Procedural Prescription Denials and Risk of Acute Care Utilization and Spending Among Medicaid Patients
Bibliographic record
Abstract
Importance: Rising prescription medication costs under Medicaid have led to increased procedural prescription denials by health plans. The effect of unresolved denials on chronic condition exacerbation and subsequent acute care utilization remains unclear. Objective: To examine whether procedural prescription denials are associated with increased net spending through downstream acute care utilization among Medicaid patients not obtaining prescribed medication following a denial. Design, Setting, and Participants: This cross-sectional study used Medicaid claims data from 2022 to 2023 for patients at inpatient, outpatient, and pharmacy sites of care across 2 states (Virginia and Washington) and 2 independent health plans. Patients with at least 1 prescription denial in the study period (January 1 through July 31, 2023) were matched to those without denials in a given medication class, based on demographics, health plan data, chronic condition history, and health care utilization. Rates of and spending for physiologically related acute care visits in the 60 days following a medication fill or denial were compared for the study period. Main Outcomes and Measures: The main outcomes were all-cause acute care utilization and total medical spending (in 2023 US dollars per member per year [PMPY]) for principal diagnoses physiologically related to each medication class, in the 60 days following a medication fill or denial. Sensitivity analyses were performed to check for spurious associations or unmeasured confounders. Results: The 19 725 patients in this study had a median age of 41 (IQR, 29-55) years, and most (60.7%) were female. Patients had a mean (SD) of 3.3 (16.1) comorbidities, 1.0 (2.6) all-cause acute care visits, and 5.6 (7.8) primary care visits during the baseline period. Patients experiencing specific procedural prescription denials had a higher risk of physiologically related emergency department visits and hospitalizations compared with those without a denial in the subsequent 60 days (adjusted odds ratio, 1.40 [95% CI, 1.03-1.88] minimum vs 1.75 [95% CI, 1.39-2.20] maximum for exposure and control groups across the 7 medication classes with significant differences). Denials in 6 medication classes were associated with net total medical spending increases, ranging from $624 (95% CI, $435-$813) to $3016 (95% CI, $1483-$4550) in additional expense PMPY after accounting for both prescription and medical costs attributed to denials. Conclusions and Relevance: The findings of this cross-sectional study suggest that although procedural prescription denials aimed to curb immediate drug costs, some denials prompted heightened acute care utilization and costs that outweighed the short-term prescription budget savings. Health plans should incorporate this potential unintended consequence when shaping prescription coverage policies. Future research should systematically review all medication classes across plans nationally.
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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 | 0.000 | 0.000 |
| 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".