Clinical Support Tool for Preventing Cognitive Decline

(PCOT Trial)

Overseen By Venkatraghavan Sundaram, Ph.D.

Age: 65+

Sex: Any

Trial Phase: Academic

Sponsor: University of Texas Southwestern Medical Center

Disqualifiers: Dementia, Alzheimer's, Heart disease, others

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

Compensation: Varies

Number of Visits: Unknown

Duration: 4 years

4000 Participants Needed

Trial Summary

What is the purpose of this trial?

The PCOT study is a multi-site randomized trial of patients 70 years or older with high BP. The main goal of the study Preventing Cognitive Decline by Reducing BP Target Trial (PCOT) is to conduct a large pragmatic clinical trial (PCT) to test the hypothesis that patients who receive care with a combination of clinical decision support (CDS) and team-based care delivered in primary care practices will have better blood pressure control and a lower incidence of mild cognitive impairment and dementia than patients receiving usual medical care. Patients will be recruited from UT Southwestern Medical Center and Parkland Health \& Hospital System.

Will I have to stop taking my current medications?

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 or your doctor.

What data supports the effectiveness of the treatment Clinical Support Decision Tool, Clinical Decision Support (CDS), Team-Based Care for preventing cognitive decline?

Research shows that Clinical Decision Support (CDS) can improve decision-making and patient outcomes in various healthcare settings, such as cancer care and medication management, suggesting it might also be beneficial in preventing cognitive decline. ^{1 2 3 4 5}

Is the Clinical Support Tool for Preventing Cognitive Decline safe for humans?

Clinical decision support systems (CDSS) are generally considered safe and can help prevent medication errors and reduce adverse drug events. However, there are concerns about the safety of using mobile devices around medical equipment and the potential for new errors if the systems are not designed well. ^{6 7 8 9 10}

How is the Clinical Support Decision Tool treatment different from other treatments for preventing cognitive decline?

The Clinical Support Decision Tool is unique because it uses real-time data analysis and electronic health records to help healthcare providers make informed decisions at the point of care, unlike traditional treatments that may not integrate technology in this way. ^{4 8 9 11 12}

Eligibility Criteria

This trial is for people aged 70 or older with high blood pressure, defined as two readings of SBP >= 130 or DBP >=80 in the last 24 months. Participants must be able to communicate in English or Spanish, have visited a primary care provider within the last two years, and own a smartphone or tablet.

Inclusion Criteria

I have had high blood pressure readings in the last 2 years.

I have seen my primary care doctor in the last 2 years.

Ability to write and speak English or Spanish

Exclusion Criteria

I do not have recent severe heart issues or organ transplants.

I am currently undergoing or have undergone chemotherapy.

Your doctors believe you have less than a year to live.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive intensive blood pressure management with clinical decision support and team-based care

4 years

Monthly visits for BP monitoring

Follow-up

Participants are monitored for safety and effectiveness after treatment

4 weeks

Quality of Life Assessment

Quality of life scores are assessed annually using the PROMIS Scale v1.2 - Global Health instrument

4 years

Treatment Details

Interventions

• Clinical Support Decision Tool

Trial Overview The PCOT study tests if patients receiving team-based care and using a clinical decision support tool have better blood pressure control and lower rates of mild cognitive impairment compared to those getting usual medical care.

Participant Groups

Group I: Intervention Arm Experimental Treatment 1 Intervention

Home BP data will be averaged each month via OmronConnect app on the patients' smartphone, which is programmed to send home BP readings to MyChart via Apple or Google Health.Participants whose home blood pressure reading average is systolic ≥ 130 and diastolic ≥ 80 will trigger the CDS (Clinical Decision Support) tool to assist their physicians with their blood pressure management. Study Team will not be involved in treatment decision making, it will be determined by subject's treating physician. .

Group II: Usual Care Arm Active Control 1 Intervention

Physicians will continue to make decisions about the participant's blood hypertension management as usual without the CDS tool.

Who Is Running the Clinical Trial?

University of Texas Southwestern Medical Center

Lead Sponsor

Trials

1,102

Recruited

1,077,000+

Duke University

Collaborator

Trials

2,495

Recruited

5,912,000+

National Institute on Aging (NIA)

Collaborator

Trials

1,841

Recruited

28,150,000+

Parkland Health and Hospital System

Collaborator

Trials

20

Recruited

99,300+

Findings from Research

A systematic review of 10 studies on clinical decision support (CDS) in cancer management found that CDS can significantly improve clinician decision-making processes in 5 out of 9 studies.

Among the studies measuring patient outcomes, 4 out of 6 showed significant improvements, indicating that CDS informed by clinical practice guidelines may enhance both decision-making and patient care in cancer settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical decision support for therapeutic decision-making in cancer: A systematic review. Beauchemin, M., Murray, MT., Sung, L., et al.[2020]

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 study involving 22 multidisciplinary healthcare providers identified key themes influencing the design and acceptance of a clinical decision support (CDS) care map for thoracic trauma, emphasizing the importance of usability and minimal extra workload for end users.

The research highlighted eight dominant themes, including the need for a minimalistic design and evidence-based support, which are crucial for improving user acceptance and ultimately enhancing patient care outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Barriers to and Facilitators for Acceptance of Comprehensive Clinical Decision Support System-Driven Care Maps for Patients With Thoracic Trauma: Interview Study Among Health Care Providers and Nurses. Jones, EK., Banks, A., Melton, GB., et al.[2023]

Medication-related clinical decision support (CDS) systems are crucial for improving medication safety, but their effectiveness relies on users valuing and acting on alerts, highlighting the need for better alert specificity and sensitivity.

To enhance the efficacy of CDS, it is essential to integrate patient-specific factors, standardize processes, and apply human factors design principles, as many systems are still underdeveloped and can lead to alert fatigue.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Improving medication-related clinical decision support. Tolley, CL., Slight, SP., Husband, AK., et al.[2022]

A clinical decision support (CDS) system was developed to provide personalized pain management recommendations for dentists, aiming to reduce opioid prescriptions after dental extractions, and was implemented in a study involving patients from February 2020 to May 2021.

The CDS tool, which integrates with electronic health records and utilizes patient-specific data, showed variable provider engagement, with up to 87.4% of providers using it during extraction encounters, indicating its potential for improving pain management practices in dental settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report. Rindal, DB., Pasumarthi, DP., Thirumalai, V., et al.[2023]

The advanced clinical decision support system (CDSS) HIGEA effectively generated alerts for potential adverse drug events (ADEs), with 51% of alerts leading to interventions that prevented possible medication errors during a 6-month observational study.

The most effective intervention program was for dose adjustments in renal impairment, achieving a positive predictive value (PPV) of 0.51, indicating that the system significantly improved medication safety across various clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Development and Evaluation of a Clinical Decision Support System to Improve Medication Safety. Ibáñez-Garcia, S., Rodriguez-Gonzalez, C., Escudero-Vilaplana, V., et al.[2020]

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 study involving 60 registered nurses demonstrated that clinical decision support (CDS) tools significantly improved the adoption of best practices and reduced care planning time compared to a control group, indicating their effectiveness in enhancing evidence-based decision-making.

While all CDS formats (text, text + graph, and text + table) showed similar adoption rates, the study found that RNs with higher numeracy and graph literacy performed better in terms of care planning time, suggesting that the effectiveness of CDS tools may vary based on individual skills.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Toward Meaningful Care Plan Clinical Decision Support: Feasibility and Effects of a Simulated Pilot Study. Keenan, GM., Lopez, KD., Yao, Y., et al.[2022]

In a study involving 16 junior doctors over 4 months, only 24% of their interactions with mobile clinical decision support (mCDS) tools occurred during their shifts, indicating limited engagement with these tools in the workplace.

Despite concerns about the safety of using mobile devices in clinical settings, patients generally had positive perceptions of mCDS, viewing it as a beneficial part of clinical practice.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Use of Mobile Clinical Decision Support Software by Junior Doctors at a UK Teaching Hospital: Identification and Evaluation of Barriers to Engagement. Patel, R., Green, W., Shahzad, MW., et al.[2018]

A systematic review of 63 articles identified 327 barriers and 291 facilitators affecting the acceptance of medication-related Clinical Decision Support Systems (CDSS) among clinicians, highlighting issues related to the perceived usefulness and ease of use of these systems.

The findings suggest that improving the relevance and efficiency of CDSS could enhance clinician engagement and decision-making, paving the way for more effective medication management in clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Barriers and facilitators influencing medication-related CDSS acceptance according to clinicians: A systematic review. Westerbeek, L., Ploegmakers, KJ., de Bruijn, GJ., et al.[2021]

Clinical decision support (CDS) tools integrated into electronic health records can significantly enhance patient care outcomes by providing real-time data analysis for clinicians during critical decision-making processes.

The implementation of CDS tools in a community hospital setting has shown positive outcome data, indicating their effectiveness in improving healthcare organization performance, especially as financial reimbursement models shift towards patient care outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical decision support. How CDS tools impact patient care outcomes. Anton, BB., Schafer, JJ., Micenko, A., et al.[2019]

A survey of 930 dental clinicians revealed a strong willingness to adopt clinical decision support (CDS) tools integrated into electronic health records, with a focus on improving patient care rather than business processes.

Positive attitudes towards the implementation of CDS tools were significantly associated with job satisfaction, comfort with the EHR, and a sense of control over work, while feelings of burnout negatively impacted these attitudes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Provider Attitudes Toward the Implementation of Clinical Decision Support Tools in Dental Practice. Mertz, E., Bolarinwa, O., Wides, C., et al.[2018]

References

1. Ireland pubmed.ncbi.nlm.nih.gov

Clinical decision support for therapeutic decision-making in cancer: A systematic review. [2020]

2. England pubmed.ncbi.nlm.nih.gov

The technical landscape for patient-centered CDS: progress, gaps, and challenges. [2022]

3. Canada pubmed.ncbi.nlm.nih.gov

Barriers to and Facilitators for Acceptance of Comprehensive Clinical Decision Support System-Driven Care Maps for Patients With Thoracic Trauma: Interview Study Among Health Care Providers and Nurses. [2023]

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

Improving medication-related clinical decision support. [2022]

5. Canada pubmed.ncbi.nlm.nih.gov

Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report. [2023]

6. Germany pubmed.ncbi.nlm.nih.gov

Development and Evaluation of a Clinical Decision Support System to Improve Medication Safety. [2020]

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

How usability of a web-based clinical decision support system has the potential to contribute to adverse medical events. [2022]

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

Toward Meaningful Care Plan Clinical Decision Support: Feasibility and Effects of a Simulated Pilot Study. [2022]

9. Canada pubmed.ncbi.nlm.nih.gov

Use of Mobile Clinical Decision Support Software by Junior Doctors at a UK Teaching Hospital: Identification and Evaluation of Barriers to Engagement. [2018]

10. Ireland pubmed.ncbi.nlm.nih.gov

Barriers and facilitators influencing medication-related CDSS acceptance according to clinicians: A systematic review. [2021]

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

Clinical decision support. How CDS tools impact patient care outcomes. [2019]

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

Provider Attitudes Toward the Implementation of Clinical Decision Support Tools in Dental Practice. [2018]