Maintaining data confidentiality is the new challenge faced by healthcare organizations. It is important for them to protect this digitized data from criminal hands. Hospitals, clinics and other healthcare organizations are slowly adapting to new technologies that are capable of protecting such data. There are some more challenges, such as accessing permission. A lot of insurance agencies, healthcare providers may require access to the data, but access control needs to be maintained for proper security.  The healthcare organizations may have data spread across various mobile devices. So, proper data encryption should be done in order to ensure data safety. The other important issue is using third party software in medical instruments; it may cause data theft. These security issues are raising concerns in the healthcare industry. To know more read: http://www.cio.com/article/2933323/healthcare/healthcare-organizations-face-unique-security-challenges.html

Sepsis is a serious medical condition that occurs when the body releases the full force of the immune system in response to an infection. The immune chemicals trigger widespread inflammation that can result in impaired blood flow and thus leading to failure of the body's organs. This disease is consuming major cost for the healthcare industry. Here Data Analytics has stepped in and provided a solution. The solution consists of a disposable wireless Band-Aid-like biosensor (the FDA-certified HealthPatch), which helps in real-time processing of patient data, and consumable analysis that allows medical professionals to take immediate action.
 The smartphone app transmits the patient clinical data to a cloud-based repository, where it is integrated with existing patient data from other data sources (NoSQL and SQL-based data sources, premium data sources, etc.). For more information visit:
http://www.cio.com/article/2949854/big-data/how-big-data-analytics-help-hospitals-stop-a-killer.html

In healthcare, the main challenge when big data is concerned is to ensure that both healthcare providers and patients are benefiting from the huge flow of information, and are not getting confused by it. Big data is not to be forced and is to be adopted by the healthcare system, in a stable and efficient way. There is a need for targeted and personalized data to improve service quality, even at doctors’ levels. Restricted accessibility to information often creates hurdles for healthcare organizations. The healthcare providers are now deriving both medical and financial information from the insurance sector. EHR data can act as a major playground for big data analytics, as the healthcare sector are adopting more and more e-measures. Read more at: http://healthitanalytics.com/news/how-healthcare-big-data-analytics-drives-systematic-improvement

Continuously evolving technology in the healthcare sector is creating immense pressure on the healthcare providing concerns, to meet their highly demanding service quality and financial goals. Organizations are trying to develop step by step connections, by keeping track of all the different stages a patient has to go through, once he enters into the concerned healthcare system. The healthcare industry has been giving a lot of effort in the development of the health information system and big data analytics, in order to improve the healthcare service. As, more and more stages of the healthcare cycle becomes electronically recordable, the easier it becomes to keep track of the patients and their health situations. Read more at: http://healthitanalytics.com/news/health-data-interoperability-requires-patience-persistence

Health care providers, lose track of patients as soon as they relocate from the healthcare facilities. The process of relocating within hospitals is equally complicated for patients. A well-defined IT infrastructure can be used to address both the issues. It is important to match patients with their appropriate health care facilities, by collecting and analyzing the data on the patients’ needs. It will also be possible for healthcare providers to draw valuable insights, by collecting and analyzing data on patient transfer procedures. Hence, we have both big data and data analytics, coming into play, by increasing the operational efficiency, but dampening the revenue earnings of the healthcare industry. Read more at: http://healthitanalytics.com/news/big-data-on-patient-transfers-raises-quality-snags-revenue

If you keep an account of your store’s electricity consumption, you would realize that almost half of it goes to waste. Energy costs are sky high apart from the fact that more consumption leads to increased carbon foot prints. Energy use can be minimized by eliminating energy wastage. FirstFuel, a software start up monitors energy wastage using bi data. It uses the electric meter data, weather data GIS (geographic information system) mapping to create the required database. This database helps analyze energy performance without physically stepping into the building, thereby saving the time effort and cost. Read more at:

http://www.businessinsider.in/How-revolutionary-technology-is-tackling-the-200B-problem-of-wasted-energy-in-buildings/articleshow/47460842.cms#ixzz3f7Nme5ct

According to a survey, big data analytics and informatics skills are the ‘prospective’ two most important resources, to be used by the healthcare providers in their decision making and data management processes. The health information sector is experiencing some major changes, like, for example, the conversion of paper health records into electronic health records (EHR). Health Information Management (HIM) is also evolving, to be utilizing big data in population health management, predictive analytics, clinical quality enhancements, etc. Health Information Management, needs to view data as an asset, in order to utilize the data, in the best possible way. Read more at: http://healthitanalytics.com/news/him-healthcare-big-data-analytics-skills-increase-in-demand

Just like the earlier days, even now we view healthcare solutions in two-dimensional ways – patient-doctor relationship or technology revolutionizing patient’s health and wellness. The problem gets more acute with invention of new technology solutions. But if we don’t intervene to gather the data and use them, there’s no use of new technologies such as wearable devices. Thus real collaboration is required where every member connected to the patient acting as a crew member can steer the patient towards possible better health. Everyone working collaboratively can harness the power of technology and big data, to deliver a 360 degree-solution built around the patient. Implementing the approach of multi-stakeholder interaction of social media, can make true social healthcare realize its potential. Read more at:  http://www.socialmediatoday.com/social-business/paul-tunnah/2015-07-09/effective-healthcare-requires-social-approach

A certain cross-country survey revealed that the Internet of Things (IoT) was first adopted by the Healthcare Industry. Organizations that adopted the IoT, believed that they could meet business challenges like patient engagement, loyalty, safety and satisfaction without any delay.
According to Laura DiDio, Director of IoT Strategies Enterprise, the need for IoT is felt highly by enterprises to address and solve pragmatic business issues. Andrew Brown, SA’s Executive Director of IoT and Mobility says that IoT can also be used for cost savings, development of new services, increased competitiveness and better understanding of the business.
It can be said that the Internet of Things has great potential in the field of healthcare and with evolvement of mobile capabilities its growth rate will be escalated.
Read more at: http://healthitanalytics.com/news/healthcare-industry-is-an-early-internet-of-things-adopter

In technology adoption, the healthcare sector is still lagging behind, due to its intricate compliance and security requirements. The healthcare sector has been mainly focusing on medicines, which is evolving continuously. However, the scenario is changing, as healthcare providers have started to compete for market share. Healthcare marketers are trying to identify prospective patients, most likely in need of their healthcare services and retain them in their institutional networks. Hence, predictive analytics is being applied to big data, in order to determine consumer behaviors and patterns in their operational areas, according to their healthcare service usage. Read more at: http://www.techrepublic.com/article/the-underexploited-big-data-sweet-spot-for-healthcare/

Interconnected devices enable, round the clock monitoring of vulnerable patients and also forestall further health threats. Three ways, enabling IOT, benefit healthcare management are;
i. Supervision of drugs and prevention of further health issues- is possible by integrating medical devices into a network of monitoring devices, along with the maintenance of data flow into a centralized repository, to minimize human transcription errors. IOT enables fast access to patient data which helps in detecting drug usage anomalies and even predicting imminent health threats.
ii. Maintenance of hand hygiene, in order to reduce infections- is possible by electronic monitoring, provided by IOT, of say, how many times a hospital personnel visits a hand washing station.
iii. Keeping track of at-risk patients, in their home environment- is again, possible by the amalgamation of monitoring devices and seamless network.  
Read more at: http://healthitanalytics.com/news/three-ways-the-internet-of-things-can-improve-patient-safety

The first step in applying analytics to healthcare data is to create a centralized repository of all the available information extracted from EHRs, health information exchanges, claims data, etc. The main motive remains in interpreting the data to derive valuable insights, which will not only benefit health management, but also fuel business growth. This methodology is also being used to tackle mental healthcare data. Analytics is being used on community data, available in a centralized manner, to identify patients, with more vulnerability to certain mental illnesses. However, since complete information of patients is not always available in such centralized data platforms, inconsistencies in analyses remain. Read more at: http://healthitanalytics.com/news/mental-healthcare-big-data-warehouse-illuminates-care-trends

The first step in effective implementation of a health management initiative is stratifying patients according to the costs incurred by them, in order to properly target the healthcare programmes. It has been observed that the majority of healthcare costs are concentrated in a small fraction of the total patient population. Focusing on the healthcare of this fraction of patients, can greatly reduce costs for the entire population, while providing the appropriate care, valued by the patients and their families. Risk analytics incorporates claims and EHR data into risk scores, in order for health care providers to target their services efficiently. Read more at: http://healthitanalytics.com/news/population-health-management-starts-with-flagging-high-costs

Healthcare is perhaps the most valuable and personal data. The risk of data breach is growing as there have been millions of data breach cases. Health data stores are mostly held in on-site software solutions, or, at cloud services, where the data stores are managed by third party hosting providers. But since cloud is not immune to such attacks, this may not be the perfect solution. A recent report by sky-high networks shows that around 93 % of these cloud services pose a security breach threat to the healthcare organizations. Since it is an open source, the origin of the threat is sometimes hard to detect. Read more at: http://www.forbes.com/sites/danmunro/2015/07/06/healthcare-moves-to-the-cloud-but-is-the-cloud-ready-for-healthcare/

Big data analytics in healthcare industry, encompasses the whole transformation of data, beginning from the recording of the fundamental data to predicting diseases and alerting patients. Any health concern’s big data analytics capabilities fall into three major categories, descriptive, predictive and prescriptive. Descriptive analytics quantifies past events, like for example, the number of patients, who visited the hospital in the last month. It provides considerable insights into the data which can be later used to make predictions, regarding disease trends. Predictive analytics uses these descriptive data to predict the future, which often reduces unnecessary costs, related to controllable diseases, by making early detections. Finally prescriptive analytics provides suggestions on ways to mitigate the imminent threats, suggested by predictive analytics. Hence, an efficiently functioning data analytics infrastructure, incorporates all the three processes and is invaluable in the healthcare industry. Read more at:

http://healthitanalytics.com/news/healthcare-big-data-analytics-from-description-to-prescription

Sigmaway consultants have worked with clients in benefits solutions workspace providing analytics on healthcare plans. For more details visit http://www.sigmaway.us/

Remote patient monitoring (RPM) is a technology (read wearable) that facilitate monitoring of patients outside the conventional clinical setup. This will basically help increase the intensity of care and decrease the cost of healthcare delivery. Jack Kreindler, MD is chairman, chief medical officer and co-founder of Sentrian, hopes that this technology will help in hugely cutting down avoidable hospitalization and dealing with the problem of chronic diseases which is a burden on every economy. In his special guest feature in Inside Bigdata, he elaborates on Remote Patient Intelligence (RPI). Till very recently this seemed to be a far dream but it seems to change in the near future. Cheaper wearable/bio sensors, omnipresent smart phones, more connectivity, highly evolved machine learning and big data analytics hold the keys for the realization of this dream. For more on the scope of this futuristic technology, follow the link http://insidebigdata.com/2015/06/10/the-promise-of-remote-patient-intelligence/

Big data is the new buzzword. It has become one of the imperative equipment required to conquer growth across industries. Here is how you can master the art by following thee 5 rules, coined by Rishi Sikka, Advocate Healthcare.

#1 Clue lies in the past: to be able to predict future, it is necessary to dig deeper into the past data and EHRs.

#2 Diversify risk through strategic distribution of resources.

#3 Impactability- healthcare organisations should focus where and to which extent do they impact.

#4 Take population Health as a predictive exercise, not academic.

#5 Minimize costs, work to provide best healthcare.

Read more at: http://www.healthcareitnews.com/news/5-tips-becoming-big-data-superhero

Study of human beings is more complex than machines and so is the study of their data. It is important to make accurate decisions which decide life and death matters and thus require error free and credible data. Therefore apart from the 3Vs- volume, variety and velocity; healthcare data should also have veracity. As much as it is required, it is difficult since there are issues in the healthcare data - is the information furnished about the patient, drug prescription, disease correct? Also since the data is huge and frequency is also high.it is difficult to clean the data, thus magnifying the credibility issue. To know more, read the following journal at: http://www.hissjournal.com/content/2/1/3

With more than three million Americans being affected with Hepatitis C Virus (HCV) and the virus posing serious challenges to reducing the costs of disease management and control, recent research from University of Michigan is promising some hope. By making the use basic EHR data, predictive analytics algorithms can now flag the affected patients who are at high risk of developing complications from the virus. Although one-third of the HCV patients are at risk, all the patients are treated which lead to huge unnecessary healthcare spending. This is where the predictive analytics model is expected to be of great use. Further integration of the model with EHR will enable the providers to deliver more targeted treatment and a chronic disease management plan can chalked out. Read more :- http://healthitanalytics.com/news/predictive-analytics-identify-high-risk-hepatitis-c-patients

Healthcare as an industry faces serious challenges in the context of improving patient care and safety of their staffs and patients, besides managing costs. Bryan Warren, the director of corporate security at Carolines Healthcare, said that the video surveillance and analytics had helped to increase productivity both within and outside of the security function. Video analytics helps to set checks in order to ensure that patient satisfaction remains high. In Europe, it affects audit scores and government funding. Video analytics can also be used for efficient staffing levels or better handling of the emergency procedure. Video surveillance plays a crucial role in the provision of evidence whenever a problem occurs and in traditional security.

 To know more, please follow the link: http://www.forbes.com/sites/avigilon/2015/06/11/healthcare-meeting-future-challenges-today-with-video-analytics/