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Patients with chronic obstructive pulmonary disease (COPD) need long-term use of COPD medications to manage their conditions. However, COPD patients enrolling in Medicare Advantage plans (MAPs) may enter the coverage gap, resulting in increasing financial burden. The purpose of this study was to identify characteristics of COPD patients who enter the Medicare coverage gap and the factors associated with time to enter the coverage gap. A retrospective cross-sectional study was conducted using a Texas MAP database between 2011 and 2014. Patients aged ≥65 years with a diagnosis of COPD and taking medication to treat COPD were included. Patients were divided into mainly 2 groups: "no gap" versus "gap," based on their pharmacy outpatient spending. Within "gap," patients were further categorized into "coverage gap" and gap with "catastrophic coverage." Multinomial logistic regression was conducted to identify characteristics associated with reaching "coverage gap" and "catastrophic coverage." Cox proportional hazards were performed to evaluate factors associated with time to reaching "coverage gap." A total of 3142 COPD patients were identified: "no gap" (79%) and "gap" (21%). Among patients in "gap," 51% fell into "catastrophic coverage." Age, low-income subsidy (LIS) level, and Centers for MedicareMedicaid (CMS) risk score were significant factors associated with entering both "coverage gap" and "catastrophic coverage." Younger age, greater CMS risk score, and higher LIS benefit were associated with a higher hazard ratio of reaching the coverage gap. These characteristics may assist health maintenance organizations to identify beneficiaries who can potentially be provided with services with or without counseling on drug utilization.

Objectives: There is great amount of evidence available indicating high emotional distress during the COVID19 pandemic. The goal of this study was to evaluate the emotional well-being of pharmacy students several months from the COVID19 pandemic in the US. Methods: A retrospective study was designed to evaluate the effect of pandemic on second, third- and fourth-year Doctor of Pharmacy (PharmD) students. Data was obtained from an online survey conducted once in November 2019 and once in November 2020. The survey consisted of the Counseling Center Assessment of Psychological Symptoms-62 (CCAPS-62) questionnaire. Subscales from CCAPS-62 considered in this study included depression, general anxiety (GA), hostility and substance abuse (SA). Raw scores for each subscale was categorized into healthy and clinical. A logistic regression model, adjusted for gender, race, class and physical activity was used to find any association between the pandemic and the probability of each subscale. Results: Overall, 305 and 159 students participated in 2019 and 2020 respectively. Majority of students were female and Asian. The results of adjusted regression model did not show any significant changes in the probability of depression, GA and SA between 2019 and 2020. However, a decrease in hostility was observed (OR=0.66 95%CI=0.43-o.997) in 2020. Conclusions: Contrary to previous studies, our study did not indicate increases in depression, general anxiety, hostility and substance abuse during the pandemic. The difference can be explained by the difference in the design of studies and the different data analysis. Previous studies were mostly cross-sectional and did not have a chance to evaluate the emotional state of the participants after controlling for other factors.

Low adherence to oral antidiabetic drugs (OADs) in the Medicare population can greatly reduce Centers for MedicareMedicaid Services (CMS) star ratings for managed care organizations (MCOs).To develop and validate a risk assessment tool (Prescription Medication Adherence Prediction Tool for Diabetes Medications [RxAPT-D]) to predict nonadherence to OADs using Medicare claims data.In this retrospective observational study, claims data for members enrolled in a Medicare Advantage Prescription Drug (MA-PD) program in Houston, Texas, were used. Data from 2012 (baseline period) were used to identify key variables to predict adherence in 2013 (follow-up period). Members aged 65 years and older with a diabetes diagnosis, at least 1 prescription for OADs (biguanides, sulfonylureas, thiazolidinediones, dipeptidyl peptidase-4 inhibitors, or meglitinides), and continuously enrolled for both years were included in the study. Patients with insulin prescriptions were excluded from the cohort. The study outcome, nonadherence in 2013, was defined as proportion of days covered (PDC)80%. Multivariable logistic models using 200 bootstrap replications (with replacement) identified factors associated with nonadherence. The final model was tested for discrimination and calibration statistics and internally validated using 10-fold cross-validation. Using weighted beta coefficients of the predictors, the RxAPT-D was created to stratify nonadherence risk and was tested for sensitivity, specificity, positive prediction value, and negative prediction value. The predictive ability of the tool was compared with that of past PDC values using net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices.Data from 7,028 MA-PD members were used for tool development. Seven predictors (age, total OAD refills, total OAD classes filled, days supply of last filled OAD, pill burden, coverage of last filled OAD, and past adherence) statistically significant in ≥ 50% of the bootstrapped samples were identified from the logistic models. The final model demonstrated good discrimination (c-statistics = 0.75) and calibration (Hosmer-Lemeshow goodness-of-fit P0.05) statistics, with good internal validity (area under the curve = 0.73). The RxAPT-D demonstrated adequate sensitivity statistics: sensitivity = 0.73, specificity = 0.63, positive prediction value = 0.74, and negative prediction value = 0.62. Compared with use of past adherence measures, the RxAPT-D had higher prediction ability, relative IDI = 2.09, and user defined NRI = 0.16 with 24% events correctly reclassified.The RxAPT is an effective tool to identify patients who are likely to become nonadherent to OADs in the follow-up year. Pharmacists in MCOs can use this tool to identify patients expected to be nonadherent to OADs and develop targeted intervention programs to assist in improving MCO CMS star ratings.This study received unrestricted partial funding from the Pharmaceutical Research and Manufacturers of America (PhRMA) Foundation Adherence Research Starter Award. Serna is employed by Cigna-HealthSpring. Mhatre is now employed with Genentech. The authors report no other potential conflicts of interest. The material in this study is based on work supported (or supported in part) by the Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, and the Center for Innovations in Quality, Effectiveness and Safety (CIN 13-413). The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the U.S. government. The abstract for this article was presented at the Academy of Managed Care Pharmacy's 28th Annual MeetingExpo, April 2016, San Francisco, California, with the title "Development and Validation of a Tool to Predict Nonadherence to Oral Antidiabetic Drugs in Medicare Beneficiaries." Study concept and design were primarily contributed by Sujit Sansgiry and Mhatre, with assistance from the other authors. Mhatre, Serna, and Sujit Sansgiry took the lead in data collection, assisted by the other authors, and data interpretation was performed by Mhatre, Shubhada Sansgiry, and Essien, assisted by the other authors. The manuscript was written by Mhatre and Fleming, assisted by the other authors, and revised primarily by Mhatre, along with Sujit Sansgiry and assisted by the other authors.

Prescription medication adherence is a known health-related barrier for elderly patients, leading to insufficient disease control and negative health outcomes. The Centers for MedicareMedicaid Services (CMS) have placed significant emphasis on medication adherence, through the Part D star measures, revolving around treatment for chronic disease states such as hypertension, diabetes, and hyperlipidemia. However, it is unclear if physicians fully grasp the extent of nonadherence within their patient populations with regard to these medications, specifically those patients enrolled in Medicare Advantage Prescription Drug (MA-PD) plans.To (a) determine physicians' perceptions of medication adherence among their patients enrolled in MA-PD plans and (b) compare those perceptions with actual adherence rates obtained from claims data.A survey was developed and administered to primary care physicians (PCPs) contracted within a Texas MA-PD plan. The previously validated questionnaire was distributed during an all-PCP quarterly meeting and was collected prior to the meeting's conclusion to increase completion and return rates. PCPs were requested to indicate what percentage of their patients they believed to be adherent to each of the CMS Part D star medication classes, which includes statins, oral antidiabetic drugs (OADs), and reninangiotensin system (RAS) antagonists; what financial category they believe the majority of their patients fall under; and what percentage of their patients receive samples. The PCPs' perceived percentage of adherent patients were compared with the calculated percentage of patients, using a chi-square test at an a priori alpha level of 0.05. The calculated adherence was obtained from pharmacy claims data, meeting the CMS targeted adherence threshold (≥ 80%). This adherence rate was calculated using proportion of days covered (PDC) for all 3 medication categories in each PCP's patient population.To compare PCP perception of patient adherence and actual adherence, 226 PCPs were used. The sample population shared similar sex and age distribution with the national physician average; however, there was more racial diversity represented. PCP perception of patient adherence, as well as the actual percentage of adherent patients, were significantly (P0.05) different across statins, OADs, and RAS antagonists; lowest perceived percentage, as well as actual percentage, were reported for statins. PCP perception of patient adherence and actual percentage of adherent patients were significantly different in the 3 medication categories. PCPs' correct estimations were significantly (P0.0001) lower than expected values, while over- and underestimations were significantly (P0.0001) higher than the expected values.PCPs were almost equally likely to over- or underestimate percentage of adherent patients in their patient pools.

Chronic infection with Pseudomonas aeruginosa (PA) is the primary cause of pulmonary deterioration in cystic fibrosis (CF). This study describes healthcare costs and resource utilization among CF patients following PA infection in the US.This retrospective study utilized data from MarketScan claims database. CF patients with an initial PA infection were identified, and their healthcare utilization, medical and pharmacy costs were extracted for 12 months, pre- and post-PA infection. Descriptive and pair-wise non-parametric statistical analyses compared healthcare utilization and costs before and after infection.Three hundred and fifty-eight CF patients met study criteria (mean age 20.1 years; 48% female). Mean annual per-patient costs following initial PA infection increased by an estimated $18,516 (outpatient: $3113; inpatient: $10,123; pharmacy: $4943). Overall healthcare costs were significantly higher (p 0.0001) following PA infection, as were overall inpatient visits, outpatient visits, and unique prescriptions (p 0.0001).PA infection in cystic fibrosis creates a significant economic burden and the cost is not uniformly distributed across the healthcare components.Key limitations of this study include the absence of clinical parameters to characterize PA infections and data on indirect costs such as loss of productivity or caretaker-related burden.

Purpose The effect of bar-code-assisted medication administration (BCMA) on nurses’ activities in an intensive care unit was evaluated. Methods A prospective, observational, time–motion study was conducted by considering two approaches to medication administration in an intensive care unit: paper-based medication administration (PBMA) and BCMA. The time spent on nursing activities was measured using a prevalidated time–motion observation instrument and categorized based on workflow factors such as direct patient care, indirect patient care, administration, and miscellaneous or other. A descriptive analysis was conducted with the amount of time spent on each of the nursing activities. A multivariate analysis of covariance was conducted to assess the difference between the two approaches for the amount of time spent on various categorized nursing activities. Covariates included in the analysis were patient characteristics, medication administration characteristics, and number of nurses involved in medication administration. Results A total of 101 PBMAs and 151 BCMAs were reviewed. The mean duration of total medication administration time was higher in the BCMA phase compared with the PBMA phase, as was the mean time spent on direct patient care activity. However, nurses spent less time on administration activity during BCMA. Statistical analysis revealed that the medication administration approach (BCMA versus PBMA) had a significant effect on time spent on direct patient care and medication administration activities. Conclusion The implementation of BCMA led to a reduction in the time spent by nurses on medication administration activities and increased the time spent on direct patient care activities.

The objective of this study was to assess the impact of a new evidence-based institutional practice algorithm on the patterns and costs of treatment of chemotherapy-induced anemia (CIA) in lymphoma patients prescribed erythropoietic-stimulating agents (ESAs).The study design was retrospective, with a historical control group. Patient demographic data, clinical data (including chemotherapy and hemoglobin values), and cost data were extracted from patient medical charts and institutional databases. Descriptive statistics, t tests, and chi-square analyses were conducted to evaluate the study objectives.The study population consisted of 154 patients, 90 patients in the pre-implementation group and 64 in the post-implementation group. Both groups had similar demographic and baseline clinical characteristics. After implementation, there was a significant decrease in the mean hemoglobin level at the time of subsequent ESA dosing from 9.59 to 8.98 g/dL (P0.0001). The proportion of patients who received an ESA at a hemoglobin level10 g/dL decreased significantly from 66% to 17% (P0.0001). There was no significant difference in the mean hemoglobin level at week 4 of ESA therapy, which may indicate that patients were not clinically affected by the change in practice. There were also no significant differences in the number of transfusions administered associated with the treatment of CIA in the study population.The results of the study show an association between implementation of the new institutional practice algorithm for ESA usage in CIA and a change in ESA utilization patterns.

Objectives Considerable disparities in breast cancer screening exist between Hispanic and non-Hispanic white (NHW) women. Identifying and quantifying the factors contributing to these racial-ethnic disparities can help shape interventions and policies aimed at reducing these disparities. This study, for the first time, identified and quantified individual-level sociodemographic and health-related factors that contribute to racial-ethnic disparities in breast cancer screening using the nonlinear Blinder-Oaxaca decomposition method. Methods Analysis of the retrospective pooled cross-sectional Medical Expenditure Panel Survey data from 2000 to 2010 was conducted. Women aged 40 years and older were included in the study. Logistic regressions were used to estimate racial-ethnic disparities in breast cancer screening. Nonlinear Blinder-Oaxaca decomposition method was used to identify and quantify the contribution of each individual-level factor toward racial-ethnic disparities. Results Based on the unadjusted analyses, Hispanic women had lower odds of receiving mammogram screening (MS) (odds ratio [OR]: 0.74; 95% confidence interval [CI]: 0.69-0.80) and breast cancer screening (OR: 0.75; 95% CI: 0.70-0.81) as compared with NHW women. However, the relationship reversed in adjusted analyses, such that Hispanic women had higher odds of receiving MS (OR: 1.27; 95% CI: 1.16-1.40) and breast cancer screening (OR: 1.28; 95% CI: 1.17-1.40) as compared with NHW women. The Blinder-Oaxaca decomposition estimated that improving insurance status, access to care, education, and income will considerably increase screening rates among Hispanic women. Conclusions The study projects that improving health care access and health education will considerably increase breast cancer screening compliance among Hispanic women. Policies like the Affordable Care Act, and patient navigation and health education interventions, might considerably reduce screening disparities in the Hispanic population.

The appropriate implementation of information technology has been perceived as an important tool for streamlining workflow, improving patient-care quality and safety, and reducing the cost of health care services.[1][1] The shortage of pharmacists[2][2],[3][3] and nurses[2][2] in the United States