Clinical Decision Support Tool for Postpartum Depression

(CDS Trial)

Recruiting at 2 trial locations

Overseen By Rochelle Joly, MD

Age: 18+

Sex: Female

Trial Phase: Academic

Sponsor: Weill Medical College of Cornell University

Disqualifiers: No internet access, others

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

Compensation: Varies

Number of Visits: Unknown

160 Participants Needed

Trial Summary

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

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

What data supports the effectiveness of the treatment Clinical Decision Support Tool for postpartum depression?

The Clinical Decision Support Tool has been shown to effectively increase the screening rate for postpartum depression by integrating a mandatory screening prompt into electronic health records, ensuring that nearly all women in a study were screened for postpartum depression. ^{1 2 3 4 5}

Is the Clinical Decision Support Tool for Postpartum Depression safe for humans?

The research articles provided do not contain specific safety data for the Clinical Decision Support Tool for Postpartum Depression or similar tools. They discuss general methods for monitoring drug safety and adverse drug events, but not the safety of this specific tool. ^{6 7 8 9 10}

How does the Clinical Decision Support Tool treatment for postpartum depression differ from other treatments?

The Clinical Decision Support Tool for postpartum depression is unique because it integrates with electronic health records to ensure universal and standardized screening for postpartum depression, addressing a major barrier in symptom detection by requiring clinicians to enter a mood assessment score for each patient. ^{1 4 5 11 12}

What is the purpose of this trial?

This study will evaluate the use of an automated process in the electronic health record (EHR) that will help providers to detect patients at risk of developing postpartum depression (PPD).

Research Team

Yiye Zhang, PhD

Principal Investigator

Weill Medical College of Cornell University

Eligibility Criteria

This trial is for pregnant individuals at least 20 weeks along, who are 18 years or older and visit one of the participating clinics. It's not for those who don't speak the language used in the study or lack internet access.

Inclusion Criteria

Being seen at one of the participating clinics

I am at least 20 weeks pregnant.

Exclusion Criteria

Does not speak inclusion

Does not have internet access

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Implementation of a clinical decision support tool to assist providers in managing patients at risk of developing postpartum depression

3 months

Ongoing monitoring through EHR

Follow-up

Participants are monitored for acceptability, appropriateness, and feasibility of the intervention

3 months

Treatment Details

Interventions

• Clinical Decision Support Tool

Trial Overview The study is testing a new tool within electronic health records designed to help healthcare providers identify patients at risk of postpartum depression before it develops.

Participant Groups

Group I: Intervention: Patients Experimental Treatment 1 Intervention

Group II: Intervention: CDS support , clinician Experimental Treatment 1 Intervention

Clinicians in the intervention arm will refer patients based on the CDS.The CDS will alert clinicians only if patients have high risk of developing PPD, and provide clinicians with risk score, risk factors, and anticipatory actions with an order set to assist with ordering. Clinicians will make the ultimate clinical judgement after receiving CDS aid, including taking no actions towards PPD prevention. Clinicians will manage patients per usual care, including initiating PPD preventive such as conducting referrals to nutrition and behavioral health, suggest educational readings through patient portals, or no actions.

Group III: No intervention: Patients Active Control 1 Intervention

The CDS will alert clinicians only if patients have high risk of developing PPD. Clinicians will manage patients per usual care, including initiating PPD preventive such as conducting referrals to nutrition and behavioral health, suggest educational readings through patient portals, or no actions.

Who Is Running the Clinical Trial?

Weill Medical College of Cornell University

Lead Sponsor

Trials

1,103

Recruited

1,157,000+

Findings from Research

A practice-based training program for postpartum depression significantly improved diagnosis and treatment rates among mothers, with 34.5% of participants showing elevated depression scores, and those in the intervention group more likely to receive appropriate care.

Women in the intervention group reported lower levels of depressive symptoms at both 6 and 12 months postpartum, indicating that structured screening and management can lead to better long-term mental health outcomes for mothers.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

TRIPPD: a practice-based network effectiveness study of postpartum depression screening and management. Yawn, BP., Dietrich, AJ., Wollan, P., et al.[2021]

Postmarketing safety evaluations of antidepressant drugs can benefit from data collected through systems like the FDA Adverse Event Reporting System and electronic medical records, which provide more extensive information than premarketing trials.

The study assesses the strengths and limitations of these data sources for pharmacovigilance, highlighting the need for consistent results and integration of evidence to improve drug safety monitoring.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

On the evidence consistency of pharmacovigilance outcomes between Food and Drug Administration Adverse Event Reporting System and electronic medical record data for acute mania patients. Duan, R., Zhang, X., Du, J., et al.[2021]

The Assessment of Risk Tool (ART) developed by a New Zealand hospital significantly improved the identification of inpatients at high risk for adverse drug events (ADEs), leading to an increase in monthly medication reconciliations from 280 to 500 patients within 18 months of implementation.

During an 8-month period, the ART helped prioritize 765 high-risk patients for discharge services and successfully prevented 526 medication errors, including 174 that could have caused moderate to major harm, demonstrating its efficacy in enhancing patient safety.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Development of an electronic patient prioritization tool for clinical pharmacist interventions. Falconer, N., Nand, S., Liow, D., et al.[2022]

The safety profile of medications can change after they are approved for public use, as new safety issues may arise that were not identified during clinical trials.

Regulatory agencies, like the FDA, actively monitor medication safety through various methods, including analyzing adverse experience reports and using large electronic databases to detect potential safety signals.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Monitoring product safety in the postmarketing environment. Sharrar, RG., Dieck, GS.[2021]

References

1. Netherlands pubmed.ncbi.nlm.nih.gov

Development and validation of a machine learning algorithm for predicting the risk of postpartum depression among pregnant women. [2022]

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

TRIPPD: a practice-based network effectiveness study of postpartum depression screening and management. [2021]

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

Stepped care treatment of postpartum depression: a primary care-based management model. [2019]

4. Austria pubmed.ncbi.nlm.nih.gov

Using clinical decision support as a means of implementing a universal postpartum depression screening program. [2022]

5. England pubmed.ncbi.nlm.nih.gov

Evidence on postpartum depression: 10 publications to guide nursing practice. [2007]

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

Development and implementation of medication-related clinical rules for obstetrics, gynaecology, and paediatric outpatients. [2022]

7. England pubmed.ncbi.nlm.nih.gov

On the evidence consistency of pharmacovigilance outcomes between Food and Drug Administration Adverse Event Reporting System and electronic medical record data for acute mania patients. [2021]

8. England pubmed.ncbi.nlm.nih.gov

Development of an electronic patient prioritization tool for clinical pharmacist interventions. [2022]

9. England pubmed.ncbi.nlm.nih.gov

Monitoring product safety in the postmarketing environment. [2021]

10. Netherlands pubmed.ncbi.nlm.nih.gov

Routine use of the "ADE scorecards", an application for automated ADE detection in a general hospital. [2013]

11. Netherlands pubmed.ncbi.nlm.nih.gov

Application of machine learning in predicting the risk of postpartum depression: A systematic review. [2022]

12. Netherlands pubmed.ncbi.nlm.nih.gov

Predictive models for predicting the risk of maternal postpartum depression: A systematic review and evaluation. [2023]