Treatment patterns and hospitalizations following rejection, reversal, or payment of the initial once-monthly paliperidone palmitate long-acting injectable antipsychotic claim among patients with schizophrenia or schizoaffective disorder.

BACKGROUND: Once-monthly paliperidone palmitate (PP1M) is a long-acting injectable antipsychotic approved for the treatment of schizophrenia and schizoaffective disorder (SCA) in adults. OBJECTIVE: To assess treatment patterns and schizophrenia/SCA-related hospitalization following payer rejection, patient reversal, or payment of an initial PP1M claim. METHODS: This was a retrospective cohort study using the IQVIA Formulary Impact Analyzer database linked to the Medical Claims, Hospital Charge Detail Master, and Experian consumer databases. Patients with schizophrenia/SCA and ≥1 PP1M pharmacy claim from January 1, 2018, to February 28, 2022, were identified and stratified into 3 cohorts based on the transaction status of the initial PP1M claim (index date): rejected (payer not approved), reversed (payer approved, patient abandoned), and paid (payer approved, patient filled). Patient characteristics during the 12 months before the index date, subsequent treatment patterns, and schizophrenia/SCA-related hospitalization for patients with >6 months of follow-up were assessed by cohort. RESULTS: The rejected, reversed, and paid cohorts included 1,260, 1,046, and 1,686 patients, respectively. Across these cohorts, the mean ages ranged between 39.2 and 44.5 years; more than half were male (50.8%-51.6%) and White (50.6%-58.3%); 19.8%-24.6% of patients had a Quan-Charlson Comorbidity Index score of ≥2. Rates of prior atypical oral and long-acting injectable antipsychotic use ranged between 76.4%-80.3% and 7.8%-12.7%, respectively. Among patients with ≥6 months of follow-up, 52.2% in the rejected and 53.1% in the reversed cohorts had a subsequent paid PP1M claim during the study period; the median (quartile 1-quartile 3) time to the first paid PP1M claim was 22 (5-74) days for rejection and 11 (1-41) days for reversal. In the rejected and reversed cohorts, 10.2% (n = 111) and 9.8% (n = 90) of patients, respectively, did not receive any paid claim for an antipsychotic after the initial PP1M rejection/reversal. The prevalence of schizophrenia/SCA-related hospitalization during follow-up was similar between patients with a paid (7.4%) and rejected PP1M claim (7.0%; P = 0.689) but higher among patients with a reversed claim (10.8%; P = 0.004). After adjusting for confounders, patients in the reversed cohort were 39% more likely to have a schizophrenia/SCA-related hospitalization than those in the paid cohort (odds ratio = 1.39; 95% CI = 1.03-1.87). CONCLUSIONS: Payer rejection and patient reversal of initial PP1M claims is a form of primary nonadherence and may influence patient trajectory. Data from this study suggest that patient reversal of PP1M may lead to an increased risk of schizophrenia/SCA-related hospitalizations, potentially caused by missed or delayed treatment. Policy initiatives that remove barriers to primary adherence or fulfillment may help improve patients' clinical outcomes.

Adherence, health care utilization, and costs between long-acting injectable and oral antipsychotic medications in South Carolina Medicaid beneficiaries with schizophrenia.

BACKGROUND: Schizophrenia and schizoaffective disorder require long-term antipsychotic treatment with antipsychotic medications, but poor medication adherence can lead to increased health care utilization and costs. Long-acting injectable antipsychotics (LAIs) offer potential therapeutic advantages in that they require less frequent dosing and improved medication adherence. South Carolina has the highest adoption of LAIs among US states, making it an ideal population for comparing the effectiveness of LAIs vs oral antipsychotics (OAPs) in treating schizophrenia or schizoaffective disorder. OBJECTIVE: To evaluate the effect of LAIs compared with OAPs on medication adherence, health care resource utilization, and costs among South Carolina Medicaid beneficiaries with schizophrenia or schizoaffective disorder. METHODS: South Carolina Medicaid beneficiaries with at least 1 claim for an LAI or OAP between January 1, 2015, and December 31, 2018, aged 18 to 65, with at least 2 claims with diagnoses of schizophrenia or schizoaffective disorder were included. Propensity scores (PSs) were calculated using logistic regression adjusting for confounders and predictors of the outcome. We estimated the "average treatment effect on the treated" by employing PS-weighted t-tests and chi-square tests. RESULTS: A total of 3,531 patients met the inclusion criteria, with 1,537 (44.5%) treated with LAIs and 1,994 (56.5%) treated with OAPs. In PS-weighted analyses, the LAI cohort had a greater proportion of days covered than the OAP cohort with a 365-day fixed denominator (69% vs 64%; P < 0.0001), higher medication possession ratio with a variable denominator while on therapy (85% vs 80%; P < 0.0001), and higher persistence (82% vs 64%; P < 0.0001). The average number of inpatient visits and emergency department visits did not significantly differ between cohorts (0.28 hospitalizations, P = 0.90; 3.68 vs 2.96 emergency department visits, P = 0.19). The number of outpatient visits, including visits for medication administration, were greater in the LAI cohort (23.1 [SD 24.2]) vs OAP (16.9 [SD 21.2]; P < 0.0001); however, including the costs for medication administration visits, outpatient costs (per member) were approximately $2,500 lower in the LAI cohort (P < 0.0001). The number of pharmacy visits was greater in the OAP cohort (LAI 21.0 [SD 17.0] vs OAP 23.0 [SD 15.0]; P = 0.006). All-cause total costs were greater in the LAI cohort ($26,025 [SD $29,909]) vs the OAP cohort ($17,291 [SD $25,261]; P < 0.0001) and were driven by the difference in pharmaceutical costs (LAI $15,273 [SD $16,183] vs OAP $4,696 [SD $10,371]; P < 0.0001). CONCLUSIONS: Among South Carolina Medicaid beneficiaries, treatment with LAIs for schizophrenia or schizoaffective disorder was associated with greater medication adherence rates. Patients using LAIs had higher drug costs and total costs, but lower outpatient and total nondrug costs compared with those using OAPs.

Low-grade mucoepidermoid carcinoma mimicking benign cystic lesions in the salivary gland: A diagnostic dilemma.

Mucoepidermoid carcinoma (MEC) is a common malignancy arising in the parotid gland. The diagnosis of MEC is typically based on its morphological features alone, characteristically containing mucocytes, intermediate cells and epidermoid cells. However, when cystic degeneration is diffuse, it is challenging to distinguish MEC from other benign cystic tumors. This is a case report of a 58-year-old Caucasian man who presented with a parotid mass. H&E sections of the mass reveal multiloculated cysts lined by bland-looking epithelium with only rare papillary architectures. The papillary proliferation contains mucocytes, and epidermoid cells highlighted by the p63 immunohistochemistry study. The diagnosis was confirmed by FISH result of positive MAML2 (11q21) rearrangement. Patient underwent parotidectomy and is disease-free 6 months post-surgery. MEC with cystic degeneration is a common diagnostic pitfall which can mimic many benign lesions in the salivary gland. We present a rare case with MEC with extensive cystic change, its molecular and pathologic findings and review the diagnostic features of MEC, its benign mimickers and useful tools for distinguishing these entities.

Post Hospitalization Clinical Quality Outcomes Among US Patients with Schizophrenia Treated with a Long-Acting Injectable or Switched to a New Oral Antipsychotic: A Retrospective Cohort Study.

BACKGROUND:  Adherence to antipsychotic medication and care discontinuity remain a challenge to healthcare practitioners providing care to patients with schizophrenia. OBJECTIVE: This study used real-world data from a US hospital-based, all-payer database to examine clinical quality measures among patients with schizophrenia initiated on a long-acting injectable (LAI) or switched to a new oral antipsychotic medication (OAP) following a hospitalization. METHODS: A retrospective cohort study using the PINC AI™ Healthcare Database compared two cohorts of patients with schizophrenia on post-index hospitalization clinical quality and care continuity endpoints. Patients initiated on an LAI (n = 7292) or switched to a new OAP (n = 31,956) during an index hospitalization between April 2017 and April 2020 were included. Propensity score weighting addressed differences in patient, hospital, and clinical characteristics between the two cohorts. RESULTS: Patients who initiated an LAI experienced significantly greater adjusted 30-day antipsychotic medication continuation to index therapy, higher rate of 30-day outpatient follow-up care, longer mean time to discontinuation of index therapy, and lower risk of discontinuing their index treatment compared to patients who switched to a new OAP (all p values < 0.001). Probability of 30-day antipsychotic medication continuation was significantly higher for LAI initiators than for patients who switched to a new OAP, even after controlling for patient, clinical, and hospital characteristics (adjusted odds ratio = 1.2, 95% CI 1.1-1.3, p < 0.001). CONCLUSION: Patients who initiated an LAI in a hospital setting experienced better clinical quality and care continuity outcomes compared to patients who were switched to a new OAP. These findings may be useful in identifying solutions to help improve the quality of medication management post-hospital discharge among patients with schizophrenia.

Optimizing Computer-Aided Diagnosis with Cost-Aware Deep Learning Models.

Classical machine learning and deep learning models for Computer-Aided Diagnosis (CAD) commonly focus on overall classification performance, treating misclassification errors (false negatives and false positives) equally during training. This uniform treatment overlooks the distinct costs associated with each type of error, leading to suboptimal decision-making, particularly in the medical domain where it is important to improve the prediction sensitivity without significantly compromising overall accuracy. This study introduces a novel deep learning-based CAD system that incorporates a cost-sensitive parameter into the activation function. By applying our methodologies to two medical imaging datasets, our proposed study shows statistically significant increases of 3.84% and 5.4% in sensitivity while maintaining overall accuracy for Lung Image Database Consortium (LIDC) and Breast Cancer Histological Database (BreakHis), respectively. Our findings underscore the significance of integrating cost-sensitive parameters into future CAD systems to optimize performance and ultimately reduce costs and improve patient outcomes.