The organization receives a high volume of mental health referrals from multiple platforms, often in inconsistent or incomplete formats. Intake staff have to manually review and organize this data, which slows down patient onboarding and makes it hard to prioritize urgent cases. Without a clear overview of referral flow or processing performance, identifying delays or inefficiencies is difficult, impacting timely clinical decisions. Additionally, the manual process increases the risk of errors and duplicated work, creating frustration for staff and potentially delaying critical care. Monitoring metrics like turnaround time and referral quality is difficult, making it harder for the organization to improve how efficiently referrals are handled.
We automate the referral process, producing patient summaries and performing eligibility checks quickly and accurately. The system consolidates incoming referrals, reduces manual review, and ensures each case is prioritized appropriately, allowing staff to focus on patient care rather than administrative tasks.
Performance dashboards provide administrators with a clear view of referral quality, processing times, and overall workflow efficiency. By streamlining these processes, the system reduces errors, eliminates duplicated work, and ensures consistent evaluation of all referrals. This end-to-end automation improves onboarding speed, supports faster decision-making, and ultimately contributes to better patient outcomes.
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Cabot implemented the referral management system through a structured, step-by-step approach. Key steps included:
Key Features
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Challenge: The referral process was largely manual and time-consuming, requiring staff to spend significant effort reviewing referrals, creating summaries, and assessing eligibility. This led to delays, inconsistencies, and made it difficult to track workflow efficiency.
Solution: The system automates patient summary generation, eligibility checks, and referral prioritization, reducing manual work and providing dashboards with real-time insights. This ensures faster, more consistent referrals and allows staff to focus on patient care.
Challenge: The referral process was largely manual and time-consuming, requiring staff to spend significant effort reviewing referrals, creating summaries, and assessing eligibility. This led to delays, inconsistencies, and made it difficult to track workflow efficiency.
Solution: The system automates patient summary generation, eligibility checks, and referral prioritization, reducing manual work and providing dashboards with real-time insights. This ensures faster, more consistent referrals and allows staff to focus on patient care.
By implementing an automated referral management system, Cabot successfully transformed a manual and fragmented workflow into a streamlined, efficient process. The solution reduced administrative effort, ensured consistent referral triage and eligibility assessment, and provided real-time insights through performance dashboards. Staff could focus more on patient care, while administrators gained actionable data to optimize operations and improve clinical decision-making.
This project highlights Cabot’s ability to deliver measurable improvements in efficiency, accuracy, and patient care through smart automation and tailored solutions. The success of this engagement demonstrates our commitment to building reliable, scalable systems that support both operational goals and better healthcare outcomes.
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