Blood Donation: An Approach to Donor Vigilance

Tomasulo, Peter; Erraguntla, Madhav; Kamel, Hany

doi:10.1002/9781118338179.ch8

Cited by 3 publications

(5 citation statements)

References 32 publications

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“…In this respect, donor vigilance represents one of ISTARE's major priorities in contributing to international efforts to optimize donor care and donor safety. The advanced work carried out in this field by some national and regional reporting systems should be noted .…”

Section: Discussionmentioning

confidence: 99%

The International Haemovigilance Network Database for the Surveillance of Adverse Reactions and Events in Donors and Recipients of Blood Components: technical issues and results

Politis

Wiersum²,

Richardson

et al. 2016

Vox Sanguinis

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Section: Discussionmentioning

confidence: 99%

The International Haemovigilance Network Database for the Surveillance of Adverse Reactions and Events in Donors and Recipients of Blood Components: technical issues and results

Politis

Wiersum²,

Richardson

et al. 2016

Vox Sanguinis

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“…Donor hemovigilance involves the collection and analysis of information related to reactions associated with blood donation [6,9,13]. The goals of donor hemovigilance are to analyze the factors influencing blood donation and to facilitate the ability of organizations to implement interventions that improve blood donors' safety.…”

Section: Introductionmentioning

confidence: 99%

“…The adjusted odds ratios that are derived from LR model coefficients are used in the medical profession to interpret and rank factors influencing the dependent variables after accounting for the confounding and correlating factors [12,13]. Such insights are used to hypothesize and design interventions to improve the focus metric [6,9]. To facilitate comparison with the previous work of the authors and other published literature in this area, LR was used as the analysis technique in this work [1,5,6,9,10,12,13].…”

Section: Introductionmentioning

confidence: 99%

“…Such insights are used to hypothesize and design interventions to improve the focus metric [6,9]. To facilitate comparison with the previous work of the authors and other published literature in this area, LR was used as the analysis technique in this work [1,5,6,9,10,12,13]. We plan to research the results of other advanced machine learning techniques and compare results obtained in our future work.…”

Section: Introductionmentioning

confidence: 99%

“…Blood donation is very safe, but a small percentage of donors can have reactions and some of these reactions can lead to serious injury. Donor hemovigilance is the surveillance and analysis of donor reactions with the goal of understanding the factors influencing reactions and indentifying steps to improve donor safety [9]. Historically in the U.S., donor hemovigilance is managed by individual collection centers to improve their specific organization's donation processes.…”

mentioning

confidence: 99%

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Data Mining to Improve Safety of Blood Donation Process

Erraguntla

Tomasulo

Land

et al. 2014

2014 47th Hawaii International Conference on System Sciences

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Blood donation is a voluntary activity in the United States and provides critical blood units for transfusions. Blood is collected, processed and transported by blood centers to hospitals, though some hospitals also collect blood directly from donors. Blood donation is very safe, but a small percentage of donors can have reactions and some of these reactions can lead to serious injury. Donor hemovigilance is the surveillance and analysis of donor reactions with the goal of understanding the factors influencing reactions and indentifying steps to improve donor safety [9]. Historically in the U.S., donor hemovigilance is managed by individual collection centers to improve their specific organization's donation processes. The Department of Health and Human Services (HHS) has developed a software tool (called DonorHART™) to collect, organize and analyze reactions that occur at different participating blood centers and hospitals [6,8]. Data mining is used to analyze factors influencing the donor reactions, and the insights are shared with the community to help blood center and hospital managers and quality improvement administrators undertake interventions to improve donor safety [10]. The paper presents the history of the donor hemovigilance development and two data mining efforts performed on the data collected to improve the safety of blood donation processes.

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