Project description:BackgroundHealthcare reform in the United States is encouraging Federally Qualified Health Centers and other primary-care practices to integrate treatment for addiction and other behavioral health conditions into their practices. The potential of mobile health technologies to manage addiction and comorbidities such as HIV in these settings is substantial but largely untested. This paper describes a protocol to evaluate the implementation of an E-Health integrated communication technology delivered via mobile phones, called Seva, into primary-care settings. Seva is an evidence-based system of addiction treatment and recovery support for patients and real-time caseload monitoring for clinicians.Methods/designOur implementation strategy uses three models of organizational change: the Program Planning Model to promote acceptance and sustainability, the NIATx quality improvement model to create a welcoming environment for change, and Rogers's diffusion of innovations research, which facilitates adaptations of innovations to maximize their adoption potential. We will implement Seva and conduct an intensive, mixed-methods assessment at three diverse Federally Qualified Healthcare Centers in the United States. Our non-concurrent multiple-baseline design includes three periods - pretest (ending in four months of implementation preparation), active Seva implementation, and maintenance - with implementation staggered at six-month intervals across sites. The first site will serve as a pilot clinic. We will track the timing of intervention elements and assess study outcomes within each dimension of the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework, including effects on clinicians, patients, and practices. Our mixed-methods approach will include quantitative (e.g., interrupted time-series analysis of treatment attendance, with clinics as the unit of analysis) and qualitative (e.g., staff interviews regarding adaptations to implementation protocol) methods, and assessment of implementation costs.DiscussionIf implementation is successful, the field will have a proven technology that helps Federally Qualified Health Centers and affiliated organizations provide addiction treatment and recovery support, as well as a proven strategy for implementing the technology. Seva also has the potential to improve core elements of addiction treatment, such as referral and treatment processes. A mobile technology for addiction treatment and accompanying implementation model could provide a cost-effective means to improve the lives of patients with drug and alcohol problems.Trial registrationClinicalTrials.gov (NCT01963234).

Project description:BACKGROUND:Despite the near ubiquity of mobile phones, little research has been conducted on the implementation of mobile health (mHealth) apps to treat patients in primary care. Although primary care clinicians routinely treat chronic conditions such as asthma and diabetes, they rarely treat addiction, a common chronic condition. Instead, addiction is most often treated in the US health care system, if it is treated at all, in a separate behavioral health system. mHealth could help integrate addiction treatment in primary care. OBJECTIVE:The objective of this paper was to report the effects of implementing an mHealth system for addiction in primary care on both patients and clinicians. METHODS:In this implementation research trial, an evidence-based mHealth system named Seva was introduced sequentially over 36 months to a maximum of 100 patients with substance use disorders (SUDs) in each of three federally qualified health centers (FQHCs; primary care clinics that serve patients regardless of their ability to pay). This paper reports on patient and clinician outcomes organized according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS:The outcomes according to the RE-AIM framework are as follows: Reach-Seva reached 8.31% (268/3226) of appropriate patients. Reach was limited by our ability to pay for phones and data plans for a maximum of 100 patients per clinic. Effectiveness-Patients who were given Seva had significant improvements in their risky drinking days (44% reduction, (0.7-1.25)/1.25, P=.04), illicit drug-use days (34% reduction, (2.14-3.22)/3.22, P=.01), quality of life, human immunodeficiency virus screening rates, and number of hospitalizations. Through Seva, patients also provided peer support to one another in ways that are novel in primary care settings. Adoption-Patients sustained high levels of Seva use-between 53% and 60% of the patients at the 3 sites accessed Seva during the last week of the 12-month implementation period. Among clinicians, use of the technology was less robust than use by patients, with only a handful of clinicians using Seva in each clinic and behavioral health providers making most referrals to Seva in 2 of the 3 clinics. Implementation-At 2 sites, implementation plans were realized successfully; they were delayed in the third. Maintenance-Use of Seva dropped when grant funding stopped paying for the mobile phones and data plans. Two of the 3 clinics wanted to maintain the use of Seva, but they struggled to find funding to support this. CONCLUSIONS:Implementing an mHealth system can improve care among primary care patients with SUDs, and patients using the system can support one another in their recovery. Among clinicians, however, implementation requires figuring out how information from the mHealth system will be used and making mHealth data available in the electronic health (eHealth) record. In addition, paying for an mHealth system remains a challenge.

Project description:BackgroundIn Catalonia, the Fundació TIC Salut Social's mHealth Office created the AppSalut Site to showcase to mobile apps in the field of health and social services. Its primary objective was to encourage the public to look after their health. The catalogue allows primary health care doctors to prescribe certified, connected apps, which guarantees a safe and reliable environment for their use. The generated data can be consulted by health care professionals and included in the patient's clinical history. This document presents the intervention and the major findings following a five-month pilot project conducted in the Barcelona area.ObjectiveThe objective of the pilot study was to test, in a real, controlled environment, the implementation of AppSalut. Specifically, we tested whether (1) the procedures corresponding to the prescription, transmission, and evaluation of the data functions correctly, (2) users interact successfully and accept the tool, and (3) the data travels through existing pathways in accordance with international standards. The evaluation is not based on clinical criteria, but rather on the usability and technological reliability of the intervention and its implementation in the context of primary care.MethodsThe project was presented to the Primary Care Team participants to encourage the involvement of doctors. The study involved at least 5 doctors and 5 patients per professional, chosen at their discretion and in accordance with their own clinical criteria. An initial consultation took place, during which the doctor discussed the pilot project with the patient and recommended the app. The patient was sent a text message (SMS, short message service) containing an access code. When the patient arrived home, they accessed their personal health record (PHR) to view the recommendation, download the app, and enter the access code. The patient was then able to start using the app. The data was collected in a standardized manner and automatically sent to the system. In a second visit, the patient looked at the data with their doctor on their clinical station screen. The latter was able to consult the information generated by the patient and select what to include in their electronic health record. In order to assess the performance of the system, three focus groups were performed and two ad-hoc case-specific questionnaires, one for doctors and one for patients, were sent by email. Response was voluntary.ResultsA total of 32 doctors made 79 recommendations of apps to patients. On average, the patients uploaded data 13 times per prescribed app, accounting for a total of 16 different variables. Results show that data traveled through the established channels in an adequate manner and in accordance with international standards. This includes the prescription of an app by a doctor, the patient accessing the recommendation via the PHR, app download by the patient from the official app stores, linking of the patient to the public platform through the app, the generation and visualization of the data on the primary care workstation, and its subsequent validation by the clinician.ConclusionsFirst, the choice of apps to be used is fundamental; the user's perception of the utility of the proposed tool being paramount. Second, thorough face-to-face support is vital for a smooth transition towards a more intense model of telemedicine. Last, a powerful limiting factor is the lack of control over people's ability to use the apps.

Project description:BackgroundPatients undergoing hemodialysis have a high mortality rate and yet underutilize palliative care and hospice resources. The Shared Decision Making-Renal Supportive Care (SDM-RSC) intervention focused on goals of care conversations between patients and family members with the nephrologist and social worker. The intervention targeted deficiencies in communication, estimating prognosis, and transition planning for seriously ill dialysis patients. The intervention showed capacity to increase substantially completion of advance care directives. The HIGHway Project, adapted from the previous SDM-RSC, scale up training social workers or nurses in dialysis center in advance care planning (ACP), and then support them for a subsequent 9-month action period, to engage in ACP conversations with patients at their dialysis center regarding their preferences for end-of-life care.MethodsWe will train between 50-60 dialysis teams, led by social workers or nurses, to engage in ACP conversations with patients at their dialysis center regarding their preferences for end-of-life care. This implementation project uses the Knowledge to Action (KTA) Framework within the Consolidated Framework for Implementation Research (CFIR) to increase adoption and sustainability in the participating dialysis centers. This includes a curriculum about how to hold ACP conversation and coaching with monthly teleconferences through case discussion and mentoring. An application software will guide on the process and provide resources for holding ACP conversations. Our project will focus on implementation outcomes. Success will be determined by adoption and effective use of the ACP approach. Patient and provider outcomes will be measured by the number of ACP conversations held and documented; the quality and fidelity of ACP conversations to the HIGHway process as taught during education sessions; impact on knowledge and skills; content, relevance, and significance of ACP intervention for patients, and Supportive Kidney Care (SKC) App usage. Currently HIGHway is in the recruitment stage.DiscussionEffective changes to advance care planning processes in dialysis centers can lead to institutional policy and protocol changes, providing a model for patients receiving dialysis treatment in the US. The result will be a widespread improvement in advance care planning, thereby remedying one of the current barriers to patient-centered, goal-concordant care for dialysis patients.Trial registrationThe George Washington University Protocol Record NCR213481, Honoring Individual Goals and Hopes: Implementing Advance Care Planning for Persons with Kidney Disease on Dialysis, is registered in ClinicalTrials.gov Identifier: NCT05324878 on April 11th, 2022.

Project description:IntroductionIn the US, many individuals with diabetes do not have consistent access to endocrinologists and therefore rely on primary care providers (PCPs) for their diabetes management. Project ECHO (Extension for Community Healthcare Outcomes) Diabetes, a tele-education model, was developed to empower PCPs to independently manage diabetes, including education on diabetes technology initiation and use, to bridge disparities in diabetes.MethodsPCPs (n=116) who participated in Project ECHO Diabetes and completed pre- and post-intervention surveys were included in this analysis. The survey was administered in California and Florida to participating PCPs via REDCap and paper surveys. This survey aimed to evaluate practice demographics, protocols with adult and pediatric T1D management, challenges, resources, and provider knowledge and confidence in diabetes management. Differences and statistical significance in pre- and post-intervention responses were evaluated via McNemar's tests.ResultsPCPs reported improvement in all domains of diabetes education and management. From baseline, PCPs reported improvement in their confidence to serve as the T1D provider for their community (pre vs post: 43.8% vs 68.8%, p=0.005), manage insulin therapy (pre vs post: 62.8% vs 84.3%, p=0.002), and identify symptoms of diabetes distress (pre vs post: 62.8% vs 84.3%, p=0.002) post-intervention. Compared to pre-intervention, providers reported significant improvement in their confidence in all aspects of diabetes technology including prescribing technology (41.2% vs 68.6%, p=0.001), managing insulin pumps (41.2% vs 68.6%, p=0.001) and hybrid closed loop (10.2% vs 26.5%, p=0.033), and interpreting sensor data (41.2% vs 68.6%, p=0.001) post-intervention.DiscussionPCPs who participated in Project ECHO Diabetes reported increased confidence in diabetes management, with notable improvement in their ability to prescribe, manage, and troubleshoot diabetes technology. These data support the use of tele-education of PCPs to increase confidence in diabetes technology management as a feasible strategy to advance equity in diabetes management and outcomes.

Project description:ImportanceCardiovascular diseases (CVDs) are the leading cause of disease burden in Indonesia. Implementation of effective interventions for CVD prevention is limited.ObjectiveTo evaluate whether a mobile technology-supported primary health care intervention, compared with usual care, would improve the use of preventive drug treatment among people in rural Indonesia with a high risk of CVD.Design, setting, and participantsA quasi-experimental study involving 6579 high-risk individuals in 4 intervention and 4 control villages in Malang district, Indonesia, was conducted between August 16, 2016, and March 31, 2018. Median duration of follow-up was 12.2 months. Residents 40 years or older were invited to participate. Those with high estimated 10-year risk of CVD risk (previously diagnosed CVD, systolic blood pressure [BP] >160 mm Hg or diastolic BP >100 mm Hg, 10-year estimated CVD risk of 30% or more, or 10-year estimated CVD risk of 20%-29% and a systolic BP >140 mm Hg) were followed up.InterventionsA multifaceted mobile technology-supported intervention facilitating community-based CVD risk screening with referral, tailored clinical decision support for drug prescription, and patient follow-up.Main outcomes and measuresThe primary outcome was the proportion of individuals taking appropriate preventive CVD medications, defined as at least 1 BP-lowering drug and a statin for all high-risk individuals, and an antiplatelet drug for those with prior diagnosed CVD. Secondary outcomes included mean change in BP from baseline.ResultsAmong 22 635 adults, 3494 of 11 647 in the intervention villages (30.0%; 2166 women and 1328 men; mean [SD] age, 58.3 [10.9] years) and 3085 of 10 988 in the control villages (28.1%; 1838 women and 1247 men; mean [SD] age, 59.0 [11.5] years) had high estimated risk of CVD. Of these, follow-up was completed in 2632 individuals (75.3%) from intervention villages and 2429 individuals (78.7%) from control villages. At follow-up, 409 high-risk individuals in intervention villages (15.5%) were taking appropriate preventive CVD medications, compared with 25 (1.0%) in control villages (adjusted risk difference, 14.1%; 95% CI, 12.7%-15.6%). This difference was driven by higher use of BP-lowering medication in those in the intervention villages (1495 [56.8%] vs 382 [15.7%]; adjusted risk difference, 39.4%; 95% CI, 37.0%-41.7%). The adjusted mean difference in change in systolic BP from baseline was -8.3 mm Hg (95% CI, -10.1 to -6.6 mm Hg).Conclusions and relevanceThis study found that a multifaceted mobile technology-supported primary health care intervention was associated with greater use of preventive CVD medication and lower BP levels among high-risk individuals in a rural Indonesian population.

Project description:BackgroundThe learning process in clinical placements for health care students is a multifaceted endeavor that engages numerous actors and stakeholders, including students, clinical tutors, link teachers, and academic assessors. Successfully navigating this complex process requires the implementation of tasks and mentorships that are synchronized with educational and clinical processes, seamlessly embedded within their respective contexts. Given the escalating number of students and the rising demand for health care services from the general population, it becomes imperative to develop additional tools that support the learning process. These tools aim to simplify day-to-day clinical practice, allowing a concentrated focus on value-based activities. This paper introduces a project funded by the European Commission that involves 5 European countries. The project's objective is to comprehensively outline the entire process of development and ultimately implement mobile technology in practice placements. The project tackles the existing gap by constructing tailored mobile apps designed for students, teachers, tutors, and supervisors within each participating organization. This approach leverages practice-based learning, mobile technology, and technology adoption to enhance the overall educational experience.ObjectiveThis study aims to introduce mobile technology in clinical practice placements with the goal of facilitating and enhancing practice-based learning. The objective is to improve the overall effectiveness of the process for all stakeholders involved.MethodsThe "4D in the Digitalization of Learning in Practice Placement" (4D Project) will use a mixed methods research design, encompassing 3 distinct study phases: phase 1 (preliminary research), which incorporates focus groups and a scoping review, to define the problem, identify necessities, and analyze contextual factors; phase 2 (collaborative app development), which involves researchers and prospective users working together to cocreate and co-design tailored apps; and phase 3, which involves feasibility testing of these mobile apps within practice settings.ResultsThe study's potential impact will primarily focus on improving communication and interaction processes, fostering connections among stakeholders in practice placements, and enhancing the assessment of training needs. The literature review and focus groups will play a crucial role in identifying barriers, facilitators, and factors supporting the integration of mobile technology in clinical education. The cocreation process of mobile learning apps will reveal the core values and needs of various stakeholders, including students, teachers, and health care professionals. This process also involves adapting and using mobile apps to meet the specific requirements of practice placements. A pilot study aimed at validating the app will test and assess mobile technology in practice placements. The study will determine results related to usability and design, learning outcomes, student engagement, communication among stakeholders, user behavior, potential issues, and compliance with regulations.ConclusionsHealth care education, encompassing disciplines such as medicine, nursing, midwifery, and others, confronts evolving challenges in clinical training. Essential to addressing these challenges is bridging the gap between health care institutions and academic settings. The introduction of a new digital tool holds promise for empowering health students and mentors in effectively navigating the intricacies of the learning process.International registered report identifier (irrid)DERR1-10.2196/53284.

Project description:BackgroundMost evidence-based practices (EBPs) do not find their way into clinical use, including evidence-based mobile health (mHealth) technologies. The literature offers implementers little practical guidance for successfully integrating mHealth into health care systems.ObjectiveThe goal of this research was to describe a novel decision-framing model that gives implementers a method of eliciting the considerations of different stakeholder groups when they decide whether to implement an EBP.MethodsThe decision-framing model can be generally applied to EBPs, but was applied in this case to an mHealth system (Seva) for patients with addiction. The model builds from key insights in behavioral economics and game theory. The model systematically identifies, using an inductive process, the perceived gains and losses of different stakeholder groups when they consider adopting a new intervention. The model was constructed retrospectively in a parent implementation research trial that introduced Seva to 268 patients in 3 US primary care clinics. Individual and group interviews were conducted to elicit stakeholder considerations from 6 clinic managers, 17 clinicians, and 6 patients who were involved in implementing Seva. Considerations were used to construct decision frames that trade off the perceived value of adopting Seva versus maintaining the status quo from each stakeholder group's perspective. The face validity of the decision-framing model was assessed by soliciting feedback from the stakeholders whose input was used to build it.ResultsPrimary considerations related to implementing Seva were identified for each stakeholder group. Clinic managers perceived the greatest potential gain to be better care for patients and the greatest potential loss to be cost (ie, staff time, sustainability, and opportunity cost to implement Seva). All clinical staff considered time their foremost consideration-primarily in negative terms (eg, cognitive burden associated with learning a new system) but potentially in positive terms (eg, if Seva could automate functions done manually). Patients considered safety (anonymity, privacy, and coming from a trusted source) to be paramount. Though payers were not interviewed directly, clinic managers judged cost to be most important to payers-whether Seva could reduce total care costs or had reimbursement mechanisms available. This model will be tested prospectively in a forthcoming mHealth implementation trial for its ability to predict mHealth adoption. Overall, the results suggest that implementers proactively address the cost and burden of implementation and seek to promote long-term sustainability.ConclusionsThis paper presents a model implementers may use to elicit stakeholders' considerations when deciding to adopt a new technology, considerations that may then be used to adapt the intervention and tailor implementation, potentially increasing the likelihood of implementation success.Trial registrationClinicalTrials.gov NCT01963234; https://clinicaltrials.gov/ct2/show/NCT01963234 (Archived by WebCite at http://www.webcitation.org/78qXQJvVI).

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Early findings from a project aimed at implementing mobile health technology for addiction in primary care

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