Rheumatologic Diseases vs PushPrescriber

Rheumatologic Diseases @Point of Care™ (PoC) provides a streamlined clinical decision support tool for clinicians who specialize in rheumatologic diseases including: Rheumatoid Arthritis, Psoriatic Arthritis, Ankylosing Spondylitis and Juvenile Idiopathic Arthritis to obtain content when it is needed, keep track of their patients—enabling better decisions, better outcomes, and better care. Featuring Ask With Watson (@sk), clinicians use @Point of Care™ Clinician Suite apps to easily access curated, evidence-based, and disease-specific medical content. Clinicians navigate content by asking voice-enabled natural language questions. The Ask With Watson, confidence-rated answers happen more quickly to efficiently incorporate best treatment options and decisions are made faster to improve patient outcomes at the point of care. Each @Point of Care™ Clinician Suite app is designed to: • Support discovery and practice change • Provide relevant, evidence-based disease-specific medical content • Improve patient outcomes at the point of care Features: • Continually updated content • Topics in diagnosis, treatment, and care management developed with expert physician authors • Case studies, videos, and interviews • Access to actionable patient-recorded data • Detailed reference list with access to original sources • Continuing medical education credit (CME/CE) • Surveys and peer polling • Patient education resources to share with patients • Receive detailed information regarding your patients' health such as: Medications and treatments; Symptoms and side effects; Charts that record test results, medication adherence, and more • Voice-activate commands for Watson, Patient Access and Clinical resources • Read-aloud feature for hands-free listening to medical texts • App Prescriber lets you prescribe one of our many patient apps to your patients

The tool provides a highly accurate and personalized likelihood of spontaneous vaginal birth versus C-Section and mother/child morbidity likelihood against each decision. The tool is the digital manifestation of the research found in “Pushing the Bounds of Second Stage in Term Nulliparas with a Predictive Model: When Should You Abandon the Ambition of Spontaneous Vaginal Delivery?” by Alexis C. Gimovsky, Jordan T. Levine, Amelie Pham, Jack Dunn, Ying Daisy, Zhuo, and Alan Peaceman, submitted for publication.