HCA 310 Module 5 Coding From Electronic Documentation Example

From Note to Code: Assigning Codes From Electronic Documentation in an Orthopedic Practice

Student Name

Health Care Administration Program, Aspen University

HCA 310: HIPAA and Electronic Health Records

Instructor Name

Month Day, Year

From Note to Code: Assigning Codes From Electronic Documentation in an Orthopedic Practice

Electronic records promise to make coding easier: diagnoses chosen during the visit carry codes automatically, and visit levels can be suggested by software. In practice, codes are only as good as the documentation behind them, and automatic suggestions can be wrong. This paper codes three composite encounters from an orthopedic practice's electronic notes and explains each decision, the tools that helped and the risks that required human review.

How Coding Works in the Record

When the surgeon selects a diagnosis from the problem list, the record attaches a diagnosis code. When he documents a procedure or selects a visit type, the record proposes procedure codes. The coder reviews these against the note before the claim is released, confirming that each code is supported and complete. Diagnosis coding follows the official guidelines, which require coding documented conditions to the highest specificity available (Centers for Medicare & Medicaid Services & National Center for Health Statistics, 2025).

Encounter One: New Patient Visit

Ms. V.'s first visit included a history, examination of both knees, review of standing x-rays taken in the office and a plan for therapy. The coder assigned a diagnosis code for primary osteoarthritis of the right knee, a new patient office visit code at the level supported by the note's medical decision-making, and a code for the two-view x-ray of both knees, since the practice owns the equipment and the surgeon interpreted the films.

Encounter Two: Injection Visit

At a later visit, Ms. V. received a corticosteroid injection into the right knee. The note documented consent, site, technique, the drug and dose. The coder assigned the large joint injection code with a right-side modifier and a supply code for the drug by units. No separate visit code was billed because the visit addressed only the knee and the decision to inject had been made earlier.

Encounter Three: Follow-Up After MRI

After her MRI, Ms. V. returned to discuss results showing a degenerative medial meniscus tear with arthritis. The surgeon reviewed the images, explained options and documented shared decision-making. The coder assigned diagnosis codes for the meniscus tear, specified as degenerative and on the right, and the osteoarthritis, plus an established patient visit code at the level supported by the complexity of the decision.

Summary of Codes

The table summarizes the three encounters.

What Code Suggestions Get Right and Wrong

The record's suggestions saved time, but the coder corrected two. For the first visit, the problem list carried an old diagnosis of unspecified knee pain, which the record added automatically; the coder removed it because the surgeon had documented a definitive diagnosis. For the third visit, the software suggested a higher visit level based on the note's length; the coder chose the level supported by the decision-making described, not by word count.

Cloned Text as a Coding Risk

Notes that copy large blocks from earlier visits can look more complex than the visit actually was. When half or more of a note's text is duplicated, as a large study found was typical across records (Steinkamp et al., 2022), a coder cannot rely on length or completeness to judge what was done at this visit. Coding from copied text risks billing for work not performed, which is a compliance problem.

Why Accuracy Needs Review

Coding is difficult even for experienced clinicians. When orthopedic surgeons and residents coded sample cases, attendings got about three in four right and residents about half, and those with any coding training scored higher (Greenky et al., 2020). Review by a trained coder catches errors that clinicians and software both miss.

A Pre-Billing Review Routine

The practice's coder checks every claim with a procedure plus a visit, every new patient visit and a sample of other visits before release. For each, she confirms that diagnoses are specific and documented, laterality is present, visit levels match the documented decision-making, modifiers are correct and copied text is not the only support. Questions go to the surgeon through a neutral query.

Queries to Clinicians

When documentation is unclear, the coder asks rather than assumes. A query presents the relevant note text and asks an open question, such as asking the surgeon to clarify which knee was examined, without suggesting the answer that pays more. The surgeon's reply becomes an addendum.

Feedback and Education

The coder shares a monthly summary with each surgeon: common corrections, missing laterality and visit level patterns. Brief education sessions address recurring issues. Over time, better documentation reduces corrections and speeds billing.

Compliance

Accurate coding protects the practice. Overcoding risks repayment and penalties, and undercoding loses revenue the practice earned. Coding from the documentation, not from assumptions or software suggestions, is the core compliance rule.

Codes and Quality Reporting

Codes serve more than billing. They feed quality measures, research and public health reporting. An unspecified or wrong diagnosis code can make a practice's quality data inaccurate, affecting payer ratings and payments. Accurate, specific coding therefore supports the practice's reputation as well as its revenue.

Keeping Up With Code Changes

Diagnosis codes are updated every year, and procedure codes change as well. The practice's coder reviews annual updates each fall, checks that the record's code lists are current and shares changes relevant to orthopedics with the surgeons. Outdated codes cause denials that are easy to prevent.

Documentation Tips for Clinicians

The coder's feedback includes simple tips: name the side for every musculoskeletal diagnosis, describe the type of arthritis or tear when known, record the drug and dose for every injection and state the decision made at each visit. These habits make coding faster and more accurate.

Conclusion

Coding from electronic documentation combines the record's suggestions with the coder's judgment. Three orthopedic encounters show how laterality, modifiers, drug units and visit levels depend on what the note actually says. Automatic suggestions and copied text can mislead, so a review routine, neutral queries and feedback to clinicians keep codes accurate and compliant.

References

Centers for Medicare & Medicaid Services & National Center for Health Statistics. (2025). ICD-10-CM official guidelines for coding and reporting FY 2026. https://www.cms.gov/medicare/coding-billing/icd-10-codes

Greenky, M. R., Winters, B. S., Bishop, M. E., McDonald, E. L., Rogero, R. G., Shakked, R. J., Raikin, S. M., Daniel, J. N., & Pedowitz, D. I. (2020). Coding education in residency and in practice improves accuracy of coding in orthopedic surgery. Orthopedics, 43(6), 380-383. https://doi.org/10.3928/01477447-20200827-10

Steinkamp, J., Kantrowitz, J. J., & Airan-Javia, S. (2022). Prevalence and sources of duplicate information in the electronic medical record. JAMA Network Open, 5(9), Article e2233348. https://doi.org/10.1001/jamanetworkopen.2022.33348