Population Health Analytics

We strongly believe that the efficiency and success of any population health program is highly dependent on the ability of payers to leverage population data. It is for this reason that Fipsar helps payers’ transition towards accountable care-delivery systems through effective analysis and management of population health data.

  • FIPSAR is an engineer population health management system for simplifying the management of clinical data, data diagnosis, and overall health management.
  • We are a health management company that combines new health analytics and population health solution tools.
  • Our custom population health management analytics enable health managers to function better through real-time data and help them make informed decisions via CDSS.(Clinical Decision Support System)
  • FIPSAR can create population health analytics integrated with data visualization that would enable health professionals to observe and identify patterns in population health data.




Claims Management

Fipsar offers specialized business and technology solutions and services in product areas such as FACETS and QNXT for our Health Plan clients. As an expert healthcare IT service provider, we are prepared to deliver specialized FACETS-QNXT services for installed and hosted clients (payers) for all aspects of the FACETS & QNXT core system.

Facets systems will enable health plans to:

  • Maximize returns on FACETS platform.
  • Leverage a much more customized plug and play model, with limited resource usage and no business disruption.
  • Retain the unique configuration architecture.


EMR/EHR

On clinical data by reducing paperwork and facilitating communication between institutions, Specialists, Patients and Healthcare Providers, Epic systems therefore increase efficiency in the healthcare sector.

  • We facilitate these functions by providing a link (real-time, bi-directional integration) between existing systems (Patient Portal) and Epic integration.
  • Epic integration allows the platform to transmit information relating to registration, scheduling, billing, clinical operations, patient records, appointment scheduling, specialist referrals, prescription refill requests, ancillary care, and healthcare data.
  • EMR/EHR integration plays a vital role within the healthcare industry.



MDM Patient-Provider

Master Data management gives healthcare organizations a complete understanding of their patients and providers. An enterprise Master Patient Index (MPI) can act as a single, trusted source of truth for an organization.

  • An enterprise Master patient index (MPI) and master provider directory give a 360-degree view of patient and provider respectively within the organization.
  • It serves as a single, trusted source of truth for each patient and provider’s demographic information.
  • This ability allows a patient to minimize the operational issues involved with duplicates and identity resolution.
  • Beyond creating a single source of truth for patient and provider information, MDM allows all enterprise applications to consume and utilize accurate and up-to-date patient and provider information in real-time.


Efficient Data Management

We have significant experience in many types of MDM projects that help support a wide range of needs for our clients.

  • Given the limited access that healthcare clients tend to have regarding clinical data when building care management systems.
  • Fipsar solutions help fully integrate the clinical data of providers with the accountable data of clients.
  • They ensure optimal visualization and standardization of collected data across a range of health, financial and operating systems by allowing end clients to easily access clinical data.


IBM-UDMH

FIPSAR leveraged the IBM Unified Data Model for Healthcare (UDMH) and other IBM technologies (Pure Data System for Analytics, DataStage, Cognos, etc.) to develop an end-to-end reporting solution. We also put together a team of BI and interoperability experts to design and develop the solution:

  • Data Analysis and Mapping to IBM UDMH
  • Data Extraction and Processing using BI-Clinical
  • Compliance and Access Implementation
  • Data Presentation