Startup Partnerships

Healthcare

This case study focuses on our experience working with a startup to co-head the development of a futuristic version of one of their existing products aimed at enhancing healthcare analytics solutions using machine learning and A.I.

Proxima helped with the design and implementation of a solution to empower  healthcare organizations comprising of all essential data for patients, providers, finances and operations in adherence to HIPAA regulations. In integration of data across all patients and providers, extracting clinical insights, we succeeded in setting up a mechanism well capable of carrying out effective prediction and intervention opportunities in various clinical and financial procedures, assuring most productive outcomes.

 

Case02
Challenges

Healthcare organizations experience pain the most in predicting and managing the risks and costs involved in their operations. This puts patients’ lives and healthcare facilities at stake as a result of avoidable complications like preventable hospital readmissions and lagged care coordination.

Our team was challenged to come up with a healthcare analytics solution that could reliably predict the involved risks along with healthcare costs based on factors like patient records, provider and claims data. Major challenges included:

  • Different systems and resources hold the essential patient data, such as physicians, ambulatory and other auxiliary providers
  • About 80% of patient data remains scattered with physicians, nursing staff and other ancillary providers in the form of unstructured notes and free-text data
  • High likelihood of limited access to patient population insights, resulting in hindrance to optimization of service
  • Overwhelming risk and cost management involved in transitioning to pay-for-performance
  • Discovery of unnecessary readmissions, network leakage and other complications after their occurrence
  • Interference of financial implications while striving to optimize health care facilities
Solution
  • Our solution offered product design with a focus on optimal integration alternatives for data across a host of provider networks
  • We devised a “Clinical Language Platform” specialized in information extraction from raw notes taken by nurses and physicians critically important in enhanced decision-making
  • We also devised a “Clinical Workflow Engine”, which resorts to advanced methodologies in enhancing patient-level data analytics by integration of HER workflow among providers elucidating insights just-in-time, assuring best possible clinical as well as financial results
  • Our solution also features Python/Scala based advanced capabilities leading to predictive models capable of dynamically extracting information from specific characteristics and health patterns of patients (like history and risk profile) and providers (like demographics, network, care, etc.)
Engagement Experience

Benefits for Patients and Providers

The distinguishing feature of our solution was that it not only focused on improved patient care, but also on improved providers’ visibility on patient data. Some major benefits are listed below:

Enhanced Patient Care

  • Creation of a Master Patient Index alongside Unified Patient View
  • Prediction and prevention of avoidable patient readmissions and other unnecessary expenditures
  • Indexation of high-risk patients even before their entry in the exam room
  • Identification of POA (Present On Admission)/HAC (Hospital Acquired Condition)
  • Modification of Risk-Adjusted Premiums with the intent of Medicare Advantage

Enhanced Providers’ Visibility

  • Better understanding of physician referral network leakage, resulting in optimized resource utilization and improved documentation
  • Prediction and prevention of avoidable and expensive medical procedures
  • Indication of available patient-specific health effects and pharmaceutical alternatives
  • Detection of fraud and waste for prevention

Customer Feedback

“Finding a world class Product Deign & Development firm with great knowledge on HIPAA compliance has been extremely difficult. Our partnership with Proxima made all our releases successful and customers happy. We couldn’t have done IT without you, THANK YOU.“

– CIO

Challenges

Healthcare organizations experience pain the most in predicting and managing the risks and costs involved in their operations. This puts patients’ lives and healthcare facilities at stake as a result of avoidable complications like preventable hospital readmissions and lagged care coordination.

Our team was challenged to come up with a healthcare analytics solution that could reliably predict the involved risks along with healthcare costs based on factors like patient records, provider and claims data. Major challenges included:

  • Different systems and resources hold the essential patient data, such as physicians, ambulatory and other auxiliary providers
  • About 80% of patient data remains scattered with physicians, nursing staff and other ancillary providers in the form of unstructured notes and free-text data
  • High likelihood of limited access to patient population insights, resulting in hindrance to optimization of service
  • Overwhelming risk and cost management involved in transitioning to pay-for-performance
  • Discovery of unnecessary readmissions, network leakage and other complications after their occurrence
  • Interference of financial implications while striving to optimize health care facilities
Challenges

Healthcare organizations experience pain the most in predicting and managing the risks and costs involved in their operations. This puts patients’ lives and healthcare facilities at stake as a result of avoidable complications like preventable hospital readmissions and lagged care coordination.

Our team was challenged to come up with a healthcare analytics solution that could reliably predict the involved risks along with healthcare costs based on factors like patient records, provider and claims data. Major challenges included:

  • Different systems and resources hold the essential patient data, such as physicians, ambulatory and other auxiliary providers
  • About 80% of patient data remains scattered with physicians, nursing staff and other ancillary providers in the form of unstructured notes and free-text data
  • High likelihood of limited access to patient population insights, resulting in hindrance to optimization of service
  • Overwhelming risk and cost management involved in transitioning to pay-for-performance
  • Discovery of unnecessary readmissions, network leakage and other complications after their occurrence
  • Interference of financial implications while striving to optimize health care facilities