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:
- 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.
- 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.
- 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
- 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.
- 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?
- 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.