Personalized CDS for Heart Failure

Overseen By Cathryn Perreira, MA

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: University of Colorado, Denver

Disqualifiers: Non-cardiology, Non-primary care, 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 aims to improve how doctors decide on treatments for heart failure with reduced ejection fraction (HFrEF), a condition where the heart doesn't pump effectively. Researchers are testing a new tool called Personalized Clinical Decision Support (CDS), which provides doctors with the most relevant advice based on their past prescribing habits. The goal is to help doctors make better treatment choices by eliminating unnecessary information. The trial seeks doctors who can prescribe medication and work in cardiology or primary care clinics at UCHealth. As an unphased trial, this study offers the opportunity to contribute to innovative research that could enhance treatment decisions for heart failure patients.

Will I have to stop taking my current medications?

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

What prior data suggests that this clinical decision support is safe for heart failure management?

Research has shown that clinical decision support (CDS) tools, like those in this trial, are generally safe. They assist doctors in making quicker and better decisions, particularly in heart failure care. Studies have found that most doctors believe these tools can enhance patient treatment, leading to improved health outcomes.

No reports of serious harm have emerged from using these digital tools, with the focus on enhancing their effectiveness. Unlike drugs or surgeries, these tools do not carry the same risks. The personalized CDS being tested aims to provide doctors with useful information based on their past choices. No evidence suggests that using these tools could cause harm; they are designed to guide and improve decision-making.

In summary, while the trial tests the effectiveness of the personalized CDS, existing evidence indicates no significant safety risk to participants. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the Personalized Clinical Decision Support (CDS) for heart failure because it tailors treatment recommendations to individual patient data, potentially improving outcomes compared to traditional methods. Unlike standard care options that often apply a one-size-fits-all approach, this personalized system uses advanced algorithms to consider a patient's unique health profile and treatment history. By offering more precise guidance to healthcare providers, it aims to enhance decision-making and optimize patient care.

What evidence suggests that this trial's clinical decision support tools could be effective for heart failure?

Research has shown that special computer systems, known as clinical decision support (CDS) systems, can help doctors manage heart failure more effectively. In this trial, participants will receive either Personalized Clinical Decision Support (CDS) or Traditional Clinical Decision Support (CDS). These personalized tools provide doctors with specific information, eliminating unnecessary details. Studies have found that these systems can reduce "alert fatigue," which occurs when doctors receive too many alerts and begin to ignore them. They also help doctors prescribe medications more accurately, leading to better treatment for heart failure with reduced ejection fraction (HFrEF) than traditional methods. Most doctors believe these systems can improve treatment in emergency situations and lead to better patient outcomes. ^{2 4 6 7 8}

Who Is on the Research Team?

Katy E Trinkley, PharmD, PhD

Principal Investigator

University of Colorado, Denver

Are You a Good Fit for This Trial?

This trial is for clinicians with prescribing privileges at UCHealth's outpatient cardiology or primary care clinics. It aims to observe and improve their prescribing behaviors, especially in the context of heart failure treatment.

Inclusion Criteria

Study subjects are potential users of the CDS, specifically clinicians with prescribing privileges who practice at one of the health system's (UCHealth) outpatient cardiology or primary care clinics. The study also evaluates patient characteristics that could influence their prescribing decisions.

Exclusion Criteria

Clinicians who do not practice in cardiology or primary care clinics or do not practice within UCHealth system.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Implementation of personalized and traditional clinical decision support (CDS) tools to evaluate their effectiveness in prescribing guideline-directed management and therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF)

6 months

Follow-up

Participants are monitored for the effectiveness of CDS tools in improving prescription practices

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Personalized Clinical Decision Support (CDS)
• Traditional Clinical Decision Support (CDS)

Trial Overview The study compares two types of Clinical Decision Support (CDS) tools: a 'personalized CDS' tailored to individual clinician's past behavior and misconceptions, versus a 'traditional CDS' that provides general guidance on heart failure prescriptions.

How Is the Trial Designed?

Group I: Traditional Clinical Decision Support (CDS) Experimental Treatment 1 Intervention

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

Who Is Running the Clinical Trial?

University of Colorado, Denver

Lead Sponsor

Trials

1,842

Recruited

3,028,000+

Published Research Related to This Trial

A study involving 51 emergency department physicians revealed that most believe clinical decision support (CDS) could enhance patient care for heart failure, but many expressed concerns about their ability to consistently follow its recommendations due to workload issues.

Physicians suggested improvements for the CDS, including better accessibility and integration into their workflow, and preferred a system that encourages interaction without making it mandatory.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Physicians' Perceptions of Clinical Decision Support to Treat Patients With Heart Failure in the ED. Casey, SD., Reed, ME., LeMaster, C., et al.[2023]

The article highlights the need for improved patient-centered clinical decision support (PC CDS) tools to enhance healthcare decision-making, emphasizing the importance of making research findings more shareable and publicly available.

A comprehensive assessment involving a technical expert panel, literature review, and interviews with 18 stakeholders identified key areas for improvement, including the need for standardized processes to integrate clinical guidelines and patient-generated health data into PC CDS systems.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The technical landscape for patient-centered CDS: progress, gaps, and challenges. Dullabh, P., Heaney-Huls, K., Lobach, DF., et al.[2022]

A clinical decision support software (CDSS) for treating chronic heart failure was developed through a collaborative process and evaluated over six months, showing that 70% of participants found it more useful than traditional paper guidelines.

The evaluation revealed that general practitioners had lower computer literacy compared to junior doctors and medical students, which may hinder the CDSS's implementation; thus, improving computer skills and integrating the CDSS into clinical workflows could enhance its usage.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical decision support software for management of chronic heart failure: development and evaluation. Leslie, SJ., Hartswood, M., Meurig, C., et al.[2022]

Clinical decision support (CDS) tools significantly improve the prescription of appropriate medications and dosages, with a pooled risk ratio of 1.48 based on 6 studies, indicating they are effective at the point of medication ordering or dispensing.

CDS tools also enhance laboratory monitoring and treatment responses to abnormal test results, showing a pooled risk ratio of 1.40, but evidence for their effectiveness in reducing adverse drug events remains inconsistent, suggesting further research is needed.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The Effect of Laboratory Test-Based Clinical Decision Support Tools on Medication Errors and Adverse Drug Events: A Laboratory Medicine Best Practices Systematic Review. Whitehead, NS., Williams, L., Meleth, S., et al.[2022]

A study analyzing the usability of clinical decision support systems (CDSS) for community-acquired pneumonia and neutropenic fever found 422 recorded events, including 3 mistakes that could have been life-threatening, highlighting the critical need for careful design and evaluation of these systems.

Incorporating usability engineering principles early in the design of CDSS can help identify interface issues that may lead to adverse medical events, emphasizing the importance of user-friendly software in improving patient safety.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

How usability of a web-based clinical decision support system has the potential to contribute to adverse medical events. Graham, TA., Kushniruk, AW., Bullard, MJ., et al.[2022]

The integrated clinical prediction rule (iCPR) project demonstrated that a novel form of clinical decision support (CDS) can be effectively integrated into electronic health records, leading to a 57.4% adoption rate among users and a 42.7% acceptance rate of its recommendations.

Key factors for the success of the iCPR included strong leadership support, dedicated training for users, and the implementation of context-sensitive triggers that prompted CDS interventions based on specific workflow events.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial. Kannry, J., McCullagh, L., Kushniruk, A., et al.[2020]

The implementation of a clinical decision support system (CDSS) significantly reduced the rate of excessive prescriptions from 4.5% to 3.6% over a 90-day study, indicating improved prescribing quality.

Physicians responded to about 25% of the alerts generated by the CDSS, with no new prescription errors occurring, suggesting that the system effectively guided safe medication practices without introducing additional risks.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Patient-specific electronic decision support reduces prescription of excessive doses. Seidling, HM., Schmitt, SP., Bruckner, T., et al.[2012]

Over a 30-month period, two organizations collected extensive user feedback on clinical decision support (CDS) tools, receiving 2,639 Likert feedback comments and 623,270 override comments, highlighting the importance of user input in improving these systems.

The feedback led to rapid responses to build errors and helped identify issues related to knowledge management and user interface, demonstrating that incorporating user suggestions can significantly enhance the effectiveness of CDS tools.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Real-Time User Feedback to Support Clinical Decision Support System Improvement. Rubins, D., McCoy, AB., Dutta, S., et al.[2023]

The CAD/DM Smart Form is a Clinical Decision Support System designed to enhance the management of chronic diseases like coronary artery disease and diabetes mellitus.

A pilot study indicates that this Smart Form could significantly improve patient care, suggesting its effectiveness in clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Improving management of chronic diseases with documentation-based clinical decision support: results of a pilot study. Schnipper, JL., McColgan, KE., Linder, JA., et al.[2019]

The study highlights the importance of trust in the adoption of standards-based clinical decision support (CDS) tools, which can be enhanced through transparency, expert collaboration, and user feedback.

While standards-based CDS resources have been developed, challenges remain in their broad implementation, particularly for lower-resourced health systems that require additional support to effectively utilize these tools.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Lessons Learned from a National Initiative Promoting Publicly Available Standards-Based Clinical Decision Support. Dhopeshwarkar, RV., Freij, M., Callaham, M., et al.[2023]

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]

Citations

1. pubmed.ncbi.nlm.nih.gov pubmed.ncbi.nlm.nih.gov/37352404/

Comparative effectiveness of generic commercial ... - PubMed Keywords: alert fatigue; clinical decision support; drug alerts; heart failure; implementation science; nonsteroidal anti-inflammatory drugs.

2. clinicaltrials.gov clinicaltrials.gov/study/NCT06293794?term=entresto

Study Details | Decision Support for Heart Failure Prescribing There are three types of expanded access: Individual Patients: Allows a single patient, with a serious disease or condition who cannot participate in a clinical ...

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

Clinical Decision Support to Treat Patients With Heart ... Most physicians believed that clinical decision support would improve emergency department treatment of patients with heart failure as well as patient outcomes.

4. withpower.com withpower.com/trial/phase-decision-support-systemsclinical-2-2024-ea0ca

Personalized CDS for Heart Failure · Info for Participants Research shows that Clinical Decision Support (CDS) systems can help doctors manage chronic heart failure by providing timely and relevant information, which ...

5. sciencedirect.com sciencedirect.com/science/article/pii/S2666602223000551

Optimizing efficiency of a custom clinical decision support ... Study objective. Improve the efficiency of an inpatient clinical decision support tool (CDS) for patients with adult congenital heart disease (ACHD).

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC5333307/

DCDS: A Real-time Data Capture and Personalized ... Heart failure disease management can improve health outcomes for elderly community dwelling patients with heart failure. This paper describes DCDS, a real-time ...

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

Sustained Effect of Clinical Decision Support for Heart Failure Sustained effect of clinical decision support for heart failure: a natural experiment using implementation science.

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

Do clinical decision support tools improve quality of care ... Do clinical decision support tools improve quality of care outcomes in the primary prevention of cardiovascular disease: A systematic review and meta-analysis.