Improve internal operations, optimize data delivery and enhance patient experiences by leveraging your data

AI augments human capabilities. That includes our ability to deliver better care.

Healthcare professionals can leverage data-driven insights and the cloud to enhance their skills and deliver care better and faster. AI, data, and the cloud drive innovation throughout the industry with solutions that use predictive models to forecast bed demand, vision at the edge to detect shortages in medical supplies, and automation to free up resources.

Enhance the patient experience and improve operational outcomes by equipping your doctors, nurses, hospital staff, pharmacists, health benefits administrators, and insurers with the right tools for the job.

Optimize and secure healthcare delivery

Empower employees and healthcare workers, improve efficiency, and deliver superior care with industry solution accelerators, modern data environments and applications, and digital consulting support provided by Neal Analytics.

Our solutions are designed to support one, or many, of the following objectives:

Improve patient-provider experiences

Help alleviate provider burnout by automatically documenting patient encounters at the point of care

Boost clinician productivity

Deliver care faster and more efficiently

Protect health information

Help your organization protect and govern sensitive health data across systems, devices, apps, and cloud services

Featured customer stories

Optimize hospital bed allocations with reinforcement learning-trained AI

Optimizing bed allocation in hospitals based on how patients (randomly) check in is a well-known and complex challenge for which...
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Addressing healthcare challenges with best-in-class AI & ML solutions

The National Center for Biotechnology Information states, "Technology drives healthcare more than any other force, and in the future, it...
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Neal Analytics announces FHIR server for Azure Stack Hub and Azure Stack Edge

Neal is excited to announce the availability of services integrating, deploying, and working with the FHIR server standard for healthcare...
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HIPAA compliant cloud infrastructure: Assessment and remediation for a payments processor

Challenge The company faced a challenge in managing its quickly growing infrastructure. They tried different approaches over time but needed...
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Our solutions

a doctor and two nurses check records on a tablet

AI for quality assurance

AI and automation can help health professionals catch more errors and boost productivity. Automate time-intensive and inefficient processes to reduce oversights and free up your staff for other tasks.

AI can help you:

  •  Improve your claims auditing process to become more efficient and raise performance on external audits
  •  Target root causes of common errors to improve workflows
  •  Proactively flag and hold potentially erroneous claims before they are paid out to help reduce overspending.
  •  Utilize your staff for high-value activities by automating tasks like ICD-10 medical coding

Our predictive models are built on top of your existing processes, working with your system and rules to help you improve performance and assure quality care at every level.

Cloud-based FHIR integration

Integrate and exchange protected health information (PHI) leveraging the HL7 Fast Healthcare Interoperability Resources (FHIR) standard on Azure.

Neal Analytics can help organizations connect disparate data sources, such as electronic health and medical record (EHR/EMR) systems leveraging the Azure API for FHIR. It provides organizations with a quicker, simpler, scalable, and more secure way to share PHI in a HIPAA compliant manner. By leveraging Microsoft’s Azure IoT Connector for FHIR, Neal Analytics can help develop data ingestion pipelines for medical IoT devices.

Other key features of the Azure IoT Connector for FHIR include:

  • Conversion of biometric data into FHIR
  • Scalability and real-time analytics
  • Integration with Azure Stream Analytics
  • Security and logging capabilities to help support compliance in the cloud
FHIR helps disparate systems and IoT devices work together

StockView for healthcare

Keep your medical supply shelves stocked and spot trends with StockView, the AI-powered solution for void detection.

Powered by Microsoft Azure Stack Edge, StockView leverages AI vision at the edge to automatically detect missing supplies in real-time and alert personnel for prompt restocking. In addition to having an extra set of “eyes” on the shelves, StockView data can be consolidated across locations to optimize supply chains, gain insights from trends, and forecast future needs.

Preventive healthcare

Act upon early signs of potential health problems, forecast needs, and identify patterns with machine learning.

Our state-of-the-art predictive models create automated systems to:

  • Identify preventative healthcare opportunities based on the relevant, real-time data
  • Pinpoint factors in avoidable readmissions to improve patient care and reduce payouts
  • Forecast hospital stay lengths and optimize patient flows to increase profitability
  • Identify risks for churn and retain loyalty to insurance coverage plans
  • Allocate resources for healthcare hotspotting
  • Deliver targeted recommendations to care managers who can provide preemptive outreach to patients
two doctors review brain scan on tablet

Secure and compliant data delivery

Protect your health information and stay compliant with GDPR and HIPAA regulations by implementing a modern data estate and secure infrastructure. Leverage the cloud’s power to migrate and modernize your data to improve storage practices, upgrade security, and reduce spend by saving on license costs.

Advanced AI-driven tumor detection on your secured edge

Project InnerEye was recently open-sourced and is now available for deployments on Azure Stack Hub to optimize for both performance and patient privacy. InnerEye uses advanced vision AI to leverage just a few doctor-initiated 2D image tagging actions to almost instantly tag and display 3D images of tumors.

InnerEye is incredibly valuable because of the scale and accuracy increases it offers. Oncologists can spend hours per patient tagging oncological MRI images as a part of their analysis and screening. Project InnerEye helps less experienced doctors ramp-up more quickly while also enabling experienced doctors to reduce the time spent tagging from three hours to 15 minutes per patient. With InnerEye, hospitals can recapture some of their most valuable employee’s time.

Neal Analytics collaborated with the Microsoft R&D team to port Project InnerEye on Azure Stack Hub, and we can leverage this unique, in-depth understanding of the underlying code to help customers customize and deploy it in a short time-to-value.

Project InnerEye