COMBINING IMPLEMENTATION SCIENCE AND HUMANCENTERED DESIGN TO EXAMINE USABILITY OF A DEPRESSION SCREENING SHARED DECISION-MAKING TOOL AMONG CORONARY HEART DISEASE PATIENTS

BACKGROUND: Only 30% of coronary heart disease (CHD) patients are screened and treated for depression, far below general population rates. Utilizing a theoretical framework based on the Behavior Change Wheel integrated with patient-centered design processes, we conducted a second round of postcoronavirus disease 2019 (COVID-19) beta-phase testing of a web-based, electronic shared decision-making (eSDM) tool for depression screening and follow-up in patients with CHD. METHODS: We recruited English-speaking patients who had internal medicine or cardiology clinic appointments from October 2020-January 2021. All participants were aged ≥21 years with CHD and a diagnosis of and/or positive screen for depression by the patient health questionnaire (PHQ)-2 and/or -8. Think aloud usability sessions with participants verbalizing their thoughts on the eSDM tool were conducted remotely. Sessions lasted approximately one hour. Pre-and post-session questionnaires assessed comfort, ease-of-use of the tool, and perceived barriers to success, and included the Decisional Conflict Scale (DCS) and System Usability Scale (SUS). Think aloud and survey feedback were analyzed for recurring themes. RESULTS: Four patients participated before we reached saturation (25% aged > 65;75% male;75% White). The average SUS score was 77.00 (C, or “Good” on the scale). Three of four participants found the tool easy to use and straightforward, and none expressed confusion/difficulty utilizing the tool. Only 25% felt the tool alone was sufficient to make informed treatment decisions (pre-post decisional conflict increased from 21.3 to 27.5). Postsession, we observed lower perceived barriers to treatment related to access/ coordination (75% vs. 50%), stigma/motivation/efficacy (100% vs. 75%) but not in cost of treatment (50% vs. 50%) or time/travel (50% vs 50%). Three of four participants found the tool's video depicting a patient's depression treatment journey after experiencing a heart attack helpful but two found it retraumatizing. Finally, all participants indicated they would spend time reading about cardiac wellness topics at the end of the tool. CONCLUSIONS: Using an innovative theory-based approach to usability testing, we found high acceptability and usability of our eSDM tool but highlighted several features that will need to be optimized to improve postCOVID-19 adoption rates (e.g., traumatization considerations and increased decisional support). Our study adds further evidence to concerns that selfadministered eSDM tools may be insufficient without provider and clinician level intervention components. Enhancing a tool's features may improve its usefulness to patients, ultimately improving patient and provider adoption.

Association between telemedicine use and diabetes risk factor assessment and control in a primary care network.

PURPOSE: Our study examined whether telemedicine use in primary care is associated with risk factor assessment and control for patients with diabetes mellitus. METHODS: This was a retrospective, 1:1 propensity score matched cohort study conducted in a primary care network between February 2020 and December 2020. Participants included patients with diabetes mellitus, ages 18 to 75. Exposure of interest was any telemedicine visit. We determined whether hemoglobin A1c (HbA1c), blood pressure (BP) and low-density lipoprotein cholesterol (LDL-C) were assessed for each patient. For each risk factor, we also determined whether the risk factor was controlled when they were assessed (i.e., last HbA1c < 8.0%, BP < 130/80 mmHg, LDL-C < 100 mg/dL). RESULTS: After 1:1 propensity score matching, we identified 1,824 patients with diabetes during the study period. Telemedicine use was associated with a lower proportion of patients with all three risk factors assessed (162/912 [18%], versus 408/912 [45%], p < 0.001). However, when individual risk factors were assessed, telemedicine use did not impact risk factor control. When compared with patients with in-person visit only, the odds ratio (OR) for HbA1c < 8% was 1.04 (95% CI 0.74 to 1.46, p = 0.23) for patients with any telemedicine visit. Similarly, the OR for BP < 130/80 mmHg was 1.08 (95% CI 0.85-1.36 p = 0.53), and the OR for LDL-C < 100 mg/dL was 1.14 (95% CI 0.76-1.72, p = 0.52). CONCLUSIONS: Telemedicine use was associated with gaps in risk factor assessment for patients with diabetes during the COVID-19 pandemic, but had limited impact on whether risk factors were controlled.

Impact of telemedicine use on blood pressure control during the covid-19 pandemic

Background: Telemedicine use vastly expanded during the Covid-19 pandemic, with uncertain impact on cardiovascular care. quality. Objectives: To examine the association between telemedicine use and blood pressure (BP) control. Methods: This is a retrospective cohort study of 32,727 adult patients with hypertension (HTN) seen in primary care and cardiology clinics at an urban, academic medical center from February to December, 2020. The primary outcome was poor BP control, defined as having no BP recorded OR if the last recorded BP was ≥140/90 mmHg. Multivariable logistic regression was used to assess the association between telemedicine use during the study period (none, 1 telemedicine visit, 2+ telemedicine visits) and poor BP control, adjusting for demographic and clinical characteristics. Results: During the study period, no BP was recorded for 486/20,745 (2.3%) patients with in-person visits only, for 1,863/6,878 (27.1%) patients with 1 telemedicine visit, and for 1,277/5,104 (25.0%) patients with 2+ telemedicine visits. After adjustment, telemedicine use was associated with poor BP control (odds ratio [OR], 2.06, 95% confidence interval [CI] 1.94 to 2.18, p<0.001 for 1 telemedicine visit, and OR 2.49, 95% CI 2.31 to 2.68, p<0.001 for 2+ telemedicine visits;reference, in-person visit only). This effect disappears when analysis was restricted to patients with at least one recorded BP (OR 0.89, 95% CI 0.83 to 0.95, p=0.001 for 1 telemedicine visit, and OR 0.91, 95% CI 0.83 to 0.99, p=0.03 for 2+ telemedicine visits). Conclusions: BP is less likely to be recorded during telemedicine visits, but telemedicine use does not negatively impact BP control when BP is recorded.