Predicting blood donor arrival

Bosnes, Vidar; Aldrin, Magne; Heier, Hans Erik

doi:10.1111/j.1537-2995.2004.04167.x

Cited by 44 publications

(20 citation statements)

References 11 publications

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“…Similar age‐specific patterns of rejections from donation have been reported previously among first‐time donors in the USA [11,12]. Previous research has shown that temporary deferral reduces future return rate [13,14]. It is therefore likely that many young persons deferred temporarily at initial screening are lost permanently from the donor pool.…”

Section: Discussionsupporting

confidence: 70%

Recruiting and retaining young people as voluntary blood donors

Misje¹,

Bosnes²,

Heier³

2007

Vox Sanguinis

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Section: Discussionsupporting

confidence: 70%

Recruiting and retaining young people as voluntary blood donors

Misje¹,

Bosnes²,

Heier³

2007

Vox Sanguinis

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“…Queuing network models [7] to determine resource requirements, computer simulation models to study work flow [8,9] and material flow [10,11], and statistical models to predict donor arrivals [12] have been shown to be well-suited to blood center applications. It has been noted that the most important variables to be considered in building a model of a blood center is the donor arrival rate and pattern and service times involved in each sequential workstation [8] .…”

Section: Introductionmentioning

confidence: 99%

Discovering Blood Donor Arrival Patterns Using Data Mining: A Method to Investigate Service Quality at Blood Centers

et al. 2010

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Blood centers without fixed appointments for collecting blood often experience nonconstant donor arrival rates, which vary due to time-of-day, day-of-week, etc. When a constant workforce size is employed in such blood centers, there is either idle personnel, or donor satisfaction is compromised due to long waiting times, or both conditions alternate over time. Consequently, a method to obtain adaptive workforce requirements might be valuable. This study utilized the Two-Step Cluster method and the Classification and Regression Trees method in succession to identify both daily and hourly donor arrival patterns at Hacettepe University Hospitals' Blood Center. A serial queuing network model of the donation process was then employed for each of the identified donor arrival patterns. By considering and accommodating variations in the donor arrival patterns, required workforce sizes and their decomposition among process steps were predicted to achieve predetermined target values of expected waiting times and to balance workforce utilizations in the blood donation processes. Although a blood center is considered for the proposed methodology, the approach is general and applications in various operations of healthcare organizations are possible.

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“…Although the return rates of first‐time donors were lower than 40%, blood banks rely more on regular donors due to lower costs of retaining them, better cooperation and better responsibility . It is also reported that the number of lifetime blood donations, high donation rates in the recent years and the short intervals between the first and the following donations may have an influence on blood donor return rates …”

Section: Introductionmentioning

confidence: 99%

Return rate in blood donors: A 7‐year follow up

Kasraian

Hosseini

Dehbidi

et al. 2019

Transfusion Medicine

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Objective: Determining the current return rates of blood donors and their related factors.Background: Understanding the current pattern of blood donors' return rates and also their motivations will be beneficial when there is a need to implement measures to encourage new blood donors and retain existing ones. Methods:This cross-sectional study was conducted on 4200 blood donors in Shiraz, Iran, from 26 November 2010 to 26 December 2010. Blood donors' return rate and its related factors were investigated in a 7-year follow up.Results: The overall return rates of blood donors indicated a significant yearly decline of 51.2%, 45.1%, 37.6%, 38.8%, 28.7%, 22.7% and 22.1% over a 7-year follow up. The return rates for first-time donors declined annually by 30%, 25%, 21%, 18.5%, 15.2%,12.3% and 11.8% (P ≤ .05). Return rates were higher among male, older, low-educated, Rh-negative and regular donors. Blood donations for altruistic reasons and religious reasons were higher in regular and older donors (P < .001); donation for positive effects on their health and free access to screening tests and curiosity was higher in first-time donors and females (P < .001). The most frequent deterrents were lack of time (42.7%), unsuitable condition (37.6%) and difficult access to donation sites (26.2%). Conclusion:Designing new strategies to retain donors, advertisement, appreciation methods and providing convenient conditions for donation are needed to increase the return rates, particularly in young, highly educated, female and first-time donors. K E Y W O R D Sblood donation, blood donor, recruitment, return rate

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Predicting blood donor arrival

Abstract: Statistical modeling can provide useful estimates of blood donor arrival, allowing for better planning of donation sessions.

Cited by 44 publications

References 11 publications

Recruiting and retaining young people as voluntary blood donors

Recruiting and retaining young people as voluntary blood donors

Discovering Blood Donor Arrival Patterns Using Data Mining: A Method to Investigate Service Quality at Blood Centers

Return rate in blood donors: A 7‐year follow up

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