Clinical Analytics

Managing a healthcare organization in today's challenging economic climate requires current and up to date information utilizing the necessary tools to assess data through innovative technology. Previous traditional approaches to decision support have become antiquated and obsolete. 

E*HealthLine’s applications offers innovative analytics and business intelligence tools embedded in a framework that supports the entire decision-making process.  This integrated network of analytic and encounter data offers immediate access to healthcare transformation initiatives.  E*HealthLine’s business analytics empower clinicians with key performance indicators and vital statistics, providing an effective method for sharing information.

E*HealthLine provides comprehensive Integrated ecosystem solutions across the entire platform of healthcare services, optimizing clinical decisions and Patient-Centered Analytics at every point of entry.

E*HealthLine’s Business Analytics, Intelligence and data mining applications interpret analytical data from different sources, while summarizing the outcomes for constructive information management. Our data mining software is one of a number of analytical tools utilized in analyzing the following categories:

  1. Patient Data
    1. Patient Information
    2. Patient History
    3. Diagnosis
    4. Treatments or Procedures
  2. Financial Data
    1. Eligibility
    2. Billing
    3. Insurance
  3. Institutional Data
    1. Resources available
    2. Resources used
    3. Inventory & Supply Chain

Healthcare Providers

Healthcare providers worldwide are struggling to maintain their quality standards and find solutions to assist in improving financial positions and care delivery models in an environment of escalating costs and increasing demand for care.   Organizations must obtain internal and external data, and have the ability to define performance indicators, predict outcomes, determine trends and monitor performance to overcome these challenges.

Financial Performance

Healthcare providers are increasingly seeking to transform themselves into quality centric value driven organizations with strong finances to ensure sustainability in an environment of outcome based government reimbursements, rising labor costs, workforce shortages and an increasing number of uninsured patients.   Vital outcomes of data complement analytical capabilities and facilitate balancing an operations optimal financial performance:

  • Improves medical loss ratio and manage medical expenses
  • Improves accuracy for increased reimbursements
  • Maintains operational efficiency
  • Identifies initiatives which employ cost and performance efficiencies
  • Develops strategies for increased revenue cycles and performance

Patient Safety and Quality of Care

Maintaining high standards of patient safely and the quality of their care require innovative tools and services that complement internal analytical capabilities and achieve the following:

  • Identifies drug to drug interaction
  • Identifies drug allergies
  • Medication safety and adherence
  • Drives evidence-based practice by sharing information at every point of care.
  • Captures and tracks clinical performance metrics against objectives.
  • Improvement in clinical productivity through a collaborative network of stakeholders
  • Effective predictive modeling
  • Identifies measurable outcomes and best practices in oppositions to benchmarks.
  • Identifies and monitors change in trends.
  • Provides consistent data and metrics.

Healthcare Payors

Given rising cost of healthcare and the ever-changing regulatory requirements, payors are continuously financially challenged and seek to reduce overall administrative costs.

Quality Management

Analytic Data Mining Facilitates the Overall Improvement of patient quality Management: 

Data mining is the process of selecting, exploring and modeling sizeable amounts of data, identifying meaningful logical patterns and relationships among key variables. Data mining is used to discover trends, predict future events and assess the merits of various courses of action within the healthcare industry.

Health insurance fraud costs the industry billions of dollars each year, requiring the industry to implement more proactive analytic techniques to ensure preventable costs are not passed onto consumers.

Analytic Data Mining:

  • Assist in identifying fraud utilizing business rules and predictive analytics technology.
  • Reduces false positives 
  • Defines and monitors vital performance metrics and measure program performance
  • Error rate reduction in claims processing

Customer Retention and Marketing

Health insurance products have commonly become standardized, with the customers selecting their insurer based solely on price. Given the minor differentiation between product offerings, it is extremely difficult for health insurance companies to retain customers, resulting in reduced loyalty and increased costs.

E*HealthLine’s Analytic Applications

  • Ensures real time and accurate data
  • Predicts customer behavior 
  • Delivers customer data and statistics based on captured demographics and geographic territories.
  • Identify trends and opportunities, monitor key provider performance metrics
  • Support portfolio planning  utilizing identified patterns

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