Blockchain is a new and popular technology in the digital age. Blockchain technology is referred to as decentralised and distributed digital ledgers, which are called blocks. These blocks are linked together with the cryptographic hashes and are used to record transactions between many computers. No single block can be altered without altering the related blocks. Modification of individual block data is impossible because each block contains information from the previous block. This is the unique strength of blockchain. Timestamps and hashes are some of the important terms when blockchains are considered. Data security is guaranteed with this advanced technology. Blockchain technology finds its application in the healthcare industry with many advantages in a queue. Medical data can be transferred safely and securely for fool-proof management of the medicine supply chain, which helps in healthcare research. Blockchains are used to securely encrypt a patient’s information in the event of an outbreak of a pandemic disease. A stroke is referred to as a brain attack, also called cerebral infarction. A cerebral infarction is a sudden stoppage of blood flow in the blood vessels connected to the brain. This study focused on evaluating the application of blockchain technology in Stroke Nursing Information Management Systems. This emerging technology is already in use in the healthcare industry. The patient’s data is kept decentralized, transparent, and mainly incorruptible, thus keeping it secured and sharing of data is quick.

Knowledge discovery and cloud computing can help early identification of ischaemic stroke and provide intelligent, humane, and preventive healthcare services for patients at high risk of stroke. This study proposes constructing a health management model for early identification and warning of ischaemic stroke based on IoT and cloud computing, and discusses its connotation, constructive ideas, and research content so as to provide reference for its health management in order to develop and implement countermeasures and to compare the awareness of early stroke symptoms and first aid knowledge among stroke patients and their families before and after the activity. The rate of awareness of early symptoms and first aid among stroke patients and their families increased from 36% to 78%, and the difference was statistically significant ( P < 0.05 ) before and after the activity.

PurposeTo explore the application value of an integrated emergency care model based on failure modes and effects analysis (FMEA) in patients with acute ischemic stroke (AIS).MethodsAccording to the convenience sampling method, 100 patients with AIS who visited the emergency department in our hospital from October 2018 to March 2019 were randomly selected as the control group and received routine emergency care mode intervention. Another 100 AIS patients who visited the emergency department from April to October 2019 were selected as the intervention group and received the integrated emergency care model based on FMEA. The total time spent from admission to completion of each emergency procedure [total time spent from admission to emergency physician reception (T0−1), total time spent from admission to stroke team reception (T0−2), total time spent from admission to imaging report out (T0−3), total time spent from admission to laboratory report out (T0−4), and total time spent from admission to intravenous thrombolysis (T0−5)] was recorded for both groups. The clinical outcome indicators (vascular recanalization rate, symptomatic intracerebral hemorrhage incidence, mortality rate) were observed for both groups. The National Institutes of Health Stroke Scale (NIHSS) score and Barthel score were evaluated for both groups after the intervention. The treatment satisfaction rate of the patients was investigated for both groups.ResultsThe total time of T0−1, T0−2, T0−3, T0−4, T0−5 in the intervention group (0.55 ± 0.15, 1.23 ± 0.30, 21.24 ± 3.01, 33.30 ± 5.28, 44.19 ± 7.02) min was shorter than that of the control group (1.22 ± 0.28, 4.01 ± 1.06, 34.12 ± 4.44, 72.48 ± 8.27, 80.31 ± 9.22) min (P &lt; 0.05). The vascular recanalization rate in the intervention group (23.00%) was higher than that in the control group (12.00%) (P &lt; 0.05). There was no statistical significance in the symptomatic intracerebral hemorrhage incidence and mortality rate in the two groups (P &gt; 0.05). After intervention, the NIHSS score of the intervention group (2.95 ± 0.91) was lower than that of the control group (6.10 ± 2.02), and the Barthel score (77.58 ± 7.33) was higher than that of the control group (53.34 ± 5.12) (P &lt; 0.05). The treatment satisfaction rate in the intervention group (95.00%) was higher than that of the control group (86.00%) (P &lt; 0.05).ConclusionThrough FMEA, the failure mode that affects the emergency time of AIS patients is effectively analyzed and the targeted optimization process is proposed, which are important to enhance the efficiency and success rate of resuscitation of medical and nursing staff and improve the prognosis and life ability of patients.