About the Customer

Healthcare Provider Profile

A leading home health services organization delivering comprehensive patient care across multiple regions. The organization manages complex patient intake workflows involving clinical staff, administrative personnel, and EHR specialists.

They process hundreds of patient admissions daily through the Kinnser Healthcare Platform, making efficient data entry and patient onboarding critical to operations.

Industry: Home Health Services
Scale: Multi-region healthcare system
Annual Patient Volume: 50,00+ patient admissions
Clinical Staff: 200+ healthcare professionals
Technology Partner: Calyza Tech

Business Problem

Manual Patient Intake Process Slowing Operations

The healthcare provider relied heavily on manual data entry for patient onboarding, creating major operational inefficiencies and delays.

Key Challenges

Manual Data Entry Bottlenecks

•  Clinical staff spent 25–30 minutes per patient entering data into the EHR system
•  Patient onboarding took 4–6 hours from referral to system entry
•  500+ patient backlog during peak periods
• Heavy dependence on experienced staff for form navigation

Accuracy & Compliance Risks

•  18–20% error rate in patient data entry
•  Inconsistent formatting across different staff members
• Missing mandatory fields causing compliance risks
• High risk of HIPAA violations due to manual handling of sensitive data

Financial Impact

•  $45 cost per patient intake due to manual processing
• $1.8M annual operational cost for data entry activities
• Revenue loss due to delayed patient onboarding

Scalability Constraints

• Difficult to handle admission spikes without hiring temporary staff
• 4–6 weeks training required for new administrative staff
• Limited operational scalability across multiple locations

These challenges created a critical bottleneck in patient onboarding, directly impacting operational efficiency, revenue, and patient care delivery.

Solution

CareOps AI – Intelligent Healthcare EHR Automation

Calyza Tech designed and implemented CareOps AI, an intelligent automation platform that converts patient referral data into complete EHR records automatically.

The solution combines cloud-native architecture, browser automation, and intelligent data validation to eliminate manual patient intake processes.

Solution Architecture

The automation pipeline uses a serverless, event-driven cloud architecture on AWS:

Automation Workflow

  Patient referral data is received in JSON format
  AWS Lambda validates and processes incoming messages
  Automation tasks are triggered using ECS Fargate Spot containers
  Playwright browser automation enters patient data into the EHR system
  Screenshots and audit logs are stored securely in Amazon S3
  Final status and results are reported back to the system

Core Technology Stack

Cloud Infrastructure

• AWS Lambda
• AWS Fargate Spot
• Amazon SQS
• Amazon S3
• AWS Secrets Manager

Automation & Processing

• Playwright browser automation
• Python 3.11 runtime
• Docker containerization
• Headless Chromium browser

Security & Compliance

• TLS 1.3 encryption
• IAM role-based access control
• HIPAA-compliant architecture
• Secure credential management

Key Capabilities

Automated patient admission into the EHR system
Intelligent field mapping between referral data and EHR forms
Automatic validation of required patient data
Error handling and retry mechanisms
Screenshot-based audit trails for compliance
Multi-environment support (DEV, UAT, PROD)
Scalable infrastructure capable of 24/7 processing

Business Outcomes

The implementation of CareOps AI delivered significant improvements across operational efficiency, cost reduction, and patient onboarding speed.

Operational Efficiency

• 92% faster processing (from 30 minutes to 2–3 minutes per patient)
• 500% increase in patient processing capacity
• Patient onboarding reduced from 6 hours to 15 minutes
• Eliminated 500-patient backlog within one week

Accuracy & Quality

• Data entry accuracy improved to 96%
• Error rate reduced from 20% to 4%
• 99.5% form submission success rate
• 100% required field completion

Financial Impact

• 78% reduction in cost per patient intake
• Reduced from $45 to $10 per patient
• $1.4M annual operational cost savings
• $180K saved annually in overtime costs

Scalability & Performance

• Enabled 24/7 automated patient intake
• Seamlessly handles 3× admission spikes
• Auto-scaling infrastructure for variable demand
• Faster patient onboarding improving care delivery timelines

Result

By implementing CareOps AI, the healthcare provider transformed a slow, manual patient intake process into a fast, automated, and scalable system, enabling staff to focus more on patient care rather than administrative work.