Big Data In Medicine

Nasir Arafat

Why Big data in medicine?

• The data generated by Hospitals or health insurance companies are becoming bigger and complex• Data are in different formats from human genetics to routine clinical

documentation, from internal imaging to motion capture, from digital epidemiology to pharmacokinetics and from treatment pathways to life course assessment• Data science have improved healthcare industry from understanding

disease to better diagnose and helping patients monitor their own conditions.

Sources of Medical Data

• The clinical trials data (data for clinical research) can be achieved using electronic health records (EHR) or web based system.• EHR designed to stores range of data (demographics, medical history,

immunization status, lab test results, radiology images)• It reduces data replication and records can be shared through network

connected • BIG DATA is the tool for medical science just like stethoscope, ECG or

thermometer • We can collect data like heart rate, temperatures, body chemistry,

weight, ECG using medical instruments

Electronic Health record

How Big Data is being used for medicine

• Cleaver usage of data to make better decisions for the medical science and health industry.• Monitor the safety of drug treatment• Better understand diseases, and develop drugs and treatments that can

change lives.• Some EMR systems automatically monitor clinical events by

analysing patient data from an EHR to predict, detect events.• Social media globalize health (important source of health data)

• We can collect heart rate, body temperature, weight, height, body chemistry, ECG data.• Without frame of reference this data is not be medically analysed .• Until we have a better understanding of what can be considered

normal.

Big data is disruptive technology for medicine

• Radical changes in health care due to advances in genetic medicine Data science is driving force in disruptive technologies born of genetic medicine. • Big data is going to revolutionize the health industry by advancing the

way of treatment, monitoring, diagnosis and medication. • Yet Big data has not become so much useful to the health industry as

we are expecting and many medical traditionalists think that data science can never replace human intuition & institution for doctors. So the big data has yet to revolutionize the health industry.

Problem with using Big data

• One of the biggest problem around big data, and the predictive models that could build on that data, really centres on how you engage others to benefits from that information.• Beyond the tools that we need to engage non-computational

individuals in this type of information and decision making.• Training is the way to handle this problem

What big data means to patients

• Big data in medicine can build better health profiles and better predictive models around individuals patients so that disease could be better diagnosed and treated.

• Future for patients is engaging them as a partner in this new mode of understanding their health and wellness better and understanding how to make better decisions around those elements.

• Most of their data collection will be passive, so individual won’t have to be actively every day (logging things)

• They’ll agree to have their data used in this way because they get some perceived benefit.

Extent to which big data make difference in medicine• Drug makers use big data to improve allergy medication supply chain

technology to make sure their products are in stock.• They have advanced their supply chain technology and are able to

combine data from thousands of stores and compare the information with other data to ensure they are meeting customer demand.• Even some companies uses real time data sources like google fly

trends, twitter trends and temperature forecasts to predict when products will be in high demand. There is some web based software that helps drug makers to review data reports which are customizable and can be analysed daily

Cancer genomics (DNA sequencing) using big data to advance breast cancer risk prediction

• With more than 230,000 new cases of invasive breast cancer diagnosed every year, according to the American cancer society.

• Big data can be new tool that may help diagnose and treat breast

cancer more effectively. Processing medical data generated by various clinical trials, genomic sequencing and individual case studies promises to unlock secrets that could not be readily observed by human eyes.

Prediction of pre-diabetes

• Google is planning to tackle diabetes with the help of big data analytics and innovative Internet of Things technologies.• Using data analytics we can create and sample models for doctors that

could predict pre-diabetes patients would gain the most from treatment with a drug that prevents diabetes. The researchers use data from 3k peoples from an area as a clinical trial of diabetes prevention• the diabetes prevention program, including a variety of different

health factors such as blood sugar levels and waist to hip ratio. even by combining Google’s interest in miniaturized medical devices that contribute to real-time patient monitoring.

Google to Tackle Diabetes Using Big Data and Internet of Things

• The company previously explored the development of a contact lens that continuously measures a patient’s blood glucose with little active effort. The lens would theoretically eliminate the need for finger-prick blood glucose tests while ensuring that patients are constantly monitored for dangerous fluctuations. • Google was granted a patent for the device in March of 2015, though a

representative declined to state whether that meant the lens was approaching market readiness.

Ebola (could Big data analytics help?)• In 2014 more than 27,000 cases of Ebola • Fatal illness in humans that kills more than 11,000 last year• We can minimize the spread of Ebola Virus Using Big Data analytics. • Using Infographics (visualisation representation of data) we can isolate the affected area to minimize the

spread of Ebola virus. • Mobile mapping is being used for this process as mobile phones widely owned by everyone and are proving

rich source of data in a region.

Big data as a Future of medicine

• Penn Medicine taps big data to save lives: Penn medicine’s modern big data initiatives applications alert doctors of at-risk patients. Penn plans to take the platform open source for other healthcare providers next year. The potential to deliver better healthcare has been one of the driving factors behind the push for big data analytics in medicine in recent years. • Future of early cancer detection using micro RNA detection platform

for molecular data gathering, analysing and interpretation. Small RNA molecules found in the blood reflect a person’s health status

The data lab cancer information program (project)

• This project is funded by data lab, digital health & care institute and Stratified medicine. The objective of this project is to develop prototype cancer intelligence system (CIS) directed towards fulfilling the needs of cancer patients and clinicians in improving care and outcomes for patients.• By combining and exploiting existing data sets and unstructured

information sources it is envisaged that the CIS shall generate new insights into patient outcomes and clinical treatments and outcomes in Scotland.

(http://www.thedatalab.com/Cancer-Intelligent-System)

CIS (prototype)