Healthcare organizations collect and analyze large amounts of data in order to measure the performance of affiliated healthcare providers, and thus, to track the quality of healthcare being delivered to patients. Collecting and analyzing data in order to track healthcare quality are difficult for a healthcare organization, particularly for a large organization having many providers. For example, a healthcare organization can include several hospitals. Within each hospital, patients visit a number of different doctors, or providers. Moreover, the patients visit multiple hospitals. Additionally, different providers or hospitals collect and store data in different formats. Thus, large amounts of healthcare data can be diverse and scattered across many different systems throughout the healthcare organization. US20140032240 illustrates the big data analytics system for measuring healthcare quality effectively and efficiently from large amounts of heterogeneous healthcare data.

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Healthcare Big Data Analytics Insights from Patents
Alex G. Lee (alexglee@techipm.com)
https://www.linkedin.com/today/author/2853055
Healthcare organizations collect and analyze large amounts of data in order to measure the performance of
affiliated healthcare providers, and thus, to track the quality of healthcare being delivered to patients. Collecting
and analyzing data in order to track healthcare quality are difficult for a healthcare organization, particularly for a
large organization having many providers. Forexample, a healthcare organization can include several hospitals.
Within each hospital, patients visit a number of different doctors, orproviders. Moreover, the patients visit multiple
hospitals. Additionally, different providers or hospitals collect and store data in different formats. Thus, large
amounts of healthcare data can be diverse and scattered across many different systems throughout the healthcare
organization. US20140032240 illustrates the big data analytics system for measuring healthcare quality effectively
and efficiently from large amounts of heterogeneous healthcare data.
One of the challenges facing in the healthcare industry is the number of sources of information, the great amount of
information from each source, and consolidation of such information in order to provide meaningful and useful
insights to those in the field. For example, when a patient sees various medical professionals over the years, there is

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no method for universally tracking recommendations, thoughts, prescriptions, referrals, or diagnosis.
US20140304003 illustrates the big data analytics system to consolidate the medical information and analyze the
patient data in a medical network for the purposeof optimizing referral practices. The big data analytics system can
generate models that assist insurers and healthcare providers to track referral practices.
US20150187036 illustrates the big data analytics system for analyzing healthcare-related entity performance.
The healthcare-related entities include hospitals, pharmacies, and health insurance payers. The healthcare-related
entities can interact with members such as an individual personseeking medical services. The big data analytics
system collects, processes, and analyzes data from the healthcare-related entities (e.g., medical claim data,
prescription medicine data, pharmacy claim data, and clinical data). Then, the big data analytics system provides
many useful insights associated with healthcare-related entities. For example, these insights can be detecting any
irregularities such as fraud associated with medical claims or prescription claims; analyzing and comparing a
specific medical provider entity’s performance with other medical provider entities in a given region; providing a
summary of the kinds of medical services being offered by medical provider entities; and providing a performance
comparison between different locations of the same medical provider entity.
US20150179079 illustrates a system for real time monitoring of a patient's cognitive responseto a stimulus. The
big data analysis of massive data obtained by the sensing devices can provide many value-added healthcare
services. The real time monitoring system includes a mobile or tablet device, a user interface disposed onthe

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mobile device, sensors monitoring user interaction with the mobile device and capturing kinesthetic and cognitive
data. The real time monitoring system also includes a processor forcomparing the kinesthetic and cognitive data
and comparing the data to a baseline, and identifying relative improvement and impairment of cognition skills from
the comparison exploiting big data analytics.

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Internet of Things (IoT) Strategic Patent Development & Monetization for New Business Creation
Goldman Sachs defines the IoT as the third wave of internet revolution: By connecting billions of devices to the
internet, the IoT can open up a host of new business opportunities and challenges. Even though the IoT is getting a
huge attention recently the conceptof interconnected billions of devices is not new and has been under
development for over 10 years. Thus, there are a large number of related patented technologies that can be
exploited for developing new products/services, and thus, new business for the emerging IoT market.
TechIPm has developed an insightful new patent development and monetization methodology for the emerging IoT
market.
Many patent applications and newly issued patents can be further developed for creating new values by amending
and creating claims and generating follow-on patents to encompass emerging technology and products/services
trends, market demands, and strategic exploitation goals. TechIPm provides consulting for improving existing
patents to obtain maximum ROI. TechIPm also provides consulting on developing new patents that can lead to new
IoT product/servicedevelopment exploiting the strategic patent preparation & prosecution, white spaceanalysis,
and scenario analysis.

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A strategically packaged patent portfolio is the collection of patents that the integrated value propositions of each
patent of the portfolio target specific value propositions that are provided by emerging new products/services.
Techipm develops the strategically packaged patent portfolio in alignment with a client’s specific IoT business
interests (e.g., smart home automation). TechIPm’s methodology for developing the strategically packaged patent
portfolio is based on a deep understating of the IoT technologies, extensive experiences in patent analysis and
development, and insights into the emerging IoT market. The strategically packaged patent portfolio can be used
for monetization through patent sale, patent licensing, commercialization, spin-off, patent banking, and patent-
backed financing. TechIPm also can provide consulting on developing monetization program for exploiting the IoT
strategically packaged patent portfolio.
For detailed information, please visit
http://www.slideshare.net/alexglee/best-practices-of-ip-patent-strategy-iot-internet-of-things-case-study