Exxat Prism for Program Success: Placement Assist (Part 6/10)

This webinar, part of the "Exxat Prism for Program Success" learning series, focused on the Placement Assist feature — a powerful matching algorithm built into Exxat Prism that automates the often-tedious work of matching students to clinical placements. Presented by Ramya, a senior account manager, the session walked attendees through the concept behind Placement Assist, the prerequisites needed before running it, the default implicit rules, and a deep dive into the nine advanced options that let programs fine-tune the algorithm to fit scenarios across PT, OT, PA, nursing, athletic training, nutrition, and other healthcare disciplines. 

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Key Takeaways:

1. Placement Assist runs on three parameters: supply, demand, and constraints. Supply is the slots received from clinical site partners; demand is optional student preferences collected through wishlists, and constraints are the rules administrators apply during the run. Wishlists are entirely optional — the algorithm can still produce valid randomized recommendations using only slots and the default implicit rules, making it accessible even for programs that don't want to surface site or location choices to students.
    
2. Three implicit rules are honored by default, and they can be overridden when needed. By default, the algorithm places each student only once per course offering, only once per rotation, and respects any pre-made placements (such as a student who already secured a site). The Max Placements advanced option lets administrators override these defaults — for example, requiring two internal medicine rotations in the same course, placing students in only one of two electives, or ensuring students rotate through every core setting at least once.
    
3. The "place closer to home or school" option was the top audience preference and requires clean address data. This was the most-voted criterion in the live poll and a popular feature across PT, PA, and nursing programs. To use it effectively, student addresses must be complete and accurate in the system.
    

4. Weighted advanced options let programs prioritize scarce or critical resources. Three customization options — by slot type, by setting, and by slot status — use a weighting system where higher weights mean higher placement priority. This is especially valuable for situations like prioritizing scarce inpatient slots in PT programs, ensuring "must be filled" slots are used before others, or placing students in confirmed slots before tentative ones. The higher the weight assigned, the greater the algorithm's bias toward selecting that slot type, setting, or status first.

    

5. For best results: maintain a 1.5–2x slot-to-student ratio, open wishlists for at least two weeks, and review past run setups year over year. Ramya's tips for getting strong outcomes from Placement Assist included accumulating roughly 1.5 to 2 times more slots than students (e.g., 160 slots for 80 students if possible), giving students at least two weeks to submit wishlist preferences, and using the "View Setup of the Run" feature to recall exactly which courses, rotations, wishlists, and advanced options were used in prior years — eliminating the need to remember setup details when running placements for a new cohort. 

Your Presenter:
Ramya Murali, Senior Account Manager at Exxat
Ramya is a seasoned Senior Account Manager with an  9+year tenure at Exxat, and she has a wealth of 15 years' experience.  During her time at Exxat, she's immersed herself in over 500+ programs in clinical education, demonstrating a flair for crafting specialized solutions tailored to navigate even the most intricate setups with finesse.