Case Study: Menonita Health System Achieves Significant Reductions in Opioid-Related Visits to ERs and Improved Suicide Prevention

Background:

Menonita Health System (MHS) is a well-known healthcare provider in Puerto Rico, aimed to improve patients' outcomes by using advanced digital healthcare data. By partnering with Trinexus and integrating the Trineuxs Data Decision Support Platform, MHS sought to make their digital healthcare data actionable, significantly improving patient care and operational efficiency.

 

Problem Statement:

Emergency Rooms (ERs) at MHS faced challenges in identifying and managing patients with special needs, particularly those affected by the opioid epidemic, suicide risks, and first psychosis episodes (FPE). For the most part, the traditional systems would lead to late responses and less than perfect results for the patients.

 

Solution:

To address these challenges, MHS, in collaboration with Trinexus, implemented Trineuxs Data Decision Support Platform to create a robust, data-driven decision-making process. The solution focused on:

 

Identification of Special Needs Patients:

  • Adapting computer algorithms to recognize people having a special need as soon as they come in through the door.

  • Utilizing historical and real-time data to provide Real-Time alerts to healthcare providers.

 

Opioid Epidemic Management:

  • Improving the detection and referral process for patients at risk of opioid overdose.

  • Providing data-driven insights to clinicians to improve intervention strategies.

 

Suicide Prevention:

  • Establishing a systematic approach to identify individuals with suicidal tendencies.

  • Integrating mental health services within the ED workflow to ensure timely intervention.

 

First Psychosis Episodes (FPE) Management:

  • Filling the gap in treating patients with FPE in mental health centers by using the combined data to normalize the symptoms and foresee the episodes comprehensively.

  • Collaborating with specialized FEP programs to ensure comprehensive patient care.

 

Implementation:

The integration process involved several key steps:

 

Pre-implementation Phase:

  • Performing a needs assessment to discover the relevant performance indicators of the emergency rooms (ERs).

  • Defining and designing the clinical pathway.

  • Designating program advocates to take up the project.

  • Conducting a detailed analysis and making reviews to confirm that the evidence-based practices are followed.

 

Implementation Phase:

  • Training of staff to handle the new platform; which requires no technical skills and is as simple as a messaging app to handle.

  • Conducting validation tests and follow-ups to ensure proper usage and information delivery, while involving users and establishing fidelity monitoring for best practices.

  • Utilizing technology to identify patients and monitor outcomes in real-time

 

Results:

The collaboration resulted in significant improvements.

 

Opioid Management:

  • A decrease of 26% in total visits related to opioid overdoses.

  • Enhanced identification and referral processes led to better patient outcomes.

 

Suicide Prevention:

  • Increased identification of individuals with suicidal thoughts by 18%.

  • As a result of performing the intervention on a timely basis, the number of failed suicide trials decreased.

 

FPE Management:

  • Creation of the largest FEP program in Puerto Rico, serving more patients effectively.

  • Improved outcomes for patients experiencing first psychosis episodes.

 

Conclusion:

The partnership between Menonita Health System, Trinexus, showcases the power of making healthcare data actionable. By integrating the advanced Trineuxs Data Decision Support Platform, MHS significantly improved patient care, streamlined operations, and set a new standard for healthcare in Puerto Rico. This case study highlights the transformative potential of data-driven healthcare solutions and interoperability in addressing critical public health challenges.

DT