Regression Analysis of Historical Blood Donors to Improve Clinic Scheduling

Geoffrey Pond, Isabelle Turner

Abstract

The Canadian Blood Services (CBS) is responsible for the collection, storage and distribution of blood products throughout the country. Like all civilian hospitals and medical facilities, the Canadian Armed Forces (CAF) Health Services System relies on CBS to provide it with required blood products through the Canadian Armed Forces Blood Distribution System. Under normal circumstances, CBS collects all blood products through organized events including mobile and permanent clinics, where prospective donors attend via either pre-booked appointments or unscheduled walk-ins. Of those who make appointments, only a portion show-up for their appointment and of these only some yield a successful donation. As donation clinics are capacity-constrained by both the labour-force and infrastructure, CBS is motivated to maximize the utilisa-tion of existing resources through implementation of an overbooking policy. Leveraging historical data, a statistical analysis was conducted to identify factors influencing conversion rates to aid in developing an improved scheduling policy. The location of the centre, the day of the week as well as demographic groups were included as candidate independent variables in a regression model to forecast the proportion of pre-booked appointments that are attended and yield a collection.

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Paper Citation


in Harvard Style

Pond G. and Turner I. (2020). Regression Analysis of Historical Blood Donors to Improve Clinic Scheduling.In Proceedings of the 9th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-396-4, pages 344-349. DOI: 10.5220/0008987003440349


in Bibtex Style

@conference{icores20,
author={Geoffrey Pond and Isabelle Turner},
title={Regression Analysis of Historical Blood Donors to Improve Clinic Scheduling},
booktitle={Proceedings of the 9th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2020},
pages={344-349},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008987003440349},
isbn={978-989-758-396-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Regression Analysis of Historical Blood Donors to Improve Clinic Scheduling
SN - 978-989-758-396-4
AU - Pond G.
AU - Turner I.
PY - 2020
SP - 344
EP - 349
DO - 10.5220/0008987003440349