Why One Doesn’t Code From Lab Reports

Why One Doesn’t Code From Lab Reports

by Chris Richards, RHIA, CCS

Normal reference ranges for common laboratory tests are readily available. While it seems reasonable, logical, and simple to look at lab values and draw clinical conclusions regarding a patient’s health status, it is important to appreciate that “normal” for one patient may not be normal for another. Because of natural variations, it has never been deemed appropriate for coders to infer clinical diagnoses based on these values.

The Official Coding Guideline 3.B. instructs us: “do not code abnormal lab findings unless the provider indicates their clinical significance.” The relevance of such test results need to be confirmed and documented by a physician in the medical record, who then may or may not assign or associate a diagnosis with the finding.

Here are some examples where external and other factors play an important role in assessing whether a given lab value has reliable meaning. (These are examples taken from the Laboratory Test Handbook, published by Lexicomp.)

  • Definition of normal – Normal reference ranges can vary from one institution to another.
  • Cut off points – Many tests do not have sharp cutoff points between normal and abnormal.
  • Medications – Medications taken by a patient have the potential to significantly affect lab results.
  • Pregnancy – Pregnancy can affect many electrolyte and hormonal findings.
  • Athletes – Athletes are apt to have elevation in BUN and LCH, as well as slow pulse rates.
  • Physical exercise – Physical exercise can create abnormally high levels of troponin, CK, creatinine, potassium, uric acid, bilirubin and white blood cell counts.
  • Patient positioning – Positioning is reported to change the normal results for a number of tests including total protein, albumin, calcium, H&H, ALT, and iron. Levels of these substances have been found to be higher in an upright position than in a reclining position.
  • Patient body weight – Some laboratory computer software makes no allowance for body weight. Creatinine clearance and blood volumes require this data. Males have body weight associations for creatinine, protein, hemoglobin and AST, while females have an inverse relationship between body weight and calcium.
  • Urinalysis – The significance of a few red cells in urine depends on the clinical setting. Voided versus catherterized urine, sex, and menstruation all affect the urinalysis results. Therefore some test cannot be classified as “normal” or “abnormal” by computer, but only by the physician caring for that particular patient.
  • Meals – Fasting versus nonfasting tests can also influence test results.
  • Impact of venipuncture – Hemolysis from hemolytic anemia or venipuncture can cause increases in LDH, bilirubin, ALT, GGT, AST, potassium, magnesium and alkaline phosphatase. Hemolysis from venipuncture may be associated with release of thromoplastins and may invalidate the results of coagulation studies.
  • Circadian rhythms – Circadian rhythms may have implications for many lab tests. Among the variations cited is the rate of drug excretion as well as cyclical responses to therapy. For example, triglycerides are higher in the afternoon as is phosphate, BUN and hematocrit.
  • Genetic variations – Genetic variations exist in how individuals metabolize drugs and, therefore, major variations in lab test values may occur.
  • Measurement versus monitoring – Evaluation of results of a given test over time may be more meaningful than a single result.
  • Finally – Other variables may include sex, stress, menstrual cycle, age, menopause and even altitude.

 

About the Author

Chris Richards, RHIA, CCS
Chris joined Barry Libman Inc. as a Senior Associate in 2014 after 27 years with Masspro, the Massachusetts Quality Improvement Organization (QIO). Chris’s areas of expertise include health information administration, case management, quality improvement, hospital payment oversight, and documentation education initiatives. He has a comprehensive understanding of the Federal Medicare program rules and regulations, as well as extensive experience ensuring that clinical coding and DRG assignment result in accurate provider reimbursement. A graduate of Hobart College, he received a postgraduate Bachelor of Science in Health Information Administration from Northeastern University.

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