Clinical Decision Support Tool for Heart Failure

(P3HF Trial)

Not yet recruiting at 1 trial location

Overseen By Nathan Wright, MA

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Yale University

Disqualifiers: Pregnancy, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests a new tool designed to help doctors decide when to refer heart failure patients to palliative care, which focuses on comfort and quality of life. The Clinical Decision Support Tool uses a proven model to predict a patient's chance of survival over the next year and guides doctors in making care decisions. Patients hospitalized with heart failure who have received certain treatments and meet specific criteria may be eligible for the trial. The researchers aim to improve how care aligns with patients' goals and needs. As an unphased trial, this study offers patients the opportunity to contribute to research that could enhance decision-making in heart failure care.

Do I need to stop taking my current medications for this trial?

The trial information does not specify whether participants need to stop taking their current medications.

What prior data suggests that this clinical decision support tool is safe for use in heart failure care?

Research shows that clinical decision support (CDS) tools are generally safe in healthcare. These tools assist doctors and nurses by providing timely information for better decision-making. Studies have found that integrating CDS tools into electronic health records can enhance patient care without causing harm. For instance, one study found no significant negative effects from using CDS tools to manage heart failure patients.

These tools have been tested in various settings and appear well-accepted by healthcare providers. They enable informed choices without compromising patient safety. While this trial does not test a drug, past studies suggest that using CDS tools in healthcare is safe. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the Clinical Decision Support (CDS) Tool for heart failure because it offers a new way to enhance decision-making in real-time. Unlike standard treatments that focus on medications and lifestyle changes, this tool provides healthcare providers with prognostic information and evidence-based guidance right at the point of care. It aims to improve timely referrals to palliative care, ensuring patients receive comprehensive support tailored to their needs. By integrating advanced decision support into everyday practice, this tool has the potential to streamline care and improve outcomes for patients with heart failure.

What evidence suggests that this clinical decision support tool is effective for heart failure?

Research has shown that clinical decision support (CDS) tools can improve care for heart failure patients. In this trial, one group of providers will use a CDS tool specifically designed for heart failure to deliver prognostic information and evidence-based decision support. One study found that a CDS tool tailored for heart failure outperformed a general one in helping doctors make quick and accurate decisions. Another study demonstrated that using a CDS tool in the emergency room helped doctors identify which heart failure patients needed urgent care. However, the success of these tools can vary, and not all CDS tools perform equally well in practice. Overall, while these tools are promising, their effectiveness depends on their design and use. ^{6 7 8 9 10}

Who Is on the Research Team?

Shelli Feder, PhD

Principal Investigator

Yale University

Are You a Good Fit for This Trial?

This trial is for hospitalized individuals with heart failure. It aims to improve their care by using a new tool that helps doctors decide when it's time to refer patients to palliative care, which focuses on relieving symptoms and stress.

Inclusion Criteria

Hospital administrator/quality and safety personnel

Not pregnant at the time of admission

Healthcare providers must meet the following criteria:

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Providers use the Clinical Decision Support (CDS) tool to deliver prognostic information and evidence-based decision support for timely referral to palliative care

15 months

Follow-up

Participants are monitored for outcomes such as consultation by Specialist Palliative Care, advance care plan documentation, and hospital readmissions

15 months

What Are the Treatments Tested in This Trial?

Interventions

• Clinical Decision Support Tool

Trial Overview The study is testing a clinical decision support tool designed to integrate with hospital systems. This tool uses a risk model to predict mortality within one year and suggests when doctors should consider palliative care for the patient.

How Is the Trial Designed?

Group I: Level 2 providers Experimental Treatment 1 Intervention

Level 2 providers are providers potentially impacted by the tool. Level 2 providers will participate in one interview.

Group II: Clinical Decision Support (CDS) Tool Experimental Treatment 1 Intervention

Providers will use the CDS tool to deliver prognostic information and evidence-based decision support at the point of care for timely referral to palliative care for participants hospitalized with heart failure.

Group III: Standard of Care Active Control 1 Intervention

Providers will provide usual standard of care for participants hospitalized with heart failure.

Who Is Running the Clinical Trial?

Yale University

Lead Sponsor

Trials

1,963

Recruited

3,046,000+

National Heart, Lung, and Blood Institute (NHLBI)

Collaborator

Trials

3,987

Recruited

47,860,000+

Published Research Related to This Trial

Patient-reported outcomes (PROs) are crucial in heart failure management as they provide insights into how patients feel and function, which can enhance patient-centered care.

The review emphasizes the need to advance PRO measurement and integrate these assessments into national databases and electronic health records to improve the quality of care for heart failure patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Patient-reported outcomes in heart failure: existing measures and future uses. Thompson, LE., Bekelman, DB., Allen, LA., et al.[2022]

A new tool for clinicians in inpatient oncology units has been developed to prevent adverse events and enhance patient safety, focusing specifically on cancer patients.

The tool includes a catalog of adverse events and a risk map, which helps healthcare providers implement best practices in their daily activities to improve clinical safety.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Improving patient safety in the inpatient setting through risk assessment and mitigation. Reche Navarro, MN.[2016]

Assessing patients' functional status in chronic heart failure is crucial for understanding the effectiveness of treatments in prolonging life while minimizing disability, bridging the gap between clinical assessments and patient-centered outcomes.

Systematic and unbiased collection of patient-reported outcomes is essential, as it provides a clearer picture of the benefits of medical interventions from the patients' perspective, rather than relying solely on healthcare providers' evaluations.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Outcome assessment: functional status measures as therapeutic endpoints for heart failure. Rector, TS.[2019]

In a study of 261 heart failure patients, common adverse drug events (ADEs) included dizziness (26%) and dry mouth (24%), with nearly half of the patients perceiving these ADEs as serious and significantly impacting their daily lives.

Patients expressed a strong belief in healthcare providers' ability to manage ADEs, but many felt that these issues were chronic and caused emotional distress, highlighting the need for better communication between patients and providers regarding ADE management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Perceived adverse drug events in heart failure: patients' perception and related factors. De Smedt, RH., Haaijer-Ruskamp, FM., Groenier, KH., et al.[2011]

The study analyzed serious and fatal adverse drug reactions (ADRs) for 137 commonly-prescribed medicines, revealing significant differences in ADR rates across various therapeutic classes, which highlights the importance of monitoring drug safety.

This research demonstrates the feasibility of creating comparative safety charts by mapping ADR reports to prescription data, which could aid healthcare professionals in making informed decisions about medication safety.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Comparative Safety Analysis of Medicines Based on the UK Pharmacovigilance and General Practice Prescribing Data in England. Mokbel, K., Daniels, R., Weedon, MN., et al.[2022]

Clinical decision support software (CDSS) can enhance the treatment of chronic heart failure by providing evidence-based guidelines, but its effectiveness is limited by low computer skills among family physicians and the software's inability to address nonmedical patient needs.

To improve the implementation of CDSS in chronic heart failure management, strategies such as enhancing computer skills among healthcare providers and integrating CDSS into existing referral pathways are recommended.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical decision support software for chronic heart failure. Leslie, SJ., Denvir, MA.[2007]

The Pediatric Quality of Life Inventory (PedsQL) showed strong responsiveness and predictive validity in a study of 4,637 pediatric patients, indicating it can effectively measure changes in health-related quality of life during hospital stays.

Patients with medically complex conditions had lower improvement scores on the PedsQL compared to those without chronic conditions, and lower admission scores were linked to higher risks of prolonged hospital stays and readmissions, highlighting its potential as a tool for assessing patient outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Validity and responsiveness of the pediatric quality of life inventory (PedsQL) 4.0 generic core scales in the pediatric inpatient setting. Desai, AD., Zhou, C., Stanford, S., et al.[2022]

The Treatment Tool, part of the SensorART platform, aids specialists in managing heart failure patients with left ventricular assist devices (LVADs) by providing decision support for treatment strategies and patient assessments.

This web-based tool calculates risk scores and predicts adverse events, enhancing the ability of healthcare providers to make informed decisions regarding LVAD management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Adverse event prediction in patients with left ventricular assist devices. Tsipouras, MG., Karvounis, EC., Tzallas, AT., et al.[2020]

A systematic review identified 31 patient-reported outcome (PRO) instruments for heart failure, but only 2—the Minnesota Living with Heart Failure and Kansas City Cardiomyopathy questionnaires—met all evaluation criteria for psychometric properties and clinical utility.

Despite the existence of effective PRO instruments, there is a need for better education for healthcare providers on their value and a more streamlined implementation process in clinical settings to enhance patient care.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Utility of Patient-Reported Outcome Instruments in Heart Failure. Kelkar, AA., Spertus, J., Pang, P., et al.[2016]

In a study of 754 heart failure patients, 50% reported experiencing dizziness and 44% reported a dry cough, with these adverse effects leading to a 38% increased likelihood of medication changes.

Among the reported adverse effects, a dry cough was associated with the highest risk of medication change (1.83 times more likely), while patients reporting gout had a fourfold increase in the likelihood of starting or intensifying alleviating medications.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The impact of perceived adverse effects on medication changes in heart failure patients. De Smedt, RH., Jaarsma, T., Haaijer-Ruskamp, FM., et al.[2013]

Patient-reported outcomes (PROs) are essential for understanding heart failure (HF) from the patient's perspective, as they capture the impact of the disease on daily life and can improve treatment adherence.

Despite their proven effectiveness in evaluating disease status and correlating with prognosis in clinical trials, the use of PROs in everyday clinical practice for heart failure remains limited, highlighting the need for strategies to integrate patient perspectives into care.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Use of patient-reported outcomes in heart failure: from clinical trials to routine practice. Savarese, G., Lindenfeld, J., Stolfo, D., et al.[2023]

The development of clinical decision support (CDS) tools for predicting hospital readmissions in heart failure patients can be enhanced by combining interdisciplinary expertise, ensuring the tools are evidence-based and user-friendly.

Involving clinicians throughout the development process helps tailor the CDS tools to meet end-user needs, facilitating better integration into clinical workflows.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Interdisciplinary Human-Centered AI for Hospital Readmission Prediction of Heart Failure Patients. Soliman, A., Nair, M., Petersson, M., et al.[2023]

The use of a clinical decision support system in telemonitoring heart failure patients allows for real-time medication adjustments based on vital signs, potentially improving patient outcomes and reducing unnecessary hospital visits.

This study evaluates the effectiveness of the decision support system within the INTENSE-HF trial, highlighting its adherence to European Society of Cardiology guidelines while also identifying areas for improvement in telehealth practices.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Telemonitoring in heart failure patients with clinical decision support to optimize medication doses based on guidelines. Kropf, M., Modre-Osprian, R., Hayn, D., et al.[2020]

Electronic health records (EHR) can significantly enhance the management of congestive heart failure (CHF) by standardizing care, promoting adherence to evidence-based guidelines, and improving workflow efficiency, as discussed in a review of various EHR tools.

The review highlights that EHR technologies, such as clinical decision support and telehealth, not only improve patient engagement and performance metrics but also contribute to quality improvement and clinical research in CHF management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Heart Failure Management Innovation Enabled by Electronic Health Records. Kao, DP., Trinkley, KE., Lin, CT.[2021]

Citations

1. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC10584394/

Sustained Effect of Clinical Decision Support for Heart Failure ... heart failure compared with an unmodified commercially available CDS. At ... effectiveness compared with a commercially available CDS tool. Keywords ...

2. jamanetwork.com jamanetwork.com/journals/jamanetworkopen/fullarticle/2812083

Clinical Decision Support to Treat Patients With Heart ... ... CDS would improve efficiency by presenting much of this important data. ... heart failure risk stratification tool in the emergency department.

3. jacc.org jacc.org/doi/10.1016/j.jacadv.2023.100354

Clinical Decision Support Tools for Optimizing Guideline ... Application of CDS for cardiovascular disease in general has been limited and with variable success. ... Failure: A Controlled Trial Investigating ...

4. clinicaltrials.gov clinicaltrials.gov/ct2/show/NCT06847906?draw=2&rank=1

Evaluating the Reach of Clinical Decision Support for ... The objective of this study is to test the reach, feasibility and acceptability of a new CDS tool for heart failure with reduced ejection fraction (HFrEF) ...

5. sciencedirect.com sciencedirect.com/science/article/pii/S266666772400223X

Do clinical decision support tools improve quality of care ... ... CDS may hinder the ability for cardiovascular health outcomes to be achieved. ... cardiovascular disease: a cluster randomized clinical trial. JAMA Netw Open ...

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC12535060/

Study protocol for the design, implementation, and evaluation ... Clinical decision support (CDS) tools ... clinical decision support tool for emergency department disposition of patients with heart failure.

7. ahajournals.org ahajournals.org/doi/10.1161/JAHA.123.031523

Evaluation of a Clinical Decision Support Tool to Guide ... CDS tools were embedded in the M Health Fairview EHR, Epic, to ... Acute decompensated heart failure, 48. Bradycardias, 48. Chest pain ...

8. sciencedirect.com sciencedirect.com/science/article/pii/S0735109723003297

Cluster-Randomized Trial Comparing Ambulatory Decision ... Electronic health record (EHR)-embedded clinical decision support (CDS) tools have the potential to improve MRA prescribing in a low-cost, scalable manner and ...

9. nature.com nature.com/articles/s41746-020-0221-y

An overview of clinical decision support systems: benefits ... ... clinical workflow tools. Each ... Clinical decision support software for management of chronic heart failure: Development and evaluation.

10. jamanetwork.com jamanetwork.com/journals/jamanetworkopen/fullarticle/2788645

Effect of Clinical Decision Support at Community Health ... The use of a CDSS in community health centers has the potential to improve reversible risk of cardiovascular disease among socioeconomically vulnerable high- ...