HIM's Role in Managing Big Data: Turning Data Collected by an EHR into Information

By Steven Bonney

For years, US healthcare facilities' electronic health record (EHR) systems have been collecting and storing exabytes of patient information. A tremendous amount of structured data is being created and given to HIM professionals, and a great deal of action is expected from them.

Structured data is every healthcare organization's most durable asset, and someone must own the responsibility of analyzing it. But information technology (IT) departments are no longer the best choice for enterprise information asset management. Today, HIM professionals are better positioned to lead the Big Data charge.

Big Data and the analytics technologies that leverage it are front and center in healthcare. Healthcare professionals should identify and implement the analytical tools that allow it to best use Big Data, and better utilize the role of HIM professionals for enterprise information asset management.

Big Data: Healthcare's Newest Opportunity

Healthcare organizations with large amounts of unstructured text information are severely handicapped in the new digital world—structured data is a requirement. And while the federal government's "meaningful use" EHR Incentive Program's measures are one driver for structured data, accountable care organizations (ACOs), healthcare reform, and population health also demand it. A recent report by IDC Health Insights states that advanced analytics and data warehouses have become the highest investment priorities for accountable care, since the basis of the ACO program is using and sharing health data to improve quality and efficiency and reduce costs.1

Structured data is well-organized patient information that is coded either by the EHR or by natural language processing (NLP). It is searchable, reportable, actionable, and interoperable, and it powers collaboration, analytics, and reimbursement. Furthermore, structured data accumulated by EHRs, pharmaceutical research, payer systems, and clinical trials provides big insights into patient care, operations, and revenue. What was maintained and managed by HIM professionals for decades is housed in IT systems and data warehouses and is now called Big Data.

Some of the biggest challenges of working with Big Data include traditional data processing applications such as capturing, curating, storing, searching, sharing, housing, transferring, and analyzing the data, according to health experts.

In the Institute for Health Technology Transformation's recent paper, "Transforming Health Care through Big Data," authors recognize micro- and macro-levels of opportunities for Big Data, including decision-making at the "individual patient, group and population levels," public health education, and increased patient education.2 However, for the healthcare industry to derive real benefit from Big Data, it must be structured in a manner that allows knowledge experts to access it. Data analytics is the next stop on healthcare's Big Data journey, as free text analytics is simply not feasible for healthcare professionals with such a large data set.

Data Analytics: Healthcare's Newest Challenge

Once data is amassed, leveraging its power requires expertise, as well as analytical tools. Health data analytics is the practical application of technology, processes, and protocols that help reap the real benefits of Big Data.

When InformationWeek recently conducted a survey of more than 500 business technology professionals, the absence of having Big Data expertise and its prohibitive cost were cited as the top concerns of respondents. Expense of data warehouse appliance platforms, lack of clarity on how Big Data analytics would create business opportunities, scarcity of analytical tools, and concerns over data accuracy rounded out the top five concerns.3 Often referred to as "business intelligence software," analytics tools may be more important than the underlying data. If one cannot access the data there is no benefit in having it.

The first step is to conduct an honest assessment of the current state of health data. The assessment should focus on identifying gaps in skills, tools, and processes.

According to an article by Joe Crandall with Greencastle Associates Consulting, several important questions must be asked during an assessment:4

  • Does my organization have a culture of sharing data?
  • Do we have a good data governance program in place?
  • Do we have data integrity issues?
  • Do our people know how to use the information we can provide?

Use the "crawl-walk-run" approach by starting with a small, sustainable Big Data project that can be scaled intelligently over time, Crandall recommends. Show results and then expand the program. Organizations can't go from a "data-averse culture to a data-driven culture overnight," Crandall advises.

One HIM-specific example of analyzing Big Data would be to use analytics tools to identify potential high risk patients in key areas, such as heart failure, pneumonia, and stroke. Using analytics, case managers could, theoretically, review core measure performance proactively versus retrospectively, improve clinical outcomes, bolster documentation, and streamline core measure reporting.

Furthermore, hospitals should not allow the hype of Big Data to outpace the practical value they can derive from it. There remains a hodge-podge of Big Data offerings in the marketplace. Industry associations and events are beginning to form around Big Data and data analytics in healthcare. The Healthcare Information and Management Systems Society (HIMSS) recently held a Big Data and Healthcare Analytics Forum, and former AHIMA CEO Linda L. Kloss, RHIA, CAE, principal of Kloss Strategic Advisors, chairs the annual Healthcare Analytics Symposium and Expo. As mentioned above, there is much work to do and HIM professionals have the analytical talents and skills to do it.

Bridging the Structured Data Gap in HIM

There are specific areas of structured data management that impact HIM, including reports sent from transcription systems to EHRs, EHR-based clinical documentation, and alternative technologies to bridge the gap between narrative, text-based information, and structured data. Specific impacts and considerations are listed below.

Meaningful Use Stage 2

Accountable Care Organizations

Providers must exchange data with providers outside their network—not faxes or free text sent from transcription systems to EHRs via HL7 messages.

Providers must measure efficacy and costs of treatment plans to accurately share reimbursement dollars with one another.

Structured data is well-formed and codified using clinical concepts containing ICD-9, ICD-10, CPT-4, LOINC, SNOMED CT, and other codes.

EHR entry provides structured data, but many providers are hesitant to use it for patient documentation (notes, H&Ps, discharge summaries, etc.).

It is not possible to perform clinical analytics on unstructured text.

Alternative technologies, such as text analytics, bridge the data void.

Text analytics converts unstructured text into structured data.

Roles for HIM in Big Data

Business intelligence implementations are lengthy. They demand realistic expectations and a focus on people, rather than technology, for lasting success. People, not systems, are at the center of data analytics. While many healthcare executives think of analytics as the CIO's problem, they're actually all healthcare professionals' problem.

Crandall writes that it's the maturity of those working with the data that determines the success of an analytics program, not the tools or the technology platform. HIM professionals' first role is to ensure that dictated and transcribed words are turned into actionable data through the use of natural language processing (NLP) technology so that data elements such as problems, medications, and allergies exist as data. Once converted to data, text-based information housed in HIM departments is combined with the organization's other electronic information—successfully turning words into action.

Subsequent HIM Big Data roles include:

  • Data analytics specialists: These professionals serve as data champions and scientists. They are skilled at viewing raw data, seeing patterns, and communicating their recommendations for corrective action to chief analytics officers.
  • Chief analytics officers: These executive-level professionals make business decisions based on analytics and drive organizational action.
  • Information/data governance directors: Perfectly suited for HIM professionals, these directors scrutinize data integrity, understand enterprise-wide data flow, and manage interdepartmental relationships.
  • Data managers: An IT-focused career, data managers work in conjunction with information and data governance directors to ensure information integrity at the database and system level.

Whether or not HIM professionals change job titles, key steps must be taken to enter the Big Data and health data analytics arena. Executive teams focused on creating data-driven cultures require a new kind of HIM director, one that uses data analysis to create efficiencies and expedite change.

Using Data Strategically

Healthcare organizations are sitting on massive reams of electronic papyrus in the form of structured data. In a few short years, organizations will compete to effectively and affordably manage patient care and identify patients who need preventive care. They must leverage their data to gain a competitive edge in healthcare.

Analytics capability leads to organizational improvements and, ultimately, advances in the healthcare industry. However, HIM skills are necessary to understand and analyze every byte of Big Data along the way. The implementation of analytics is a journey, and HIM must be involved.


  1. Burghard, Cynthia. "Business Strategy: Analytics Leads Accountable Care Investment Priority." IDC Health Insights. March 2013. http://www.idc-hi.com/getdoc.jsp?containerId=HI239735.
  2. Institute for Health Technology Transformation. "Transforming Health Care through Big Data: Strategies for leveraging big data in the health care industry." 2013. http://ihealthtran.com/big_data_in_healthcare.html.
  3. Henschen, Douglas. "Research: 2013 Analytics & Info Management Trends." InformationWeek. November 16, 2012. http://reports.informationweek.com/abstract/166/9298/.
  4. Crandall, Joe. "Readers Write: Health Data Analytics Provides Great Value Over Big Data." HIS Talk. June 26, 2013. http://histalk2.com/2013/06/26/readers-write-health-data-analytics-provides-greater-value-over-big-data/.

Steve Bonney (steve@bayscribe.com) is vice president, business development and strategy at BayScribe, based in Naples, FL.

Article citation:
Bonney, Steven. "HIM's Role in Managing Big Data: Turning Data Collected by an EHR into Information" Journal of AHIMA 84, no.9 (September 2013): 62-64.