Why the Gap in Evaluating the Social Constructs and the Value of Medicines?

The compounding effects of occupying two or more social identities, such as being "Black" and "female" have been described in intersectionality theory. Intersectionality, a term coined by legal scholar and activist Kimberlé Crenshaw, is a framework to consider race and other social identities as overlapping, dynamic, and interdependent identities. Since its inception, intersectionality has made significant in-roads to inform the conceptualization and empirical investigations of race, gender, and other social identities in sociology, critical race theory, anthropology, feminist theory, and other disciplines. However, to date, cost effectiveness research has not systematically examined race intersecting with other social identities in the valuation of medicines using social theory, such as intersectionality. Consequently, cost effectiveness analysis, which is a method to study the value of medicines in diverse populations, has not been subject to sufficient examination through an intersectionality framework. In the US context, the racial injustices experienced and documented within diverse communities highlight that health outcomes cannot be examined in a vacuum; overlapping social identities such as race and class in relation to context have real effects on health behaviors, measured preferences, and economic costs. Failure to examine the effects of overlapping social identities on heterogeneity in benefits and costs can result in inadequate information for decision makers to evaluate the value of treatments. Without consideration of the overlapping social identities in diverse populations, there is a risk that cost effectiveness analysis results will not accurately reflect the value of treatments in socially disadvantaged populations. In this Current Opinion, we provide an outline for conducting socially conscious cost effectiveness analyses, using intersectionality as one example.

Exploring beliefs about pneumococcal vaccination in a predominantly older African American population: the Pharmacists' Pneumonia Prevention Program (PPPP).

Objectives: To assess the association of the Pharmacists' Pneumonia Prevention Program (PPPP) with changes in beliefs related to pneumonia vaccination (PV) in a predominately older African American population.Methods: PPPP was an educational intervention delivered using a senior center model of care consisting of a formal pharmacist presentation, live skit, small group action planning, and optional PV. A 15-item instrument assessed participants' beliefs at baseline, post-test, and three months across four domains: pharmacists and pharmacies, vaccination, pneumococcal disease, and physicians. Friedman tests and pairwise Wilcoxon signed rank tests were used to determine the statistical significance of the mean change in belief responses across timepoints.Results: 190 older adults participated; the sample was majority female (76.3%) and African American (80.5%), and had a mean age of 74.3 years. Statistically significant improvements in beliefs at post-test were observed in the following domains: pharmacists and pharmacies, vaccination, and the pneumococcal disease; however, some of these gains were incompletely sustained at three months.Conclusion: PPPP positively impacted beliefs post-program regarding the pneumococcal disease, pharmacists and pharmacies, and vaccination; however, sustained efforts may be needed to reinforce these gains.Policy implications: Support for pharmacist educational services in senior centers should be considered.

Healthcare Resource Utilization Following a Discharge Against Medical Advice: An Analysis of Commercially Insured Adults.

BACKGROUND: A discharge against medical advice (DAMA) is associated with adverse health outcomes. Its association with postdischarge healthcare resource utilization (HcRU) outside an inpatient setting is unknown. This information can help us understand how a DAMA may affect healthcare-seeking behavior following a hospital stay. We evaluated the relationship between a DAMA and 30-day postdischarge HcRU. METHODS: This retrospective cohort study uses a 10% random sample of enrollees in the IQVIA PharMetrics® Plus database. We included individuals aged 18 to 64 years with an inpatient admission during 2007-2015 and continuous insurance coverage. We defined comparison groups as DAMA and routine discharge. Both groups were matched on baseline covariates. We quantified the association between a DAMA and 30-day HcRU, as well as 90-day for sensitivity analysis, with use of generalized linear models for binary outcomes (inpatient readmissions, emergency department [ED] visits) and count outcomes (physician office visits, nonphysician outpatient encounters, prescription drug fills). RESULTS: Of the 457,530 individuals in the unmatched sample, 2,245 (0.5%) had a DAMA. In the matched sample, a DAMA was positively associated with an ED visit (adjusted odds ratio, 2.28; 95% confidence interval, 1.90-2.72) but not with an inpatient readmission. There were no differences between groups based on the count outcomes. A DAMA was positively associated with 90-day HcRU (ie, inpatient readmission, ED visit, and prescription drug fills). CONCLUSION: The relationship between a DAMA and HcRU varied with the HcRU category and postdischarge time interval. This examination of HcRU in the inpatient and outpatient settings provides important information about outcomes following a DAMA.

Cost-Related Non-Utilization of Health Services and Self-Perceived Reactions to Race.

Purpose: There is limited information regarding the prevalence and predictors of cost-related non-utilization (CRNU), while there is increasing attention to the rising out-of-pocket cost of health services including prescription medications. Prior studies have not quantified the role of perceived racism despite its documented relationship with health services utilization. We examine perceptions of reactions to race and quantify their relationship with CRNU. Methods: This retrospective cross-sectional study utilized data from the 2014 Behavioral Risk Factor Surveillance System (BRFSS) public use file, an annual, state-based telephone survey of US adults aged 18 and older. We utilized data for four states that provided responses to five Reactions to Race items, including information about the self-perceived quality of the respondent's health care experience compared with people of other races (worse vs same or better) and whether the respondent experienced physical symptoms because of treatment due to their race. The three binary outcomes were: 1) did not visit a physician; 2) did not visit a physician due to cost; 3) did not fill a prescription due to cost. We estimated covariate-adjusted odds ratios associated with each outcome using logistic regression models. Results: The BRFSS sample consisted of 20,366 respondents of whom 8% were African American non-Hispanic, 12% were Hispanic and 73% were White. Three percent of respondents considered their experience to be worse than people of other races. Three percent of individuals reported physical symptoms because of treatment due to their race while 5% of respondents reported becoming emotionally upset because of treatment due to their race. The proportions for the three study outcomes were 11%, 13% and 7%, respectively. In covariate-adjusted models, a worse experience with the health care system was statistically significantly associated with CRNU (physician visit: 2.6 [95% CI: 1.6 - 4.3]). The experience of physical symptoms because of treatment due to race was statistically significantly associated with CRNU (physician visit: 2.6 [95% CI: 1.7 - 4]; prescription fills: 2.1 [1.2 - 3.6]). No Reactions to Race items were associated with general non-utilization. Conclusions: Negative perceptions of reactions to race during the time of health services utilization is positively associated with CRNU, ie, foregoing physician visits and prescription fills due to cost.

Predicting risk of hospitalisation: a retrospective population-based analysis in a paediatric population in Emilia-Romagna, Italy.

OBJECTIVES: Develop predictive models for a paediatric population that provide information for paediatricians and health authorities to identify children at risk of hospitalisation for conditions that may be impacted through improved patient care. DESIGN: Retrospective healthcare utilisation analysis with multivariable logistic regression models. DATA: Demographic information linked with utilisation of health services in the years 2006-2014 was used to predict risk of hospitalisation or death in 2015 using a longitudinal administrative database of 527 458 children aged 1-13 years residing in the Regione Emilia-Romagna (RER), Italy, in 2014. OUTCOME MEASURES: Models designed to predict risk of hospitalisation or death in 2015 for problems that are potentially avoidable were developed and evaluated using the C-statistic, for calibration to assess performance across levels of predicted risk, and in terms of their sensitivity, specificity and positive predictive value. RESULTS: Of the 527 458 children residing in RER in 2014, 6391 children (1.21%) were hospitalised for selected conditions or died in 2015. 49 486 children (9.4%) of the population were classified in the 'At Higher Risk' group using a threshold of predicted risk >2.5%. The observed risk of hospitalisation (5%) for the 'At Higher Risk' group was more than four times higher than the overall population. We observed a C-statistic of 0.78 indicating good model performance. The model was well calibrated across categories of predicted risk. CONCLUSIONS: It is feasible to develop a population-based model using a longitudinal administrative database that identifies the risk of hospitalisation for a paediatric population. The results of this model, along with profiles of children identified as high risk, are being provided to the paediatricians and other healthcare professionals providing care to this population to aid in planning for care management and interventions that may reduce their patients' likelihood of a preventable, high-cost hospitalisation.

Prospective Service Use and Health Care Costs of Medicaid Beneficiaries with Treatment-Resistant Depression.

BACKGROUND: Although the clinical and health economic characteristics of commercially insured adults with treatment-resistant depression (TRD) have been well characterized, little is known about TRD in the Medicaid population. OBJECTIVE: To describe clinical and health economic characteristics of adult Medicaid beneficiaries with TRD. METHODS: Retrospective longitudinal cohort analyses were performed with Truven Health MarketScan Medicaid Database (2008-2014), focusing on adults with major depressive disorder (MDD) following an index antidepressant prescription. TRD was operationally defined as starting a third treatment regimen after 2 adequate regimens of antidepressants or augmentation therapy within 12 months of an index antidepressant prescription. Among patients with and without TRD, percentages with inpatient admissions, emergency department visits, and outpatient visits (all cause, mental health related, and depression related) were determined. Logistic regression models were used to examine associations between TRD status and use of inpatient, outpatient, and emergency services. Separate analyses were performed for the first and second year after the index antidepressant prescription. RESULTS: Approximately one quarter (25.9%) of pharmacologically treated adults with MDD met criteria for TRD. In relation to MDD patients without TRD, patients with TRD were proportionately more likely to be older, male, and white. Compared with MDD patients without TRD, patients with TRD were also significantly more likely to receive inpatient care for any cause (31.0% vs. 21.6%; P < 0.001), a mental health-related reason (12.7% vs. 7.6%; P < 0.001), or depression (10.1% vs. 6.1%; P < 0.001) during the first year following their index antidepressant prescription. Over the second follow-up year, patients with TRD continued to be more likely than patients without TRD to receive inpatient care for any reason (26.7% vs. 19.5%; P < 0.001), a mental health-related reason (5.6% vs. 2.7%; P < 0.001), and depression (3.7% vs. 1.7%; P < 0.001). The mean health care costs of patients with TRD were also significantly higher than the costs of patients without TRD during the first year ($18,982 [SD ± $35,276] vs. $11,642 [SD ± $29,203]) and second year ($17,997 [SD ± $34,146] vs. $10,325 [SD ± $28,224]) following the index antidepressant prescription. CONCLUSIONS: In the U.S. Medicaid program, adults with TRD have substantially and persistently higher health care costs than their counterparts who do not meet criteria for TRD. The service use and health care cost patterns of patients with TRD in the Medicaid program highlight challenges of developing interventions and care coordination strategies to meet their complex clinical needs. DISCLOSURES: This project was sponsored by Janssen Scientific Affairs. Olfson received a grant from Janssen Scientific Affairs through Columbia University Medical Center. Amos and Benson are employees of Janssen Scientific Affairs. Marcus was paid by Janssen Scientific Affairs to provide consulting support for this study and reports fees from Sunovion Pharmaceuticals and Alkermes outside of this study. McRae was a fellow affiliated with Janssen Scientific Affairs during the development of this research and manuscript. Study concept and design were contributed by Amos, Olfson, Marcus, Benson, and McRae. Data analysis was performed by all the authors. The manuscript was primarily written by Olfson, along with the other authors, and revised by McRae, Benson, Amos, Marcus, and Olfson. A different data cut from the same database was presented previously at the 2017 Annual Meeting of the International Society for Pharmacoeconomics and Outcomes Research; May 20-24, 2017; Boston, MA; and the 2017 AcademyHealth Annual Research Meeting; June 25-27, 2017; New Orleans, LA.

Mortality Differences Between Traditional Medicare and Medicare Advantage: A Risk-Adjusted Assessment Using Claims Data.

Medicare Advantage (MA) has grown rapidly since the Affordable Care Act; nearly one-third of Medicare beneficiaries now choose MA. An assessment of the comparative value of the 2 options is confounded by an apparent selection bias favoring MA, as reflected in mortality differences. Previous assessments have been hampered by lack of access to claims diagnosis data for the MA population. An indirect comparison of mortality as an outcome variable was conducted by modeling mortality on a traditional fee-for-service (FFS) Medicare data set, applying the model to an MA data set, and then evaluating the ratio of actual-to-predicted mortality in the MA data set. The mortality model adjusted for clinical conditions and demographic factors. Model development considered the effect of potentially greater coding intensity in the MA population. Further analysis calculated ratios for subpopulations. Predicted, risk-adjusted mortality was lower in the MA population than in FFS Medicare. However, the ratio of actual-to-predicted mortality (0.80) suggested that the individuals in the MA data set were less likely to die than would be predicted had those individuals been enrolled in FFS Medicare. Differences between actual and predicted mortality were particularly pronounced in low income (dual eligibility), nonwhite race, high morbidity, and Health Maintenance Organization (HMO) subgroups. After controlling for baseline clinical risk as represented by claims diagnosis data, mortality differences favoring MA over FFS Medicare persisted, particularly in vulnerable subgroups and HMO plans. These findings suggest that differences in morbidity do not fully explain differences in mortality between the 2 programs.

A Review of US Drug Costs Relevant to Medicare, Medicaid, and Commercial Insurers Post-Affordable Care Act Enactment, 2010-2016.

Since passage of the Affordable Care Act (ACA) in 2010, US stakeholders are increasingly being held accountable for the value of healthcare services and drugs administered to patients. Pharmacoeconomic analyses offer one method of demonstrating a product's value, yet there is a lack of resources specific to US drug costs relevant to each stakeholder. The aim of this study was to review current US drug costs (post-ACA). A literature review aimed at finding evidence on outpatient prescription drug costs was performed using the following sources: PubMed, governmental agencies, news websites, the Academy of Managed Care Pharmacy (AMCP) website, and Google Scholar. Articles were limited to those published in the years "2010-2016" and the "English" language, and those that described drug acquisition costs, reimbursement costs, and rebates or discounting for Medicare, Medicaid, and commercial payors. The Drug Cost Focus Group (DCFG) was convened to supplement the literature review; the DCFG provided their expertise on US drug costs and emerging issues affecting drug costs. ACA legislation increased drug rebates for manufacturers participating in the Medicaid Drug Rebate Program. Acquisition costs commonly referred to in the literature include the wholesale acquisition cost and average manufacture price. Drugs reimbursed by Medicaid are currently based on the actual acquisition cost and ACA-Federal Upper Limit. Evidence suggests that reimbursement methods in the public market are varied. Current gaps in the literature regarding commercial insurers' drug costs (post-ACA) present barriers to the application of relevant drug costs to pharmacoeconomic analyses.

Cost-of-Illness Studies: An Updated Review of Current Methods.

INTRODUCTION: Cost-of-illness (COI) studies provide policy-relevant information for cross-country, longitudinal, and other cost comparisons. Prior studies have called for standardization in COI methods. We investigated trends, identified factors associated with variation in COI estimation methods, and characterized reporting of heterogeneity in COI estimates. METHODS: The review of COI studies was implemented following (i) a structured search of PubMed, SCOPUS and EMBASE; (ii) a review of abstracts; (iii) a full-text review; and (iv) classification of articles according to six COI estimation methods: Sum_All Medical, Sum_Diagnosis Specific, Matched, Regression, Other_Total and Other_Incremental. Descriptive and multivariable regression analyses were conducted. RESULTS: Of the 993 studies included in the full-text review, 186 (18.7 %) were Sum_All Medical, 458 (46.1 %) were Sum_Diagnosis Specific, 96 (9.7 %) were Matched, 97 (9.8 %) were Regression, 70 (7.1 %) were Other_Incremental, and 68 (6.9 %) were Other_Total. Compared with the early period, publications in the middle and late period were associated with lower odds of using Sum_All Medical compared with Sum_Diagnosis Specific (adjusted odds ratio [AOR]middle 0.14; 95 % CI 0.07-0.28; AORlate 0.44; 95 % CI 0.29-0.67). Overall, 640 articles (64 %) reported COI estimates across patient groups defined by patient-level factors, while 247 articles (25 %) reported COI estimates across patient groups defined by non-patient-level factors. CONCLUSION: The disease-specific total costing method (Sum_Diagnosis Specific) was most commonly used and its use increased over the time period covered by this review. The investigation of subgroup heterogeneity in COI estimates represents an area for future research.