Mary A. Whooley

Background: Depression, a known comorbidity in coronary heart disease (CHD), is associated with adverse cardiac events, mortality, symptom burden, physical limitation, and poor quality of life (QOL). Evidence has shown that depression impedes self-care behaviors, including physical activity. Similarly, regular physical activity has been shown to lessen depressive symptoms and improve cardiovascular health. Objective: The aim of our study was to investigate the direct effect of depressive symptoms on physical activity and QOL. We also sought to investigate the mediator effects of physical activity and depressive symptoms on QOL and to test the moderator effects of depressive symptoms on physical activity and QOL. Methods: In this cross-sectional study, 20-year follow-up survey data were collected from 126 survivors from the Heart and Soul prospective cohort study. A mediation test was conducted using the steps described by Baron and Kenny. Results: Physical activity significantly predicted QOL (β = 0.13, P = .02) and significantly predicted depressive symptoms (β = −0.19, P < .001). Depressive symptoms significantly predicted QOL (β = −0.76, P < .0001). The average causal mediation effect was statistically significant (0.15, P < .001). Depression was not a moderator of physical activity and QOL. Conclusions: This study demonstrated that depression mediated the effect of physical activity on QOL. Identifying and treating depressive symptoms simultaneously while addressing physical activity may be of importance to improving QOL in patients with chronic CHD.

Background: Heart failure (HF) affects 6.7 million American adults and is associated with significant morbidity and mortality. Cardiac rehabilitation (CR) is a behavior modification program recommended to improve health outcomes in patients with HF. In 2014, Medicare began covering facility‐based CR for patients with stable HF, and some Veterans Affairs (VA) facilities began offering home‐based CR. Methods: We conducted an observational study to assess CR participation among patients with stable HF and patient characteristics associated with participation. National electronic health record data from the VA and claims data from a 5% Medicare sample were used to identify patients using International Classification of Diseases, Ninth Revision ( ICD‐9 ) or Tenth Revision ( ICD‐10 ) codes. CR participation was determined using Current Procedural Terminology codes and VA stop codes during the 12 months following HF diagnosis. A multivariable logistic regression was constructed to identify patient characteristics associated with participation. Results: From 2012 to 2022, VA participation increased from 7.4% to 10.4% and Medicare decreased from 7.4% to 5.1%. From 2016 to 2022, 13.2% of veterans and 6.7% of Medicare beneficiaries with stable HF participated in CR. Older age, female sex, and non‐White race were associated with lower participation, and comorbid ischemic heart disease was associated with greater participation (odds ratio [OR], 1.48 [95% CI, 1.45–1.52] in VA; OR, 2.69 [95% CI, (2.62–2.78] in Medicare). Conclusions: Following the VA's implementation of home‐based CR and Medicare's facility‐based CR coverage for stable HF, participation increased among veterans but not among Medicare beneficiaries. Lower participation was observed among women and non‐White patients. These findings suggest that covering home‐based CR could improve participation among Medicare beneficiaries.

Objective: The American College of Rheumatology recommends HLA‐B*58:01 allele testing before the initiation of allopurinol, specifically among Asian and African American/Black patients, due to their increased risk for severe hypersensitivity reactions. However, testing rates remain low at many health care facilities. This study aimed to determine whether the introduction of a clinician‐facing dashboard, with or without a best practice alert (BPA), would increase HLA‐B*58:01 testing rates among eligible patients at two VA medical centers. Methods: In October 2022, we launched a clinician‐facing dashboard that displayed HLA‐B*58:01 testing results for all patients prescribed allopurinol at two VA medical centers. In January 2023, we added a synchronous BPA that appeared at one of the two medical centers whenever a provider entered a prescription for allopurinol. The BPA was presented as blue text on the medication order entry form and stated “HLA‐B*58:01 genotyping recommended before rx for Asian or African American.” Using data from the electronic health record, we compared the change in proportion of patients receiving allopurinol prescriptions who had HLA‐B*58:01 genotype testing done after implementation of the dashboard (±BPA) at the two VA medical centers. Results: From October 2022 through December 2023, the number of Asian or African American/Black patients who filled one or more prescriptions for allopurinol was 262 at the BPA + dashboard site and 330 at the dashboard only site. The percentage of Asian or African American/Black patients who had HLA‐B*58:01 testing before or during the month allopurinol was prescribed increased from 8.8% in October 2022 to 35.5% in December 2023 at the dashboard + BPA site and from 2.1% to 4.5% at the dashboard only site ( P < 0.0001 for difference in difference). The cumulative percentage of prescribers whose patient(s) completed HLA‐B*58:01 testing increased from 11.7% to 46.8% at the dashboard + BPA site and from 6.9% to 10.8% at the dashboard only site ( P < 0.0001 for difference in difference). Conclusion: Implementing a dashboard plus simple text BPA was associated with a greater increase in the proportion of patients who completed guideline‐recommend HLA‐B*58:01 testing compared to implementing a dashboard alone. image

BACKGROUND Allopurinol carries a risk of severe cutaneous adverse reactions among patients with the HLA-B58:01 allele, yet uptake of guideline-recommended testing remains low in clinical practice. OBJECTIVE To develop, implement, and evaluate a national, electronic health record (EHR)-based dashboard to promote HLA-B58:01 testing among allopurinol users at risk for severe cutaneous adverse reactions within the Veterans Health Administration (VHA). METHODS This observational study used structured laboratory and prescribing data from the VHA Corporate Data Warehouse to identify allopurinol users across 56 VA facilities between October 2022 and April 2024. The dashboard was built in Microsoft PowerBI and deployed nationally in April 2023. We applied a two-group interrupted time series (ITS) design to evaluate the association between facility-level dashboard engagement and completion of HLA-B58:01 testing among Veterans prescribed allopurinol who self-identified as Asian or African American. Facilities were categorized as high or low engagement based on the proportion of post-launch weeks with at least one recorded dashboard session (≥20% vs. <20%). Weekly testing completion rates were calculated for each facility using structured lab result fields. Dashboard use was measured through PowerBI activity logs. Facilities were excluded if they participated in pilot testing, used the Cerner EHR, lacked structured test result fields, or had no recorded dashboard sessions. RESULTS The study included 56 facilities, of which one third were identified as high engagement facilities. A total of 294 unique individuals had accessed the dashboard at least once during the study period across all facilities. The median (IQR) number of allopurinol users at baseline was 312 (115 - 625). By week 80, the overall rate increased to 3.3% from 1.8%, with greater improvements at high-engagement facilities (from 3.4% to 5.7%) than at low-engagement facilities (from 1.2% to 2.4%). In ITS analysis, the weekly post-intervention increase in testing was significantly higher at high-engagement sites compared to low-engagement sites (0.032 vs. 0.004 percentage points/week; between-group difference 0.027 percentage points/week; p = 0.03). CONCLUSIONS National implementation of an EHR-based dashboard was associated with increased HLA-B58:01 testing among allopurinol users in high-risk racial groups, although overall testing remained infrequent. Greater engagement with the dashboard was linked to more substantial gains, highlighting the potential of scalable health IT tools to improve medication safety and address pharmacogenomic disparities across integrated healthcare systems. Although testing rose modestly after rollout, overall rates remained low, indicating that further strategies are required to align testing practices with guidelines.

Adoption of a common data model (CDM), such as the Observational Medical Outcomes Partnership (OMOP) CDM, is a critical component of health information exchange, but the extent to which CDMs facilitate patient-level interoperability is unclear. We sought to determine the feasibility of using a CDM for health information exchange between two healthcare organizations.We executed a single Structured Query Language (SQL) query on OMOP-transformed data from the University of California, San Francisco (UCSF) and the San Francisco VA Healthcare System for five patients.The SQL query was successfully executed, and complementary healthcare information was obtained for five of five patients, but interoperability was limited by (1) lack of uniform patient identifiers, (2) use of different coding vocabularies, and (3) variations in mapping of source data to the CDM.Although transformation of EHR data to a CDM can facilitate health information exchange, our study suggests that patient-level interoperability of a CDM may require further alignment of both semantics and syntax.

Background: Patients with cardiovascular implantable electronic devices (CIEDs) typically attend in-person CIED clinic visits at least annually, paired with remote monitoring (RM). As the CIED data available through in-person CIED clinic visits and RM are nearly identical, the 2023 Heart Rhythm Society expert consensus statement introduced “alert-based RM,” an RM-first approach where patients with CIEDs that are consistently and continuously connected to RM, in the absence of recent alerts and other cardiac comorbidities, could attend in-person CIED clinic visits every 24 months or ultimately only as clinically prompted by actionable events identified on RM. However, there is no published information about patient and clinician perspectives on barriers and facilitators to such an RM-first care model. Objective: We aimed to understand patient and clinician perspectives about an RM-first care model for CIED care. Methods: We interviewed 40 rural veteran patients who were experienced with RM with CIEDs and 22 CIED clinicians who were experienced in using RM regarding barriers and facilitators to an RM-first care model. We conducted a reflexive thematic analysis of interviews. Two authors familiarized themselves with the dataset and generated separate codebooks based on the interview guides and inductively coded notes. These 2 authors met and reviewed each other’s codes, sought additional author input, and resolved differences before 1 author coded the remaining interviews and developed candidate themes. These themes were refined, named, and supported with quotations. Results: Patients expressed interest in an RM-first approach, to reduce the burden of long travel times, sometimes in inclement weather, and to enable clinicians to provide care for other patients. However, many preferred routine in-person visits; reasons included a skepticism of the capabilities of RM, a sense that in-person visits provided superior care, and enjoyment of in-person patient-clinician relationships. Clinicians were interested in RM-first care, especially for stable, RM-adherent patients who were not device-dependent. Clinicians most frequently cited the benefit of reducing patient travel burden as well as optimizing clinic space and time to focus on other care such as reviewing routine RM transmissions, but also noted barriers including lack of in-person assessment, patient-perceived diminution of the patient-clinician relationship, possible loss to follow-up, and technological difficulties. Clinicians felt that an RM-first care model should be evaluated for success based on patient satisfaction and assessment of timely addressing of rhythm issues to prevent adverse outcomes. Most clinicians believed that RM-first care represented the future of CIED care. Conclusions: Both patients and CIED clinicians interviewed who were experienced in using RM were open to an RM-first care model that reduces in-person visits but reported some barriers to solely relying on RM and possible diminution of the patient-clinician relationship. Implementation of new RM recommendations will require attention to these perceptions and prioritization of patient-centered approaches.

Objective: To develop, deploy, and evaluate a national, electronic health record (EHR)‐based dashboard to support safe prescribing of biologic and targeted synthetic disease‐modifying agents (b/tsDMARDs) in the United States Veterans Affairs Healthcare System (VA).Data Sources and Study Setting: We extracted and displayed hepatitis B (HBV), hepatitis C (HCV), and tuberculosis (TB) screening data from the EHR for users of b/tsDMARDs using PowerBI (Microsoft) and deployed the dashboard to VA facilities across the United States in 2022; we observed facilities for 44 weeks post‐deployment.Study Design: We examined the association between dashboard engagement by healthcare personnel and the percentage of patients with all screenings complete (HBV, HCV, and TB) at the facility level using an interrupted time series. Based on frequency of sessions, facilities were grouped into high‐ and low/none‐engagement categories. We modeled changes in complete screening pre‐ and post‐deployment of the dashboard.Data Collection Methods: All VA facilities were eligible for inclusion; excluded facilities participated in design of the dashboard or had p = 0.01).Conclusions: We observed significant improvements in screening for latent infections among facilities with high engagement with the dashboard, compared with those with fewer sessions.

Background. Network motif analysis is a technique used to explore recurrent and statistically significant subgraphs within a network. Applying a motif analysis to the complex network of inflammation and depression may yield nuanced insight into the specific interaction mechanisms between inflammatory markers and individual depression symptoms, which is our aim. Methods. This cross-sectional study is based on patients with stable coronary heart disease (CHD). A partial correlation network was initially constructed to link inflammatory markers, including C-reactive protein (CRP), Interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), monocyte chemoattractant protein-1 (MCP-1), individual depression symptoms, and covariates. A network-centric approach searched all possible non-isomorphic subgraph patterns of size k = 4 in the network. Results. Although CRP, IL-6, and TNF-α displayed an insignificant association with specific depression symptoms, the motif analysis revealed various subgraph patterns of interactions between depression symptoms associated with MCP-1. Generally, MCP-1 formed a closed loop with psychomotor problems and sleep disturbances, and this configuration was connected in various forms with other symptoms, particularly cognitive (e.g., feelings of worthlessness, concentration difficulty, and suicidal ideation) and neurovegetative/somatic (e.g., appetite changes and fatigue) symptoms. Moreover, MCP-1 was frequently associated with a closed-loop triangle comprising cognitive and neurovegetative/somatic symptoms but not with mood symptoms (e.g., loss of interest and feelings of sadness). Conclusions. The findings provide insight into how MCP-1 may be involved in the pathology of depression among patients with stable CHD in a more precise manner. This study also proposes future directions for research on depression.

Background: Social distancing from the COVID-19 pandemic may have decreased engagement in cardiac rehabilitation (CR) and may have had possible consequences on post-CR exercise maintenance. The increased use of technology as an adaptation may benefit post-CR participants via wearables and social media. Thus, we sought to explore the possible relationships of both the pandemic and technology on post-CR exercise maintenance. Objective: This study aimed to (1) understand CR participation during the COVID-19 pandemic, (2) identify perceived barriers and facilitators to physical activity after CR completion, and (3) assess willingness to use technology and social media to support physical activity needs among older adults with cardiovascular disease. Methods: We recruited participants aged 55 years and older in 3 different CR programs offered at both public and private hospitals in Northern California. We conducted individual interviews on CR experiences, physical activity, and potential for using technology. We used thematic analysis to synthesize the data. Results: In total, 22 participants (n=9, 41% female participants; mean age 73, SD 8 years) completed in-depth interviews. Themes from participants’ feedback included the following: (1) anxiety and frustration about the wait for CR caused by COVID-19 conditions, (2) positive and safe participant experience once in CR during the pandemic, (3) greater attention needed to patients after completion of CR, (4) notable demand for technology during the pandemic and after completion of CR, and (5) social media networking during the CR program considered valuable if training is provided. Conclusions: Individuals who completed CR identified shared concerns about continuing physical activity despite having positive experiences during the CR program. There were significant challenges during the pandemic and heightened concerns for safety and health. The idea of providing support by leveraging digital technology (wearable devices and social media for social support) resonated as a potential solution to help bridge the gap from CR to more independent physical activity. More attention is needed to help individuals experience a tailored and safe transition to home to maintain physical activity among those who complete CR.