Tailored Risk Reduction Strategies for Preventable Causes of Death

Overseen By Jonathan Feelemyer

Age: 18 - 65

Sex: Any

Trial Phase: Academic

Sponsor: NYU Langone Health

Disqualifiers: Regular care elsewhere, High mortality conditions, others

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

Compensation: Varies

Number of Visits: Unknown

150 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to determine if personalized help can reduce the risk of dying from preventable issues such as heart attacks, strokes, alcohol use, substance abuse, and HIV. Participants will receive tailored support, including visits from peer navigators trained to motivate and guide them in managing their health. The trial seeks individuals aged 35 to 64 with lower income who may be at higher risk for these health issues. Participants must be willing to attend health services in New York City and be able to consent in English or Spanish. As an unphased trial, this study offers a unique opportunity to contribute to research that could lead to innovative health solutions.

Do I need to stop my current medications for the trial?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators.

What prior data suggests that this intervention is safe for reducing preventable causes of death?

Research shows that patient navigation programs, like the one in this study, are generally safe and well-tolerated. These programs guide patients through healthcare systems and connect them with necessary services. Studies have shown that such programs often improve patient outcomes without significant safety concerns.

The intervention in this trial includes navigation, compensation, and personalization. Although specific safety data on this exact combination is unavailable, patient navigation has been used successfully in many healthcare settings. It helps patients understand their health and access care without reports of harmful effects.

This study is marked as "Not Applicable" for its phase, indicating a focus on understanding how well the intervention works rather than testing new drugs or treatments. Therefore, the intervention's components are not expected to pose significant risks.

Participants interested in joining should feel reassured that no evidence links these types of interventions to adverse events. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it explores a holistic approach to reducing preventable deaths in low socioeconomic status (SES) populations. Unlike traditional treatments that often focus solely on medical interventions, this study integrates navigation, compensation, and personalization. These elements aim to address social determinants of health by employing trained peer navigators who use Motivational Interviewing techniques to guide and support participants. This approach is innovative because it targets the root causes of health disparities and empowers individuals with tailored strategies, potentially leading to more sustainable health outcomes.

What evidence suggests that this trial's interventions could be effective in reducing preventable causes of death?

This trial will compare two approaches for participants from low socioeconomic status (SES) populations. One group will receive no intervention, continuing with their normal medical care. The other group will receive a study intervention composed of navigation, compensation, and personalization. Research has shown that approaches like the one being studied—using guidance, support, and customization—can help people manage their health better. Studies have found that personal guides and motivational talks can encourage patients to take a more active role in their health care. Another study found that programs helping patients navigate the health system can be cost-effective for managing conditions like strokes. While some combined care methods haven't greatly improved survival rates, they often help reduce unexpected hospital visits. Overall, these strategies could help lower preventable deaths from conditions such as heart attacks, strokes, and substance abuse. ^{5 6 7 8 9}

Who Is on the Research Team?

Ronald S Braithwaite, Braithwaite

Principal Investigator

NYU Langone Health

Are You a Good Fit for This Trial?

This trial is for people aged 35-64 with low income (≤ $38,000), at high risk of heart disease (10-year risk ≥10%), and who drink heavily based on SAMHSA's definition. Participants must be willing to use New York's public health system and can consent in English or Spanish.

Inclusion Criteria

Expected mortality ≥1% per year (based on age, sex, race/ethnicity), with ≥1 of the following contributors: 10-year cardiovascular risk ≥10% (assessed by ASCVD risk tool), Heavy alcohol consumption (defined using SAMHSA binge drinking definition, drinking >4 standard drinks for men and >3 standard drinks for women on same occasion in past month), Willing to be navigated to Health and Hospitals Corporation of New York health system, Ability to provide written informed consent in English or Spanish

I am between 35 and 64 years old.

My annual income is $38,000 or less, adjusted for my family size.

Exclusion Criteria

Receives regular care elsewhere than Health and Hospitals Corporation of New York

I have a life-threatening condition not covered in the study.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Participants receive the study intervention, composed of navigation, compensation, and personalization, administered by peer navigators trained in Motivational Interviewing techniques

12 months

Regular in-person visits

Follow-up

Participants are monitored for changes in alcohol use, cardiovascular risk, and HIV risk

12 months

What Are the Treatments Tested in This Trial?

Interventions

• Compensation
• Navigation
• Personalization

Trial Overview The study tests a personalized intervention aimed at reducing death from preventable causes like heart disease, excessive alcohol use, substance abuse, and HIV. It includes patient outreach navigation, individualized health benefits personalization, and covering patients' health-related costs.

How Is the Trial Designed?

Group I: Low SES Population - Intervention Experimental Treatment 1 Intervention

Participants receive the study intervention, composed of navigation, compensation, and personalization for study participants. The intervention will be administered in person to the participants recruited for the study and will be administered by peer navigators who will be trained on Motivational Interviewing (MINT) techniques.

Group II: Low SES Population - No Intervention Active Control 1 Intervention

Participants receive no intervention components of navigation, compensation, and personalization. Participants will receive their normal medical care through regular doctor visits without any intervention or personalization.

Who Is Running the Clinical Trial?

NYU Langone Health

Lead Sponsor

Trials

1,431

Recruited

838,000+

National Institute on Alcohol Abuse and Alcoholism (NIAAA)

Collaborator

Trials

865

Recruited

1,091,000+

Published Research Related to This Trial

Search query data from Google indicates that public interest in health-related behaviors like 'weight', 'diet', 'fitness', and 'smoking' peaks in January and declines throughout the year, suggesting a seasonal pattern in health-related searches.

Understanding these patterns can help design more effective public health interventions and campaigns by targeting specific times and locations when interest in these behaviors is highest.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Search query data to monitor interest in behavior change: application for public health. Carr, LJ., Dunsiger, SI.[2021]

A qualitative study involving 36 adults with type 2 diabetes explored their reactions to a cardiovascular risk calculator, revealing complex cognitive and emotional responses that may hinder behavior change despite the calculator's intended purpose of motivating healthier choices.

The findings suggest that cardiovascular risk calculators are more effective when used alongside health professionals, who can help interpret the risk information and encourage users to take preventive actions.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Patient reactions to a web-based cardiovascular risk calculator in type 2 diabetes: a qualitative study in primary care. Nolan, T., Dack, C., Pal, K., et al.[2022]

In a study of 7740 HIV-positive patients, the 8-year risk of all-cause mortality was found to be 17.5%, with HIV-related mortality accounting for 39% of total mortality risk when using a cause-of-death weighting approach.

The study revealed that using this weighting method highlighted a higher risk of cardiovascular disease among patients with a history of injection drug use, showing an 8% attribution compared to only 4% when considering just the underlying cause.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Estimating a Set of Mortality Risk Functions with Multiple Contributing Causes of Death. Breger, TL., Edwards, JK., Cole, SR., et al.[2022]

Traditional national cause of death statistics often oversimplify complex health issues by reducing them to a single cause, which can overlook important contributing factors.

A new multidimensional approach that includes multiple causes of death from death certificates reveals that many major causes, like diabetes, significantly contribute to deaths beyond their classification as the underlying cause, highlighting the need for more comprehensive data in understanding health patterns.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

New dimensions in cause of death statistics. Chamblee, RF., Evans, MC.[2019]

In a study analyzing 2,846,305 deaths in the US, only 0.16% were classified as due to medical adverse events, indicating a significant underreporting of such incidents in current diagnostic coding systems.

Younger individuals, black ethnicity, and those with higher education levels were found to have higher odds of adverse event deaths, suggesting potential disparities in how these events are recorded and recognized.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Medical adverse events in the US 2018 mortality data. Oura, P.[2022]

In 2001, there were approximately 4.3 million visits to healthcare facilities in the U.S. due to adverse drug events (VADEs), indicating a significant patient safety concern.

The study found that VADEs were more common in elderly patients aged 65-74 and in females, highlighting the need for targeted safety measures in these populations.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Ambulatory care visits for treating adverse drug effects in the United States, 1995-2001. Zhan, C., Arispe, I., Kelley, E., et al.[2019]

A new risk prediction model developed using data from 8,241 respondents accurately estimates a person's 10-year mortality risk based on 12 major behavioral and biometric risk factors, showing good predictive ability with an ROC curve of 0.84 for both men and women.

The model highlights that a small percentage of the population (5.1% of men and 5.9% of women aged 30-44) accounts for a significant portion (25%) of mortality risk, indicating that targeted interventions could be effective in improving population health.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Validation of a new predictive risk model: measuring the impact of the major modifiable risks of death for patients and populations. Lim, SS., Carnahan, E., Nelson, EC., et al.[2023]

From 1999 to 2010, age-adjusted death rates in the U.S. declined for six of the ten leading causes of death, with the most significant decrease seen in cerebrovascular disease (-36.5%), while rates increased for four causes, notably Alzheimer disease (52.4%).

Despite overall declines in death rates, disparities in mortality by sex and race/ethnicity persisted across all causes, highlighting the need for targeted public health interventions to address these inequalities.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Trends in Disparity by Sex and Race/Ethnicity for the Leading Causes of Death in the United States-1999-2010. Chang, MH., Moonesinghe, R., Athar, HM., et al.[2022]

In a study analyzing data from 606,260 patients in Maine, significant regional differences were found in behavioral risks for cardiovascular disease, such as smoking (12.4%-28.6%) and poor diet (43.6%-73.0%), which are strongly linked to cardiovascular mortality.

Despite variations in medical interventions like revascularization, there was no significant association between these procedures and reduced cardiovascular disease mortality, highlighting the importance of focusing on modifiable risk factors for prevention.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Behavioral Risk Factors and Regional Variation in Cardiovascular Health Care and Death. Fairfield, KM., Black, AW., Lucas, FL., et al.[2019]

Tobacco use was identified as the leading cause of death in the United States in 2000, accounting for 435,000 deaths (18.1% of total deaths), highlighting the critical need for smoking prevention and cessation programs.

Poor diet and physical inactivity were also significant contributors, causing 365,000 deaths (15.2%), suggesting that these factors may soon surpass tobacco as the leading cause of mortality, emphasizing the urgency for preventive health measures.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Actual causes of death in the United States, 2000. Mokdad, AH., Marks, JS., Stroup, DF., et al.[2022]

The study created detailed US mortality rates from 1960 to 1989 using multiple cause-of-death data, revealing that death certificates typically list an average of 2.66 causes, which has increased over the decades.

Multiple-cause analysis identified significant excesses of renal disease and arthritis among granite cutters, highlighting the importance of considering contributory conditions in understanding occupational health risks.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Use of multiple-cause mortality data in epidemiologic analyses: US rate and proportion files developed by the National Institute for Occupational Safety and Health and the National Cancer Institute. Steenland, K., Nowlin, S., Ryan, B., et al.[2022]

In 2014, the estimated number of potentially preventable deaths from cancer, stroke, and heart disease decreased compared to 2010, indicating progress in public health efforts, with cancer deaths dropping by 25%.

However, deaths from chronic lower respiratory diseases and unintentional injuries increased, highlighting areas that still require attention and targeted prevention strategies to reduce premature deaths.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Potentially Preventable Deaths Among the Five Leading Causes of Death - United States, 2010 and 2014. García, MC., Bastian, B., Rossen, LM., et al.[2017]

Adverse drug events are a major cause of death in US hospitals, ranking as the fourth to sixth leading cause, with fatalities surpassing those from pneumonia and diabetes.

The economic impact of drug-related morbidity and mortality is substantial, estimated at $30 billion annually, potentially exceeding $130 billion in severe cases, highlighting the need for improved monitoring and prevention strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Counting the costs of drug-related adverse events. White, TJ., Arakelian, A., Rho, JP.[2022]

Citations

1. valueinhealthjournal.com valueinhealthjournal.com/article/S1098-3015(20)34410-7/fulltext

Cost-Effectiveness of the Wellness Incentives and ... The WIN intervention used a personal navigator, motivational interviewing, and a flexible wellness expense account to increase patient activation.

2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC8519430/

Cost-effectiveness of patient navigation programs for stroke ... The aim of this systematic review is to analyze the level of evidence on the cost-effectiveness of PN for stroke survivors.

3. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC10350749/

Unveiling the Significance and Challenges of Integrating ... In recent years, there has been a global increase in human life expectancy, but preventable morbidity and mortality remain significant ...

4. sciencedirect.com sciencedirect.com/science/article/pii/S0168851022000653

The impact of an integrated care intervention on mortality ... The intervention was associated with small increases in unplanned hospitalisation and unchanged survival, with similar effects by deprivation group.

5. acsjournals.onlinelibrary.wiley.com acsjournals.onlinelibrary.wiley.com/doi/10.3322/caac.21788

Patient navigation across the cancer care continuum: An ... Overall evidence from 43 unique primary studies across nine reviews suggested that patient navigation interventions were effective at reducing ...

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC10165767/

Effectiveness of system navigation programs linking ... This systematic review aims to identify the effectiveness of system navigation programs linking primary care with community-based health and social services.

7. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC8287353/

Factors Influencing the Implementation of Patient Navigation ... We conducted a scoping review to identify and summarize the current state of knowledge regarding the implementation and outcomes of existing implemented PNPs.

8. jons-online.com jons-online.com/issues/2014/april-2014-vol-5-no-2/3665-the-effect-of-different-types-of-navigators-on-patient-outcomes

The Effect of Different Types of Navigators on Patient ... This review examines the outcomes of different types of navigators reported in 14 studies published between 2007 and 2013.

9. pressroom.cancer.org pressroom.cancer.org/2022-06-14-National-Navigation-Roundtable-publishes-new-supplement-on-the-role-patient-navigation-plays-in-improving-patient-outcomes

National Navigation Roundtable Publishes New ... Press Releases. National Navigation Roundtable Publishes New Supplement on the Role Patient Navigation Plays in Improving Patient Outcomes.