The Implementation of a Clinically Based Electronic Medical Record in a Division I Athletic Medicine Clinic: A Clinical Practice Report
Bibliographic record
Abstract
Clinical Problem: Implementation and sustainability of a clinical electronic medical record (EMR) allowing for multiple billable encounters in an athletic medicine practice.Environment: Division-I collegiate athletics clinic.Variables: For ATs to complete billable documentation clinicians must: use an electronic health record (EHR), understand and appropriately use Current Procedural Terminology (CPT) and International Classification of Diseases version 10 (ICD-10) codes, understand patient encounter types, Relative Value Units (RVUs), and the role of a service provider related to incident-to capability.Strategy: Proposed and implemented the use of a clinic based EMR which communicated within the entire medical system with all providers. Proposed and implemented structural changes within the athletic medicine clinic to support athletic trainer billing in a traditional clinical atmosphere. Implementation resulted in the ability to bill incident-to but posed a challenge in compliance of adopting a new documentation strategy.Strategy: Proposed and implemented the use of a clinic based EMR which communicated within the entire medical system with all providers. Proposed and implemented structural changes within the athletic medicine clinic to support athletic trainer billing in a traditional clinical atmosphere. Implementation resulted in the ability to bill incident-to but posed a challenge in compliance of adopting a new documentation strategy.Strategy: Proposed and implemented the use of a clinic based EMR which communicated within the entire medical system with all providers. Proposed and implemented structural changes within the athletic medicine clinic to support athletic trainer billing in a traditional clinical atmosphere. Implementation resulted in the ability to bill incident-to but posed a challenge in compliance of adopting a new documentation strategy.Findings: ATs were able to be reimbursed by some insurance companies. The use of the clinical EMR resulted in athletic trainers billing 13 CPT codes and insurance reimbursement as high as $38,000 per fiscal year in the 5 years since implementation.Outcome: Documentation in a clinical-based record has standardized communication between members of the athletic medicine team, generated revenue, and is used as a tool to measure productivity and demonstrate the fiscal value of the athletic trainer.Lessons Learned: ATs must buy-in to and understand the need to shift from an "athletic trainer specific EMR" to a clinical based EMR. Although the quantity of documentation does not change, the quality and structure of the notes must meet CMS guidelines. This significant change requires policy updates and demands that ATs in this system re-structure documentation practices. Creating a culture of growth is critical, allowing others to see that while this method is different, ATs can complete this level of documentation. (298 words).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.101 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".