Jennifer Yu

Introduction: Heart failure care requires coordination across hospital and community settings, yet information is often fragmented across electronic medical records and clinical systems. Clinical dashboards can bring together and display information to support care delivery and service management; however, existing dashboards have generally focused on specific measures, interventions and monitoring pathways. This study aimed to co-design, iteratively develop and user-test an integrated heart failure dashboard that links patient-level clinical decision-making with service-level management. Methods: A human-centred design approach comprising needs identification, collaborative ideation, iterative prototype development and end-user testing was applied across two complementary operational and clinical dashboard streams. Thirty-six clinicians, health service managers, data and implementation scientists, and consumers from metropolitan and regional services participated. Results: For operational decision-making, participants prioritised real-time visibility of patients across heart failure services, patient trajectories, service-performance information, and identification of variation in guideline-directed care and outcomes. Clinical priorities included rapid synthesis of longitudinal information, optimisation of guideline-directed medical therapy, continuity across care settings, and clinical workload prioritisation. These requirements informed the dashboard prototypes. Many prioritised information elements were incompletely represented in structured data and distributed across disconnected systems and structured and unstructured clinical data sources. Conclusion: Human-centred co-design identified complementary patient- and service-level information needs and translated them into linked dashboard prototypes. The proposed dashboard brings together current clinical status and longitudinal heart failure care history at the patient-level alongside service-level patterns. Implementation is required to evaluate whether these linked views improve care processes and patient outcomes.

Aims: Heart failure (HF) is a global health challenge with increasing burden. This study characterized HF across different severity levels to inform service delivery and health system responses. Methods and results: Using Global Burden of Disease (GBD) Study 2021 data, we analyzed age-standardized rates of prevalence and years lived with disability (YLDs) for HF, stratified into four levels based on symptom severity as determined by the GBD: treated, mild, moderate and severe. Estimates were stratified by sex, region, and underlying causes. Spearman's rank correlation tests were used to assess the relationships between burden and sociodemographic index (SDI) and universal health coverage (UHC). Temporal trends and contributions were evaluated using estimated annual percentage changes and decomposition analyses. The overall prevalence of HF was 55.5 million (M), and using GBD symptom severity categories, there were 20.5 M treated HF globally in 2021, resulting in 1.3 M YLDs. Mild HF was 10.3 M (0.4 M YLDs), moderate HF was 6.7 M (0.5 M YLDs), and severe HF was 18.0 M (3.1 M YLDs). Ischaemic heart disease remained the leading underlying cause of HF. Males experienced a burden 25% higher than females. Geographic variation was observed, with higher YLDs due to treated HF correlating with lower SDI and UHC levels, while no significant association for mild, moderate, or severe HF. During 1990–2021, prevalence and YLDs increased across all groups with an increase of 0.2%, predominantly driven by population growth and ageing. Conclusion: The burden of HF is projected to rise significantly. Advancing strategies to strengthen health systems and address disparities in access to guideline-directed care, particularly in low- and middle-income countries, is an important focus for action.

Background: Mobile health (mHealth) interventions are increasing in popularity for the management of heart failure and coronary artery disease. The use of these interventions is dependent on rates of smartphone ownership. It is estimated that approximately 90% of the Australian adult population owns a smartphone; however, international studies suggest that smartphone ownership is significantly lower in patient populations, ranging from 34% to 91%. Smartphone ownership in patients with cardiovascular disease has not previously been examined. Objective: This study aimed to examine and compare pre–COVID-19 and post–COVID-19 pandemic smartphone ownership rates of inpatients admitted with coronary artery disease or heart failure. Methods: Data from prescreening logs of 2 multicenter randomized controlled trials, TeleClinical Care (TCC)-Pilot and TCC-Cardiac, were reviewed. TCC-Pilot recruited patients between February 2019 and March 2020. This formed the pre–COVID-19 cohort, with 377 patients screened who lived in Sydney, had a qualifying hospital admission, and had information regarding their phone ownership status. TCC-Cardiac recruited patients from July 2021 to February 2023, with 718 patients meeting the criteria and forming the post–COVID-19 cohort. Supplemental patient demographic and medical history data were collected from the electronic medical record. Results: In the pre–COVID-19 cohort (N=377), 194 (51.5%) patients owned smartphones, 79 (21%) owned phones that were incompatible with the mHealth intervention, and the remaining 104 (27.6%) did not own a mobile phone. Smartphone owners were predominantly male ( P <.001) and more often had private health insurance ( P =.002). In the post–COVID-19 cohort (N=718), 366 (51%) patients owned smartphones, 106 (14.8%) owned incompatible phones, and the remaining 246 (34.3%) did not own any mobile phone. In both cohorts, younger patients were more likely to own smartphones ( P <.001). Multiple comorbidities were associated with not owning a phone. Conclusions: Smartphone ownership accounted for just over 50% of the patients in this population. It was less common among older adults, patients with comorbidities, and those with markers of lower socioeconomic status. This needs to be considered when delivering mHealth interventions.

To compare the time from triage to ECG sign-off in patients with acute coronary syndrome, before and after the introduction of an electronic medical record-integrated ECG workflow system (Epiphany). Additionally, to assess for any correlation between patient characteristics and ECG sign-off times. A retrospective, single-centre cohort study was performed at Prince of Wales Hospital, Sydney. Patients were included if they were over 18 years, presented to Prince of Wales Hospital ED during 2021, had an ED diagnosis code of 'ACS', 'UA', 'NSTEMI' or 'STEMI' and were subsequently admitted under the cardiology team. ECG sign-off times and demographic data were compared between patients presenting prior to 29 June (pre-Epiphany group) and those presenting after (post-Epiphany group). Those without ECGs signed-off were excluded. There were 200 patients (100 each group) included in the statistical analysis. There was a significant decrease in the median triage to ECG sign-off time, from 35 min (IQR 18-69) pre-Epiphany, to 21 min (IQR 13-37) post-Epiphany. There were only 10 (5%) patients in the pre-Epiphany group and 16 (8%) in the post-Epiphany group, who had ECG sign-off times less than the 10-min. There was no correlation between gender, triage category, age or time of shift with triage to ECG sign-off time. The introduction of the Epiphany system has significantly reduced the triage to ECG sign-off time in the ED. Despite this, there remains a large proportion of patients with acute coronary syndrome who do not have an ECG signed-off within the guideline-recommended 10 min.

Background: Patients hospitalized with acute coronary syndrome (ACS) or heart failure (HF) are frequently readmitted. This is the first randomized controlled trial of a mobile health intervention that combines telemonitoring and education for inpatients with ACS or HF to prevent readmission. Objective: This study aims to investigate the feasibility, efficacy, and cost-effectiveness of a smartphone app–based model of care (TeleClinical Care [TCC]) in patients discharged after ACS or HF admission. Methods: In this pilot, 2-center randomized controlled trial, TCC was applied at discharge along with usual care to intervention arm participants. Control arm participants received usual care alone. Inclusion criteria were current admission with ACS or HF, ownership of a compatible smartphone, age ≥18 years, and provision of informed consent. The primary end point was the incidence of unplanned 30-day readmissions. Secondary end points included all-cause readmissions, cardiac readmissions, cardiac rehabilitation completion, medication adherence, cost-effectiveness, and user satisfaction. Intervention arm participants received the app and Bluetooth-enabled devices for measuring weight, blood pressure, and physical activity daily plus usual care. The devices automatically transmitted recordings to the patients’ smartphones and a central server. Thresholds for blood pressure, heart rate, and weight were determined by the treating cardiologists. Readings outside these thresholds were flagged to a monitoring team, who discussed salient abnormalities with the patients’ usual care providers (cardiologists, general practitioners, or HF outreach nurses), who were responsible for further management. The app also provided educational push notifications. Participants were followed up after 6 months. Results: Overall, 164 inpatients were randomized (TCC: 81/164, 49.4%; control: 83/164, 50.6%; mean age 61.5, SD 12.3 years; 130/164, 79.3% men; 128/164, 78% admitted with ACS). There were 11 unplanned 30-day readmissions in both groups (P=.97). Over a mean follow-up of 193 days, the intervention was associated with a significant reduction in unplanned hospital readmissions (21 in TCC vs 41 in the control arm; P=.02), including cardiac readmissions (11 in TCC vs 25 in the control arm; P=.03), and higher rates of cardiac rehabilitation completion (20/51, 39% vs 9/49, 18%; P=.03) and medication adherence (57/76, 75% vs 37/74, 50%; P=.002). The average usability rating for the app was 4.5/5. The intervention cost Aus $6028 (US $4342.26) per cardiac readmission saved. When modeled in a mainstream clinical setting, enrollment of 237 patients was projected to have the same expenditure compared with usual care, and enrollment of 500 patients was projected to save approximately Aus $100,000 (approximately US $70,000) annually. Conclusions: TCC was feasible and safe for inpatients with either ACS or HF. The incidence of 30-day readmissions was similar; however, long-term benefits were demonstrated, including fewer readmissions over 6 months, improved medication adherence, and improved cardiac rehabilitation completion. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12618001547235; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375945

Background: Cardiovascular disease (CVD) remains the leading cause of death worldwide. Mobile phones have become ubiquitous in most developed societies. Smartphone apps, telemonitoring, and clinician-driven SMS allow for novel opportunities and methods in managing chronic CVD, such as ischemic heart disease, heart failure, and hypertension, and in the conduct and support of cardiac rehabilitation. Objective: A systematic review was conducted using seven electronic databases, identifying all relevant randomized control trials (RCTs) featuring a mobile phone intervention (MPI) used in the management of chronic CVD. Outcomes assessed included mortality, hospitalizations, blood pressure (BP), and BMI. Methods: Electronic data searches were performed using seven databases from January 2000 to June 2019. Relevant articles were reviewed and analyzed. Meta-analysis was performed using standard techniques. The odds ratio (OR) was used as a summary statistic for dichotomous variables. A random effect model was used. Results: A total of 26 RCTs including 6713 patients were identified and are described in this review, and 12 RCTs were included in the meta-analysis. In patients with heart failure, MPIs were associated with a significantly lower rate of hospitalizations (244/792, 30.8% vs 287/803, 35.7%; n=1595; OR 0.77, 95% CI 0.62 to 0.97; P=.03; I2=0%). In patients with hypertension, patients exposed to MPIs had a significantly lower systolic BP (mean difference 4.3 mm Hg; 95% CI −7.8 to −0.78 mm Hg; n=2023; P=.02). Conclusions: The available data suggest that MPIs may have a role as a valuable adjunct in the management of chronic CVD.

BACKGROUND Cardiovascular disease (CVD) remains the leading cause of death worldwide. Mobile phones have become ubiquitous in most developed societies. Smartphone apps, telemonitoring, and clinician-driven SMS allow for novel opportunities and methods in managing chronic CVD, such as ischemic heart disease, heart failure, and hypertension, and in the conduct and support of cardiac rehabilitation. OBJECTIVE A systematic review was conducted using seven electronic databases, identifying all relevant randomized control trials (RCTs) featuring a mobile phone intervention (MPI) used in the management of chronic CVD. Outcomes assessed included mortality, hospitalizations, blood pressure (BP), and BMI. METHODS Electronic data searches were performed using seven databases from January 2000 to June 2019. Relevant articles were reviewed and analyzed. Meta-analysis was performed using standard techniques. The odds ratio (OR) was used as a summary statistic for dichotomous variables. A random effect model was used. RESULTS A total of 26 RCTs including 6713 patients were identified and are described in this review, and 12 RCTs were included in the meta-analysis. In patients with heart failure, MPIs were associated with a significantly lower rate of hospitalizations (244/792, 30.8% vs 287/803, 35.7%; n=1595; OR 0.77, 95% CI 0.62 to 0.97; P=.03; I2=0%). In patients with hypertension, patients exposed to MPIs had a significantly lower systolic BP (mean difference 4.3 mm Hg; 95% CI −7.8 to −0.78 mm Hg; n=2023; P=.02). CONCLUSIONS The available data suggest that MPIs may have a role as a valuable adjunct in the management of chronic CVD.

Background: Cardiac rehabilitation ( CR ) for patients with cardiovascular disease has traditionally involved low‐ to moderate‐intensity continuous aerobic exercise training ( MICT ). There is growing and robust evidence that high‐intensity interval training ( HIIT ) shows similar or greater efficacy compared with MICT across a range of cardiovascular and metabolic measures, in both healthy populations and populations with a chronic illness. However, there is understandable concern about the safety aspects of applying HIIT in CR settings. This systematic review analyzed safety data drawn from recent proof‐of‐concept studies of HIIT during CR among patients with cardiovascular disease. Methods and Results: We included trials comparing HIIT with either MICT or usual care in patients with coronary artery disease or heart failure participating in tertiary care services, such as phase 2 (outpatient) CR . Adverse events occurring during or up to 4 hours after an exercise training session were collated. There were 23 studies included, which analyzed 1117 participants ( HIIT =547; MICT =570). One major cardiovascular adverse event occurred in relation to an HIIT session, equating to 1 major cardiovascular event per 17 083 training sessions (11 333 training hours). One minor cardiovascular adverse events and 3 noncardiovascular adverse events (primarily musculoskeletal complaints) were also reported for HIIT . Two noncardiovascular events were reported in relation to MICT . Conclusions: HIIT has shown a relatively low rate of major adverse cardiovascular events for patients with coronary artery disease or heart failure when applied within CR settings.