HomeMeds Case Study: Optimizing Medication Assessments with AI for Managed Care
HomeMeds Case Study: Optimizing Medication Assessments with AI for Managed Care
Case Studies
HomeMeds Case Study: Optimizing Medication Assessments with AI for Managed Care
Customer Overview
Rescuing a stalled transformation, on time and at scale
Our client is a nationally recognized non-profit organization dedicated to pioneering innovative programs and services for older adults and individuals with complex health needs. As a key partner to managed care organizations, our client serves as a catalyst for person-centered care that reduces costs and improves health outcomes for high-risk member populations. The HomeMeds program is one of its key initiatives, demonstrating the foundation’s commitment to leveraging technology for a more efficient and effective healthcare ecosystem.
HomeMeds is an evidence-based digital platform designed to improve medication use and safety for older adults receiving in-home services. By helping to prevent medication errors, a leading cause of emergency room visits and hospital readmissions, the program directly addresses significant drivers of avoidable healthcare costs for managed care plans. The platform’s structured process relies on in-home care providers to perform medication reviews and enter data into a web-based system for a pharmacist’s review.
The Challenge
Operational Bottlenecks and Data Risks in Medication Assessments
Time-Consuming Practices
Manual medication entry significantly extended the duration of in-person assessments, limiting the number of patients clinicians could see in a given timeframe and reducing overall productivity.
Operational Inefficiency
High administrative overhead required clinicians to spend a considerable portion of their time on non-clinical tasks, diverting focus away from direct patient care and impacting care quality.
Concerns over Data Integrity
Routine manual data transcription introduced a higher risk of human error, leading to inconsistencies in medication records and potential downstream impacts on patient safety and reporting accuracy.
Lack of Workflow Optimization
The care delivery workflow remained fragmented across multiple self-contained phases, resulting in inefficiencies, delays, and limited visibility across the end-to-end assessment process.
Practical Constraints
The organization needed to scale its operations to support a growing patient population, but faced limitations in doing so without proportionally increasing staffing levels and operational costs.
Client Requirements
Need for Scalable, Accurate, and Efficient Medication Workflows
Workflow Automation
The system needed to automate key administrative tasks, such as manual data entry, to significantly reduce the per-assessment time and improve clinician efficiency.
Advanced Data Capture
The platform had to support innovative data capture methods, including optical character recognition (OCR) for scanning medication labels and speech recognition for hands-free note-taking.
IoT-Enabled Vitals Capture
The solution needed to integrate with IoT devices to allow for automated, real-time capture of patient vitals like blood pressure and glucose levels, enabling proactive risk management.
Telehealth Functionality
A secure, in-app telehealth feature was required to facilitate cost-effective remote consultations and follow-up care between clinicians and patients.
Platform Scalability
The solution had to be built to handle a larger member population without a proportionate increase in staff, allowing the program to expand its reach for managed care contracts.
The Solution
AI-Driven Automation and Workflow Transformation
Quickly Scan Labels
Use the device's camera to scan medication bottles, automatically populating the member's record with drug names, dosages, and other key information.
Dictate Notes
Use speech-to-text functionality to record notes and observations during the assessment, eliminating the need for manual typing.
Automate Data Entry
Directly link the captured data to the backend system, streamlining the entire workflow.
The Impact
Measurable Gains in Efficiency, Accuracy, and Scalability
Foundation Layer
Reduced PMPM Costs
Lowered administrative burden reduced cost per member while improving overall care delivery efficiency.
Foundation Layer
Enhanced Risk Stratification
Improved data accuracy through OCR enabled more reliable risk assessment and proactive care planning.
Foundation Layer
Increased Operational Efficiency
Centralized records streamlined workflows, accelerating reviews and reducing manual effort.
Foundation Layer
Proactive Vitals Monitoring
Real-time IoT data enabled early intervention, helping prevent adverse events and reduce high-cost care.
Foundation Layer
Cost-Effective Remote Care
Integrated telehealth enabled consultations, lowering in-person costs while maintaining quality.
Foundation Layer
Scalable Growth Enablement
Optimized workflows supported higher member volumes without proportional increases in staffing.
Next Step
Download the Case Study
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