Title : What Big Data Analytics can do for Stroke Patients
Introduction Data from UK and USA’ studies show that the average age of stroke patients is falling. Give that stroke is the main cause of adult disability, it becomes essential for policy makers to know the trends and the outcomes of the prevention campaigns/therapies.
Methods Our retrospective study included 244,276 admissions to Hospitals in Queensland between 2002 and 2015 for stroke and related issues (ICD = I60-I69). 151,733 admissions had stroke (I60-I64) as a principal diagnosis, of which 57,713 were defined as first ever episode. We analyzed the patient data on the basis of age range (under or equal 65 and over 65 years of age) and year of admission.
Results Data from 57,713 patients reveals that the crude incidence rate of stroke patients age 25-64 x 100,000 inhabitants increased from 44 to 62 (p<0.0001). It represents a jump of + 18/100,000 from 2002 to 2015.
Moreover, preliminary data shows that younger people seem to get to the hospital later than older ones, missing the chance for acute therapy and facing a worse outcome with chronic disability.
Conclusion Our study suggests that stroke is becoming more frequent in younger Australians. Primary and secondary prevention techniques are effective, as results from older shows, but that they need to be carried over to younger at-risk groups too, together with an awareness campaign.
Yet, there are patterns that usual analysis can’t detect therefore there are info we are missing which could be useful especially in understanding why younger people are slower in seeking for help. This is where big data analytics can play a crucial role.
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