ABSTRACT
The large amount of biomedical data derived from wearable sensors, electronic health records, and molecular profiling (e.g., genomics data) is rapidly transforming our healthcare systems. The increasing scale and scope of biomedical data not only is generating enormous opportunities for improving health outcomes but also raises new challenges ranging from data acquisition and storage to data analysis and utilization. To meet these challenges, we developed the Personal Health Dashboard (PHD), which utilizes state-of-the-art security and scalability technologies to provide an end-to-end solution for big biomedical data analytics. The PHD platform is an open-source software framework that can be easily configured and deployed to any big data health project to store, organize, and process complex biomedical data sets, support real-time data analysis at both the individual level and the cohort level, and ensure participant privacy at every step. In addition to presenting the system, we illustrate the use of the PHD framework for large-scale applications in emerging multi-omics disease studies, such as collecting and visualization of diverse data types (wearable, clinical, omics) at a personal level, investigation of insulin resistance, and an infrastructure for the detection of presymptomatic COVID-19.
Subject(s)
Data Science/methods , Medical Records Systems, Computerized , Big Data , Computer Security , Data Analysis , Health Information Interoperability , Humans , Information Storage and Retrieval , SoftwareABSTRACT
Abstract With the COVID-19 outbreak, AATM took an early initiative to provide the membership instructive recommendations and informative Aide Mémoire. Optimizing membership support a survey was sent to 25 pandemic affected member-countries, to collect challenges and approaches on blood supply and transfusion. Approach Survey sent to AATM country representatives. Five questions focused on in-country blood collection and pandemic situation, diagnosis, treatment and personal protection equipment (PPE), including a snapshot question on disease magnitude;and 2 descriptive questions on challenges and responses to overcome challenges. Country classification 2018 UNDP statistical update Human Development Indices/Indicators (HDI). Basic metric statistics. Results Response rate: 92%;HDI classification: Low ? 1;Medium ? 9;High ? 9 and Very High ? 4 countries;population range: 540,544-1,380,000,000;blood collection/1000: 2.4-36.1. Ranges/1000: hospital beds, Intensive Care/isolation beds and ventilators respectively: 0.5-8.2;0.019-1.8;0.0007-1.11. All countries had quarantine facilities. Sufficient PPE: all but 3 countries. Testing facilities: all but 3 countries. All but 1 country listed challenges and responses. Most common challenges and approaches were respectively shortages in blood donors and supply (19/22), staff safety (13/22);and mass media education and awareness campaigns (21/22), staff education on safety practices and universal precautions (18/22). Conclusion High response from Medium and High HDI countries. Major challenges reported: effects of pandemic on blood donors and blood supply, where most countries already were suffering from shortages due to their development state. Key approaches: staff education to prevent infection;focused public awareness campaigns to convince donors to keep coming to support the nation?s blood availability during crisis.