Rationale and design of a cluster-randomized pragmatic trial aimed at improving use of guideline directed medical therapy in outpatients with heart failure: PRagmatic trial of messaging to providers about treatment of heart failure (PROMPT-HF)

Rationale, Design, and Patient Characteristics of a Cluster-Randomized Pragmatic Trial to Improve Mineralocorticoid Antagonist Use

BACKGROUND

Despite robust evidence and strong guideline recommendations supporting use of mineralocorticoid receptor antagonists (MRAs) to improve outcomes in patients with heart failure with reduced ejection fraction (HFrEF), these medications remain underused in clinical practice.

OBJECTIVES

The goal is to determine if providing a tailored best practice alert (BPA) to outpatient providers suggesting guideline-recommended MRAs or information about available hyperkalemia treatment, if present, for patients with HFrEF will increase short-term MRA prescriptions.

METHODS

PROMPT-MRA (Pragmatic Trial of Messaging to Providers About Treatment With Mineralocorticoid Receptor Antagonists) is a pragmatic, cluster-randomized, controlled study. A total of 119 providers were randomized to receive a BPA or usual care. During an outpatient visit with participating providers, the BPA displayed recent laboratory test values and ejection fraction. The alert suggested guideline-recommended MRAs for eligible patients with a serum potassium of <5.0 mEq/L or novel potassium binders for those with a serum potassium of ≥5.0 mEq/L, each linked to an order set containing the corresponding medication and laboratory monitoring.

RESULTS

PROMPT-MRA completed enrollment with 1,210 patients. The primary outcome of PROMPT-MRA is to determine if a tailored BPA for outpatients with HFrEF will lead to higher MRA prescriptions 6 months following randomization compared with usual care. Secondary outcomes included incidence of hyperkalemia, use of novel potassium binders, heart failure hospitalizations, and mortality.

CONCLUSIONS

If effective, the BPA can be scaled to improve population health outcomes with increased MRA prescribing among eligible patients with HFrEF, with or without a history of hyperkalemia. (Pragmatic Trial of Alerts for Use of Mineralocorticoid Receptor Antagonists [PROMPT-MRA]; NCT04903717).

Strategies for secondary use of real-world clinical and administrative data for outcome ascertainment in pragmatic clinical trials

BACKGROUND

Pragmatic trials are gaining popularity as a cost-effective way to examine treatment effectiveness and generate timely comparative evidence. Incorporating supplementary real-world data is recommended for robust outcome monitoring. However, detailed operational guidelines are needed to inform effective use and integration of heterogeneous databases.

OBJECTIVE

Lessons learned from the Veterans Affairs (VA) Diuretic Comparison Project (DCP) are reviewed, providing adaptable recommendations to capture clinical outcomes from real-world data.

METHODS

Non-cancer deaths and major cardiovascular (CV) outcomes were determined using VA, Medicare, and National Death Index (NDI) data. Multiple ascertainment strategies were applied, including claims-based algorithms, natural language processing, and systematic chart review.

RESULTS

During a mean follow-up of 2.4 (SD = 1.4) years, 907 CV events were identified within the VA healthcare system. Slight delays (∼1 year) were expected in obtaining Medicare data. An additional 298 patients were found having a CV event outside of the VA in 2016 - 2021, increasing the CV event rate from 3.5 % to 5.7 % (770 of 13,523 randomized). NDI data required ∼2 years waiting period. Such inclusion did not increase the number of deaths identified (all 894 deaths were captured by VA data) but enhanced the accuracy in determining cause of death.

CONCLUSION

Our experience supports the recommendation of integrating multiple data sources to improve clinical outcome ascertainment. While this approach is promising, hierarchical data aggregation is required when facing different acquisition timelines, information availability/completeness, coding practice, and system configurations. It may not be feasible to implement comparable applications and solutions to studies conducted under different constraints and practice. The recommendations provide guidance and possible action plans for researchers who are interested in applying cross-source data to ascertain all study outcomes.

Electronic health record alerts for management of heart failure with reduced ejection fraction in hospitalized patients: the PROMPT-AHF trial

BACKGROUND AND AIMS

Patients hospitalized for acute heart failure (AHF) continue to be discharged on an inadequate number of guideline-directed medical therapies (GDMT) despite evidence that inpatient initiation is beneficial. This study aimed to examine whether a tailored electronic health record (EHR) alert increased rates of GDMT prescription at discharge in eligible patients hospitalized for AHF.

METHODS

Pragmatic trial of messaging to providers about treatment of acute heart failure (PROMPT-AHF) was a pragmatic, multicenter, EHR-based, and randomized clinical trial. Patients were automatically enrolled 48 h after admission if they met pre-specified criteria for an AHF hospitalization. Providers of patients in the intervention arm received an alert during order entry with relevant patient characteristics along with individualized GDMT recommendations with links to an order set. The primary outcome was an increase in the number of GDMT prescriptions at discharge.

RESULTS

Thousand and twelve patients were enrolled between May 2021 and November 2022. The median age was 74 years; 26% were female, and 24% were Black. At the time of the alert, 85% of patients were on β-blockers, 55% on angiotensin-converting enzyme inhibitor/angiotensin receptor blocker/angiotensin receptor-neprilysin inhibitor, 20% on mineralocorticoid receptor antagonist (MRA) and 17% on sodium-glucose cotransporter 2 inhibitor. The primary outcome occurred in 34% of both the alert and no alert groups [adjusted risk ratio (RR): 0.95 (0.81, 1.12), P = .99]. Patients randomized to the alert arm were more likely to have an increase in MRA [adjusted RR: 1.54 (1.10, 2.16), P = .01]. At the time of discharge, 11.2% of patients were on all four pillars of GDMT.

CONCLUSIONS

A real-time, targeted, and tailored EHR-based alert system for AHF did not lead to a higher number of overall GDMT prescriptions at discharge. Further refinement and improvement of such alerts and changes to clinician incentives are needed to overcome barriers to the implementation of GDMT during hospitalizations for AHF. GDMT remains suboptimal in this setting, with only one in nine patients being discharged on a comprehensive evidence-based regimen for heart failure.

Guideline-directed medical therapy for HFrEF: sequencing strategies and barriers for life-saving drug therapy

Multiple landmark trials have helped to advance the treatment of heart failure with reduced ejection fraction (HFrEF) significantly over the past decade. These trials have led to the introduction of four main drug classes into the 2021 ESC guideline, namely angiotensin-receptor neprilysin inhibitors/angiotensin-converting-enzyme inhibitors, beta-blockers, mineralocorticoid receptor antagonists, and sodium-glucose cotransporter-2 inhibitors. The life-saving effect of these therapies has been shown to be additive and becomes apparent within weeks, which is why maximally tolerated or target doses of all drug classes should be strived for as quickly as possible. Recent evidence, such as the STRONG-HF trial, demonstrated that rapid drug implementation and up-titration is superior to the traditional and more gradual step-by-step approach where valuable time is lost to up-titration. Accordingly, multiple rapid drug implementation and sequencing strategies have been proposed to significantly reduce the time needed for the titration process. Such strategies are urgently needed since previous large-scale registries have shown that guideline-directed medical therapy (GDMT) implementation is a challenge. This challenge is reflected by generally low adherence rates, which can be attributed to factors considering the patient, health care system, and local hospital/health care provider. This review of the four medication classes used to treat HFrEF seeks to present a thorough overview of the data supporting current GDMT, discuss the obstacles to GDMT implementation and up-titration, and identify multiple sequencing strategies that could improve GDMT adherence. Sequencing strategies for GDMT implementation. GDMT: guideline-directed medical therapy; ACEi: angiotensin-converting enzyme inhibitor; ARB: Angiotensin II receptor blocker; ARNi: angiotensin receptor-neprilysin inhibitor; BB: beta-blocker; MRA: mineralocorticoid receptor antagonist; SGLT2i: sodium-glucose co-transporter 2 inhibitor.

Electronic Health Record Embedded Strategies for Improving Care of Patients With Heart Failure

PURPOSE

A majority of clinical decisions use the electronic health record (EHR) and there is an unmet need to use its capability to help providers to make evidence-based decisions that improve care for heart failure patients. These electronic nudges are rooted in the human psychology of decision-making and often target specific cognitive biases. This review outlines the development of novel EHR nudges and specific lessons learned from each experience to inform the development of future interventions.

RECENT FINDINGS

There have been several randomized clinical trials examining the impact of EHR alerts on quality of care for heart failure patients. These interventions have targeted both clinicians and patients. There are features of each trial that inform best practices and future directions for EHR nudges. Recent clinical trials have demonstrated that some EHR alerts can improve care for heart failure patients. These trials utilized default options, involved clinicians in the alert design process, provided actionable recommendations, and aimed to minimize disruptions to typical workflow. Alerts aimed at improving care should be examined in a randomized fashion in order to evaluate their impact on clinician satisfaction and patient care.

Pragmatic trial of messaging to providers about treatment of acute heart failure: The PROMPT-AHF trial

Acute Heart failure (AHF) is among the most frequent causes of hospitalization in the United States, contributing to substantial health care costs, morbidity, and mortality. Inpatient initiation of guideline-directed medical therapy (GDMT) is recommended for patients with heart failure with reduced ejection fraction (HFrEF) to reduce the risk of cardiovascular death or HF hospitalization. However, underutilization of GDMT prior to discharge is pervasive, representing a valuable missed opportunity to optimize evidence-based care. The PRagmatic Trial Of Messaging to Providers about Treatment of Acute Heart Failure tests the effectiveness of an electronic health record embedded clinical decision support system that informs providers during hospital management about indicated but not yet prescribed GDMT for eligible AHF patients with HFrEF. PRagmatic Trial Of Messaging to Providers about Treatment of Acute Heart Failureis an open-label, multicenter, pragmatic randomized controlled trial of 1,012 patients hospitalized with HFrEF. Eligible patients randomized to the intervention group are exposed to a tailored best practice advisory embedded within the electronic health record that alerts providers to prescribe omitted GDMT. The primary outcome is an increase in the proportion of additional GDMT medication classes prescribed at the time of discharge compared to those in the usual care arm.

Rationale and design of a pragmatic trial aimed at improving treatment of hyperlipidemia in outpatients with very high risk atherosclerotic cardiovascular disease: A pragmatic trial of messaging to providers about treatment of hyperlipidemia (PROMPT-LIPID)

BACKGROUND

Despite guideline recommendations to optimize low-density lipoprotein cholesterol (LDL-C) reduction with intensification of lipid-lowering therapy (LLT) in patients with atherosclerotic cardiovascular disease (ASCVD), few of these patients achieve LDL-C < 70 mg/dL in practice.

PURPOSE

We developed a real-time, targeted electronic health record (EHR) alert with embedded ordering capability to promote intensification of evidence based LLT in outpatients with very high risk ASCVD.

METHODS

We designed a pragmatic, multicenter, single-blind, cluster randomized trial to test the effectiveness of an EHR-based LLT intensification alert. The study will enroll about 100 providers who will be randomized to either receive the alert or undergo usual care for outpatients with high risk ASCVD with LDL-C > 70 mg/dL. Total enrollment will include 2,500 patients. The primary outcome will be the proportion of patients with LLT intensification at 90 days. Secondary outcomes include achieved LDL-C at 6 months and the proportion of patients with LDL-C < 70 mg/dL or < 55 mg/dL at 6 months.

RESULTS

Enrollment of 1,250 patients (50% of goal) was reached within 47 days (50% women, mean age 72, median LDL-C 91). At baseline, 71%, 9%, and 3% were on statins, ezetimibe, or proprotein convertase subtilisin/kexin type 9 inhibitors, respectively.

CONCLUSIONS

PRagmatic Trial of Messaging to Providers about Treatment of HyperLIPIDemia has rapidly reached 50% enrollment of patients with very high risk ASCVD, demonstrating low baseline LLT utilization. This pragmatic, EHR-based trial will determine the effectiveness of a real-time, targeted EHR alert with embedded ordering capability to promote LLT intensification. Findings from this low-cost, widely scalable intervention to improve LDL-C may have important public health implications.

TRIAL REGISTRATION

clinicaltrials.gov NCT04394715.

Alerting Clinicians to 1-Year Mortality Risk in Patients Hospitalized With Heart Failure: The REVEAL-HF Randomized Clinical Trial

Importance

Heart failure is a major cause of morbidity and mortality worldwide. The use of risk scores has the potential to improve targeted use of interventions by clinicians that improve patient outcomes, but this hypothesis has not been tested in a randomized trial.

Objective

To evaluate whether prognostic information in heart failure translates into improved decisions about initiation and intensity of treatment, more appropriate end-of-life care, and a subsequent reduction in rates of hospitalization or death.

Design, Setting, and Participants

This was a pragmatic, multicenter, electronic health record-based, randomized clinical trial across the Yale New Haven Health System, comprising small community hospitals and large tertiary care centers. Patients hospitalized for heart failure who had N-terminal pro-brain natriuretic peptide (NT-proBNP) levels of greater than 500 pg/mL and received intravenous diuretics within 24 hours of admission were automatically randomly assigned to the alert (intervention) or usual-care groups.

Interventions

The alert group had their risk of 1-year mortality calculated using an algorithm that was derived and validated using similar historic patients in the electronic health record. This estimate, including a categorical risk assessment, was presented to clinicians while they were interacting with a patient's electronic health record.

Main Outcomes and Measures

The primary outcome was a composite of 30-day hospital readmissions and all-cause mortality at 1 year.

Results

Between November 27, 2019, through March 7, 2021, 3124 patients were randomly assigned to the alert (1590 [50.9%]) or usual-care (1534 [49.1%]) group. The alert group had a median (IQR) age of 76.5 (65-86) years, and 796 were female patients (50.1%). Patients from the following race and ethnicity groups were included: 13 Asian (0.8%), 324 Black (20.4%), 136 Hispanic (8.6%), 1448 non-Hispanic (91.1%), 1126 White (70.8%), 6 other ethnicity (0.4%), and 127 other race (8.0%). The usual-care group had a median (IQR) age of 77 (65-86) years, and 788 were female patients (51.4%). Patients from the following race and ethnicity groups were included: 11 Asian (1.4%), 298 Black (19.4%), 162 Hispanic (10.6%), 1359 non-Hispanic (88.6%), 1077 White (70.2%), 13 other ethnicity (0.9%), and 137 other race (8.9%). Median (IQR) NT-proBNP levels were 3826 (1692-8241) pg/mL in the alert group and 3867 (1663-8917) pg/mL in the usual-care group. A total of 284 patients (17.9%) and 270 patients (17.6%) were admitted to the intensive care unit in the alert and usual-care groups, respectively. A total of 367 patients (23.1%) and 359 patients (23.4%) had a left ventricular ejection fraction of 40% or less in the alert and usual-care groups, respectively. The model achieved an area under the curve of 0.74 in the trial population. The primary outcome occurred in 619 patients (38.9%) in the alert group and 603 patients (39.3%) in the usual-care group (P = .89). There were no significant differences between study groups in the prescription of heart failure medications at discharge, the placement of an implantable cardioverter-defibrillator, or referral to palliative care.

Conclusions and Relevance

Provision of 1-year mortality estimates during heart failure hospitalization did not affect hospitalization or mortality, nor did it affect clinical decision-making.

Trial Registration

ClinicalTrials.gov Identifier NCT03845660.

The use of multidisciplinary teams, electronic health records tools, and technology to optimize heart failure population health

PURPOSE OF REVIEW

Given the limited population level, adoption of optimal therapy that has been shown in recent clinical trials and heart failure registries, efforts to rapidly and safely improve adoption of guideline-directed medical therapy for heart failure should be prioritized. Opportunities to leverage remote monitoring technology, the electronic health record (EHR), and multidisciplinary teams to improve heart failure care merit review.

RECENT FINDINGS

Dedicated multidisciplinary teams employing algorithmic medication titration schema have shown better efficacy than clinician alerts or quality initiatives that focus on education and audit-feedback processes alone. Technology that enables invasive pressure monitoring and wearable devices that transmit physiologic data have the potential to predict decompensation and allow for early intervention by alerting clinicians to signs of congestion/clinical worsening but further real-world data is needed to prove efficacy and develop effective treatment protocols.

SUMMARY

The combination of technology, multidisciplinary teams, and identification of populations for intervention using the EHR will be central to impactful innovation in heart failure population health and prevention of avoidable morbidity. Novel approaches to study implementation efforts including cluster randomized trials are needed.

OUP accepted manuscript

The increasing volume and richness of healthcare data collected during routine clinical practice have not yet translated into significant numbers of actionable insights that have systematically improved patient outcomes. An evidence-practice gap continues to exist in healthcare. We contest that this gap can be reduced by assessing the use of nudge theory as part of clinical decision support systems (CDSS). Deploying nudges to modify clinician behaviour and improve adherence to guideline-directed therapy represents an underused tool in bridging the evidence-practice gap. In conjunction with electronic health records (EHRs) and newer devices including artificial intelligence algorithms that are increasingly integrated within learning health systems, nudges such as CDSS alerts should be iteratively tested for all stakeholders involved in health decision-making: clinicians, researchers, and patients alike. Not only could they improve the implementation of known evidence, but the true value of nudging could lie in areas where traditional randomized controlled trials are lacking, and where clinical equipoise and variation dominate. The opportunity to test CDSS nudge alerts and their ability to standardize behaviour in the face of uncertainty may generate novel insights and improve patient outcomes in areas of clinical practice currently without a robust evidence base.