Impact of a value-based insurance design for physical therapy to treat back pain on care utilization and cost
Bibliographic record
Abstract
OBJECTIVE: To assess the impact of a value-based insurance design providing enhanced access to physical therapy (PT) for treatment of back pain on treatment patterns and cost of care. STUDY DESIGN: A retrospective analysis of claims data obtained from Geisinger Health Plan (GHP). In April 2013, GHP began offering "PT bundle" - i.e., a bundle of up to five PT visits for a single one-time copay that can be renewed for another bundle of five PT visits - for its employer-based plan members with back pain. METHODS: A cohort of GHP members who were preauthorized for the PT bundle were compared against a contemporaneous cohort of GHP members who were preauthorized for PT under the standard per-visit copay arrangement between January 2013 and October 2014. RESULTS: Among the PT bundle cohort, the PT visit rate during the first 9 months since the PT preauthorization date had dramatically increased and then gradually decreased in subsequent months. The PT bundle was also associated with 29%-35% short-term reductions in emergency department visits and with 12%-20% reductions in primary care visits after 6 months. No significant impact on hospitalization or cost was observed. CONCLUSION: Implementation of the PT bundle appears to have led to a change in the treatment pattern of back pain that is more consistent with the recommended guidelines to use more conservative management such as PT as the first-line treatment for back pain.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, not a consensus.
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".