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Background: Gaps in accessibility and communication hinder diabetes care in poor communities. Combining mobile health (mHealth) and community health workers (CHWs) into models to bridge these gaps has great potential but needs evaluation. Objective: To evaluate a mHealth-based, Participant-CHW-Clinician feedback loop in a real-world setting. Design: Quasi-experimental feasibility study with intervention and usual care (UC) groups. Participants: A total of 134 participants (n = 67/group) who were all low-income, uninsured Hispanics with or at-risk for type 2 diabetes. Intervention: A 15-month study with a weekly to semimonthly mHealth Participant-CHW-Clinician feedback loop to identify participant issues and provide participants monthly diabetes education via YouTube. Main Measures: We used pre-defined feasibility measures to evaluate our intervention: (a) implementation, the execution of feedback loops to identify and resolve participant issues, and (b) efficacy, intended effects of the program on clinical outcomes (baseline to 15-month HbA1c, systolic blood pressure (SBP), diastolic blood pressure (DBP), and weight changes) for each group and their subgroups (at-risk; with diabetes, including uncontrolled (HbA1c ≥ 7%)). Key Results: CHWs identified 433 participant issues (mean = 6.5 ± 5.3) and resolved 91.9% of these. Most issues were related to supplies, 26.3% (n = 114); physical health, 23.1% (n = 100); and medication access, 20.8% (n = 90). Intervention participants significantly improved HbA1c (− 0.51%, p = 0.03); UC did not (− 0.10%, p = 0.76). UC DBP worsened (1.91 mmHg, p < 0.01). Subgroup analyses revealed HbA1c improvements for uncontrolled diabetes (intervention: − 1.59%, p < 0.01; controlled: − 0.72, p = 0.03). Several variables for UC at-risk participants worsened: HbA1c (0.25%, p < 0.01), SBP (4.05 mmHg, p < 0.01), DBP (3.21 mmHg, p = 0.01). There were no other significant changes for either group. Conclusions: A novel mHealth-based, Participant-CHW-Clinician feedback loop was associated with improved HbA1c levels and identification and resolution of participant issues. UC individuals had several areas of clinical deterioration, particularly those at-risk for diabetes, which is concerning for progression to diabetes and disease-related complications. Clinical Trial: NCT03394456, accessed at https://clinicaltrials.gov/ct2/show/NCT03394456 [ABSTRACT FROM AUTHOR]

Background: Increasingly, women are serving in the military and seeking care at the Veterans Health Administration (VHA). Women veterans face unique challenges and barriers in seeking mental health (MH) care within VHA. VA Video Connect (VVC), which facilitates video-based teleconferencing between patients and providers, can reduce barriers while maintaining clinical effectiveness.Objective: Primary aims were to examine gender differences in VVC use, describe changes in VVC use over time (including pre-COVID and 6 months following the beginning of COVID), and determine whether changes over time differed by gender.Design: A retrospective cohort investigation of video-to-home telehealth for MH care utilization among veterans having at least 1 MH visit from October 2019 to September 2020.Participants: Veterans (236,268 women; 1,318,024 men).Interventions (if Applicable): VVC involves face-to-face, synchronous, video-based teleconferencing between patients and providers, enabling care at home or another private location.Main Measures: Percentage of MH encounters delivered via VA Video Connect.Key Results: Women veterans were more likely than men to have at least 1 VVC encounter and had a greater percentage of MH care delivered via VVC in FY20. There was an increase in the percentage of MH encounters that were VVC over FY20, and this increase was greater for women than men. Women veterans who were younger than 55 (compared to those 55 and older), lived in urban areas (compared to those in rural areas), or were Asian (compared to other races) had a greater percentage of MH encounters that were VVC since the start of the pandemic, controlling for the mean percentage of VVC MH encounters in the 6 months pre-pandemic.Conclusions: VVC use for MH care is greater in women veterans compared to male veterans and may reduce gender-specific access barriers. Future research and VVC implementation efforts should emphasize maximizing patient choice and satisfaction. [ABSTRACT FROM AUTHOR]

Background: We previously found that a 6-month multidimensional diabetes program, TIME (Telehealth-Supported, Integrated Community Health Workers, Medication-Access) resulted in improved clinical outcomes. Objective: To follow TIME participant clinical outcomes for 24 months Participants: Low-income Latino(a)s with type 2 diabetes Design and Intervention: We collected post-intervention clinical data for five cohorts (n = 101, mean n = 20/cohort) who participated in TIME programs from 2018 to 2020 in Houston, Texas. Main Measures: We gathered HbA1c (primary outcome), weight, body mass index (BMI), and blood pressure data at baseline, 6 months (intervention end), and semiannually thereafter until 24 months after baseline to assess sustainability. We also evaluated participant loss to follow-up until 24 months. Key Results: Participants decreased HbA1c levels during the intervention (p < 0.0001) and maintained these improvements at each timepoint from baseline to 24 months (p range: < 0.0001 to 0.015). Participants reduced blood pressure levels during TIME and maintained these changes at each timepoint from baseline until 18 months (systolic p range < 0.0001 to 0.0005, diastolic p range: < 0.0001 to 0.008) but not at 24 months (systolic: p = 0.065; diastolic: p = 0.85). There were no significant weight changes during TIME or post-intervention: weight (p range = 0.07 to 0.77), BMI (p range = 0.11 to 0.71). Attrition rates (loss to follow-up during the post-intervention period) were 5.9% (6 months), 24.8% (12 months), 35.6% (18 months), and 41.8% (24 months). Conclusions: It is possible for vulnerable populations to maintain long-term glycemic and blood pressure improvements using a multiple dimensional intervention. Attrition rates rose over time but show promise given the majority of post-intervention timepoints occurred during the COVID-19 pandemic when low-income populations were most susceptible to suboptimal healthcare access. Future studies are needed to evaluate longitudinal outcomes of diabetes interventions conducted by local clinics rather than research teams. [ABSTRACT FROM AUTHOR]

Background: Given its widespread dissemination across primary care, the Veterans Health Administration (VA) is an ideal setting to examine the impact of the patient-centered medical home (PCMH) on diabetes outcomes.Objective: To assess the impact of PCMH implementation on diabetes outcomes among patients receiving care in the Veterans Health Administration.Design: Retrospective cohort analysis and multilevel logistic regression.Patients: Twenty thousand eight hundred fifty-eight patients in one Midwest VA network who had a diabetes diagnosis in both 2009 and 2012 and who received primary care between October 1, 2008 and September 30, 2009.Main Measures: Glycemic and lipid control using VA quality indicators [hemoglobin (Hb) A1c < 9%, low-density lipoprotein cholesterol (LDL-C) < 100 mg/dL].Key Results: Odds of glycemic control were lower in 2012 than 2009 (OR = 0.72, 95% CI = 0.67-0.77, p  < 0.001), and this change in control over time varied by race (OR of the interaction between time and race = 1.18, 95% CI = 1.02-1.36, p  = 0.028). While the disparity in glycemic control between white and black patients persisted post-PCMH, the magnitude of the disparity was smaller in 2012 compared to 2009 (2012: OR = 1.32, 95% CI = 1.18-1.47, p  < 0.0001 and 2009: OR = 1.59, 95% CI = 1.39-1.82, p  < 0.0001). Odds of lipid control did not significantly change between 2009 and 2012 and change did not vary by race and/or gender.Conclusions: Although there were no significant improvements in odds of lipid control, and odds of glycemic control decreased following PCMH implementation, there was evidence of reduced racial disparities in glycemic control post-PCMH implementation. [ABSTRACT FROM AUTHOR]

Background: Clinical-performance measurement has helped improve the quality of health-care; yet success in attaining high levels of quality across multiple domains simultaneously still varies considerably. Although many sources of variability in care quality have been studied, the difficulty required to complete the clinical work itself has received little attention.Objective: We present a task-based methodology for evaluating the difficulty of clinical-performance measures (CPMs) by assessing the complexity of their component requisite tasks.Design: Using Functional Job Analysis (FJA), subject-matter experts (SMEs) generated task lists for 17 CPMs; task lists were rated on ten dimensions of complexity, and then aggregated into difficulty composites.Participants: Eleven outpatient work SMEs; 133 VA Medical Centers nationwide.Main Measures: Clinical Performance: 17 outpatient CPMs (2000-2008) at 133 VA Medical Centers nationwide. Measure Difficulty: for each CPM, the number of component requisite tasks and the average rating across ten FJA complexity scales for the set of tasks comprising the measure.Key Results: Measures varied considerably in the number of component tasks (M = 10.56, SD = 6.25, min = 5, max = 25). Measures of chronic care following acute myocardial infarction exhibited significantly higher measure difficulty ratings compared to diabetes or screening measures, but not to immunization measures ([Formula: see text] = 0.45, -0.04, -0.05, and -0.06 respectively; F (3, 186) = 3.57, p = 0.015). Measure difficulty ratings were not significantly correlated with the number of component tasks (r = -0.30, p = 0.23).Conclusions: Evaluating the difficulty of achieving recommended CPM performance levels requires more than simply counting the tasks involved; using FJA to assess the complexity of CPMs' component tasks presents an alternate means of assessing the difficulty of primary-care CPMs and accounting for performance variation among measures and performers. This in turn could be used in designing performance reward programs, or to match workflow to clinician time and effort. [ABSTRACT FROM AUTHOR]