(r2) GenMedRoster < ORUA

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-- Main.TWikiAdminGroup - 14 Nov 2010

---+ Roster Redesign Exploration (RRE)
---++ Objective

The purpose of this project is to investigate how the current roster for General Medicine registrar. The main goal is to implement a working model of an "Idealized roster". Currently a 12 week, rotating roster is used. The timeline of this project is 10 weeks and as such is not expected to produce a full working roster to provide the basis for further investigation, possibly as a 4th year project.

The desired outcomes of the summer project are:
   * Develop a detailed understanding of how the roster works and what is required 
   * Identify a significant subset of the important constraints to include in the optimization of the roster governing measures of patient care and staff quality-of-life. 
   * Develop a code shell for roster generation. 
   * Produce example of a improved roster 
---++ Progress

Initial meeting held 25th November with Andrew Peterson, Tim Denison, Rupert Handy, Nicolas Szecket, Mike O'Sullivan and Amelia White.

From the initial meeting it seems that the main issues is variation in patient numbers across the teams which results in registrars being overworked and can compromise continuation of care for patients. This variation means that on some days the registrar may have to see upwards of 15 patients whereas on others they may have 2 or 3. This means that on a given day one sub team may be extremely busy whereas another team may be quiet. The important aspect at this stage to address appears to be "smoothing" out the number of patients admitted across the week for each team to reduce variability.

---+++ Current Roster and Notes
 The current roster is based from historical preferences but it is not known how it was developed. There are 4 GM wards and 4 teams: White, Gold, Red and black, each consisting of 3 sub-teams. Each team is allocated to a ward.

A and B call each take approximately 1/3 of the new patients each day, C and D call take the remaining 1/3.

Patients stay on average 3.5 days, however this is a long tailed distribution with around 50% of the patients being discharged within 24 hours.

40% of the time there are not enough GM beds.

Workload of registrars tends to peak later in the day.

Admissions are 10-20% lower on weekends

---++ Next Steps
 Look at historical data regarding patient admission and verify split of admissions across team. From this we will develop initial ideas of how to mathematically model the roster.
Topic revision: r2 - 2010-11-25 - AmeliaWhite
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