Adapting a home telemonitoring intervention for underserved Hispanic/Latino patients with type 2 diabetes: an acceptability and feasibility study.

BACKGROUND: Home telemonitoring is a promising approach to optimizing outcomes for patients with Type 2 Diabetes; however, this care strategy has not been adapted for use with understudied and underserved Hispanic/Latinos (H/L) patients with Type 2 Diabetes. METHODS: A formative, Community-Based Participatory Research approach was used to adapt a home telemonitoring intervention to facilitate acceptability and feasibility for vulnerable H/L patients. Utilizing the ADAPT-ITT framework, key stakeholders were engaged over an 8-month iterative process using a combination of strategies, including focus groups and structured interviews. Nine Community Advisory Board, Patient Advisory, and Provider Panel Committee focus group discussions were conducted, in English and Spanish, to garner stakeholder input before intervention implementation. Focus groups and structured interviews were also conducted with 12 patients enrolled in a 1-month pilot study, to obtain feedback from patients in the home to further adapt the intervention. Focus groups and structured interviews were approximately 2 hours and 30 min, respectively. All focus groups and structured interviews were audio-recorded and professionally transcribed. Structural coding was used to mark responses to topical questions in the moderator and interview guides. RESULTS: Two major themes emerged from qualitative analyses of Community Advisory Board/subcommittee focus group data. The first major theme involved intervention components to maximize acceptance/usability. Subthemes included tablet screens (e.g., privacy/identity concerns; enlarging font sizes; lighter tablet to facilitate portability); cultural incongruence (e.g., language translation/literacy, foods, actors "who look like me"); nursing staff (e.g., ensuring accessibility; appointment flexibility); and, educational videos (e.g., the importance of information repetition). A second major theme involved suggested changes to the randomized control trial study structure to maximize participation, including a major restructuring of the consenting process and changes designed to optimize recruitment strategies. Themes from pilot participant focus group/structured interviews were similar to those of the Community Advisory Board such as the need to address and simplify a burdensome consenting process, the importance of assuring privacy, and an accessible, culturally congruent nurse. CONCLUSIONS: These findings identify important adaptation recommendations from the stakeholder and potential user perspective that should be considered when implementing home telemonitoring for underserved patients with Type 2 Diabetes. TRIAL REGISTRATION: NCT03960424; ClinicalTrials.gov (US National Institutes of Health). Registered 23 May 2019. Registered prior to data collection. https://www.clinicaltrials.gov/ct2/show/NCT03960424?term=NCT03960424&draw=2&rank=1.

A Randomized Controlled Trial Comparing Telehealth Self-Management to Standard Outpatient Management in Underserved Black and Hispanic Patients Living with Heart Failure.

Background:Although the American Heart Association promotes telehealth models to improve care access, there is limited literature on its use in underserved populations. This study is the first to compare utilization and quality of life (QoL) for underserved black and Hispanic heart failure (HF) patients assigned to telehealth self-monitoring (TSM) or comprehensive outpatient management (COM) over 90 days.Methods:This randomized controlled trial enrolled 104 patients. Outcomes included emergency department (ED) visits, hospitalizations, QoL, depression, and anxiety. Binary outcomes for utilization were analyzed using chi-square or Fisher's exact test. Poisson or negative binomial regression, repeated-measures analysis of variance, or generalized estimating equations were also used as appropriate.Results:Of 104 patients, 31% were Hispanic, 69% black, 41% women, and 72% reported incomes of <$10,000/year. Groups did not differ regarding binary ED visits (relative risk [RR] = 1.37, confidence interval [CI] = 0.83-2.27), hospitalization (RR = 0.92, CI = 0.57-1.48), or length of stay in days (TSM = 0.54 vs. COM = 0.91). Number of all-cause hospitalizations was significantly lower for COM (TSM = 0.78 vs. COM = 0.55; p = 0.03). COM patients reported greater anxiety reduction from baseline to 90 days (TSM = 50-28%; COM = 57-13%; p = 0.05).Conclusions:These findings suggest that TSM is not effective in reducing utilization or improving QoL for underserved patients with HF. Future studies are needed to determine whether TSM can be effective for populations facing health care access issues.

Ensuring fidelity: key elements to consider in disseminating a diabetes telemanagement program for underserved Hispanic/Latinos living with type 2 diabetes.

Background: The Hispanic/Latino population has greater risk (estimated >50%) of developing type 2 diabetes (T2D) and developing it at a younger age. The American Diabetes Association estimates costs of diagnosed diabetes in 2017 was $327 billion; with medical costs 2.3x higher than patients without diabetes. The purpose of this manuscript is to describe the methodology utilized in a randomized controlled trial aimed at evaluating the efficacy of a diabetes telemanagement (DTM) program for Hispanic/Latino patients with T2D. The intent is to provide information for future investigators to ensure that this study can be accurately replicated. Methods: This study was a randomized controlled trial with 240 participants. Eligible patients (Hispanic/Latino, aged 18+, living with T2D) were randomized to Comprehensive Outpatient Management (COM) or DTM. DTM was comprised of usual care, including routine clinic visits every three months, as well as: Biometrics (a tablet, blood glucose meter, blood pressure monitor, and scale); Weekly Video Visits (facilitated in the patient's preferred language); and Educational Videos (including culturally congruent diabetes self-management education and quizzes). COM consisted of usual care including routine clinic visits every three months. For this study, COM patients received a glucometer, glucose test strips, and lancets. Establishing a therapeutic nurse-patient relationship was a fundamental component of our study for both groups. First contact (post-enrollment) centered on ensuring that patients and caregivers understood the program, building trust and rapport, creating a non-judgmental environment, determining language preference, and establishing scheduling availability (including evenings and weekends). DTM were provided with a tablet which allowed for self-paced education through videos and weekly video visits. The research team and Community Advisory Board identified appropriate educational video content, which was incorporated in diabetes educational topics. Video visits allowed us to assess patient involvement, motivation, and nonverbal communication. Communicating in Spanish, and awareness of diverse Hispanic/Latino backgrounds was critical, as using relevant and commonly-used terms can increase adherence and improve outcomes. Shared decision-making was encouraged to make realistic health care choices. Conclusion: Key elements discussed above provide a framework for future dissemination of an evidence-based DTM intervention to meet the needs of underserved Hispanic/Latino people living with T2D.

Bayesian learning and predictability in a stochastic nonlinear dynamical model.

Bayesian inference methods are applied within a Bayesian hierarchical modeling framework to the problems of joint state and parameter estimation, and of state forecasting. We explore and demonstrate the ideas in the context of a simple nonlinear marine biogeochemical model. A novel approach is proposed to the formulation of the stochastic process model, in which ecophysiological properties of plankton communities are represented by autoregressive stochastic processes. This approach captures the effects of changes in plankton communities over time, and it allows the incorporation of literature metadata on individual species into prior distributions for process model parameters. The approach is applied to a case study at Ocean Station Papa, using particle Markov chain Monte Carlo computational techniques. The results suggest that, by drawing on objective prior information, it is possible to extract useful information about model state and a subset of parameters, and even to make useful long-term forecasts, based on sparse and noisy observations.

COVID-19 stressors for Hispanic/Latino patients living with type 2 diabetes: a qualitative study.

Background and aim: During the early stages of the COVID-19 pandemic, nationwide lockdowns caused disruption in the diets, physical activities, and lifestyles of patients with type 2 diabetes. Previous reports on the possible association between race/ethnicity, COVID-19, and mortality have shown that Hispanic/Latino patients with type 2 diabetes who are socioeconomically disadvantaged are disproportionately affected by this novel virus. The aim of this study was to explore stressors associated with changes in diabetes self-management behaviors. Our goal was to highlight the health disparities in these vulnerable racial/ethnic minority communities and underscore the need for effective interventions. Methods and participants: Participants were enrolled in part of a larger randomized controlled trial to compare diabetes telehealth management (DTM) with comprehensive outpatient management (COM) in terms of critical patient-centered outcomes among Hispanic/Latino patients with type 2 diabetes. We conducted a thematic analysis using patient notes collected from two research nurses between March 2020 and March 2021. Two authors read through the transcripts independently to identify overarching themes. Once the themes had been identified, both authors convened to compare themes and ensure that similar themes were identified within the transcripts. Any discrepancies were discussed by the larger study team until a consensus was reached. Results: Six themes emerged, each of which can be categorized as either a source or an outcome of stress. Sources of stress associated with the COVID-19 pandemic were (1) fear of contracting COVID-19, (2) disruptions from lockdowns, and (3) financial stressors (e.g., loss of income). Outcomes of COVID-19 stressors were (1) reduced diabetes management (e.g., reduced diabetes monitoring and physical activity), (2) suboptimal mental health outcomes (e.g., anxiety and depression), and (3) outcomes of financial stressors. Conclusion: The findings indicated that underserved Hispanic/Latino patients with type 2 diabetes encountered a number of stressors that led to the deterioration of diabetes self-management behaviors during the pandemic.

Universal probabilistic programming offers a powerful approach to statistical phylogenetics.

Statistical phylogenetic analysis currently relies on complex, dedicated software packages, making it difficult for evolutionary biologists to explore new models and inference strategies. Recent years have seen more generic solutions based on probabilistic graphical models, but this formalism can only partly express phylogenetic problems. Here, we show that universal probabilistic programming languages (PPLs) solve the expressivity problem, while still supporting automated generation of efficient inference algorithms. To prove the latter point, we develop automated generation of sequential Monte Carlo (SMC) algorithms for PPL descriptions of arbitrary biological diversification (birth-death) models. SMC is a new inference strategy for these problems, supporting both parameter inference and efficient estimation of Bayes factors that are used in model testing. We take advantage of this in automatically generating SMC algorithms for several recent diversification models that have been difficult or impossible to tackle previously. Finally, applying these algorithms to 40 bird phylogenies, we show that models with slowing diversification, constant turnover and many small shifts generally explain the data best. Our work opens up several related problem domains to PPL approaches, and shows that few hurdles remain before these techniques can be effectively applied to the full range of phylogenetic models.

Comparative Analysis of Dengue and Zika Outbreaks Reveals Differences by Setting and Virus.

The pacific islands of Micronesia have experienced several outbreaks of mosquito-borne diseases over the past decade. In outbreaks on small islands, the susceptible population is usually well defined, and there is no co-circulation of pathogens. Because of this, analysing such outbreaks can be useful for understanding the transmission dynamics of the pathogens involved, and particularly so for yet understudied pathogens such as Zika virus. Here, we compared three outbreaks of dengue and Zika virus in two different island settings in Micronesia, the Yap Main Islands and Fais, using a mathematical model of transmission dynamics and making full use of commonalities in disease and setting between the outbreaks. We found that the estimated reproduction numbers for Zika and dengue were similar when considered in the same setting, but that, conversely, reproduction number for the same disease can vary considerably by setting. On the Yap Main Islands, we estimated a reproduction number of 8.0-16 (95% Credible Interval (CI)) for the dengue outbreak and 4.8-14 (95% CI) for the Zika outbreak, whereas for the dengue outbreak on Fais our estimate was 28-102 (95% CI). We further found that the proportion of cases of Zika reported was smaller (95% CI 1.4%-1.9%) than that of dengue (95% CI: 47%-61%). We confirmed these results in extensive sensitivity analysis. They suggest that models for dengue transmission can be useful for estimating the predicted dynamics of Zika transmission, but care must be taken when extrapolating findings from one setting to another.

Labor analytics software can help control labor costs.

One of the largest costs in healthcare organizations is labor. As volume of activity fluctuates, the labor supply needs to be adjusted appropriately. Having an appropriate quantity and skill mix of full- and part-time employees affects labor costs per hour and labor efficiency, two labor-cost control points that department managers need to monitor to make effective hiring decisions. Managers can use software applications for operating budgets, productivity monitoring, position control, and staffing/scheduling to manage labor expenses. Knowing the type of information each of these cost-control tools provides is critical to making effective decisions related to labor expenses. Because of their unique expertise, healthcare financial managers can serve as a resource to help the organization's department managers manage labor costs.

CASASTART: a community-based, school-centered intervention for high-risk youth.

During the past decade, increasing numbers of drug- and alcohol-related delinquency cases have entered the juvenile justice system. The majority of these young people face multiple challenges and risks, yet have few resources to mitigate these risks. This article suggests that the skills, competencies and supports, and protective factors needed to help young people grow into healthy adulthood are not readily available to high-risk youth. We offer lessons from the development, implementation, and institutionalization of one promising model of an evidence-based, community-, and school-centered program for high-risk youth (CASASTART). The experience with this program thus far suggests that program models that encompass a youth development, strength-based, and community-focused approach can intervene successfully with many high-risk youth and their families, reduce use of drugs and alcohol, reduce violent crime, and achieve funding and programmatic stability.