Status post–often written as ‘S/P’–is medical or clinical shorthand that refers to a state after an intervention. This term is generally used when a patient has had a significant procedure or event, such as a surgery, stroke, or heart attack. For example, if your patient was just released from a surgery where their tonsils were removed, you would see it notated on their chart as, “The patient is S/P tonsillectomy.”
When we extend the definition of status post to health status, we can find even more useful data about a patient or a group of patients. Health status measures how patients perceive their health and is typically noted on a scale of excellent to poor. Reported health status, however, is a predictor of important health outcomes, such as:
These scales and notations can be extremely used during data extraction practices that aid in assessing risk adjustment factor (RAF) scores. For example, RAF scores generally rely on hierarchical condition category (HCC) coding, which communicates patient complexity and creates a holistic picture of the patient. This helps predict healthcare resource utilization while the RAF score uses risk to adjust quality and cost metrics.
When looking at a patient’s chart or records, you may confuse their history and status post. A patient’s history refers to a code that indicates the patient no longer has the condition and is not receiving any treatment at present. However, this information remains relevant because the condition may potentially have a recurrence.
One example may be a patient who tore their anterior cruciate ligament (ACL), which is a common injury for athletes. The patient may have undergone surgery, months of physical therapy, and successfully healed their ACL. Ten years later, they are no longer receiving treatment that targets this specific condition, but the history of this condition should be considered if the patient complains of knee pain.
Status post, in contrast, is the residual or sequelae of a condition or disease that may affect the course of treatment. Unlike history, the condition or disease is still being actively monitored.
The HCC model was originally designed to estimate future healthcare costs for patients; HCC coding relies on ICD-10-CM coding that assigns risk scores to patients. These codes rely on demographic data to assign a risk assessment factor (RAF) score to said patients.
Insurance companies use software and algorithms alongside the RAF score to predict the costs of a patient’s medical care. For example, a patient with numerous chronic conditions or diseases will be expected to have higher healthcare utilization and costs as opposed to a patient with few or none.
When conducting HCC coding, it’s recommended to code to the highest level of specificity so that diagnoses are properly sequenced on the claim. This is where the status post may be referenced. Other factors to include or consider when selecting diagnosis codes are:
By considering these factors while you input codes, you can ensure your diagnoses are sequenced correctly on the claim.
Inferscience offers the best diagnosis suggestions tool for HCC coding, starting with the HCC Assistant. The HCC Assistant is an electronic health record (EHR)-integrated HCC coding platform that analyzes structured and unstructured data in a patient’s chart. This allows providers to find diagnoses that may be overlooked and display HCC code suggestions in real-time in the EHR.
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