With the expansion of electronic health records, it’s easier to collect and analyze big data than ever before. In today’s digital age, data is also readily available online. This provides a whole host of opportunities for writers. With a little time and effort spent researching your topic, data can essentially take an average article and turn it into a compelling and persuasive piece of content.

Data can be used most effectively for these three purposes:

  1. Support an opinion or statement. Statistical data (e.g., studies, polls, surveys) is most helpful. Weave this information throughout your content and link to the original study, when possible.
  1. Resonate with a reader more personally, inviting him or her to take action. Anecdotal data (i.e., based on an individual’s personal observations or experiences) works best. Consider opening your content with a personal story/experience to grab the reader’s attention.
  1. Indirectly market your products or services. Both statistical and anecdotal data (e.g., testimonials) are helpful. For example, when promoting denial management outsourcing, find a study that captures how much hospitals can save when using a third-party vendor. How much do hospitals lose when managing denials internally simply because they can’t keep up?

Where to find data

Data can be gleaned from a variety of sources, including:

  • Governmental agencies (e.g., CMS or CDC)
  • Professional associations (e.g., AHIMA, HFMA, or AAPC)
  • Publishing companies
  • Non-competing vendors
  • Your company’s own internal research (e.g., customer surveys or polls)

Tips for using data

  1. Always question the source of the data. Is it biased in any way? Consider a pharmaceutical company sponsoring a study about the efficacy of its own drug. This study may be biased. Look for other evidence that can bolster support for the study.
  1. Question the method of the study. Consider a study about medical necessity denials in ICD-10. What types of hospitals were polled and over what time period? Critical access hospitals? Large teaching facilities? Was the study conducted immediately post-go-live or six month post-go live when most payers had actually begun to adjudicate ICD-10 claims?
  1. Drill down into the study participants. When referring to a study about the quality of ICD-10 documentation, who actually provided the input? Was it the coder/biller? A physician? The CEO? A coder/biller would have greater insight into this topic and therefore provide a more accurate response. If this information isn’t available, it becomes important to raise these questions when referring to the data in your content.