The California Trusted Exchange Network enables HIEs and hospital systems to share health information statewide through a simple but robust trust framework that supports any exchange mechanism. Directory Services is a critical component of California’s strategy for statewide health information sharing among community HIEs, health systems and enterprise HIEs, and HIE service providers. In August 2016, CAHIE began development of an electronic services registry as part of Directory Services conforming to the emerging RESTful FHIR STU 3 specifications for Organization, Location, and Endpoint resources to support the Patient Unified Lookup System for Emergencies (PULSE) project.
Diabetes Predictive Analytics application analyses risk for Type 2 Diabetes for identifying patients who may benefit from additional clinical and laboratory screening using different medical algorithms. This application supports three algorithms for predicting the diabetes risk (for type 2 diabetes), in different medical conditions. Diabetes Risk Prediction (Griffin et al) - Predicting risk by calculating diabetes risk score using an algorithm developed by Griffin et al, to help identify patients in general practice with risk for Type 2 diabetes mellitus.
What would access to analytics, directly in the workflow of the EHR, do for your clinicians? Inform decision making, enabling improved outcomes? Speed decision making, having information seamlessly available? Focus decision making, efficiently using clinician time? Embedded analytics would do these three things and more. The SMART Analytics Adapter by Qlik enables electronic health records (EHR) software users to embed Qlik Sense® analytics directly into workflows. This allows your clinical decision makers to layer and view relevant information, uncover new insights, and use those insights to promote better clinical and business decisions.
Precision cancer medicine will require ready access to genomic data within the clinical workflow and tools to assist clinical interpretation and enable decisions. Since most electronic health record (EHR) systems do not yet provide such functionality, we developed an EHR-agnostic, clinico-genomic mobile app to demonstrate several features that will be needed for point-of-care conversations. Our prototype, called SMART Precision Cancer Medicine, visualizes genomic information in real-time, comparing a patient’s diagnosis-specific somatic gene mutations detected by PCR-based hotspot testing to a population-level set of comparable data.
A robust communications platform that keeps everyone in the loop Physicians, Nurses & Clinical Staff Administrative & Office Staff Patients & Caregivers Partners & Affiliates Leverage your EHR to positively identify patients and share medical record summaries. Manage schedules in line with your provider directory and share access. Capture notes, codes, and attachments to transmit back to the EHR.
Healthcare providers need to exchange large amounts of data while complying with inescapable industry and government regulations, including HIPAA, Meaningful Use, and the Final Omnibus Rule. Without pervasive integration capabilities, providers risk millions in dollars in fines for breaches that may expose Patient Health Information (PHI) or Personally Identifiable Information (PII). Exchanging sensitive healthcare information across various systems, applications, and processes, leave the organization vulnerable to inherent data security risk. Whether you need secure file sharing for discharge care instructions to patients, secure file transfer to support document exchange for medical files such as MRI images and doctors’ notes to payers, or secure notifications leveraging a desktop MFT integration, Cleo provides comprehensive integration solutions that help ensure compliance and provide accelerated ROI.
1upHealth’s provider application helps aggregate patient data from external health systems into one place. Providers can view the data sources that patients have connected via the 1upHealth patient application. Data is presented in an easy to understand patient timeline which supports demographics, medications, labs, conditions, and history. Supported 3rd party data sources include: Other health system FHIR® servers CCDA Uploads (converted to FHIR®) Patient reported data (converted to FHIR®) Wearable sensors & phone activity (converted to FHIR® and Open mHealth) Provider health systems can reduce the amount of time calling patient referral sources or previous clinics to track down data.