Faster Recovery, Reduced Costs: Optimizing EOC Durations with AI

Overview

The client operates a reputable rehabilitation center in the US, with facilities spanning across cities like New York, Los Angeles, Chicago, and Houston, dedicated to providing comprehensive care and support to individuals recovering from various health conditions. With years of experience in the healthcare industry, the client has established a successful practice centered around personalized patient care. However, to further enhance their services, the client seeks to make advancements in their existing Electronic Medical Record (EMR) system.

Business challenges

1. Inefficient assessment analysis:

Therapists spent significant time manually scoring and interpreting assessment data, hindering their ability to focus on patient interaction and treatment delivery.

2. Inconsistent EOC (Episode Of Care):

Manual creation of EOC (Episode Of Care) led to potential variations in approaches across therapists, impacting treatment effectiveness and potentially delaying patient progress.

3. Limited data insights:

Difficulty in gaining insights from assessment data hindered the center's ability to improve care protocols and measure outcomes effectively.

Solution

Using the gathered client requirements data, the team formulated a feature list outlining the project's scope. To address the client's challenges, our team proposed a comprehensive solution focused on updating the assessment questionnaires within the client's EMR system and AI-powered Episode of care generation feature within their existing EMR:

1. Advanced Assessment Questionnaires:

Our team has developed an AI-powered assessment scoring and analysis engine within the EMR. The team has utilized Natural Language Processing (NLP) to understand and analyze textual responses within assessments. Also, pre-trained machine learning models specific to rehabilitation assessments were implemented to score and identify key findings automatically.

2. Standardized Episode Of Care (EOC):

The team has implemented a standardized EOC creation module within the EMR system. Incorporate decision support algorithms to guide therapists in selecting appropriate EOC templates based on patient assessment data and treatment goals.

Also, the team has utilized machine learning algorithms trained on data to predict optimal EOC durations based on patient progress and diagnoses. We have provided customizable templates and guidelines to ensure therapist control over final EOC decisions.

3. Enhanced Data Insights:

Our technical team has Integrated advanced analytics capabilities into the EMR system to extract actionable insights from assessment data. Utilize data mining techniques to identify patterns, trends, and correlations in patient responses. We have developed customizable dashboards and reporting tools to visualize key metrics and performance indicators, enabling therapists to make informed decisions and optimize care protocols.

Value Delivered

This value delivers nothing but a satisfactory response from the client after feature implementation.

• Improved efficiency and accuracy:

  Reduction in assessment analysis time by 40%, allowing therapists to allocate more time to direct patient care. Also, accuracy is improved in assessment interpretation, leading to a 30% reduction in errors and inconsistencies.

• Great Consistency in Treatment and Optimized EOC durations:

  Post-implementation, it achieved a 22% reduction in treatment variation across therapists through standardized EOC implementation. based on data-driven predictions, potentially leading to faster patient progress and reduced unnecessary treatment costs.

• Data-Driven Decision Making:

  Empowered therapists with actionable insights, leading to a 15% increase in informed decision-making based on data analysis.

Don't just take our word for it; hear from satisfied client :

Physical Therapist From Client’s (Doctor’s) Office-

"Before the AI-powered scoring engine, manual assessments were tedious and time-consuming. Now, I can focus on building connections with patients while the system handles the scoring and analysis. The NLP insights from open-ended responses are invaluable, revealing subtle issues I might have missed. It's like having an extra pair of eyes, helping me deliver more targeted and personalized care."