Wednesday 13 September 2017

BIG DATA TRENDS TRANSFORMING THE HEALTHCARE INDUSTRY



Big data is a revolution that is under way in the healthcare sector, and it is here to stay. Over the last decade, there’s been a remarkable increase in the supply of information followed by years of research and development. The use of big data technologies along with advanced analytics not only helps reduces cost but also increase patient outcomes. While the price of treatments, diagnosis and medication become lower, the advantage is in using predictive analytics to anticipate the outbreak of epidemic and endemic diseases.

Health systems are now using big data solutions to execute analytics in multiple data streams including unstructured and structured data. Risk models are being built with the expectation of predicting undesirable outcomes a patient may experience. This may include negligibility, being readmitted post discharge or even being affected with an infection while hospitalized. This analysis can further be used to enhance patient outcomes and gain actionable healthcare insights that improve patient care.

A McKinsey report states that healthcare currently represents 17.6% of the country’s GDP, a steady increase, more than 20 years.

Other industries are aggressively creating new analytics tools, data application and strategies to reap higher benefits such as predictive analysis, machine learning and graph. The healthcare industry is now looking at acute data analysis and larger application methods to progress and collaborate with each other for business success. As the healthcare industry experiences a drastic change in data technology and transformation, let’s take a closer look at big data trends that are quickly changing the healthcare industry for the better.

Individual Patient Care

With the rise of big data, patient focused care is steadily becoming a priority. Doctors and staff are able to serve patients better as they can quickly analyze and locate patient related data. The value of data is benefitting patients as well as hospitals as it is improving the overall quality of the experience. The structured approach can greatly reduce the net of healthcare costs while improving patient outcomes.

Hospitals are able to provide proactive patient care with real-time monitoring. The vital signs can be continually monitored, analyzed and instantly alert representatives in case the patient’s condition deteriorates. Processing these real-time events along with machine learning algorithms gives doctors the much-needed insight to make life-saving decision.

In a 2016 PWC survey, majority of people participating already agree that they would be excited to experience wearable technology. 65 percent voted yes to using wearables from doctors, 62 percent from hospitals and health insurance company

The trend of wearable technology is quickly becoming a norm. These wearable devices and sensors allow nurses and care givers to interact with a patient in a more convenient way. Devices can be used to remotely monitor weight and track changes in a patient battling a heart disease. These applications can go as far as detecting fluid medication to check if hospitalization is required. The end result is capturing extensive data that allows for superior patient engagement and patient care coordination that is personalized to each individual patient needs.

Reducing Waste, Fraud And Abuse

The spiraling healthcare costs in the United States are majorly caused by the fraud, abuse and waste costs in the healthcare sector. Countering this notion, big data analytics is a huge game changer. In a predictive modeling environment, big data solutions and Hadoop can be used to identify inaccurate claims that are systematic and repeatable. However, a large number of the healthcare data that is stored remains unstructured. Using machine learning algorithms, patterns and anomalies across historical claims can be detected leading to preventing fraudulent occurrences.

Individual data is collected from sources such as claims, pharmacy, EMR, notes, logo, clinical and third party data which makes way for personalized experience. Implementing big data solutions in the data hub serves as a medium to detect fraud, waste and abuse in the healthcare industry. For example, analytics can be used to model the flag to certain charges and raise a red flag. This makes it easier to prevent many fraudulent insurance claims or medical claims across the industry and the country.

The Centers for Medicare and Medicaid Services prevented more than $210.7 million in healthcare fraud in one year alone using predictive analysis.

Apart from this, healthcare sector can analyze billing and patient records to identify irregularities and notify in case of excess utilization of services in a short notice. This is possible across healthcare services across locations and organizations consecutively. The data is filtered clearly leaving very little room for error in information such as identical prescriptions that could be filed for the same patient in multiple locations.



Author Bio – Matt Wilson – A Healthcare Expert, is working with Aegis Health Tech as senior developer from last 5 years. He has extensive experience in patient management system, EMR & EHR Development, Implementation and Integration.

Saturday 2 September 2017

Hl7 Healthcare Solutions for Improved Business Standards


What Is HL7?

HL7 or Health Level-7 is a set of international standards, definitions, formats used for transfer of administrative and clinical data. It is developed and propagated by an international standards organization known as Health Level Seven International. However, it is also operated and adopted by other standard issuing bodies and many healthcare providers in developing and exchanging (EHRs) electronic health records.

The HL7 standards provide a framework and define how information is communicated and packaged between medical applications. HL7 healthcare solutions are widely recognized and used in the world as it sets the language, data types, and structure for transmission of health related information.

Main Classifications Of HL7

      Primary standards: One of the most frequent primary standards and in-demand in this category, this section is used for systems integration, compliance, and interoperability. 

Foundational Standards: Provides HL7 healthcare solutions by defining the fundamental tools to build technology infrastructure for HL7 standards to manage.

Administrative and Clinical Domains: Usually implemented only when primary standards are in place. This section covers document standards and messaging for clinical groups and specialties.

EHR Profiles: These are standards that provide functional profiles and models. They provide access to HL7 healthcare solutions by enabling the conception of EHR management.

Implementation Guides: This section is for creating support documents which will be used in conjunction with an existing standard, like a supplement.

Rules and References: A segment used for making software and standard guideline, structures, and technical specifications.

Education and Awareness: Helpful resources and tools for understanding HL7 standards can be found here, including drafts for trial use and current projects.

Key Standards of HL7

The mission of HL7 was to create a common healthcare standard. However, there are different versions associated with each unique structure. For example, an HL7 version 3 isn’t altered to that of HL7 version 2. The latter produces a negotiated framework while the former was targeted to eliminate variances. Nevertheless, HL7 healthcare solutions are all adopted in meaningful use standards in an effort to improve communication among all users.

Few main standards include:

·      HL7 version 2 (v2), a database query language mostly used as a messaging standard. This is where clinical information, patient care, and health data are generally exchanged.

·    An ISO approved standard, CDA, which is an exchange model for medical documents like discharge summaries, notes and admission records.

·   The system functional models EHR-PHR that provides common language parameters. Primarily used to develop EHR systems, their components and draft standard functions in PHR model for data exchange between the two.

·       A web based exchange language (FHIR) Fast Health Interoperability Resource is a perfect example of HL7 healthcare solutions as it makes the applications easier, simpler and faster to write.

Benefits of HL7

·    Enables sharing public health information and creating a national network by way of (EHR) Electronic Health Record.
·  Makes communication between system faster and easier thereby facilitating the development of systems that are interoperable.
·      Leads to HL7 healthcare solutions that are cost-effective
·      The standards help deliver consistent information to patients.
·      Strengthens and streamlines the community of referring physicians


How Do We Help?

AegisHealthTech provides optimum HL7 healthcare solutions that empower hospitals, organizations, and customers. This is an environment where the industry has to comply and the key aspect of multiple regulatory reforms is HL7. We have the experience of clinical expertise across applications and multiple third party HIE and EHR systems; this, in turn facilitates us to aggregate diverse healthcare applications and interconnect them in a seamless manner. With us, you can always be sure that a robust solution and optimal integration of frameworks will be implemented that is based on your functional and technological architecture.

HL7 Integration Services
·         Healthcare interoperability standards
·         Expert in EAI tools
·         Highly experienced in leading HIE and healthcare platforms
·         Validations on message format structure data
·         Standards-based integration adapters with 3rd party EMRs

Aegis provides HL7 integration services so you can increase resources with assurance of complete conformance to HL7 healthcare solutions and messaging standards. We work with you as part of your team, bringing in our skill and expertise to design an interface that is tailored to your requirement. Our HL7 healthcare solutions enable for an end-to-end automation of the validation process, allow for effort reduction, early detection of defects and increased productivity. Gain enhanced coverage with quick validation of messages in HL7, customization and faster time solutions with Aegis.