Application of Blockchain Technology in the Field of Medical Devices

In recent years, Blockchain technology has been mentioned for many times in the fields of finance, Internet and energy, and it is a distributed data ledger that is decentralized, authentic, reliable, traceable open and transparent. Blockchain is constantly figuring out how to integrate with other industries. This paper analyzes the current situation in the field of medical devices of China by combing the Annual Report on Medical Device Adverse Event Monitoring from 2013-2019, and using the compound annual average growth rate. The analysis found that this field has pain points such as lack of third-party regulation and difficulty in traceability, and then it proposed the specific application of blockchain technology in the field of medical devices to solve the problems in this field.

Frequency of Adverse Event Monitoring in Ambulatory Patients on Amiodarone or Dofetilide

Background: Published studies state that adherence to regular laboratory assessments for anti-arrhythmic drugs is as low as 20%. Monitoring adherence is important as other studies have shown that up to 93% of patients on amiodarone experience an adverse drug event leading to a potentially lethal event. Objective: To determine whether patients prescribed amiodarone or dofetilide are being monitored according to package labeling and guideline recommendations for adverse events. Methods: Patients prescribed amiodarone or dofetilide from a 2-year period were eligible for inclusion. Patients with ventricular arrhythmias, prescribed more than 1 anti-arrhythmic agent, or received anti-arrhythmic monitoring outside the health-care system were excluded. Adherence to monitoring parameters was assessed according to labeled recommendations and published guidelines. The primary objective was to determine the frequency of baseline and follow-up monitoring recommendations for patients receiving amiodarone or dofetilide. The secondary objective was to determine rates of adverse drug events. Results: One hundred patients were evaluated (amiodarone n = 50, dofetilide n = 50). Average rates of baseline and follow-up amiodarone monitoring parameters were 55% and 57%, respectively. Average rates of baseline and follow-up dofetilide monitoring were 99.6% and 85%, respectively. There was a statistically significant difference in abnormally elevated thyroid-stimulating hormone levels (8%-30%, P ≤ .005) after patients were prescribed amiodarone. Twelve percent of patients taking dofetilide had an increase in QTc interval by >15%. Conclusions: Amiodarone adverse event monitoring was lower than dofetilide in this cohort. Improving the monitoring of these agents may decrease morbidity risk in this population.