Background

Telemedicine and telemonitoring have become invaluable tools in managing chronic diseases, such as heart failure (HF). With the recent pandemic, telemedicine has become the preferred method of providing consultative care.

Local problem

This rapid paradigm shift from face-to-face (F2F) consultations to telemedicine required a collaborative approach for successful implementation while maintaining quality of care. The processes for conducting a telemedicine visit for HF patient are not well defined or outlined.

Method

Using a collaborative practice model and nurse practitioner led program, technology was leveraged to manage the high-risk HF population using virtual care (consultation via phone or video-to-home) with two aims: first to provide ongoing HF care using available telemedicine technologies or F2F care when necessary and, second, to evaluate and direct those needing urgent/emergent level of care to emergency department (ED).

Intervention

The process was converted into an intuitive algorithm that describes essential elements and team roles necessary for execution of a successful HF consultation.

Results

Following the algorithm, nurse practitioners conducted 132 visits, yielding 100% success in the conversion of F2F appointments to telemedicine, with 3 patients referred to ED for care. The information obtained through telemedicine consultation accurately informed decision for ED evaluation with resultant admission.

Conclusion

Collaborative team-based approach delineated in the algorithm facilitated successful virtual consultations for HF patients and accurately informed decisions for higher level of care.

To address ambulatory care sensitive hospitalisations in heart failure (HF), we implemented a quality improvement initiative to reduce admissions and improve guideline-directed medical therapy (GDMT) prescription, through proactive integration of remote patient monitoring-home telehealth (RPM-HT) and pharmacist consultations. Each enrolled patient (n=38) was assigned an RPM-HT registered nurse (RN), cardiology licensed independent provider (provider), and, if referred, a clinical pharmacy specialist (pharmacist). The RN called patients weekly and for changes detected by RPM-HT, while the pharmacist worked to optimise GDMT. The RN and pharmacist communicated clinical status changes to the provider for expedited management. Process measures were the percentage of outbound RN weekly calls missed per enrolled patient; the weekly percentage of provider interventions missed; and the number of initiative-driven diuretic changes. Outcome measures included eligible GDMT medications prescribed, optimisation of those medications, and the pre-post difference in emergency department (ED) visits/hospitalisations. After a 4-week run-in period, RN weekly calls missed per enrolled patient decreased from a mean of 21.4% (weeks 5-15) to 10.2% (weeks 16-23). Weekly missed provider interventions decreased from a mean of 15.1% (weeks 1-15) to 3.4% (weeks 16-23), with special cause variation detected. The initiative resulted in 43 diuretic changes in 21 patients. Among 34 active patients, 65 ED visits (0.16 per person-month) occurred in 12 months pre intervention compared with 8 ED visits (0.04 per person-month) for 6 intervention months (p<0.001). Among 16 patients referred to pharmacist, the per cent of eligible GDMT medications prescribed increased by 17.1% (p<0.001); the number of patients receiving all eligible medications increased from 3 to 11 (p=0.008). Similarly, the per cent optimisation of GDMT doses increased by 25.3% (p<0.001), with the number of patients maximally optimised on GDMT increasing from 1 to 6 (p=0.06). We concluded that a cardiology, RPM-HT RN and pharmacist team improved prescription of GDMT and may have reduced HF admissions.

Background

Gaps in the receipt and dosing of guideline-directed medical therapy (GDMT) persist for patients with heart failure with reduced ejection fraction (HFrEF) [1]. In 2020, the Veterans Affairs (VA) developed a heart failure (HF) specific population dashboard to monitor care quality and performance on standard HFrEF performance measures [2].

Methods

The Dashboard Activated Services and Telehealth for HF (DASH-HF) study is a pragmatic randomized quality improvement study designed to evaluate the utility of proactive population management clinics using the VA's HF dashboard to optimize GDMT for patients with HFrEF. Panel management telemedicine clinics incorporated multidisciplinary clinicians to perform chart review and impromptu telephone encounters to evaluate current HFrEF management and opportunities to optimize GDMT. The study will evaluate the efficacy of proactive panel management to usual care at 6 months as quantified by the GDMT optimization potential score. Secondary outcomes include hospitalizations, mortality, and clinician time per intervention. The study completed enrollment and randomization of 300 participants. The intervention was performed from September to December 2021.

Conclusion

DASH-HF will contribute to the literature by evaluating use of the existing VA dashboard to identify HF patients with the lowest adherence to GDMT and proactively target this group for the intervention.

Registration

https://clinicaltrials.gov/. Unique identifier: NCT05001165.

Flexible electronics have enabled catheter-based intravascular sensing. However, real-time interrogation of unstable plaque remains an unmet clinical challenge. Here, we demonstrate the feasibility of stretchable electrochemical impedance spectroscopy (EIS) sensors for endoluminal investigations in New Zealand White (NZW) rabbits on diet-induced hyperlipidemia. A parylene C (PAC)-based EIS sensor mounted on the surface of an inflatable silicone balloon affixed to the tip of an interrogating catheter was deployed (1) on the explants of NZW rabbit aorta for detection of lipid-rich atherosclerotic lesions, and (2) on live animals for demonstration of balloon inflation and EIS measurements. An input peak-to-peak AC voltage of 10 mV and sweeping-frequency from 300 kHz to 100 Hz were delivered to the endoluminal sites. Balloon inflation allowed EIS sensors to be in contact with endoluminal surface. In the oxidized low-density-lipoprotein (oxLDL)-rich lesions from explants of fat-fed rabbits, impedance magnitude increased significantly by 1.5-fold across the entire frequency band, and phase shifted ~5° at frequencies below 10 kHz. In the lesion-free sites of the normal diet-fed rabbits, impedance magnitude increased by 1.2-fold and phase shifted ~5° at frequencies above 30 kHz. Thus, we demonstrate the feasibility of stretchable intravascular EIS sensors for identification of lipid rich lesions, with a translational implication for detecting unstable lesions.

Background

Heart failure is a prevailing diagnosis of hospitalization and readmission within 6 months, and nearly a quarter of these patients die within a year. Guideline-directed medication therapies reduce risk of mortality by 73% over 2 years; however, the implementation of these therapies to their target dose in clinical practice continues to be challenging. In 2020, the Veterans Affairs (VA) Health Care System developed a HF dashboard to monitor and improve outpatient HF management. The DASH-HF (Dashboard Activated Services and Telehealth for Heart Failure) study is a randomized, pragmatic clinical trial to evaluate proactive dashboard-directed telehealth clinics to improve the use and dosing of guideline-directed medication therapy for patients with heart failure with reduced ejection fraction not on optimal guideline-directed medication therapy within the VA.

Methods

Three hundred veterans with heart failure with reduced ejection fraction met inclusion criteria with an optimization potential score (OPS) of 5 or less out of 10, representing nonoptimal guideline-directed medication therapy. The primary outcome was a composite score of guideline-directed medical therapy, the OPS, 6 months after the end of the intervention. Secondary outcomes included active prescriptions for each individual guideline-directed medical therapy class, HF-related hospitalizations, deaths, and clinician time per patient during the intervention clinics.

Results

There was no significant difference between the intervention arm and usual care group in the primary outcome (OPS, 2.9; SD=2.1 versus OPS, 2.6, SD=2.1); adjusted mean difference 0.3 (95% CI, -0.1 to 0.7) or in the prespecified secondary outcomes for hospitalization and all-cause mortality for the intervention of proactive dashboard-based clinics.

Conclusions

A dashboard-based clinic intervention did not improve the OPS or secondary outcomes of hospitalization and all-cause mortality. There remains a larger opportunity to better target patients and provide more intensive follow-up to further evaluate the utility of proactive dashboard-based clinics for HF management and quality improvement.

Registration

URL: https://www.

Clinicaltrials

gov; Unique identifier: NCT05001165.