Measuring the effectiveness of online search ads on blood donor recruitment and donation.

BACKGROUND: Acutely highlighted during the COVID-19 pandemic, the tenuousness of the blood supply continues to be a lynchpin of the most important medical procedures. Online advertisements have become a mainstay in donor recruitment. We set out to determine the effectiveness of online search ads and variations thereof on blood donations with an emphasis on first-time donors. STUDY DESIGN AND METHODS: From September 01, 2022 through March 31, 2023, we performed a campaign comparison experiment through a major search-ads platform with two distinct messages: one altruistic ("Altruistic") and one with a prospect of rewards ("Promotion"). We developed a method to track donation outcomes and associated them with impressions, click-throughs, and conversions. We compared the performance of the Altruistic and Promotion arms to a control group that was not associated with any search-ads ("Baseline"). RESULTS: Analyzing 34,157 donations during the study period, the Promotion group, and not Altruistic, had a significant difference of first-time donors over Baseline (24% vs. 12%, p = 7e-6). We analyzed 49,305 appointments and discovered that appointments made from the Altruistic arm resulted in a significantly higher percentage of donations when compared to Baseline (57% vs. 53%, p = .009); however, the Promotion group had a higher percentage of donations from first-time donors when compared to Baseline (12% vs. 8%, p = .006). CONCLUSION: We developed a method for determining the effectiveness of online search ads on donation outcomes. Rewards/promotions messaging was most effective at recruiting first-time donors. Our methodology is generalizable to different blood centers to explore messaging effectiveness among their unique communities.

Blood Demand Forecasting and Supply Management: An Analytical Assessment of Key Studies Utilizing Novel Computational Techniques.

Use of data-driven methodologies in enhancing blood transfusion practices is rising, leveraging big data, machine learning, and optimization techniques to improve demand forecasting and supply chain management. This review used a narrative approach to identify, evaluate, and synthesize key studies that considered novel computational techniques for blood demand forecasting and inventory management through a search of PubMed and Web of Sciences databases for studies published from January 01, 2016, to March 30, 2023. The studies were analyzed for their utilization of various techniques, and their strengths, limitations, and areas for improvement. Seven key studies were identified. The studies focused on different blood components using various computational methods, such as regression, machine learning, hybrid models, and time series models, across different locations and time periods. Key variables used for demand forecasting were largely derived from electronic health record data, including clinical related predictors such as laboratory test results and hospital census by location. Each study offered unique strengths and valuable insights into the use of data-driven methods in blood bank management. Common limitations were unknown generalizability to other healthcare settings or blood components, need for field-specific performance measures, lack of ABO compatibility consideration, and ethical challenges in resource allocation. While data-driven research in blood demand forecasting and management has progressed, limitations persist and further exploration is needed. Understanding these innovative, interdisciplinary methods and their complexities can help refine inventory strategies and address healthcare challenges more effectively, leading to more robust, accurate models to enhance blood management across diverse healthcare scenarios.

Advancing Understandings of Blood Donation Motivation and Behavior.

In this review, we provide critical analysis of social science research into blood donation motivation and behavior. We first share an understanding of the existing literature and recommendations for future research collectively developed by members of the Working Group on Blood Donors and the Supply: Diversifying while Maintaining the Donor Pool, Donor Selection, and Optimizing Blood Availability and Safety, as part of the National Heart, Lung, and Blood Institute's 2022 State of the Science in Transfusion Medicine symposium. Then, rather than aim for a comprehensive treatment, we review 4 newer manuscripts that exemplify aspects of the group's recommendations and report results from countries where the blood supply is based on voluntary, nonremunerated donations. From the substantial existing literature, we selected: (1) a study that employed motivational interviewing techniques, thematic analysis, and surveys to link donation motivations and barriers reported by diverse young donors in the United States to actual donation behavior over a year of subsequent eligibility; (2) a survey regarding donation motivations and barriers and monetary amounts associated with willingness to participate in whole blood, plasma, or platelet collection; (3) a survey-based assessment of various emotional states reported by donors at 2 time points during donation and the relationship between emotional experience and subsequent vasovagal reactions; and (4) an interpretive discourse analysis of blood collection agency messaging to donors and the public in the beginning of the COVID-19 pandemic. We close by noting several challenges posed by the structure of the United States blood system and the current funding environment to conducting rigorous research and translating findings into practice.

A call for better validation of opioid overdose risk algorithms.

Clinical decision support (CDS) systems powered by predictive models have the potential to improve the accuracy and efficiency of clinical decision-making. However, without sufficient validation, these systems have the potential to mislead clinicians and harm patients. This is especially true for CDS systems used by opioid prescribers and dispensers, where a flawed prediction can directly harm patients. To prevent these harms, regulators and researchers have proposed guidance for validating predictive models and CDS systems. However, this guidance is not universally followed and is not required by law. We call on CDS developers, deployers, and users to hold these systems to higher standards of clinical and technical validation. We provide a case study on two CDS systems deployed on a national scale in the United States for predicting a patient's risk of adverse opioid-related events: the Stratification Tool for Opioid Risk Mitigation (STORM), used by the Veterans Health Administration, and NarxCare, a commercial system.

Correlates of Housing Sustainability Among Youth Placed Into Permanent Supportive Housing and Rapid Re-Housing: A Survival Analysis.

PURPOSE: Youth experiencing homelessness (YEH) are vulnerable to multiple adverse health outcomes. Connecting YEH with housing is critical to addressing youth homelessness and to preventing long-term negative health consequences among this vulnerable population. Using administrative data, this study aims to explore correlates of YEH's sustainability in two major housing programs: permanent supportive housing (PSH) and rapid re-housing (RRH) programs. METHODS: This study used Homelessness Management Information System administrative data collected from 16 communities across the U.S. between January 1, 2015 and May 1, 2017 (n = 10,902). We conducted Cox proportional hazards survival analyses to explore correlates (e.g., demographics, homeless experiences, and overall vulnerability) of YEH's PSH (n = 577) and RRH (n = 2,883) sustainability separately. RESULTS: For YEH receiving PSH, only individuals' level of vulnerability is associated with greater hazard of exiting PSH. As for RRH sustainability, YEH who were 17 years old or younger, black or Latinx (as compared to white), of higher level of vulnerability, or previously spent most nights couch surfing or in transitional living programs (as compared to on the street) are associated with higher hazard of exiting RRH. CONCLUSIONS: Both PSH and RRH programs should incorporate comprehensive services targeting youth experiencing high vulnerability to prevent them from re-entering homelessness. Future RRH programming should also address housing sustainability disparities faced by racial and ethnic minority YEH, especially when they are disproportionately influenced by homelessness. Finally, RRH programs should incorporate services to foster independent living among younger YEH to sustain their housing status once temporary housing subsidies expire.