cAnalytics© Integrated Clinical Trail Data Analytic
E*HealthLine’s applications offer 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.
cAnalytics© addresses the entire statistical analysis process for planning, data collection, analysis, reporting and better decision making and performance.
cAnalytics© efficiently transforms, analyzes and reports on clinical trial data, offering access to powerful pharma analytics. cAnalytics© delivers a cloud analytics solution for pharma that includes embedded analytic solutions, support for data standards and optional integrated analytic applications.
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. The combination of our own innovative thinking, with critical participation from patients and providers, serves as the foundation to create innovations that really matter.
E*HealthLine’s business analytics, intelligence and data mining applications interpret analytical data from different sources, while summarizing the outcomes for constructive information management. The company’s data mining software is one of a number of analytical tools utilized in analyzing the following categories:
1. Patient Data
a. Patient Information
b. Patient History
d. Treatments or Procedures
2. Financial Data
a. Resources available
b. Resources used
c. Inventory & Supply Chain
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.
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 operation's 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 safety 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
Given rising cost of healthcare and the ever-changing regulatory requirements, payors are continuously financially challenged and seek to reduce overall administrative costs.
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 and 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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