Healthcare Analytics Software and Solutions

As a self-hosted embedded analytics solution, our goal is to ensure you maintain your HIPAA compliance. Data never leaves your environment and our software is self-contained.

Qrvey takes a different approach to embedded analytics by starting with data, not charts. 

Qrvey includes a full-featured data lake powered by Elasticsearch, not a basic relational caching layer. Furthermore, by including a data lake, the cost to scale out is much less than traditional data warehouses.

For the user-facing components of the platform, Qrvey offers more embedded components and APIs to personalize the experience beyond static dashboards. 

Qrvey offers:

• Everything is a JS embed, no iFrames
• Dashboards and builders
• Dataset creation for individual users
• No-code workflow automation
• Full white-labeling and CSS support

All of this is backed by a semantic layer that makes integrating Qrvey into the security model of SaaS applications simple. 

Every customer has direct access to support and customer success. During your free POC period, we even give you a dedicated Slack channel where our engineers participate for those deeply technical questions.

Healthcare analytics software, sometimes referred to as medical analytics software, is important to healthcare organizations for several key reasons:

• Improves clinical outcomes – Analytics helps identify high-risk patients, enables early interventions, and guides treatment plans to improve patient health.
• Optimizes operations – Analytics increases workflow efficiency by optimizing scheduling, staffing, bed allocation and other hospital operations.
• Reduces costs – By analyzing patient data, healthcare organizations can reduce readmissions, avoid unnecessary tests, and cut operational waste, thereby reducing costs.
• Enhances patient engagement – Analytics helps segment patients for tailored engagement strategies to improve satisfaction, loyalty, and outcomes.
• Supports value-based care – In a fee-for-value model, analytics helps identify care gaps, monitor quality metrics, and demonstrate value to payers.
• Enables data-driven decisions – Analytics provides data-backed insights to inform strategy and planning around new programs, expansions, investments, etc.
• Identifies revenue opportunities – By analyzing physician referrals, service utilization, market trends, hospitals can identify new revenue streams.
• Assesses risks – Analytics adopts statistical and AI models to predict risk of diseases, readmissions, infection outbreaks, etc.
• Maintains regulatory compliance – Auditing analytics helps hospitals meet quality reporting requirements and highlights areas of improvement.

While there are many types of healthcare analytics solutions for agencies, Qrvey’s unique approach offers a multi-tenant ready solution that can speed up development time for agencies looking to serve multiple clients. 

Qrvey offers every customer a free POC to test us out within your environment. We’re not here to rush you through a trial. We want you to be successful and we know that means seeing it live within your cloud platform first hand.

Healthcare analytics leverages data analysis and statistical techniques to uncover meaningful patterns and insights from the vast amounts of data generated in healthcare. By collecting and examining large datasets like patient medical records, financial records, and operational data, healthcare analytics enables data-driven decision-making and enhances outcomes in the healthcare industry.

Qrvey’s customers can expect to achieve:

• Faster development time to market
• Lower infrastructure costs for analytics
• ROI from adding analytics as part of premium tier packages
• Increase in CSAT or NPS
• New monetization opportunities

It can be used for various purposes, such as predicting disease outbreaks, identifying high-risk patients, optimizing treatment plans, improving resource allocation, and evaluating the effectiveness of healthcare interventions.

Healthcare analytics enables healthcare providers, administrators, and researchers to identify patterns, trends, and correlations in the data, leading to improvements in patient care, operational efficiency, cost management, and decision-making.