Healthcare Data Solutions for Clinically Integrated Networks

The healthcare industry is undergoing a digital transformation. In the past few years, there has been an increase in the number of data-driven solutions that are being developed to help solve some of the most pressing challenges in healthcare.

Clinically Integrated Networks (CINs) are one such solution that is being developed to help improve patient care and outcomes while reducing costs.

CINs are networks of health care providers who collaborate and share clinical data to achieve better outcomes for patients. CINs are effective for improving quality, safety, and cost-efficiency in the healthcare system.

Healthcare Data Solutions for Value-based Care

The healthcare industry is one of the most regulated industries in the world. Healthcare providers and payers are required to comply with a set of regulations and standards.

Healthcare data solutions in the future will be focused on value-based care which is all about providing high-quality care, at an affordable price.

Healthcare data is a valuable resource in the healthcare industry. It can be used to improve the quality of care, reduce costs and provide more personalized treatments.

There are many solutions for managing healthcare data, such as HIEs (Health Information Exchange), EHRs (Electronic Health Record modernization services) and CDMs (Clinical Data Management Systems). These solutions have different strengths and weaknesses. For example, CDMs are good at storing large amounts of data but not so good at extracting insights from it.

Some hospitals are turning to AI-based solutions for value-based care.

The goal of these AI-based solutions is to identify patterns in health records that can lead to better diagnoses for patients with chronic conditions like diabetes or heart disease. They also help providers with clinical decision

The healthcare industry is in the process of adopting data-driven solutions to improve patient care and reduce costs. The use of AI technology in the healthcare industry is on the rise, as it can be used to automate tasks and provide new insights for clinicians.

The use cases for AI technology in healthcare are varied and include:

- Creating personalized care plans based on patient data

- Predicting which patients are at risk for diseases or complications

- Providing real-time alerts when a patient's condition changes

Components of Clinically Integrated Networks

• Effective Population Health ManagementSupport System for Successful Interdependence

• Referral System

• Patient History-based Risk Analysis

• Unified Care Practice

GAVS’ Rhodium Framework

GAVS Rhodium Framework allows the healthcare industry to move towards creating value-based care such as CINs. The framework utilizes the core tenants of blockchain to create a single version of truth for all stakeholders, facilitates de-centralized ownership of smart contracts, and offers the ability to provide transaction traceability throughout the value chain. The framework helps with master patient index, patient consent management, practitioner directory and credentialing, and Fraud, Wastage and Abuse (FWA).