• Industry Status

    Raw Data
    Information scattered across
    different systems
    Low Quality and
    Non-structured Data
    Hard to find research ideas
    Disconnection
    between Hospitals
    Different data standards and
    uneven quality

    Application Value

    Research Idea Discovery
    Based on real world studies, integrate data from multiple sources such as clinical data, documents and death causes to establish a patient’s full life cycle model and use AI technologies to actively explore medical research ideas
    High Quality and Efficient Research Outputs
    Improve the efficiency of data collecting and processing, significantly shorten research cycle, make full course of data quality controlled and traceable and facilitate precision medicine
    Collaborative Network
    of Disease
    Accumulate medical intelligence and build disease models; data collecting by intelligent technology to improve research efficiency, work with several medical institutions and build a disease data network
    • Guarantee High
      Quality Research Output

      1. Full data covered to support outcome studies with large sample capacities
      2. Long-term studies
      3. Integration of multiple source to facilitate precision medicine with multi-dimensional evaluation
    • Provide Help for Doctors

      1. Work with top experts to establish diseases diagnosis and treatment criteria
      2. Second-level search of massive data, providing scientific research inspiration
      3. Intelligent recommendation of relevant popular documents
    • Improve Clinical Diagnosis and Treatment Outcomes

      1. Establish patient diagnosis and treatment models by collecting multi-source data throughout a hospital
      2. 360° rendering of a patient’s full life cycle data
      3. Patients’ tracking and follow-up visit data included
    • Build Disease Data Networks

      1. Establish disease models with accumulative medical intelligence
      2. Intelligent data integrated to enhance research efficiency
      3. Work with over 100 top
        medical institutions to build disease-based data networks

    Application Mode

    Yidu Cloud Disease Data Centers

    Patient Statistics Overview

    Disease Standard Data Sets

    Review of Patient Cases

    Re-entry of Review Traces

    Patient Diagnosis and Treatment Timeline

    360° View of Patient

    Data Quality Statistics

    Patient Data Tracing

    Research Follow-up Visit Management

    Multi-center Projects Management

  • Industry Status

    Complex data indicators and different
    data sourcesmake it impossible to
    pinpoint the root of problems
    “Isolated island of data” within a hospital,
    lack of regional baselines and disease
    benchmarks, incomparable indicators
    for specific disease

    Application Value

    Insights
    Discover the Essence beneath the Surface of Numbers
    Go Deep into Diseases for Lean Management
    Disease-based Management,Improvement
    and Progress Monitoring
    Indicator Prediction and Data Normalization
    AI Predictive Analysis, Dynamic Baseline Prospective Management
    • Monitor Operational Indicators

      1. Forecast key operational indicators to gain new insights through reviewing old materials
      2. Automatic classification of abnormal indicators for prevention at the outset
      3. Push key events on mobile terminals
    • Quality Control of Intelligent Medical Data of Disease Cases

      1. ICD automatic coding support, closed loop of coding quality control supported by data
      2. Intelligent record quality screening
      3. Data result reporting
    • Management of DRG

      1. Capability evaluation system of specialized disease
      2. Evaluation of efficiency and quality for disease departments
      3. Analysis and monitoring of disease treatment cost, and internal review of medical insurance cost control
    • Disease Process Management

      1. Analysis of clinical pathway variation to discover opportunities of improvement
      2. Pathway discovery and improvement and continual optimization of nodes
      3. Efficiency of key process to eliminate process choke points

    Application Mode

    Rare Complicated Diseases

    Guarantee disease coverage

    MDT collaboration

    Monitoring of key quality

    Evaluation of discipline construction

    Common Diseases

    Standardize diagnosis and treatment pathway

    Lower average daily bed cost

    Key efficiency management

    Operation indicator assessment

    Key Advantageous Diseases Of Department

    Guarantee resources allocation

    Formation of competitive advantage

    Development of key personnel

    Growth indicator assessment

    Unsophisticated Diseases

    Process efficiency optimization

    Formation of cost advantage

    Key process optimization

    Capacity indicator assessment

  • Industry Status

    Passive collection of information
    and low efficiency of post-regulatory
    Information is not interconnected
    among institutions

    Application Value

    Active Regulatory Services
    Driven by real world data,
    meet regulatory and compliance requirements actively, efficiently
    and cost-effectively to provide decision making supports
    Interconnection and Quality Control of Data
    Help governments with interconnection, fusion and
    quality control of multi-sources heterogeneous data, and achieve intelligent medical case
    and drug coding
    Application and Disclosure of Government Data
    Achieve transparent drug purchase and spending of medical insurance, and accomplish accuracy, transparency, security and
    sharing of personal medical data

    Application Mode

  • Industry Status

    Long duration and high cost of
    clinical trials, especially
    for recruitment.
    Uneven quality of trial data.
    Significant difference between actual clinical effects and clinical
    trial results.

    Application Value

    Efficiency

    Based on biological samples and clinical data platform.

    Quality

    Based on AI big data technologies, standardize various data from clinical trials to improve its quality.

    Real World Evaluation

    Track clinical effects of drugs for a long term, completely and accurately evaluate clinical value of drugs to support medical decision making such as developing guides and standards of clinical diagnosis & treatment

    Application Mode

    Drug Development
    • Target identification
    • Drug screening
    • Pre-clinical researches
    Market Launching Application
    • Randomized controlled trial (RCT) with efficiency and high quality
    Clinical Value
    • Real world studies (RWS) based on big data
    Medical Decision Making
    • Guides providing and standards establishing for clinical diagnosis & treatment
  • Industry Status

    Residents
    Unable to track and manage their
    own health information
    Patients
    Imperfect follow-up visits and diagnosis cause unnecessary development and deterioration of diseases

    Application Value

    Active Regulatory Service
    Integrate hospital health data to provide residents with full life cycle health
    information records
    Data Interconnection And Data Quality Control
    Full cycle diagnosis & treatment management model for patients with medical treatment alliance and disease based intelligent technologies

    Full life cycle data of patients

    Internal data sharing across hospitals and regions

    Efficient and high-quality follow-up visit management to increase
    user viscosity

    Provide patients with health record access, data interpretation, health risk evaluation, visit appointment, doctor-patient communication and health education

    Search, recommendation and review services based on big data core algorithm and application

    Establish a patient-based platform and build a closed loop of hospital, doctor and patient services

    Application Mode