Literature DB >> 9753379

The efficient organization of blood donation.

M M van der Pol1, J A Cairns.   

Abstract

This paper models the costs of collecting whole blood in the north of Scotland in order to investigate strategies whereby the annual collection target can be met at lower cost. Data on the costs of the individual sessions held in 1993-1995 are analyzed using multilevel analysis. A new technique, namely the conditioned iterative generalized least squares (CIGLS) estimator is applied. Then the feasibility of collecting increased volumes from particular panels and areas is assessed by examining which factors determine the number of blood donors at a session. Results show that fixed cost and marginal cost vary across panels but marginal cost does not vary by volume. This implies that the cost-minimizing policy is to equalize marginal costs and collect higher volume at fewer panels (those with lower fixed costs). The level of donations can be increased by increasing the number of opportunities to donate and/or increasing the average length of a session. The latter policy is shown to be more cost-effective. Multilevel analysis proves not only to be appropriate but also particularly useful.

Mesh:

Year:  1998        PMID: 9753379     DOI: 10.1002/(sici)1099-1050(199808)7:5<455::aid-hec356>3.0.co;2-8

Source DB:  PubMed          Journal:  Health Econ        ISSN: 1057-9230            Impact factor:   3.046


  2 in total

1.  Cost-effectiveness of alternative minimum recall intervals between whole blood donations.

Authors:  Zia Sadique; Sarah Willis; Kaat De Corte; Mark Pennington; Carmel Moore; Stephen Kaptoge; Emanuele Di Angelantonio; Gail Miflin; David J Roberts; Richard Grieve
Journal:  PLoS One       Date:  2022-08-17       Impact factor: 3.752

2.  Cost-effectiveness of alternative changes to a national blood collection service.

Authors:  S Willis; K De Corte; J A Cairns; M Zia Sadique; N Hawkins; M Pennington; G Cho; D J Roberts; G Miflin; R Grieve
Journal:  Transfus Med       Date:  2018-05-16       Impact factor: 2.019

  2 in total

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