{"title":"Preventing Medical Errors Using mm-Wave Technology; a Letter to the Editor.","authors":"Andreas G Siamarou","doi":"10.22037/aaem.v11i1.2138","DOIUrl":null,"url":null,"abstract":"Dear editor About 795,000 people die or are permanently disabled each year due to diagnostic errors and related harms across clinical settings, according to estimates based on nationally representative disease incidence data for 2012 to 2014 (1). Studies show that the number of medical errors is increasing annually (2). This undergoing research study has its impact on improving human healthcare and reducing diagnostic errors due to fast, accurate, and robust data storage, transmission, and analysis with the use of information technology (IT) (3). Reducing diagnostics errors using IT in primary care and, generally, in healthcare is limited and huge steps must be taken to establish the use of IT for this purpose. To address this issue, the study proposes the use of ultrafast wireless big data transmission in primary care, specifically in remote smart sensors monitoring devices. It suggests that wireless transmission with a speed up to 100 GB/s (12.5 GBytes/s) within a very short distance (1-10 meters) is necessary to reduce diagnostic errors. High-speed data transfer could facilitate rapid transmission of medical images, such as CT scans, MRIs, or ultrasound images, between different systems or departments within the hospital. This would allow for faster interpretation and analysis of critical medical data, aiding in the diagnosis and treatment of patients in the ICU. The ability to transmit large amounts of data quickly, could facilitate telemedicine applications. For instance, doctors or specialists located remotely could have real-time access to patient data, video feeds, and diagnostic images, allowing them to provide expert consultations without being physically present in the ICU. Using a controlled experimental setup that mimics the challenges and requirements of an Intensive Care Unit (ICU),","PeriodicalId":8146,"journal":{"name":"Archives of Academic Emergency Medicine","volume":"11 1","pages":"e64"},"PeriodicalIF":2.9000,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/44/77/aaem-11-e64.PMC10568942.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Academic Emergency Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22037/aaem.v11i1.2138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"EMERGENCY MEDICINE","Score":null,"Total":0}
引用次数: 0
Abstract
Dear editor About 795,000 people die or are permanently disabled each year due to diagnostic errors and related harms across clinical settings, according to estimates based on nationally representative disease incidence data for 2012 to 2014 (1). Studies show that the number of medical errors is increasing annually (2). This undergoing research study has its impact on improving human healthcare and reducing diagnostic errors due to fast, accurate, and robust data storage, transmission, and analysis with the use of information technology (IT) (3). Reducing diagnostics errors using IT in primary care and, generally, in healthcare is limited and huge steps must be taken to establish the use of IT for this purpose. To address this issue, the study proposes the use of ultrafast wireless big data transmission in primary care, specifically in remote smart sensors monitoring devices. It suggests that wireless transmission with a speed up to 100 GB/s (12.5 GBytes/s) within a very short distance (1-10 meters) is necessary to reduce diagnostic errors. High-speed data transfer could facilitate rapid transmission of medical images, such as CT scans, MRIs, or ultrasound images, between different systems or departments within the hospital. This would allow for faster interpretation and analysis of critical medical data, aiding in the diagnosis and treatment of patients in the ICU. The ability to transmit large amounts of data quickly, could facilitate telemedicine applications. For instance, doctors or specialists located remotely could have real-time access to patient data, video feeds, and diagnostic images, allowing them to provide expert consultations without being physically present in the ICU. Using a controlled experimental setup that mimics the challenges and requirements of an Intensive Care Unit (ICU),