Universal PCR in endemic states is an effective blood donation screening strategy at a threshold of $50,000/QALY. Using a higher cost-effectiveness ratio, universal Ab/PCR is the most effective strategy.
European law now requires AI to be explainable in the context of adverse decisions affecting the European Union (EU) citizens. At the same time, we expect increasing instances of AI failure as it operates on imperfect data. This paper puts forward a neurally inspired theoretical framework called “decision stacks” that can provide a way forward in research to develop Explainable Artificial Intelligence (X-AI). By leveraging findings from the finest memory systems in biological brains, the decision stack framework operationalizes the definition of explainability. It then proposes a test that can potentially reveal how a given AI decision was made.
Blood products are essential components of any healthcare system, and their safety, in terms of being free of transfusion-transmittable infections, is crucial. While the Food and Drug Administration (FDA) in the United States requires all blood donations to be tested for certain infection types, it does not dictate which particular tests should be used by blood centers. Multiple FDA-licensed blood screening tests are available for each infection type, and screening tests are imperfectly reliable and have different costs. In addition, infection prevalence rates within the donor population are uncertain for both emerging and established infection types. In this setting, the budget-constrained blood center’s objective is to devise a “robust” postdonation bloodscreening scheme that minimizes the risk of an infectious donation being released into the blood supply. Toward this goal, we study the minimization of the transfusion-transmittable infection risk considering regret- and expectation-based objectives, and we characterize structural properties of their optimal solutions. This allows us to gain insight, derive the price of robustness, and develop efficient algorithms. The proposed robust solution lowers the expected infection risk over various FDA-compliant testing schemes as well as the expectation-based scheme under forecast error. These findings have important public policy implications. The e-companion is available at https://doi.org/10.1287/opre.2017.1658 .
recent evidence-albeit in hamsters-that PCR-positive and/ or antibody-positive (titer 256) units caused symptomatic infections in 34% of subjects. 5 However, they are not supported by human data. Of 29 known PCR-positive units that were transfused, only one recipient (3.4%) became symptomatically ill, and there were no reported symptomatic cases from those receiving the 29 PCR-negative units. Using the transmissibility and progression estimates from Bish and coworkers, we would suppose that in 29 known PCR-positive units transfused, five to six recipients would develop uncomplicated yet symptomatic infections, while three to four would have complicated babesiosis with a mortality of 12%. Thus, Bish and colleagues have likely overstated the burden of TTB morbidity and mortality.In summary, while decision analysis and cost-effectiveness modeling are well suited to inform policy on this topic, the most recent analysis likely overestimates the burden of transfusion-transmitted babesiosis and the cost-effectiveness of blood screening in endemic areas. Policy-makers would be well served to closely inspect all available models and each of their strengths and limitations before promulgating guidance. CONFLICT OF INTERESTBC is and EB was employed by Blood Systems Inc. (BSI) when this letter was written. BSI has supported development of a B. microti ELISA with Immunetics. EB participates in ongoing studies of donor screening and follow-up using the Immunetics ELISA. The other authors have disclosed no conflicts of interest.
Problem definition: In an environment where consumers’ rising valuation of Instagrammable memories drives their spending from products to experiences, retailers offer experiences to attract consumers back to their stores. Yet, it is not obvious under which settings consumers can benefit from these experiences and raise retailers’ profits. Methodology/results: We use a random utility model for consumer choice in both monopoly and duopoly settings. For the latter, we pose a game-theoretic model to analyze the equilibrium prices, profits, and consumer welfare for various problem cases. We show that medium-quality experiences can lower the product sales and store traffic below the level when no experience is offered. Sufficiently low- or high-quality experiences overcome this issue, making the consumers better off. Yet, the former presents the only profitable option when a single retailer in the market offers an experience. In contrast, when both retailers adopt experiences, low-quality experiences may not be profitable, and the retailers would need to adopt even higher-quality experiences, which lead to a “win-win-win” outcome for the two retailers and consumers. A fee structure for the experience elevates retailer profits but can turn stores into outlets where consumers visit to purchase experiences and not products. When experiential retailing is the common practice in the market, it enables “win-win-win” outcomes when free experiences fail. Managerial implications: Being the first to study this new retail format, our results contribute to the ongoing debate on the settings under which experiential offerings are beneficial for the retailers and consumers and highlight that there is no one-size-fits-all strategy. Our results show that experiences affect main product sales in nonobvious ways, especially in competitive markets. In a (post-)pandemic world where retailers try to attract consumers back to stores, we offer insights that can guide retailers in the process. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0339 .
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