Recently, big data has been garnering attention as a potential problem-solver for today's industry woes. But, before jumping into the new "data-driven paradigm" of leveraging big data, a recent report by CSC suggests organizations take a look at their basic, data-centered strategy.

"Most organizations have more data to work with than they realize, but they need to recognize the challenges and plan to overcome them," the report reads. "For example, the data landscape is constantly changing. The size, scope, and types of data available are rapidly evolving, and so are the tools needed to make sense of it all. To identify competitive advantages and achieve better command and control over their data, entrepreneurial healthcare executives need to recognize this evolution."  

The report outlines six keys to making better use of your data. 

1. Data governance. Prior to embarking on a big data plan, according to the report, all organizations should create a clear data governance plan. The plan should include how the organization plans to collect, maintain, protect, and curate data assets. "Governance includes guidelines for sharing data, such as how it may be done, when, and with whom," the report reads. "Many organizations fail to address governance early on, but a good governance plan is important because it sets the expectations for the polices, standards, and business rules for using data." A best practice to keep in mind, the authors added, is to set up "special competency centers" within an organization, which is tasked with integrating analytics across the enterprise and participating in decision-making for data-related matters. 

[See also: Data breaches top of mind for IT decision makers.]

2. Data acquisition. New opportunities are emerging from the acquisition of unstructured or semi-structured data, the report says, which come from disparate sources, such as patients, home monitoring systems and other caregivers. "Good data acquisition means ensuring that data are captured in a usable form," the report states. "Best practices include consistent documentation of metadata and classification of data elements." Additionally, taxonomies for demographic fields and medical codes should be used, according to the report. "Finally, for privacy and security, patient records should always be properly deidentified."

3. Data sharing. To maximize the value of their data, an organization needs to collaborate and cultivate relationships that encourage data sharing across provider, plan, and life sciences communities. One new trend in data sharing, the report says, is to "virtualize" selected data from disparate sources or multiple facilities. "Data virtualization is a technique that allows multiple applications and multiple users to access and work with the data at the same time," the report reads. "This makes it easier for people across the organization to perform analysis and reporting." Cloud computing is an option, the report continues, since it allows organizations to migrate large amounts of data onto a temporary platform. "This can be attractive from a cost management perspective because organizations only pay cloud service providers for the computing resources that they use, thus avoiding large capital expenditures for servers."

4. Data standardization. There's still little interoperability in the industry, according to the report, so organizations need to be aware of the need to carefully select and adhere to common data models, so "data from disparate systems can be combined and compared. This is an important benefit of good data governance." According to the report, multiple organizations have pioneered new solutions for standardizing data, which includes translating data from different sources into a standard structure and language, "so that it can be managed and analyzed more easily. This allows researchers to query multiple data sources at once and get more comprehensive results." 

[See also: Data center help to cost CMS $28M.]

5. Data integration. Data integration is the merger of data from internal and external data sources into a single, patient-centric data structure optimized for analysis. "Examples include the merger of patient demographics, conditions, procedures, drugs, and observations from an electronic medical record, along with lab values and diagnostic results," the report reads. For operational or financial analysis, it concluded, administrative claims data is added to the data structure.

6. Analytics. Analytics is the "final component that delivers the payoff," the report says. "Once all of the other building blocks are aligned – from governance to standardization – organizations can apply analytics tools to glean meaningful and actionable insights from their data." Benefits of analytics include improved clinical performance; improved monitoring, predicting, and optimizing of the financial and operational performance of a hospital; and improved information security to anticipate data breaches and losses before they occur. 

Follow Michelle McNickle on Twitter, @Michelle_writes