Postpartum Depression
Conditions
Keywords
Clinical decision support tool
Brief summary
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).
Detailed description
The goal of this randomized clinical trial is to assess the implementation of a clinical decision support (CDS) tool. The tool is designed to assist providers in managing patients at risk of developing of postpartum depression. Investigators hypothesize that this tool will be acceptable and feasible for use and improve the use of mental health services for postpartum depression. Patients in the control arm will receive usual care, while those in the intervention arm will receive CDS. 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. Clinicians in the intervention arm will refer patients based on the CDS.
Interventions
The CDS in and AI algorithm that 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 prevention such as conducting referrals to nutrition and behavioral health, suggest educational readings through patient portals, or no actions. Clinicians in the intervention arm will refer patients based on the CDS.
Sponsors
Study design
Eligibility
Inclusion criteria
* 18 years or older * being seen at one of participating clinics * pregnancy at 20 week gestation or more
Exclusion criteria
* Does not speak inclusion * does not have internet access Clinician eligibility: * If they manage patients in the three clinics as a board-certified OBGYN clinician. * No
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Acceptability as measured by Unified Theory of Technology Acceptance Theory (UTAUT). | One month after initiation of tool use and three months after use. | UTAUT has five constructs: performance expectation, effort expectation, social influence, facilitating conditions, and behavioral intention. The performance expectation construct in UTAUT is the CDS's ability to identify patients at risk of PPD that clinicians agree with. For each construct, responses will be sought in the 7-point Likert scale, setting 1 as 'strongly disagree', 2 as 'disagree', to 7 as 'strongly agree'. We will average the acceptability survey responses at the end of the study for each of the 5 UTAUT constructs to create a binary variable. An average score of 5 or above will be considered acceptance and non-acceptance otherwise |
| Appropriateness as measured by Appropriateness Measure (IAM). | One month after initiation of tool use and three months after use. | IAM is a 4-item measure to assess the appropriateness of the intervention, respectively, with excellent usability. IAM is to be answered by participants in 5-point response scale: 1 = Completely disagree, 2 = Disagree, 3 = Neither agree nor disagree, 4 = Agree, 5 = Completely agree. |
| Feasibility as measured by Feasibility of Intervention Measure (FIM). | One month after initiation of tool use and three months after use. | FIM is a 4-item measure to assess the feasibility of the intervention, respectively, with excellent usability. FIM is to be answered by participants in 5-point response scale: 1 = Completely disagree, 2 = Disagree, 3 = Neither agree nor disagree, 4 = Agree, 5 = Completely agree. |
| Mental Health service utilization as measured by number of mental health visits | one month and three month | Mental health service utilization includes presentations to ED or inpatient admission for mental health related reasons. |
Countries
United States
Contacts
Weill Medical College of Cornell University