Medical Costs and Health Care Utilization Among Self-Insured Members with Carve-In Versus Carve-Out Pharmacy Benefits.

BACKGROUND: Pharmacy benefit can be purchased as part of an integrated medical and pharmacy health package-a carve-in model-or purchased separately and administered by an external pharmacy benefit manager-a carve-out model. Limited peer-reviewed information is available assessing differences in use and medical costs among carve-in versus carve-out populations. OBJECTIVE: To compare total medical costs per member per year (PMPY) and utilization between commercially self-insured members receiving carve-in to those receiving carve-out pharmacy benefits overall and by 7 chronic condition subgroups. METHODS: This study used deidentified data of members continuously enrolled in Cambia Health Solutions self-insured Blue plans without benefit changes from 2017 through 2018. Cambia covers 1.6 million members in Oregon, Washington, Idaho, and Utah. The medical cost PMPY comparison was performed using multivariable general linear regression with gamma distribution adjusting for age, gender, state, insured group size, case or disease management enrollment, 7 chronic diseases, risk score (illness severity proxy), and plan paid to total paid ratio (benefit richness proxy). Medical event objectives were assessed using multivariable logistic regression comparing odds of hospitalization and emergency department (ED) visit adjusting for the same covariates. Sensitivity analyses repeated the medical cost PMPY comparison excluding high-cost members, greater than $250,000 annually. Chronic condition subgroup analyses were performed using the same methods separately for members having asthma, coronary artery disease, chronic obstructive pulmonary disease, heart failure, diabetes mellitus, depression, and rheumatoid arthritis. RESULTS: There were 205,835 carve-in and 125,555 carve-out members meeting study criteria. Average age (SD) was 34.2 years (18.6) and risk score (SD) 1.1 (2.3) for carve-in versus 35.2 years (19.3) and 1.1 (2.4), respectively, for carve-out. Members with carve-in benefits had lower medical costs after adjustment (4%, P < 0.001), translating into an average $148 lower medical cost PMPY ($3,749 carve-out vs. $3,601 carve-in annualized). After adjustment, the carve-in group had an estimated 15% (P < 0.001) lower hospitalization odds and 7% (P < 0.001) lower ED visit odds. Of 7 chronic conditions, significantly lower costs (12%-17% lower), odds of hospitalization (22%-36% lower), and odds of ED visit (16%-20% lower) were found among members with carve-in benefits for 5 conditions (all P < 0.05). CONCLUSIONS: These findings suggest that integrated, carve-in pharmacy and medical benefits are associated with lower medical costs, fewer hospitalizations, and fewer ED visits. This study focused on associations, and defining causation was not in scope. Possible reasons for these findings include plan access to both medical and pharmacy data and data-informed care management and coordination. Future research should include investigation of integrated data use and its effect across the spectrum of integrated health plan offerings, provider partnerships, and analytic strategies, as well as inclusion of analyzing pharmacy costs to encompass total cost of care. DISCLOSURES: This study received no external funding. The study was jointly conducted by employees of Cambia Health Solutions and Prime Therapeutics, a pharmacy benefit manager servicing Cambia Health Solutions. Smith, Lam, Lockwood, and Pegus are employees of Cambia Health Solutions. Qiu and Gleason are employees of Prime Therapeutics.

Long-term Outcomes of the ATHENA (Athletes Targeting Healthy Exercise & Nutrition Alternatives) Program for Female High School Athletes.

Adolescence and emerging adulthood are critical windows for establishing life-long behaviors. We assessed long-term outcomes of a prospective randomized harm reduction/health promotion program for female high school athletes. The intervention's immediate beneficial effects on diet pill use and unhealthy eating behaviors have been reported; however, tobacco, alcohol and marijuana use were not immediately altered (Elliot et al, 2004). One to three years following graduation, positive benefits in those domains became evident, and intervention students reported significantly less lifetime use of cigarettes, marijuana, and alcohol. Sport teams may be effective vehicles for gender-specific interventions to promote competency skills and deter harmful actions, and those benefits may manifest when acquired abilities are applied in new environments following high school graduation.

Healthy Team Healthy U: A Prospective Validation of an Evidence-Based Worksite Health Promotion and Wellness Platform.

OBJECTIVE: To evaluate the effects of a research-tested, team-based health promotion and wellness program combined with digital technologies and implemented in a diverse worksite setting among hospital, clinic, and university employees. METHODS: A prospective cohort study of employees completing biometrics and questionnaires before and after the initial 12-session wellness program and its 12-session booster, 1 year later. RESULTS: After both the initial intervention and booster, blood pressure and weight were reduced, with greater reductions among employees with pre-hypertension and hypertension and those with a body mass index ≥25. After both the initial intervention and booster, there was a significant increase in (1) daily intake of fruit and vegetable servings, (2) days/week of ≥30 min of exercise, (3) days/week of strength training, and (4) levels of moderately vigorous and vigorous daily physical activity. Self-reported indices of both depression and work-related stress were reduced, while participants reported increased happiness. Post booster, average sleep quality, and sleep duration increased among higher risk employees reporting ≤6 h of daily sleep. Employees reported receiving encouragement from co-workers to engage in healthful diet and physical activities, and exercised together more, and indicated that they would recommend the program to other employees. Longitudinal analysis revealed the durability of the initial intervention outcomes with further beneficial effects after the booster. CONCLUSION: A research tested, comprehensive team-based health promotion and wellness program, combined with digital technologies, improved employee health behaviors, mood, sleep, elements of co-worker cohesion, and biometrics among a diverse multi-site workforce. Positive program effects were durable, with enhanced results after the booster.

Drug testing athletes to prevent substance abuse: background and pilot study results of the SATURN (Student Athlete Testing Using Random Notification) study.

PURPOSE: To assess the deterrent effect of mandatory, random drug testing among high school (HS) athletes in a controlled setting. METHODS: Two high schools, one with mandatory drug testing (DT) consent before sports participation, and a control school (C), without DT, were assessed during the 1999-2000 school year. Athletes (A) and nonathletes (NA) in each school completed confidential (A) or anonymous (NA) questionnaires developed for this study, respectively, at the beginning and end of the school year. Positive alcohol or drug tests required parent notification and mandatory counseling without team or school suspension. Thirty percent of the DT athletes were tested. Data were analyzed using the end of the school year measure, adjusted for the initial questionnaire results. Demographics of the athlete sample revealed that mean age was 15.5 years with 81.5% white, 9.6% Hispanic, 4.5% Asian, 2.6% American Indian/Native Alaskan, 1.3% African-American, and 1.3% Native Hawaiian/Pacific Islander. RESULTS: A (n = 276) and NA (n = 507) were assessed at the beginning (baseline) and at the end of the school year (A, n = 159; NA, n = 338). The past 30-day index of illicit drugs (4-fold difference) and athletic enhancing substances (3-fold difference) were lower (p < .05) among DT athletes at follow-up without difference in alcohol use. However, most drug use risk factors, including norms of use, belief in lower risk of drugs, and poorer attitudes toward the school, increased among DT athletes (p < .05). Although a reduction in the illicit drug use index was present among nonathletes at the DT school, at the end of the school year, it did not achieve statistical significance (p < .10). CONCLUSIONS: Random DT may have reduced substance use among athletes. However, worsening of risk factors and small sample size suggests caution to this drug prevention approach. A larger long-term study to confirm these findings is necessary.

A comparison of methods to test mediation and other intervening variable effects.

A Monte Carlo study compared 14 methods to test the statistical significance of the intervening variable effect. An intervening variable (mediator) transmits the effect of an independent variable to a dependent variable. The commonly used R. M. Baron and D. A. Kenny (1986) approach has low statistical power. Two methods based on the distribution of the product and 2 difference-in-coefficients methods have the most accurate Type I error rates and greatest statistical power except in 1 important case in which Type I error rates are too high. The best balance of Type I error and statistical power across all cases is the test of the joint significance of the two effects comprising the intervening variable effect.

Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods.

The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal distribution. This article uses a simulation study to demonstrate that confidence limits are imbalanced because the distribution of the indirect effect is normal only in special cases. Two alternatives for improving the performance of confidence limits for the indirect effect are evaluated: (a) a method based on the distribution of the product of two normal random variables, and (b) resampling methods. In Study 1, confidence limits based on the distribution of the product are more accurate than methods based on an assumed normal distribution but confidence limits are still imbalanced. Study 2 demonstrates that more accurate confidence limits are obtained using resampling methods, with the bias-corrected bootstrap the best method overall.

Mediation analyses: applications in nutrition research and reading the literature.

Mediation analysis is a newer statistical tool that is becoming more prominent in nutrition research. Its use provides insight into the relationship among variables in a potential causal chain. For intervention studies, it can define the influence of different programmatic components and, in doing so, allows investigators to identify and refine a program's critical aspects. We present an overview of mediation analysis, compare mediators with other variables (confounders, moderators, and covariates), and illustrate how mediation analysis permits interpretation of the change process. A framework is outlined for the critical appraisal of articles purporting to use mediation analysis. The framework's utility is demonstrated by searching the nutrition literature and identifying articles citing mediation cross referenced with the terms "nutrition," "diet," "food," and "obesity." Seventy-two articles were identified that involved human subjects and behavior outcomes, and almost half mentioned mediation without tests to define its presence. Tabulation of the 40 articles appropriately assessing mediation demonstrates an increase in these techniques' appearance and the breadth of nutrition topics addressed. Mediation analysis is an important new statistical tool. Familiarity with its methodology and a framework for assessing articles will allow readers to critically appraise the literature and make informed independent evaluations of works using these techniques.

Distribution of the product confidence limits for the indirect effect: program PRODCLIN.

This article describes a program, PRODCLIN (distribution of the PRODuct Confidence Limits for INdirect effects), written for SAS, SPSS, and R, that computes confidence limits for the product of two normal random variables. The program is important because it can be used to obtain more accurate confidence limits for the indirect effect, as demonstrated in several recent articles (MacKinnon, Lockwood, & Williams, 2004; Pituch, Whittaker, & Stapleton, 2005). Tests of the significance of and confidence limits for indirect effects based on the distribution of the product method have more accurate Type I error rates and more power than other, more commonly used tests. Values for the two paths involved in the indirect effect and their standard errors are entered in the PRODCLIN program, and distribution of the product confidence limits are computed. Several examples are used to illustrate the PRODCLIN program. The PRODCLIN programs in rich text format may be downloaded from www.psychonomic.org/archive.

Advances in statistical methods for substance abuse prevention research.

The paper describes advances in statistical methods for prevention research with a particular focus on substance abuse prevention. Standard analysis methods are extended to the typical research designs and characteristics of the data collected in prevention research. Prevention research often includes longitudinal measurement, clustering of data in units such as schools or clinics, missing data, and categorical as well as continuous outcome variables. Statistical methods to handle these features of prevention data are outlined. Developments in mediation, moderation, and implementation analysis allow for the extraction of more detailed information from a prevention study. Advancements in the interpretation of prevention research results include more widespread calculation of effect size and statistical power, the use of confidence intervals as well as hypothesis testing, detailed causal analysis of research findings, and meta-analysis. The increased availability of statistical software has contributed greatly to the use of new methods in prevention research. It is likely that the Internet will continue to stimulate the development and application of new methods.