Decision Support Tool for Chronic Kidney Disease

Recruiting at 1 trial location

Overseen By Chandana Gowdara, MAS

Age: 65+

Sex: Any

Trial Phase: Academic

Sponsor: VA Palo Alto Health Care System

Disqualifiers: Cognitive impairment

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

Compensation: Varies

Number of Visits: 1

25 Participants Needed

Trial Summary

What is the purpose of this trial?

The aim of this study is to evaluate the impact of a web-based dialysis decision support tool on decisional conflict, and values-treatment concordance and other decisional outcomes in individuals with advanced chronic kidney disease, and to assess the tool's acceptability and usability.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the treatment Web-based dialysis decision support tool, Dialysis Decision Support Tool, Web-Based Dialysis Decision Aid?

The research suggests that decision aids, like the Web-based dialysis decision support tool, help patients make better treatment choices by providing clear information and involving family input, which can lead to better treatment compliance and outcomes. ^{1 2 3 4 5}

Is the Decision Support Tool for Chronic Kidney Disease safe for humans?

The research does not provide specific safety data for the Decision Support Tool for Chronic Kidney Disease, but it highlights that patients with chronic kidney disease (CKD) are at high risk for adverse safety events due to the complexity of their care. This suggests the importance of careful monitoring and management when using any decision support tools in this population. ^{4 5 6 7 8}

How does the Decision Support Tool for Chronic Kidney Disease differ from other treatments?

This treatment is unique because it uses digital health tools to help patients and their families make informed decisions about kidney replacement treatments, focusing on shared decision-making and preparation. Unlike traditional treatments, it emphasizes patient education and involvement in the decision process, tailored to individual needs and preferences. ^{2 4 5 9 10}

Research Team

Manjula Tamura, MD, MPH

Principal Investigator

U.S. Department of Veterans Affairs - Palo Alto Health Care System

Eligibility Criteria

This trial is for individuals with advanced chronic kidney disease who are facing decisions about dialysis. The study seeks participants willing to use a web-based tool designed to support these decisions. Specific eligibility criteria details were not provided.

Inclusion Criteria

I am 65 years old or older.

English speaking

Not a candidate for kidney transplant based on nephrologist assessment.

Exclusion Criteria

Patients with cognitive impairment will be excluded; however, their family member or caregiver is eligible to participate.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Baseline Assessment

Participants complete baseline surveys assessing demographics, knowledge of kidney failure treatments, and decisional conflict during a nephrology clinic visit

1 visit

1 visit (in-person)

Intervention

Participants access the web-based dialysis decision support tool with follow-up support provided by the study coordinator

1-4 weeks

Follow-up

Participants complete follow-up surveys to re-evaluate knowledge, decisional conflict, values-treatment concordance, and the quality of shared decision-making. Telephone interviews are conducted to explore participants' understanding of treatment options and gather feedback on the decision support tool

1 month

Treatment Details

Interventions

• Web-based dialysis decision support tool

Trial Overview The study is testing a web-based dialysis decision support tool, aiming to see if it helps reduce decisional conflict and improves alignment between patients' values and their chosen treatments. It also evaluates the tool's ease of use and satisfaction among users.

Participant Groups

Group I: Intervention Experimental Treatment 1 Intervention

Web-based dialysis decision support tool

Group II: Control Active Control 1 Intervention

Historical controls

Who Is Running the Clinical Trial?

VA Palo Alto Health Care System

Lead Sponsor

Trials

97

Recruited

58,500+

Findings from Research

Patients with end-stage renal disease can choose and change their treatment options, making the way information is presented crucial for their decision-making process.

Using structured 'patient decision aids' that follow simple principles can help patients make informed choices about dialysis options, leading to better treatment compliance and improved health outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

How to select among dialysis options. Mooney, A.[2019]

A nonrandomized controlled trial involving 361 hemodialysis patients found that a computer-based clinical decision support system did not significantly improve blood pressure control compared to standard care over 12 months.

Despite providing audits and management suggestions to physicians, the intervention did not lead to a higher proportion of patients achieving target blood pressure levels, indicating that this approach may not be effective in this patient population.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical decision support to improve blood pressure control in hemodialysis patients: a nonrandomized controlled trial. Thompson, S., Hemmelgarn, B., Wiebe, N., et al.[2015]

The 'Kidney Failure Decision Aid' was developed to support shared decision-making in kidney failure treatment by providing real-world outcome information, including survival probabilities and treatment event rates, through a paper hand-out, an interactive website, and a personal summary sheet.

Initial testing showed that while some patients found survival probabilities confronting, both patients and clinicians believed the PtDA would enhance informed decision-making and align treatment choices with patient values and preferences.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Development of an online patient decision aid for kidney failure treatment modality decisions. Engels, N., van der Nat, PB., Ankersmid, JW., et al.[2022]

A new decision aid, consisting of a 50-minute video and an informational handbook, was developed to help patients with end-stage renal disease (ESRD) and their families understand treatment options for renal replacement therapy (RRT).

Preliminary evaluations showed that the materials were well-received and comprehensible, with the handbook written at a 4th to 6th grade reading level, making it accessible for patients with varying health literacy and cognitive abilities.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Development of a decision aid to inform patients' and families' renal replacement therapy selection decisions. Ameling, JM., Auguste, P., Ephraim, PL., et al.[2021]

The development of an intelligent decision support system for managing chronic kidney failure aims to enhance treatment by utilizing existing knowledge and adapting based on real-time data from its use.

This system incorporates various decision support techniques to address the complexities and challenges faced by healthcare practitioners in managing end-stage renal disease patients, potentially improving patient outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Developing decision support for dialysis treatment of chronic kidney failure. Raghavan, SR., Ladik, V., Meyer, KB.[2019]

A clinical decision support (CDS) tool significantly improved the appropriate adjustment of medication prescriptions for patients with kidney impairment, with adjustments made 17% of the time in the intervention group compared to only 5.7% in the control group.

The CDS tool was particularly effective with prospective alerts, leading to appropriate adjustments in 55.6% of cases, highlighting its potential to enhance patient safety in medication prescribing for those with renal issues.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The impact of real-time alerting on appropriate prescribing in kidney disease: a cluster randomized controlled trial. Awdishu, L., Coates, CR., Lyddane, A., et al.[2018]

Chronic kidney disease (CKD) that does not require dialysis significantly increases the risk of adverse safety events, which can lead to poor patient outcomes, highlighting the need for better safety measures in CKD care.

Medication errors are prevalent in CKD patients and contribute to safety lapses, indicating that a standardized set of disease-specific safety indicators is essential for improving patient safety and outcomes in this population.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Finding a common language for patient safety in CKD. Fink, JC., Joy, MS., St Peter, WL., et al.[2019]

In a study of 267 predialysis patients with chronic kidney disease (CKD), 69.3% experienced at least one adverse safety event, highlighting the high risk of complications in this population.

The most common adverse events reported were hypoglycemia in diabetic patients and hyperkalemia (high potassium levels), with significant co-occurrences of these events, indicating a need for better safety monitoring in CKD patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Patient-reported and actionable safety events in CKD. Ginsberg, JS., Zhan, M., Diamantidis, CJ., et al.[2021]

The implementation of digital health tools in four chronic kidney disease clinics successfully identified 1,032 patients, with 24% classified as high-risk for kidney failure, demonstrating the efficacy of these tools in patient management.

The digital tools improved shared decision-making, as evidenced by 91% of patients completing a values clarification tool and 87% having their treatment preferences documented in the electronic health record, indicating high acceptability and usability among patients and healthcare providers.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Integrated Digital Health System Tools to Support Decision Making and Treatment Preparation in CKD: The PREPARE NOW Study. Green, JA., Ephraim, PL., Hill-Briggs, F., et al.[2022]

A consensus workshop with 24 participants, including 11 patients and 6 caregivers, identified key content preferences for an e-health tool to support chronic kidney disease self-management, emphasizing the need for reliable information on kidney health, diet, medication, and mental health.

Preferred features for the e-health tool included visuals, health tracking capabilities, and easy access to healthcare providers, highlighting the importance of user-friendly design in enhancing patient engagement and self-management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Preferences for a self-management e-health tool for patients with chronic kidney disease: results of a patient-oriented consensus workshop. Donald, M., Beanlands, H., Straus, S., et al.[2020]

References

1. Switzerland pubmed.ncbi.nlm.nih.gov

How to select among dialysis options. [2019]

2. Italy pubmed.ncbi.nlm.nih.gov

Clinical decision support to improve blood pressure control in hemodialysis patients: a nonrandomized controlled trial. [2015]

3. England pubmed.ncbi.nlm.nih.gov

Development of an online patient decision aid for kidney failure treatment modality decisions. [2022]

4. England pubmed.ncbi.nlm.nih.gov

Development of a decision aid to inform patients' and families' renal replacement therapy selection decisions. [2021]

5. United States pubmed.ncbi.nlm.nih.gov

Developing decision support for dialysis treatment of chronic kidney failure. [2019]

6. England pubmed.ncbi.nlm.nih.gov

The impact of real-time alerting on appropriate prescribing in kidney disease: a cluster randomized controlled trial. [2018]

7. United States pubmed.ncbi.nlm.nih.gov

Finding a common language for patient safety in CKD. [2019]

8. United States pubmed.ncbi.nlm.nih.gov

Patient-reported and actionable safety events in CKD. [2021]

9. United States pubmed.ncbi.nlm.nih.gov

Integrated Digital Health System Tools to Support Decision Making and Treatment Preparation in CKD: The PREPARE NOW Study. [2022]

10. Canada pubmed.ncbi.nlm.nih.gov

Preferences for a self-management e-health tool for patients with chronic kidney disease: results of a patient-oriented consensus workshop. [2020]