Difference between revisions of "Template:Article of the week"

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'''"[[Journal:The growing need for microservices in bioinformatics|The growing need for microservices in bioinformatics]]"'''
'''"[[Journal:Deployment of analytics into the healthcare safety net: Lessons learned|Deployment of analytics into the healthcare safety net: Lessons learned]]"'''


Within the information technology (IT) industry, best practices and standards are constantly evolving and being refined. In contrast, computer technology utilized within the healthcare industry often evolves at a glacial pace, with reduced opportunities for justified innovation. Although the use of timely technology refreshes within an enterprise's overall technology stack can be costly, thoughtful adoption of select technologies with a demonstrated return on investment can be very effective in increasing productivity and at the same time, reducing the burden of maintenance often associated with older and legacy systems.
As payment reforms shift healthcare reimbursement toward value-based payment programs, providers need the capability to work with data of greater complexity, scope and scale. This will in many instances necessitate a change in understanding of the value of data and the types of data needed for analysis to support operations and clinical practice. It will also require the deployment of different infrastructure and analytic tools. [[Federally qualified health center|Community health centers]] (CHCs), which serve more than 25 million people and together form the nation’s largest single source of primary care for medically underserved communities and populations, are expanding and will need to optimize their capacity to leverage data as new payer and organizational models emerge.  


In this brief technical communication, we introduce the concept of microservices as applied to the ecosystem of data analysis pipelines. Microservice architecture is a framework for dividing complex systems into easily managed parts. Each individual service is limited in functional scope, thereby conferring a higher measure of functional isolation and reliability to the collective solution. Moreover, maintenance challenges are greatly simplified by virtue of the reduced architectural complexity of each constitutive module. This fact notwithstanding, rendered overall solutions utilizing a microservices-based approach provide equal or greater levels of functionality as compared to conventional programming approaches. [[Bioinformatics]], with its ever-increasing demand for performance and new testing algorithms, is the perfect use-case for such a solution. ('''[[Journal:The growing need for microservices in bioinformatics|Full article...]]''')<br />
To better understand existing capacity and help organizations plan for the strategic and expanded uses of data, a project was initiated that deployed contemporary, Hadoop-based, analytic technology into several multi-site CHCs and a primary care association (PCA) with an affiliated data warehouse supporting health centers across the state.('''[[Journal:Deployment of analytics into the healthcare safety net: Lessons learned|Full article...]]''')<br />
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''Recently featured'':  
''Recently featured'':  
: ▪ [[Journal:The growing need for microservices in bioinformatics|The growing need for microservices in bioinformatics]]
: ▪ [[Journal:Challenges and opportunities of big data in health care: A systematic review|Challenges and opportunities of big data in health care: A systematic review]]
: ▪ [[Journal:Challenges and opportunities of big data in health care: A systematic review|Challenges and opportunities of big data in health care: A systematic review]]
: ▪ [[Journal:The impact of electronic health record (EHR) interoperability on immunization information system (IIS) data quality|The impact of electronic health record (EHR) interoperability on immunization information system (IIS) data quality]]
: ▪ [[Journal:The impact of electronic health record (EHR) interoperability on immunization information system (IIS) data quality|The impact of electronic health record (EHR) interoperability on immunization information system (IIS) data quality]]
: ▪ [[Journal:Bioinformatics workflow for clinical whole genome sequencing at Partners HealthCare Personalized Medicine|Bioinformatics workflow for clinical whole genome sequencing at Partners HealthCare Personalized Medicine]]

Revision as of 21:24, 27 February 2017

Fig1 Hartzband OJPHI2016 8-3.png

"Deployment of analytics into the healthcare safety net: Lessons learned"

As payment reforms shift healthcare reimbursement toward value-based payment programs, providers need the capability to work with data of greater complexity, scope and scale. This will in many instances necessitate a change in understanding of the value of data and the types of data needed for analysis to support operations and clinical practice. It will also require the deployment of different infrastructure and analytic tools. Community health centers (CHCs), which serve more than 25 million people and together form the nation’s largest single source of primary care for medically underserved communities and populations, are expanding and will need to optimize their capacity to leverage data as new payer and organizational models emerge.

To better understand existing capacity and help organizations plan for the strategic and expanded uses of data, a project was initiated that deployed contemporary, Hadoop-based, analytic technology into several multi-site CHCs and a primary care association (PCA) with an affiliated data warehouse supporting health centers across the state.(Full article...)

Recently featured:

The growing need for microservices in bioinformatics
Challenges and opportunities of big data in health care: A systematic review
The impact of electronic health record (EHR) interoperability on immunization information system (IIS) data quality