DOC 3 · CLERKSHIP ALLOCATION SYSTEM

Turning 143 Individual Preferences Into One Workable Clerkship Cycle

A purpose-built, intelligent allocation algorithm that considers student preferences, hospital logistics, and clinical workload across groups, bringing them together in one balanced, workable solution.

143
Students
572
Hospital-level assignments
4
Rotations per student
3
Teaching hospitals
143 Students Preferences Allocation Engine Final Clerkship
THE PROBLEM

The difficult part wasn't assigning students. It was making the whole year work.

143 students submitted four rotations each, creating 572 hospital-level assignments to reconcile.

Those requests had to coexist within three hospitals, four departments, four rotation periods, and different student preferences.

There were easier ways to allocate clerkship. They just came with compromises.
Fixed Groups

One simple approach would be to create permanent groups and rotate them together throughout the year.

Easy to administer.

But a student could end up spending the entire clerkship cycle with a group they did not choose.

Manual Balancing

Another approach would be to place students manually and adjust the groups until the numbers looked reasonable.

Possible to do.

But every adjustment could affect another student's preference, another department, another hospital, or another rotation.

Preference-First

Or we could simply prioritize the most requested choices.

Good for individual requests.

But without class-wide balancing, some hospital–department groups could become too large while others become too small.

The problem wasn't choosing one of these approaches.
It was that we needed the advantages of all three without inheriting their weaknesses.
Student preferences
Hospital + department capacity
Group balance
Hospital movement
Complete four-rotation cycle
One workable allocation for the class

That is why a digital allocation solution was built. Not simply to replace manual work, but to make it possible to evaluate the class as one connected system—preserving meaningful student preferences while keeping clinical groups workable and the overall rotation cycle coherent.

A choice that works for one student can affect the available space for another.
Student preference
Hospital + Department
Group capacity
Rotation sequence
Class-wide allocation
PREFERENCE ANALYTICS

The preferences were not evenly distributed

143 students submitted four rotations each, creating 572 hospital-level assignments to reconcile. Those requests did not arrive as an even distribution across the three hospitals.

CHUB — 22940%
CHUK — 19434%
RMH — 14926%

The allocation therefore could not simply assign students according to the raw popularity of each hospital. Demand had to be reconciled with clinical capacity and the structure of the four-rotation cycle.

🏥 CHUB
92 students  •  229 assignments
RotationPediatricsInternal MedicineSurgeryObstetrics & GynecologyTotal
Rotation 1928121665
Rotation 2171572362
Rotation 3111172756
Rotation 476231046
Total44604976229
View CHUB Sheet (Original Preferences) →
🏥 CHUK
93 students  •  194 assignments
RotationPediatricsInternal MedicineSurgeryObstetrics & GynecologyTotal
Rotation 192061348
Rotation 211139841
Rotation 320582255
Rotation 421724750
Total42554750194
View CHUK Sheet (Original Preferences) →
🏥 RMH
87 students  •  149 assignments
RotationPediatricsInternal MedicineSurgeryObstetrics & GynecologyTotal
Rotation 16151830
Rotation 22279240
Rotation 31638532
Rotation 413329247
Total57284717149
View RMH Sheet (Original Preferences) →
WHY THE REQUESTS WERE COMPLEX

A hospital preference was never just a hospital preference.

Each request carries several dimensions at once: Hospital · Department · Rotation · the student's complete four-rotation plan.

The system had to reason about the complete rotation cycle rather than treating each request as an isolated placement.

ROTATION 1
Dept + Hospital
ROTATION 2
Dept + Hospital
ROTATION 3
Dept + Hospital
ROTATION 4
Dept + Hospital
HOW THE ALGORITHM WORKS

How the allocation works

The allocation engine evaluates the class as a connected system rather than making independent decisions for each student.

What the optimization algorithm is not doing
  • It is not randomly assigning students.
  • It is not ignoring submitted preferences.
  • It is not simply giving everyone their first choice regardless of class-wide consequences.
  • It is not intentionally creating unnecessary hospital movement.
  • It is not arbitrarily changing students' choices.
  • It is not treating every student identically regardless of their actual preference structure.
  • It is not filling groups without considering whether the resulting four-rotation cycle is valid.
Instead, it is a constraint-aware optimization algorithm that evaluates feasible allocation patterns and selects arrangements designed to balance individual preference preservation with class-wide operational requirements.
Individual preferences
Clinical capacity
Hospital logistics
Valid rotation structures
One workable class-wide allocation
THE HUMAN TRADE-OFF

The goal was not to make every request possible.

With finite clinical capacity and competing preferences, it is not possible to satisfy every individual request exactly.

The objective was to preserve meaningful student preferences wherever possible while producing a complete allocation that remains workable for the entire class.

Individual preferences
Class-wide feasibility
Clinical capacity
CLERKSHIP ANALYTICS

From preferences to a workable allocation

After the submitted preferences were reconciled with the allocation constraints, the resulting clerkship schedule could be examined across hospitals, rotation blocks, and departments.

This reflects published allocation data, distinct from the original preference data shown above.

Generated At 2026-08-18 17:43:14

Total Published Students: 143

🏥 CHUB
Published Students: 85 View CHUB Placement Sheet →
Total Assignments199
All 4 Here17
Rotating Between Hospitals68
Avg per Rotation Block49.8
Underfilled Groups
Overloaded Groups0 groups
RotationPediatricsInternal MedicineSurgeryObstetrics & GynecologyTotal
Rotation 11314121453
Rotation 21113101246
Rotation 31211131450
Rotation 41111141450
Total47494954199
🏥 CHUK
Published Students: 88 View CHUK Placement Sheet →
Total Assignments198
All 4 Here9
Rotating Between Hospitals79
Avg per Rotation Block49.5
Underfilled Groups
Overloaded Groups0 groups
RotationPediatricsInternal MedicineSurgeryObstetrics & GynecologyTotal
Rotation 11214101046
Rotation 21411131351
Rotation 31411131452
Rotation 41014141149
Total50505048198
🏥 RMH
Published Students: 86 View RMH Placement Sheet →
Total Assignments175
All 4 Here8
Rotating Between Hospitals78
Avg per Rotation Block43.8
Underfilled Groups
Overloaded Groups0 groups
RotationPediatricsInternal MedicineSurgeryObstetrics & GynecologyTotal
Rotation 11112101144
Rotation 21412101046
Rotation 31110101041
Rotation 41010141044
Total46444441175
THREE-PHASE JOURNEY

Three phases. One complete allocation journey.

Phase I

Preference Submission

Students submitted their desired four-rotation plans.

Purpose: capture the class's original preferences before allocation.

Phase II

Provisional Allocation & Student Swap Window

After optimization, students received their provisional clerkship allocation, then a defined window to exchange clerkship sites among themselves.

Phase II was not another optimization phase — it was the period in which students could mutually request exchanges of their assigned clerkship sites. A student who wanted a change needed to identify a colleague willing to exchange and submit the official request for confirmation.
Phase III

Final Clerkship Decision

After the swap window closed, submitted swap requests were reviewed and incorporated where appropriate. The resulting allocation was finalized → sealed → communicated.

EMAIL TRAIL

Every phase had a corresponding student communication

Three existing email artifacts, one per phase.

The system automatically generated and sent the appropriate student communication at each phase by reading the relevant submitted preferences, provisional allocation, swap/review outcomes, and final clerkship data.

This same workflow allowed the system to generate the clerkship documents required for the process without manual preparation or repetitive data entry.

Phase I
Submitted Preferences
System reads preference data
Preference Confirmation Email
Phase II
Optimized Clerkship Data
System reads provisional allocation
Phase II Decision Email
Phase III
Final / Reviewed Clerkship Data
System reads final allocation
Final Clerkship Decision Email
Phase I

We Received Your Rotation Plan

Preference submission confirmation

Phase II

Phase II Clerkship Decision

Provisional allocation + 72-hour swap window

Phase III

Final Clerkship Decision

Final allocation after the review and swap process

From data to documents

Once the underlying clerkship data was available, the system could generate the documents needed for the process automatically — including student communications, allocation outputs, rotation information, and related clerkship materials — without requiring manual preparation for each student.

This was not just a scheduling algorithm

It was a complete workflow — collecting preferences, analyzing demand, optimizing a class-wide allocation, producing the published clerkship schedule, handling the three-phase communication process, and automatically generating the required student communications and clerkship documents.

01 — ALLOCATION

Reconciling preferences and constraints

The system reconciles student preferences and operational constraints.

02 — ANALYTICS

Understanding the data

The system makes the resulting preference and allocation data understandable.

03 — AUTOMATION

Generating communications and documents

The system uses the resulting data to generate the required clerkship communications and documents.

🔒 Anonymized examples

The names, registration numbers, student identities, and student-level records shown throughout this presentation are anonymized placeholders or illustrative examples.

The original submission data, allocation records, student roster, and related student-level information are confidential property of the University of Rwanda Medical School, DOC 3 Class of 2027, and are reserved for authorized access only.

COMPLETE SYSTEM TIMELINE

From 143 preferences to a sealed clerkship schedule

01
Preferences
143 students · 572 hospital-level assignments
02
Analytics
Understand the demand
03
Allocation Engine
Reconcile preferences + constraints
04
Provisional Allocation
Phase II
05
Student Swap Window
Students mutually exchange sites
06
Final Review
Swap requests incorporated
07
Final Decision
Phase III
Published Clerkship
UNDER THE HOOD

Under the Hood

Inputs
  • Student preferences
Processing
  • Preference normalization
  • Hospital eligibility
  • Rotation structure
  • Capacity considerations
  • Allocation logic
  • Validation
Outputs
  • Published Clerkship
  • Student allocation emails
  • Rotation team information
  • Analytics
FINAL TAKEAWAY

The goal was never to make every individual schedule perfect.

The goal was to create the strongest workable allocation for the class — one that respects student preferences as far as possible while maintaining practical clinical groups, sensible hospital logistics, and a coherent four-rotation cycle.

143
students
572
assignments
4
rotations
3
hospitals
1
class-wide allocation
🔒

Confidential Information

This information is confidential property of the University of Rwanda Medical School, DOC 3 Class of 2027 and is intended for authorized use only.

For further information or access inquiries, please contact urmedicine2027@gmail.com.