The Seven Deadly Data Sins – and Why You Should Care

What are your data trying to tell you?

In this time of implementation of electronic health records, rapid data transfer and emergence of pay-for-performance programs, understanding your data has never been more critical. But if your data aren’t clean and complete, they won’t deliver the insight you need to be successful in the current health care environment.

I work with a number of health care organizations that are implementing our Clinical PerformerSM product, both in initial implementation and on an ongoing basis. (The product integrates financial, operational, satisfaction and quality information for a complete picture of performance by hospital, department, clinical category, physician and physician group.) During the initial implementation, many clients are challenged to clean up their data files, addressing documentation, coding and reporting errors that must be overcome in order for them to get the best use of the product. The rewards for such efforts are always worth it.

I received an email from one client who said, “You forced me to clean up my master files.” While this IT professional may have been frustrated with the rounds of sending and correcting data files that are needed to begin work with Clinical Performer, I was happy to see that she realized that the Clinical Performer team was alerting her internal team about questionable data elements in its systems, and advising correction of those issues.

If you think about it, data validation is actually the top performance improvement opportunity in many hospitals and health systems. Don’t believe me? See if you recognize any of these events occurring while reviewing hospital data:

  • Cases assigned to an incorrect physician.
  • Major surgical procedures attributed to a hospitalist or family practice physician.
  • Seeing procedures coded in the medical record, but absent the identity of the physician or professional who performed the procedure.
  • Diagnosis codes with present-on-admission flags missing.
  • Charge master descriptions that have the same charge description number, but the descriptions are different.
  • Charge master items described as “miscellaneous, or DrX implant.”
  • Cases that have to be rebilled following the discovery of a test or lab result missing at the time of abstraction.
Some of these issues sound trivial; however, the ramifications are huge and range from the inability of a team to use data in decision-making, all the way to legal liability for fraudulent claim submissions. Think about the consequences of these seven deadly, but commonplace, data sins:

  • Cases assigned to the wrong physician reach a payer’s desk and do not match the bill from the physician who actually performed the procedure. Do you believe that payers do not compare the hospital and physician bills for their covered populations? If the claims were incorrect frequently enough, would it affect the next set of contract negotiations?
  • A procedure is attributed to a specialist who is not trained or qualified to perform the procedure, nor has been awarded those privileges. What does that say about your ongoing performance evaluations and credentialing/privileging responsibilities?
  • A missing present-on-admission flag for a diagnosis code matching the Centers for Medicare and Medicaid Services’ hospital-acquired condition (HAC) list puts hospital reimbursement in jeopardy. It also would cause someone to ask about the original assessment of patients in your facility and the possibility that inadequate evaluation may have occurred. Worse yet, physicians and staff are labeled by public web sites that monitor hospital performance as having a higher-than-expected rate of HACSs. To add insult to injury, a hospital’s high number of HACs may be related to a decision to include present-on-admission flags only on those charts where payers require it.
  • Charge master items that are listed on a patient bill by their hospital assigned number and title that do not adequately describe the actual item used or, worse, describe another item with that same hospital-assigned number. What if that item should never be used in this specific type of hospitalization? How often do you think these bills will be questioned? How bad would it be if an implant were miscoded in the charge master and the patient with the implant did not get notified if the implant were recalled?
  • Hospital teams reviewing billing data to understand their processes and compliance with pathways and order sets have to decipher that $2,500 item on the bill with the title “Misc.” Incorrect practice patterns could be attributed to physicians in error and ruin the collaborative relationship hospitals have to nurture with their docs.
No one likes to fail validation reports and have their data rejected at the warehouse. However, what kind of business partner handles your most critical information without meticulous scrutiny?

Whenever I begin to work with a hospital, the first discussion centers around the “data cleansing” it is about to embark on. I owe my hospital clients the benefit of all the knowledge and experience Press Ganey provides, not only about their financial and clinical opportunities, but also about the need to diligently review and validate data.

Useful reports cannot be created in the absence of credible data. I want to assure hospitals that wherever their data are electronically transmitted in the electronic-medical-record world, the data are telling the truth.