General Overview of Big Data in Medical Industry

In general, the role of big data to the medical world is to continuously provide live streams of data readily available for medical experts to track and analyze in order to obtain valuable information hidden within. Most of the data are gathered by the use of “personal data trackers” such as Fitbit. What these personal data trackers do is that it measures the amount of steps taken, heart rate and amount of calories burned within a period of 24 hours (WIRED UK, 2014). All these collected raw data are then made available for the doctors to process and obtain valuable insight with permission from the data owners.

From a clinical point of view, doctors are able to identify patients with potentially life threatening diseases just by analyzing the data collected from these personal data trackers. This is done by studying the correlation between the occurrence of an event to a certain condition based on the data from the past, and compare it with the data that is just recently collected and handed over to the doctor by the patient. What this process done is that it effectively shortens the amount of time required for the doctors to observe and diagnose a patient, reducing the amount of time that is usually used to observe and diagnose when the symptoms have already appeared.

Real time healthcare allows the patient to be monitored after being diagnosed of a certain illness. Live streams of data allow the doctors to be constantly updated of the condition of the patient. What big data is also capable of is to reduce the amount of time required for a certain drug to be created and to be manufactured. Big data enables the companies to monitor and observe how effective their drugs are and also what are the side effects of their drugs. With comprehensive knowledge of their new products, companies are able to develop drugs in much faster cycle compared to the traditional experimental group.

The utilization of big data in hospital also allows significant cost reduction and downtime for the hospital, while at the same time a significant savings for the patient. Hospitals are able to use their own data collected in-house to determine what are the busiest period of time and allocate the most resources to facilitate it, while at the same time allowing patients to be discharged as soon as they are deemed fit. Big data also can be utilized in a way that reduces the number of equipment downtime by predicting the amount of patient to be admitted and also determining the best possible time to carry out maintenance work.

Overall, all the above utilize big data to achieve the larger end goal of the medical industry, which is to provide the most value to the patients, while ensuring high customer satisfaction and trust towards the industry in general. The reduction of drug development cycle, waiting time in the hospital and lower cost of treatment ensures that patients gets the best treatment and care possible with the aid of big data. While at the same time providing doctor a better platform in which data are readily available for them to carry out researches to help prevent diseases or development of drugs.

References

WIRED UK. (2014). Activity trackers like Fitbit bring big data to US healthcare. [online] Available at: http://www.wired.co.uk/article/internet-things-health [Accessed 8 Jun. 2016].

Prepared by Yee Kang

How Big Data help reduce medical cost?

As a doctor, we would like to know what is best care possible for each patient. However, as a patient one of our biggest concern is the cost of healthcare. By reducing the medical cost, not only it will reduce the burden of the patients, but it can also allow patients with minimum income to enjoy treatments that they previously could not afford. According to Versel (2015), by using big data analytic Beaufort Memorial Hospital in South Carolina estimate that they could approximately save $435,000 by allowing patients to discharge half a day earlier. So how Beaufort Memorial Hospital managed to accomplished this? Their IT department analyzes 180 parameters and report on important key data points. The purpose of all these important key data points are to plan prescriptions, wheelchair transportation, follow-up-visits and room cleaning. By setting mini daily goals for the staffs such as assigning patients to their bed/room within 10 minutes will reduce the average amount of stay length and this would eventually help Beaufort Memorial Hospital save cost (Versel, 2015).

Another way on how Big Data can help reduce medical cost is to reduce emergency room visits. A research by the Minnesota Department of Health recently found out that every year there are 1.3 million unnecessary trips to the emergency room. With this 1.3 million unnecessary visits, it cost the medical facilities $2 Billion (Health.state.mn.us, 2016). After this discovery, the state government of Minnesota started using Big Data analytic to help reduce unnecessary emergency room visits. For example, the state distinguishes 50,000 local residents that had at least four preventable emergency room visits due to chronic diseases. Instead of assigning them to the emergency room before receiving primary medical care, the state ensures that these 50,000 local immediately receive primary medical care by working closely with doctors, nurses and hospital staffs (Health.state.mn.us, 2016). This will not only help the hospital to save cost, it can also decrease the severity of an illness due to early admissions.

With Big Data analysis, St. Louis Children’s hospital was able to eliminate unnecessary number of tests for Dravet Syndrome (a rare form of epilepsy) which cost $6,000 per test. These test are often carried out on infants with seizures. However, according to Dr.Nephi Walton uses data analytic to determine the effectiveness of the Dravet Syndrome Test and 100% of the time the test result is negative for the last 5 years (Healthcare Finance News, 2015). One of the easiest and effective way of saving money is to reduce small resource waste that add up over time.

Using Business Intelligent and analytic tools, hospital can monitor essential hardware to predict and prevent breakdowns. By ensuring all these medical equipments are working at optimal level not only save cost, it can also ensure patients care and safety. This can be accomplished by remotely sensing data from equipment, correlating data obtain from equipment with business information to predict future malfunctions, and also ensuring maintenance work is performed at the right time using the prediction generated from the data collected. As a result, hospitals that practice this preventive and predictive maintenance technique achieve 17% lower annual maintenance cost, 44% lower unplanned downtime and 28% higher return on assets. (Humphries, 2015).

Nearly 45,000 deaths are correlated with the lack of health insurance in the America itself (Cecere, 2009). However, with the help of big data analysis, we can help reduce medical cost. With the reduced cost, more patients can afford to pay for a better medical treatment. Hence, saving more lives.

REFERENCE

Cecere, D. (2009). New study finds 45,000 deaths annually linked to lack of health coverage. [online] Harvard Gazette. Available at: http://news.harvard.edu/gazette/story/2009/09/new-study-finds-45000-deaths-annually-linked-to-lack-of-health-coverage/ [Accessed 3 Jun. 2016].

Healthcare Finance News. (2015). Healthcare providers show success with predictive analytics at Boston symposium. [online] Available at: http://www.healthcarefinancenews.com/news/healthcare-providers-so-success-predictive-analytics-boston-symposium [Accessed 6 Jun. 2016].

Humphries, D. (2015). How Health Care Analytics Boosts Efficiency & Reduces Costs. [online] Software Advice. Available at: http://www.softwareadvice.com/resources/bi-how-data-analytics-solutions-reduce-costs/ [Accessed 3 Jun. 2016].

Health.state.mn.us. (2016). News release: Novel MDH study yields first statewide estimate of potentially preventable health care events. [online] Available at: http://www.health.state.mn.us/news/pressrel/2015/hcevents.html [Accessed 4 Jun. 2016].

Versel, N. (2015). Cleveland Clinic, Other Health Groups Use Data to Boost Patient Satisfaction. [online] US News & World Report. Available at: http://health.usnews.com/health-news/hospital-of-tomorrow/articles/2015/01/16/cleveland-clinic-other-health-systems-use-analytics-to-boost-patient-satisfaction [Accessed 1 Jun. 2016].

Prepared by Soam Wei Jie

How Big Data Is Transforming Healthcare

It’s difficult to think about a more beneficial use for big data today than saving valuable lives every day. Around the globe today the healthcare sector is discovering more approaches to do that each day.

The main sources of big data on medicine has been identified through a report compiled by McKinsey & Company for the Center for US Health System Reform. The main source of big data that is transforming medicine are activity and cost data, clinical data, Pharmaceutical R&D data and patient behaviour and sentiment data.

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Clinical data

These incorporate patient medical records and pictures accumulated through examinations or strategies, and in addition specialists’ notes. For instance, the Carilion Clinic, in Virginia, says it used programming language to process and analyze the big data of 350,000 patient records. The results then show that there are 8,500 individuals at danger of heart issues or disease. Additionally, the American Medical Association reported that examination of patient records discovered just 26% of kids who had recorded three hypertension readings at partitioned visits to their specialists had been analyzed as torment hypertension. This indirectly highlights the countless failures to the condition. (Bernard Marr, 2015)

Other than that, when we visit a specialist or go to the clinic, we have confidence in the learning that the healthcare experts treating us as per proven medical techniques, also called evidence-based medication (EBM). This implies they’re recommending sedates or selecting treatment techniques that have been tested effective in clinical examination. By mining patients records which are clinical data, we could take into account the way we administer to people. (Bernard Marr, 2016)

Patient behaviour and sentiment data

This is information from over-the-counter medication sales joined with the most recent “wearables” which screens your physical and heart rates. Data and information about daily lifestyles of patients which their experience and satisfaction can be obtained from social media which is updated frequently. Right now wearable gadgets are usually utilized for individual wellness. However, this is set to change as consumers are spending on savvy watches, wrist groups, running shoes and different wearables which is possible to reach $52 million by 2019, as indicated by a study by ABI Research.  There are many applications available out there that enables patients to monitor their healthcare through sensor-construct applications on their cell phones. An “ingestible” scanner made by Protues, which is able to measure of a grain of sand, can be used to track when and how patients are taking their medicine. This will provide data about the consistent rates on how frequently patients take after their specialist’s instructions and will notify relatives if needed to. (Bernard Marr, 2015)

In conclusion, it is plain to see that there are lots of advantages to be retrieved from understanding the data about our wellbeing today. The quote “prevention is better than cure” has make researches work harder in finding proper treatment and solving problems in early stage of illness when it is easier to be treated now than later. This is because in earlier stages, the illness is much easier to be contained.

Later on we are likely to recuperate more rapidly from disease and harm, and we will live longer. New medications will be produced and our hospitals and surgeries will work more effectively because we have more information about the illness and what needs to be done. (Bernard Marr, 2016)

Also as quoted by Schulte (Apixio Chief Medical Officer before appointed as CEO) “If we want to learn how to better care for individuals and understand more about the health of the population as a whole, we need to be able to mine unstructured data for insights.”

References

Forbes Welcome. 2016. Forbes Welcome. [ONLINE] Available at:http://www.forbes.com/sites/bernardmarr/2016/02/16/how-big-data-is-transforming-medicine/#1783da7a1cd4. [Accessed 04 June 2016].

4 Ways Big Data Is Transforming Healthcare – Data Science Central. 2016. 4 Ways Big Data Is Transforming Healthcare – Data Science Central. [ONLINE] Available at:http://www.datasciencecentral.com/profiles/blogs/4-ways-big-data-is-transforming-healthcare. [Accessed 04 June 2016].

Prepared by Samuel Low

Big Data in Medical Research and Development

With the current trend revolving around big data, it’s just the matter of time where the medical field would soon adopt it into part of its process. Big data is a collection of real-life data stream from the users whereby many industries can benefit from its enormous capabilities. This post will be discussing a few of its main capabilities in the medical industry and how it will revolutionize it.

Prior to the era of big data, the average development cycle of a drug is roughly around 10 years and costs as high as USD 1 billion dollars (Anon 2014). This cycle takes up too much time and money, so much so that people that needs it the most either don’t have the luxury of time or money to wait for the drug to be publically available. The aim of implementation of big data into the research and development side of medical drug is to reduce the development cycle and help produce a more affordable and effective drug for the public. A great emphasis is being put on how the integration between biomedical field and computing field. Collaboration between these two fields are necessary in order to facilitate and reduce the cycle of the research and development stage.

Another great innovation made possible by big data in the medical field is the ability to conduct real-time healthcare and clinical analytics (Lives n.d.). This allows medical practitioners to monitor the patient in real-time and observe their health condition. This allows the doctor to take better preventive measures and also provide a better treatment that is more suitable to the patient’s lifestyle. The ability to capture live datasets also provides significant value to drug manufacturers as it can also show how effective the drugs are, and also what are the side-effects that are not being discussed by the patient. Big data also allows medical institution to leverage on the statistical tools and algorithm to further predict the current health condition of the surrounding area. This allows the medical institution to allocate resources to department where it needs the most, thus speeding up medical treatment and reduce risks.

In conclusion, the main benefit that the medical industry can leverage from big data is the ability to speed up the process cycle from diagnostic to prescription of drugs. When it comes to health, being able to react quickly is also as crucial as prescribing the correct drug to the patient.

References

Anon, 2014. How to Transform Big Data into Better Health: Envisioning a Health Big Data Ecosystem for Advancing Biomedical Research and Improving Health Outcomes in Europe. , (November).

Lives, I., Big Data Analytics in Life Sciences and Healthcare : An Overview.

Prepared by Yee Kang

Improving customer satisfaction in healthcare by using big data

The world is changing because the big data age is in full force today. Big data relates to data and information that cannot be managed or analyze using traditional procedures or tools (Paul, Chris, Dirk, Thomas and George). More and more organization and businesses today are facing big data challenges. They produce a wealth of information but they have no idea to get the value out of it. All the data they produce are unstructured or is raw, as result, many organization have no idea whether the data is worth keeping. There are a lot of great things we can do with big data such as to know customer satisfaction. By generate results by mining big data, healthcare companies able to predict which item or services that satisfied their patient the most.

Healthcare providers seek to differentiate themselves by supplying outstanding patient outcomes, patient satisfaction and patient experience from patient’s reports (oracle, 2016). They must carry out services in a predictable and safe manner to analyst that develop new business models that may help to improve patient’s satisfaction towards the specific healthcare provider. Therefore, predictive analytic are the main role in developing for such changes. Furthermore, predictive analytic are occasionally used to predict whether recent trends will continue and potential implications. From here, healthcare provider able to improve quality of care and outcomes and better management of facilities, staffing, supplies and equipment to improve their customer satisfaction.

According to Dr James Merlino, using patient’s comments, and anecdotes to further improve their knowledge on customer perceptions. The hospital were surprised to discover that on the scale of what is most important that affect patient’s satisfaction. As results, the hospital thought their patient satisfaction scores were low because of terrible wait times before seeing a doctor but instead patients are more concerned about how the hospital workers communicate with them, they want to be treated with respect. Healthcare providers need to put patients first and at the center of everything if they want to improve their patient experience and satisfaction.

Alteryx is a data analytic company, according to George Mathew, the company’s president discuss on how do big data able to improve health care patient satisfaction. Applying analytics to health care organization through marketing, patient behavior, demographics, and population statistics, in result getting result of stronger patient satisfaction. Alteryx clients in the health care commerce are able to include all types of data, combine the data together and integrate predictive, spatial and other analytic in order to discover the answers to deliver better service to patients, predict what patient needs and offer programs and strategies that will increase patient loyalty and satisfactions.

The excellence of patient experience will continuously be improved if a healthcare organization able to rapidly respond through the accurate channels to properly achieve the expectations of its patient. Using software analytic to develop the correct data foundations and metrics and then proactively giving appropriate and related information, is superior. If healthcare organizations want to win patients or customer, they need to know them as individuals. They require to connect and quickly analyze all of the data at that available from their organization, to create keener predictions about their requests and behaviors. By better understanding of patient’s expectations, healthcare organization able to deliver the level of service that will generate growth in satisfaction, increase retention, and turn patients into advocates.

References

Health2con.com. (2016). Improving Customer Satisfaction Through Big Data with George Mathew. [online] Available at: http://www.health2con.com/news/2013/07/19/improving-customer-satisfaction-through-big-data-with-george-mathew/ [Accessed 5 Jun. 2016].

Merlino, J. (2015). How Cleveland Clinic Improved Patient Satisfaction Scores with Data and Analytics. [online] Health Catalyst. Available at: https://www.healthcatalyst.com/how-cleveland-clinic-improve-patient-satisfaction-scores-data-analytics [Accessed 5 Jun. 2016].

Oracle, 2015. Improving Healthcare Provider Performance with Big Data. Architect’s Guide and Reference Architecture Introduction, pp. 1-26.

Zikopoulos, P. (2012). Understanding big data. New York: McGraw-Hill.

Prepared by Kasper Liew

There’s always a past to talk about

Let’s talk about the history of healthcare with big data. Let’s talk about how it all started. Big Data’s has been around for many years now. Big data was defined as volume, variety and velocity by Doug Laney back in 2001. It is slowly blooming as technology era becomes more important and big data is finally becoming popular among us. Big data can be used for various sectors but let’s ask ourselves, how did big data end up being used for health care?

Large volumes of data is collected in the healthcare but most are said to be more recreational data meaning that the data collected from patients may be useful for later down the road for analyzing purpose and creating new paths to solve healthcare problems In healthcare they have been using the traditional methods to save data of a patient in the hospitals. Even they have databases, it is no match for Big Data as it can store pretty much anything and everything. The healthcare stakeholders had a harder time using the traditional methods to share and analyze data of a patient.

In order for the hospitals to start applying big data in their industry, they have to undergo a huge change from the traditional methods to the modern methods. The big data has shown many successful events in various fields generating profits and also customer satisfaction. With the use of this in healthcare, it makes it easier for researchers and data miners to analyze patient’s records creating a better solution to treat the patient and also other patients in the future, analyzing new drugs for treatments purpose to curb certain viruses, and also gain important data that can help patients to reduce costs.

A reason why they prefer big data is that standard medical practice decided to rely on evidence based rather than having an ad-hoc decision making and more subjective decision making. The in influences big data has on healthcare is remarkable. This opens work opportunities to many big data scientist and also data analyst or data miners that are mainly into analyzing, discovering many other patterns to cure and create new ways to help in healthcare. They also help to create many new software in order to help with analyzing and create statistical inferences based on the data they have collected throughout hospitals and patients from over the world from time to time.

There are many questions that arise from various people in many fields around the world. Is it safe because now anyone can access it since it’s in the cloud, what are the security measures taken to overcome this problem, does it save time and money and most of all, will it work? There are many security measure taken into consideration to curb the issue. For instance it is just like your iCloud.

Even though it is in the cloud instead of traditional database, there are security measures which stops hackers, spammers from retrieving the data and in order to retrieve it, you will definitely need access to retrieve. Big data has proven in other sectors that it has save tons of money and time because its way simpler and easier to analyze data rather than the longer traditional method therefor it is introduced to healthcare because we all know healthcare is not cheap. It can come up to hundreds till thousands of dollars.

References

Raghupathi W: Data Mining in Health Care. Healthcare Informatics: Improving Efficiency and Productivity. Edited by: Kudyba S. 2010, Taylor & Francis, 211-223.

Burghard C: Big Data and Analytics Key to Accountable Care Success. 2012, IDC Health Insights

Manyika J, Chui M, Brown B, Buhin J, Dobbs R, Roxburgh C, Byers AH: Big Data: The Next Frontier for Innovation, Competition, and Productivity. 2011, USA: McKinsey Global Institute

Adamson, D. (2016) Big Data in Healthcare Made Simple: Where It Stands Today and Where It’s Going (online). Available at https://www.healthcatalyst.com/big-data-in-healthcare-made-simple

Reddy, C. and Sun, J. (2013). Big Data Analytics for Healthcare (online). Available at https://www.siam.org/meetings/sdm13/sun.pdf

Groves, P. , Kayyali, B. ,Knott, D. and Kuiken, S. (2013). Center for US Health System Reform Business Technology Office. “The ‘big data’ revolution in healthcare” (e-journal). 

Prepared by Seevinnash

Welcome there Homosapiens !

Now for those that does not know what is big data, you may refer to the picture above. In other words, Big Data is whereby data that exceeds the processing capability of most common databases which are too fast, too big thus does not fit in the conventional database system we all have.

WHY MEDICLOUD ?

We are going to make use of big data in the Medical Industry, thats why!

by Seevinnash