protocolSection identificationModule nctId: NCT06382636, orgStudyIdInfo id: 23-101, briefTitle: Engaging Patients in Prenatal Genetic Testing Decisions as a Pathway to Improve Obstetric Outcomes, acronym: OPUS, statusModule overallStatus: NOT_YET_RECRUITING, startDateStruct date: 2024-05-31, primaryCompletionDateStruct date: 2027-02-28, completionDateStruct date: 2027-02-28, studyFirstPostDateStruct date: 2024-04-24, lastUpdatePostDateStruct date: 2024-04-24, sponsorCollaboratorsModule leadSponsor name: The Cleveland Clinic, class: OTHER, descriptionModule briefSummary: The goal of this study is to ensure that pregnant patients have the resources and support needed to access Prenatal Screening \& Diagnostic Testing (PS\&D) in an informed and evidence-based fashion by developing an innovative digital tool to support patients' decision-making and contributing fundamental knowledge to advance science in a way that promotes patients' access to new prenatal applications of genomic science and technology. Our central hypothesis is that, by focusing on patient engagement as a key driver to improve patient outcomes, the use of an evidence-based artificial-intelligence (AI) powered patient engagement tool will increase patients' ability to seek information and structure a decision-making process that, in turn, increases informed decisions about PS\&D and decreases decisional conflict associated with those decisions.Using data from NEST (Ensuring Patients Informed Access to NIPT \[non-invasive prenatal testing\]), the investigators designed the next iteration of NEST, a point-of care shared decision-making tool powered by artificial intelligence (AI) to provide a personalized and dynamic decision support tool: Obstetric Prenatal Genetic Testing Engagement Solution (OPUS). OPUS is an AI-enabled healthcare chatbot (a computer program capable of processing and simulating human conversation) that provides patients with personalized information and decision-making support at different stages of the PS\&D pathway. It functions using a series of questions contained in the NEST with a branching logic sequence of questions and answers based on the responses to and from the patient, using a conversational and adaptable interaction. It also contains nested tiers of information, ranging from introductory to detailed information about patient engagement, health literacy, the different PS\&D options, and resources to learn about insurance coverage for PS\&D. OPUS was designed to be accessed by patients with different technological resources and preferences, using a cell phone, a mobile device, or a computer., conditionsModule conditions: Prenatal Disorder, designModule studyType: INTERVENTIONAL, phases: NA, designInfo allocation: RANDOMIZED, interventionModel: PARALLEL, primaryPurpose: HEALTH_SERVICES_RESEARCH, maskingInfo masking: NONE, enrollmentInfo count: 600, type: ESTIMATED, armsInterventionsModule interventions name: Standard Care, interventions name: Obstetric Prenatal Genetic Testing Engagement Solution (OPUS) AI Chatbot, outcomesModule primaryOutcomes measure: Patient activation, eligibilityModule sex: FEMALE, minimumAge: 18 Years, maximumAge: 50 Years, stdAges: ADULT, contactsLocationsModule locations facility: Neighborhood Family Practice, city: Cleveland, state: Ohio, zip: 44102, country: United States, contacts name: Heidi Gullett, MD, role: CONTACT, phone: 216-368-0776, email: hlg31@case.edu, geoPoint lat: 41.4995, lon: -81.69541, locations facility: MetroHealth Medical Center, city: Cleveland, state: Ohio, zip: 44109, country: United States, contacts name: Angela Ranzini, MD, role: CONTACT, phone: 216-778-3513, email: aranzini@metrohealth.org, geoPoint lat: 41.4995, lon: -81.69541, locations facility: Cleveland Clinic, city: Cleveland, state: Ohio, zip: 44195, country: United States, contacts name: Ruth Farrell, MD, MA, role: CONTACT, phone: 216-445-7085, email: farrelr@ccf.org, contacts name: Christina Collart, MEd, role: CONTACT, phone: 216-470-9796, email: collarc@ccf.org, geoPoint lat: 41.4995, lon: -81.69541, hasResults: False