Factors Associated with Adherence to the HEDIS Quality Measure in Medicaid Patients with Schizophrenia.
Bibliographic record
Abstract
BACKGROUND: Treatment continuity is a major challenge in the long-term management of patients with schizophrenia; poor patient adherence to antipsychotic drugs has been associated with negative clinical outcomes. Long-acting injectable therapies may improve adherence and lessen the risk for psychiatric-related relapse, often leading to rehospitalization and higher healthcare costs. Therefore, understanding the determinants of adherence to antipsychotics is critical in the management of patients with schizophrenia. OBJECTIVE: To assess the impact of baseline patient characteristics on adherence as measured by the Healthcare Effectiveness Data and Information Set (HEDIS) measure of continuity of antipsychotic medications among patients with Medicaid coverage. METHODS: Medicaid healthcare claims data between 2008 and 2011 from 5 states were used to identify patients who were diagnosed with schizophrenia (aged 25-64 years) and received ≥1 antipsychotic prescriptions in baseline year 2010 and in measurement year 2011. The HEDIS continuity of antipsychotic medications (ie, adherence) measure was defined as the proportion of days covered with any antipsychotic medication ≥80% during the measurement year. The 2 cohorts compared paliperidone palmitate with any other antipsychotics, including quetiapine, risperidone, and haloperidol. The baseline-year characteristics were evaluated as potential predictive factors of adherence in the measurement year using multivariate logistic regressions. The regression models incorporated the inverse probability of treatment weights to control for differences in baseline characteristics between the paliperidone palmitate and the other antipsychotics cohort. RESULTS: Among the 12,990 patients who received an antipsychotic during the study period, 48.6% successfully achieved the continuity criteria in the measurement year. After controlling for other covariates, the odds of adherence were improved by adherence at baseline (odds ratio [OR], 9.42; 95% confidence interval [CI], 8.55-10.39). The use of paliperidone palmitate was associated with a 26% increase in the odds of achieving adherence compared with the use of the other antipsychotics studied (OR, 1.26; 95% CI, 1.14-1.39). In addition, female sex (OR, 1.11; 95% CI, 1.01-1.22), age 55 to 64 years (OR, 1.26; 95% CI, 1.09-1.46) versus age 25 to 34 years, Hispanic race (OR, 1.37; 95% CI, 1.05-1.81) versus white race, and an increase of $10,000 in baseline inpatient costs (OR, 1.11; 95% CI, 1.08-1.15) were associated with greater odds of treatment continuity. CONCLUSIONS: In addition to sex, age, and race, the baseline characteristics that were associated with achieving the HEDIS continuity of antipsychotic medication measure included previous-year adherence, inpatient costs, and the use of paliperidone palmitate. These findings offer insight to healthcare plans that cover Medicaid populations on the effects that patient characteristics and treatment types may have on adherence among patients with schizophrenia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".