Options for possible changes to the blood donation service: health economics modelling

A Comparison of Ordered Categorical versus Discrete Choices within a Stated Preference Survey of Whole-Blood Donors

HIGHLIGHTS

This article compares the relative preferences from stated preference (SP) questions requiring ordered categorical versus discrete choice responses. The approaches were contrasted for blood donation service characteristics that offer opportunities to donate blood.The estimates of relative preferences for alternative blood donation service characteristics were similar between the 2 forms of SP approach.This study illustrates how SP survey questions can be formulated to provide responses on an ordered categorical scale and to estimate marginal rates of substitution between different attributes, which can be compared with those derived from discrete choice experiment (DCE) choices.The article highlights the potential value of considering alternative choice framings rather than relying solely on DCEs.

Impact of a post-donation hemoglobin testing strategy on efficiency and safety of whole blood donation in England: A modeling study

BACKGROUND

Deferrals due to low hemoglobin are time-consuming and costly for blood donors and donation services. Furthermore, accepting donations from those with low hemoglobin could represent a significant safety issue. One approach to reduce them is to use hemoglobin concentration alongside donor characteristics to inform personalized inter-donation intervals.

STUDY DESIGN AND METHODS

We used data from 17,308 donors to inform a discrete event simulation model comparing personalized inter-donation intervals using "post-donation" testing (i.e., estimating current hemoglobin from that measured by a hematology analyzer at last donation) versus the current approach in England (i.e., pre-donation testing with fixed intervals of 12-weeks for men and 16-weeks for women). We reported the impact on total donations, low hemoglobin deferrals, inappropriate bleeds, and blood service costs. Personalized inter-donation intervals were defined using mixed-effects modeling to estimate hemoglobin trajectories and probability of crossing hemoglobin donation thresholds.

RESULTS

The model had generally good internal validation, with predicted events similar to those observed. Over 1 year, a personalized strategy requiring ≥90% probability of being over the hemoglobin threshold, minimized adverse events (low hemoglobin deferrals and inappropriate bleeds) in both sexes and costs in women. Donations per adverse event improved from 3.4 (95% uncertainty interval 2.8, 3.7) under the current strategy to 14.8 (11.6, 19.2) in women, and from 7.1 (6.1, 8.5) to 26.9 (20.8, 42.6) in men. In comparison, a strategy incorporating early returns for those with high certainty of being over the threshold maximized total donations in both men and women, but was less favorable in terms of adverse events, with 8.4 donations per adverse event in women (7.0, 10,1) and 14.8 (12.1, 21.0) in men.

DISCUSSION

Personalized inter-donation intervals using post-donation testing combined with modeling of hemoglobin trajectories can help reduce deferrals, inappropriate bleeds, and costs.

Impact of alternative strategies to improve the pool of blood donation by off-hour donation: A pilot study and its future prospects

Background

The escalating need for blood component due to increasing accidents and surgeries are always challenging for blood banks and hospitals. In this fast and busy world, collecting blood from a healthy and voluntary donor is quite challenging due to time constraints. Many blood donors who wish to donate blood were unable to go to the blood bank because of simultaneous operational timings of the blood bank and office hours of the donors. We dealt with this concern by extending the donation hours and also started collecting blood on the weekends following LAARC (Listen, Acknowledge, Assess, Respond, Confirm) methodology as a pilot project for improving blood donor convenience and satisfaction at the blood bank.

Methodology

It was a prospective observational pilot study conducted at the government tertiary care institute in the Department of Transfusion Medicine from December 2018 to June 2019. All blood donations were made as per the guidelines laid down by the Drug and Cosmetic Act. The donation timings were divided as office-hour donations (8 am to 5 pm on weekdays) and off-hours donations (5 pm to 8 pm, weekends and holidays).

Results

In this pilot project, over 7 months out of a total of 1,591 donations, 664 donations (41.73%) were done during the off-hours. The donor experiences were pleasing, and they felt extra cared due to the convenient donation timings.

Conclusions

Increasing the donation base needs more donor-friendly timings for the pleasant donation experience without hampering their work. More extensive studies should be conducted to include such strategies for increasing voluntary blood donation.

Stated versus revealed preferences: An approach to reduce bias

Stated preference (SP) survey responses may not predict actual behavior, leading to hypothetical bias. We developed an approach that harnesses large-scale routine data to help SP surveys provide more accurate estimates of revealed preferences (RPs), within a study which elicited preferences for alternative changes to the blood service in England. The SP survey responses were used to predict the mean number of annual whole blood donations. Ex ante, the iterative survey design estimated hypothetical bias by contrasting pilot SP survey responses (N = 1254), with individually linked data on RPs, to inform the main SP survey design (N = 25,187). Ex post, the analysis recognized mediation of the relationship between SP and RP when blood donation is deferred. The pilot survey reported that donors' intended donation frequency of 3.2 (men) and 2.6 (women) times per year, exceeded their actual frequency by 41% and 30% respectively. Choice scenario attributes for the main SP survey were then modified, and over-prediction subsequently decreased to 34% for men and 16% for women. The mediating effect of deferrals explained 29% (men) and 86% (women) of the residual discrepancy between SP and RP. Future studies can use this approach to reduce hypothetical bias, and provide more accurate predictions for decision-making.