Digital Salutem
15 September 2016

Big Data: Healthcare Prevention

By João Bocas

This is the second in a series of five Healthcare Big Data blogs and its impact written by John Morton about Big data for Digital Salutem. The first is: Big Data: Challenge, or Opportunity for Healthcare?  and the third Big Data: Healthcare Diagnosis 

big-data-health-prevention

The greatest challenge in healthcare is to understand the demand for healthcare. Too often health services have to react to a patient arriving. Then, through urgency and concern they must respond and provide decisions based on little information. Regular and /or continuous monitoring of a patient can help in two ways. Informing the patient and providing information that a health care professional (in the absence of no other information) may find useful.

People are more active in their care and wellbeing, their knowledge level of  health, sickness and the impact of lifestyle choices on their health is better understood.  Although some believe this is all new, the technology sensing, measurement and calibration has been available for professional athletes for some time. Now ease of use, reduced cost and availability of algorithms (often free) is leading to a more and more people monitoring, reviewing and assessing their health progress. 

Commonly, smartphones are becoming the platform used to combine information, analyse it and present it. Often these smartphones are gateway to gather information from other smart devices like fitbit and others. As you visit your electronic store, retail stores and look on the internet there are vast array of cheap commercially available health care devices available. 

These devices can be used for monitoring your vitals under stress, be weighing scales to determine your current BMI index and have the capacity to help track progress against a self defined, or prescribed healthcare plan.  Even large corporates are seeking to include information for such things as medication dosage and frequency to assure that courses of treatment are taken as prescribed, are completed and that, certain drugs, are accounted for.

Similarly, monitoring can add value by meeting the needs for clinical demands for exercise, movement and show that a healthy systematic habit of self healthcare is being obtained. 

Tracking, monitoring and analysing physical fitness has been with us for a number of years. Today applications and devices can be used to monitor long term conditions and symptons, providing new and valuable information as to the deterioration of a patient over one, two or more years. Here analytics and “small data” (patients own records) can be analysed to show changes in memory loss, increase in Asthma, the impact of changing amounts of drugs. 

This type of information is very valuable. Insurance companies are providing rewards to those who can demonstrate achievements of goals keeping patients healthy and returning them to health. (e.g. Vitality Health provides rewards for staying healthy. The monitoring and surveillance being undertaken through creating a health record. ) 

This is also good for the economy, patients and the health service keeping people out of “clinical” care. Although, this information that is gathered about wellness isn’t clinically vetted or assured, it may be considered as fairly reliable. 

This “small data” (patient specific data) can mount up over a year, or more, giving a rich  group of datasets about a patient. This can be analysed on its own to show trends of getting better, deterioration and identify effectiveness of specific treatments, initially and over longer timeframes. For medications, and changing medications, providing the specific accurate dosage is more an art than a science for a number of reasons. Here continuous monitoring can may highlight more quickly the need for a change and through digital health communications allow the clinician to inform a change on the dosage. Savings in time, convenience and providing a heightened level of health and safety for patients are core to many medical technology startups. From talking to such in the UK, Germany, Romania and Lithuania, it is a health tragedy that drives many to improve the health ecosystem, to make things better and reduce the risk of what has happened to them. 

This “small data” (patient specific data) can be combined with other data to drive new and innovative insight; to prevent, or even predict when a patient may require clinical care. 

This rich seam of new health related information (eHealth or HealthIT) is being used by researchers in conjunction with clinical pathways and care plans to enrich existing clinical information. Combining this information gives new insight into understanding the intersection of lifestyle, treatment and disease. 

This analysis is being used to help identify trends from the data. Thus, your healthcare records can be compared with others people with the same disease and, giving you insight on what to expect and more importantly giving you time to plan and prepare. 

With further research, more accurate assessment and analysis of patients the promise is that early detection, months earlier than by today’s methods will save lives. 

This is the second of five blogs on Healthcare Big Data and its impact. The remaining will consider big data for:

1. Big Data: Challenge, or Opportunity for Healthcare?  2. Big Data: Healthcare Prevention  3. Big Data: Healthcare Diagnosis  4. Big Data: Healthcare Treatment 5.  Big Data: Healthcare Awareness

John Morton

John Morton is a Big Data Advisor having with experience across the whole data value chain, business intelligence and analytics in a number of industries including clinical, healthcare informatics and Pharma. John’s has been fundamental in creating new medical IT solutions and medical devices for clinical environments; enabling the digital hospital; a physician on my shoulder; as well as the challenges and impact of technology within clinical environments.

More articles:

–  How Wearable Devices Can Work In Digital Health

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