with virtual care, and (4) identifying appropriate patients for virtual care. CONCLUSION: Our Think Tank took an important step in setting a partnered research agenda to optimize the use of virtual care within the VHA. We brought together research and operations stakeholders and identified possibilities, partnerships, and potential solutions for virtual care.

Implementation of social needs screening in primary care: a qualitative study using the health equity implementation framework.

BACKGROUND: Screening in primary care for unmet individual social needs (e.g., housing instability, food insecurity, unemployment, social isolation) is critical to addressing their deleterious effects on patients' health outcomes. To our knowledge, this is the first study to apply an implementation science framework to identify implementation factors and best practices for social needs screening and response. METHODS: Guided by the Health Equity Implementation Framework (HEIF), we collected qualitative data from clinicians and patients to evaluate barriers and facilitators to implementing the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE), a standardized social needs screening and response protocol, in a federally qualified health center. Eligible patients who received the PRAPARE as a standard of care were invited to participate in semi-structured interviews. We also obtained front-line clinician perspectives in a semi-structured focus group. HEIF domains informed a directed content analysis. RESULTS: Patients and clinicians (i.e., case managers) reported implementation barriers and facilitators across multiple domains (e.g., clinical encounters, patient and provider factors, inner context, outer context, and societal influence). Implementation barriers included structural and policy level determinants related to resource availability, discrimination, and administrative burden. Facilitators included evidence-based clinical techniques for shared decision making (e.g., motivational interviewing), team-based staffing models, and beliefs related to alignment of the PRAPARE with patient-centered care. We found high levels of patient acceptability and opportunities for adaptation to increase equitable adoption and reach. CONCLUSION: Our results provide practical insight into the implementation of the PRAPARE or similar social needs screening and response protocols in primary care at the individual encounter, organizational, community, and societal levels. Future research should focus on developing discrete implementation strategies to promote social needs screening and response, and associated multisector care coordination to improve health outcomes and equity for vulnerable and marginalized patient populations.

Perceptions of Using Multiple Mobile Health Devices to Support Self-Management Among Adults With Type 2 Diabetes: A Qualitative Descriptive Study.

PURPOSE: This study identified facilitators and barriers pertaining to the use of multiple mobile health (mHealth) devices (Fitbit Alta® fitness tracker, iHealth® glucometer, BodyTrace® scale) that support self-management behaviors in individuals with type 2 diabetes mellitus (T2DM). DESIGN: This qualitative descriptive study presents study participants' perceptions of using multiple mobile devices to support T2DM self-management. Additionally, this study assessed whether participants found visualizations, generated from each participant's health data as obtained from the three separate devices, useful and easy to interpret. METHODS: Semistructured interviews were completed with a convenience sample of participants (n = 20) from a larger randomized control trial on T2DM self-management. Interview questions focused on participants' use of three devices to support T2DM self-management. A study team member created data visualizations of each interview participant's health data using RStudio. RESULTS: We identified two themes from descriptions of study participants: feasibility and usability. We identified one theme about visualizations created from data obtained from the mobile devices. Despite some challenges, individuals with T2DM found it feasible to use multiple mobile devices to facilitate engagement in T2DM self-management behaviors. DISCUSSION: As mHealth devices become increasingly popular for diabetes self-management and are integrated into care delivery, we must address issues associated with the use of multiple mHealth devices and the use of aggregate data to support T2DM self-management. CLINICAL RELEVANCE: Real-time patient-generated health data that are easily accessible and readily available can assist T2DM self-management and catalyze conversations, leading to better self-management. Our findings lay an important groundwork for understanding how individuals with T2DM can use multiple mHealth devices simultaneously to support self-management.

Implementing remote triage in large health systems: A qualitative evidence synthesis.

Remote triage (RT) allows interprofessional teams (e.g., nurses and physicians) to assess patients and make clinical decisions remotely. RT use has developed widespread interest due to the COVID-19 pandemic, and has future potential to address the needs of a rapidly aging population, improve access to care, facilitate interprofessional team care, and ensure appropriate use of resources. However, despite rapid and increasing interest in implementation of RT, there is little research concerning practices for successful implementation. We conducted a systematic review and qualitative evidence synthesis of practices that impact the implementation of RT for adults seeking clinical care advice. We searched MEDLINE®, EMBASE, and CINAHL from inception through July 2018. We included 32 studies in this review. Our review identified four themes impacting the implementation of RT: characteristics of staff who use RT, influence of RT on staff, considerations in selecting RT tools, and environmental and contextual factors impacting RT. The findings of our systemic review underscore the need for a careful consideration of (a) organizational and stakeholder buy-in before launch, (b) physical and psychological workplace environment, (c) staff training and ongoing support, and (d) optimal metrics to assess the effectiveness and efficiency of implementation. Our findings indicate that preimplementation planning, as well as evaluating RT by collecting data during and after implementation, is essential to ensuring successful implementation and continued adoption of RT in a health care system.

Effectiveness of Acute Care Remote Triage Systems: a Systematic Review.

BACKGROUND: Technology-based systems can facilitate remote decision-making to triage patients to the appropriate level of care. Despite technologic advances, the effects of implementation of these systems on patient and utilization outcomes are unclear. We evaluated the effects of remote triage systems on healthcare utilization, case resolution, and patient safety outcomes. METHODS: English-language searches of MEDLINE (via PubMed), EMBASE, and CINAHL were performed from inception until July 2018. Randomized and nonrandomized comparative studies of remote triage services that reported healthcare utilization, case resolution, and patient safety outcomes were included. Two reviewers assessed study and intervention characteristics independently for study quality, strength of evidence, and risk of bias. RESULTS: The literature search identified 5026 articles, of which eight met eligibility criteria. Five randomized, two controlled before-and-after, and one interrupted time series study assessed 3 categories of remote triage services: mode of delivery, triage professional type, and system organizational level. No study evaluated any other delivery mode other than telephone and in-person. Meta-analyses were unable to be performed because of study design and outcome heterogeneity; therefore, we narratively synthesized data. Overall, most studies did not demonstrate a decrease in primary care (PC) or emergency department (ED) utilization, with some studies showing a significant increase. Evidence suggested local, practice-based triage systems have greater case resolution and refer fewer patients to PC or ED services than regional/national systems. No study identified statistically significant differences in safety outcomes. CONCLUSION: Our review found limited evidence that remote triage reduces the burden of PC or ED utilization. However, remote triage by telephone can produce a high rate of call resolution and appears to be safe. Further study of other remote triage modalities is needed to realize the promise of remote triage services in optimizing healthcare outcomes. PROTOCOL REGISTRATION: This study was registered and followed a published protocol (PROSPERO: CRD42019112262).

Self-management of Epilepsy: A Systematic Review.

Background: Although self-management is recommended for persons with epilepsy, its optimal strategies and effects are uncertain. Purpose: To evaluate the components and efficacy of self-management interventions in the treatment of epilepsy in community-dwelling persons. Data Sources: English-language searches of MEDLINE, Cochrane Central Register of Controlled Trials, PsycINFO, and CINAHL in April 2018; the MEDLINE search was updated in March 2019. Study Selection: Randomized and nonrandomized comparative studies of self-management interventions for adults with epilepsy. Data Extraction: An investigator assessed study characteristics; intervention details, including 6 components of self-management; and outcomes, which were verified by a second reviewer. Risk of bias (ROB) was assessed independently by 2 investigators. Data Synthesis: 13 randomized and 2 nonrandomized studies (2514 patients) evaluated self-management interventions. Interventions were delivered primarily in group settings, used a median of 4 components, and followed 2 general strategies: 1 based on education and the other on psychosocial therapy. Education-based approaches improved self-management behaviors (standardized mean difference, 0.52 [95% CI, 0.0 to 1.04]), and psychosocial therapy-based approaches improved quality of life (mean difference, 6.64 [CI, 2.51 to 10.77]). Overall, self-management interventions did not reduce seizure rates, but 1 educational intervention decreased a composite of seizures, emergency department visits, and hospitalizations. Limitation: High ROB in most studies, incomplete intervention descriptions, and studies limited to English-language publications. Conclusion: There is limited evidence that self-management strategies modestly improve some patient outcomes that are important to persons with epilepsy. Overall, self-management research in epilepsy is limited by the range of interventions tested, the small number of studies using self-monitoring technology, and uncertainty about components and strategies associated with benefit. Primary Funding Source: U.S. Department of Veterans Affairs. (PROSPERO: CRD42018098604).

Addressing Diabetes and Poorly Controlled Hypertension: Pragmatic mHealth Self-Management Intervention.

BACKGROUND: Patients with diabetes and poorly controlled hypertension are at increased risk for adverse renal and cardiovascular outcomes. Identifying these patients early and addressing modifiable risk factors is central to delaying renal complications such as diabetic kidney disease. Mobile health (mHealth), a relatively inexpensive and easily scalable technology, can facilitate patient-centered care and promote engagement in self-management, particularly for patients of lower socioeconomic status. Thus, mHealth may be a cost-effective way to deliver self-management education and support. OBJECTIVE: This feasibility study aimed to build a population management program by identifying patients with diabetes and poorly controlled hypertension who were at risk for adverse renal outcomes and evaluate a multifactorial intervention to address medication self-management. We recruited patients from a federally qualified health center (FQHC) in an underserved, diverse county in the southeastern United States. METHODS: Patients were identified via electronic health record. Inclusion criteria were age between 18 and 75 years, diagnosis of type 2 diabetes, poorly controlled hypertension over the last 12 months (mean clinic systolic blood pressure [SBP] ≥140 mm Hg and/or diastolic blood pressure [DBP] ≥90 mm Hg), access to a mobile phone, and ability to receive text messages and emails. The intervention consisted of monthly telephone calls for 6 months by a case manager and weekly, one-way informational text messages. Engagement was defined as the number of phone calls completed during the intervention; individuals who completed 4 or more calls were considered engaged. The primary outcome was change in SBP at the conclusion of the intervention. RESULTS: Of the 141 patients enrolled, 84.0% (118/141) of patients completed 1 or more phone calls and had follow-up SBP measurements for analysis. These patients were on average 56.9 years of age, predominately female (73/118, 61.9%), and nonwhite by self-report (103/118, 87.3%). The proportion of participants with poor baseline SBP control (50/118, 42.4%) did not change significantly at study completion (53/118, 44.9%) (P=.64). Participants who completed 4 or more phone calls (98/118, 83.1%) did not experience a statistically significant decrease in SBP when compared to those who completed fewer calls. CONCLUSION: We did not reduce uncontrolled hypertension even among the more highly engaged. However, 83% of a predominately minority and low-income population completed at least 67% of the multimodal mHealth intervention. Findings suggest that combining an automated electronic health record system to identify at-risk patients with a tailored mHealth protocol can provide education to this population. While this intervention was insufficient to effect behavioral change resulting in better hypertension control, it does suggest that this FQHC population will engage in low-cost population health applications with a potentially promising impact. TRIAL REGISTRATION: ClinicalTrials.gov NCT02418091; https://clinicaltrials.gov/ct2/show/NCT02418091 (Archived by WebCite at http://www.webcitation.org/76RBvacVU).

Type 2 Diabetes Education and Support in a Virtual Environment: A Secondary Analysis of Synchronously Exchanged Social Interaction and Support.

BACKGROUND: Virtual environments (VEs) facilitate interaction and support among individuals with chronic illness, yet the characteristics of these VE interactions remain unknown. OBJECTIVE: The objective of this study was to describe social interaction and support among individuals with type 2 diabetes (T2D) who interacted in a VE. METHODS: Data included VE-mediated synchronous conversations and text-chat and asynchronous emails and discussion board posts from a study that facilitated interaction among individuals with T2D and diabetes educators (N=24) in 2 types of sessions: education and support. RESULTS: VE interactions consisted of communication techniques (how individuals interact in the VE), expressions of self-management (T2D-related topics), depth (personalization of topics), and breadth (number of topics discussed). Individuals exchanged support more often in the education (723/1170, 61.79%) than in the support (406/1170, 34.70%) sessions or outside session time (41/1170, 3.50%). Of all support exchanges, 535/1170 (45.73%) were informational, 377/1170 (32.22%) were emotional, 217/1170 (18.55%) were appraisal, and 41/1170 (3.50%) were instrumental. When comparing session types, education sessions predominately provided informational support (357/723, 49.4%), and the support sessions predominately provided emotional (159/406, 39.2%) and informational (159/406, 39.2%) support. CONCLUSIONS: VE-mediated interactions resemble those in face-to-face environments, as individuals in VEs engage in bidirectional exchanges with others to obtain self-management education and support. Similar to face-to-face environments, individuals in the VE revealed personal information, sought information, and exchanged support during the moderated education sessions and unstructured support sessions. With this versatility, VEs are able to contribute substantially to support for those with diabetes and, very likely, other chronic diseases.

Social Support for Diabetes Self-Management via eHealth Interventions.

eHealth interventions have been increasingly used to provide social support for self-management of type 2 diabetes. In this review, we discuss social support interventions, types of support provided, sources or providers of support, outcomes of the support interventions (clinical, behavioral, psychosocial), and logistical and clinical considerations for support interventions using eHealth technologies. Many types of eHealth interventions demonstrated improvements in self-management behaviors, psychosocial outcomes, and clinical measures, particularly HbA1c. Important factors to consider in clinical application of eHealth support interventions include participant preferences, usability of eHealth technology, and availability of personnel to orient or assist participants. Overall, eHealth is a promising adjunct to clinical care as it addresses the need for ongoing support in chronic disease management.

Diabetes Learning in Virtual Environments: Testing the Efficacy of Self-Management Training and Support in Virtual Environments (Randomized Controlled Trial Protocol).

BACKGROUND: Ongoing self-management improves outcomes for those with Type 2 diabetes (T2D); however, there are many barriers to patients receiving assistance in this from the healthcare system and peers. Findings from our pilot study showed that a virtual diabetes community on the Internet with real-time interaction among peers with T2D-and with healthcare professionals-is feasible and has the potential to influence clinical and psychosocial outcomes. OBJECTIVE: The purpose of this article is to present the protocol for the Diabetes Learning in Virtual Environments (LIVE) trial. PROTOCOL: Diabetes LIVE is a two-group, randomized controlled trial to compare effects of a virtual environment and traditional Web site on diet and physical activity. Our secondary aims will determine the effects on metabolic outcomes; effects of level of engagement and social network formation in LIVE on behavioral outcomes; potential mediating effects of changes in self-efficacy; and diabetes knowledge, diabetes-related distress, and social support on behavior change and metabolic outcomes. We will enroll 300 subjects at two sites (Duke University/Raleigh-Durham, NC and New York University/New York, NY) who have T2D and do not have serious complications or comorbidities. Those randomly assigned to the intervention group have access to the LIVE site where they can find information, synchronous classes with diabetes educators, and peer support to enhance self-management. Those in the control group have access to the same informational and educational content in a traditional asynchronous Web format. Measures of self-management, clinical outcomes, and psychosocial outcomes are assessed at baseline and 3, 6, 12, and 18 months. DISCUSSION: Should LIVE prove effective in improved self-management of diabetes, similar interventions could be applied to other prevalent chronic diseases. Innovative programs such as LIVE have potential for improving healthcare access in an easily disseminated alternative model of care that potentially improves the reach of self-management training and support.