ArticleProceedings of the National Academy of Sciences of the United States of America2017
Big data modeling to predict platelet usage and minimize wastage in a tertiary care system.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 74 citations in OpenAlex.
- AI and Blood Banking: Predicting Transfusion Demand - A Systematic Review of Forecasting Approaches.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2026Review
- A Method for Predictive Analysis of Platelet Supply.Indian journal of hematology & blood transfusion : an official journal of Indian Society of Hematology and Blood Transfusion · 2026Article
- Reducing blood component wastage through targeted interventions: A four-year retrospective study at a Saudi tertiary hospital.Transfusion medicine (Oxford, England) · 2025Article
- A quantitative analysis of the factors that influence clinical blood demand in the Suzhou area.Scientific reports · 2025Article
- The effect of modulating platelet reactive oxygen species by the addition of antioxidants to prevent clearance of cold-stored platelets.Hematology, transfusion and cell therapy · 2024Article
- Platelet Storage-Problems, Improvements, and New Perspectives.International journal of molecular sciences · 2024Review
- Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare.BMC medical informatics and decision making · 2024Article
- Demand forecasting for platelet usage: From univariate time series to multivariable models.PloS one · 2024Article
- Machine learning in transfusion medicine: A scoping review.Transfusion · 2024Article
- Statistical Learning and Uncommon Soil Microbiota Explain Biogeochemical Responses after Wildfire.Applied and environmental microbiology · 2022Article
- A robust autonomous method for blood demand forecasting.Transfusion · 2022Article
- Reduction of Platelet Outdating and Shortage by Forecasting Demand With Statistical Learning and Deep Neural Networks: Modeling Study.JMIR medical informatics · 2022Article
- The path from big data analytics capabilities to value in hospitals: a scoping review.BMC health services research · 2022Article
- Autophagy Ameliorates Reactive Oxygen Species-Induced Platelet Storage Lesions.Oxidative medicine and cellular longevity · 2022Article
- Blood usage at a large academic center in Maryland in relation to the COVID-19 pandemic in 2020.Transfusion · 2021Article
- Antioxidant prevents clearance of hemostatically competent platelets after long-term cold storage.Transfusion · 2021Article
- RBC Inventory-Management System Based on XGBoost Model.Indian journal of hematology & blood transfusion : an official journal of Indian Society of Hematology and Blood Transfusion · 2021Article
- Effects of amotosalen treatment on human platelet lysate bioactivity: A proof-of-concept study.PloS one · 2020Article
- Development and Implementation of Real-Time Web-Based Dashboards in a Multisite Transfusion Service.Journal of pathology informatics · 2019Article
- Application of Time-Series Analysis and Expert Judgment in Modeling and Forecasting Blood Donation Trends in Zimbabwe.MDM policy & practiceArticle
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
Maintaining a robust blood product supply is an essential requirement to guarantee optimal patient care in modern health care systems. However, daily blood product use is difficult to anticipate. Platelet products are the most variable in daily usage, have short shelf lives, and are also the most expensive to produce, test, and store. Due to the combination of absolute need, uncertain daily demand, and short shelf life, platelet products are frequently wasted due to expiration. Our aim is to build and validate a statistical model to forecast future platelet demand and thereby reduce wastage. We have investigated platelet usage patterns at our institution, and specifically interrogated the relationship between platelet usage and aggregated hospital-wide patient data over a recent consecutive 29-mo period. Using a convex statistical formulation, we have found that platelet usage is highly dependent on weekday/weekend pattern, number of patients with various abnormal complete blood count measurements, and location-specific hospital census data. We incorporated these relationships in a mathematical model to guide collection and ordering strategy. This model minimizes waste due to expiration while avoiding shortages; the number of remaining platelet units at the end of any day stays above 10 in our model during the same period. Compared with historical expiration rates during the same period, our model reduces the expiration rate from 10.5 to 3.2%. Extrapolating our results to the ∼2 million units of platelets transfused annually within the United States, if implemented successfully, our model can potentially save ∼80 million dollars in health care costs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.