Variations in breast cancer surgical treatment and timing: determinants and disparities.

PURPOSE: To describe clinical and non-clinical factors associated with receipt of breast conserving surgery (BCS) versus mastectomy and time to surgical intervention. METHODS: Cross-sectional retrospective study of January 1, 2012 through March 31, 2018 data from the IBM MarketScan Commercial Claims and Encounter and Medicare Supplemental Databases. Area Health Resource Files provided non-clinical characteristics and sociodemographic data. Eligibility: Female sex, claim(s) with ICD-9-CM or ICD-10-CM diagnosis of non-metastatic invasive breast cancer, > 6 months of continuous insurance pre- and post-diagnosis, evidence of BCS or mastectomy following initial ICD9/10 code diagnosis. Logistic and quantile multivariable regression models assessed the association between clinical and non-clinical factors and the outcome of BCS and time to surgery, respectively. RESULTS: A total of 53,060 women were included in the study. Compared to mastectomy, BCS was significantly associated with older age (ORs: 1.54 to 2.99, 95% CIs 1.45 to 3.38; ps < .0001) and higher community density of medical genetics (OR: 5.88, 95% CIs 1.38 to 25.00; p = 0.02) or obstetrics and gynecology (OR: 1.13, 95% CI 1.02 to 1.25; p = .02) physicians. Shorter time-to-BCS was associated with living in the South (-2.96, 95% CI -4.39 to -1.33; p < .0001). Longer time-to-BCS was associated with residence in more urban (4.18, 95% CI 0.08 to 8.29; p = 0. 05), educated (9.02, 95% CI 0.13 to 17.91; p = 0.05), or plastic-surgeon-dense (4.62, 95% CI 0.50 to 8.73; p = 0.03) communities. CONCLUSIONS: Clinical and non-clinical factors are associated with adoption of BCS and time to treatment, suggesting opportunities to ensure equitable and timely care.

Clinical Decision Support for High-Risk Stage II Colon Cancer: A Real-World Study of Treatment Concordance and Survival.

BACKGROUND: Prognostic and pathologic risk factors typically guide clinicians and patients in their choice of surveillance or adjuvant chemotherapy when managing high-risk stage II colon cancer. However, variations in treatment and outcomes in patients with stage II colon cancer remain. OBJECTIVE: This study aimed to assess the survival benefits of treatments concordant with suggested therapeutic options from Watson for Oncology, a clinical decision support system. DESIGN: This is a retrospective observational study of concordance between actual treatment and Watson for Oncology therapeutic options. SETTING: This study was conducted at a top-tier cancer center in China. PATIENTS: Postoperative treatment data were retrieved from the electronic health records of 306 patients with high-risk stage II colon adenocarcinoma. MAIN OUTCOME MEASURES: The primary outcomes measured were the treatment patterns plus 3- and 5-year overall and disease-free survival for concordant and nonconcordant cases. RESULTS: Overall concordance was 90%. Most nonconcordant care resulted from adjuvant chemotherapy use (rather than surveillance) in patients with high-level microsatellite instability and ≥70 years old. No difference in overall survival (p = 0.56) or disease-free survival (p = 0.19) was observed between concordance groups. Patients receiving adjuvant chemotherapy had significantly higher 5-year overall survival than those undergoing surveillance (94% vs 84%, p = 0.01). LIMITATIONS: This study was limited by the use of retrospective cases drawn from patients presenting for surgery, the lack of complete follow-up data for 58% of patients who could not be included in the analysis, and a survival analysis that assumes no unmeasured correlation between survival and censoring. CONCLUSIONS: Watson for Oncology produced therapeutic options highly concordant with human decisions at a top-tier cancer center in China. Treatment patterns suggest that Watson for Oncology may be able to guide clinicians to minimize overtreatment of patients with high-risk stage II colon cancer with chemotherapy. Survival analyses suggest the need for further investigation to specifically assess the association between surveillance, single-agent and multiagent chemotherapy, and survival outcomes in this population. See Video Abstract at http://links.lww.com/DCR/B291. APOYO A LA DECISIÓN CLÍNICA DEL CÁNCER DE COLON EN ESTADIO II DE ALTO RIESGO: UN ESTUDIO DEL MUNDO REAL SOBRE LA CONCORDANCIA DEL TRATAMIENTO Y LA SUPERVIVENCIA: Los factores de riesgo pronósticos y patológicos generalmente guían a los médicos y pacientes en su elección de vigilancia o quimioterapia adyuvante cuando se trata el cáncer de colon en estadio II de alto riesgo. Sin embargo, las variaciones en el tratamiento y los resultados en pacientes con cáncer de colon en estadio II permanecen.Evaluar los beneficios de supervivencia de los tratamientos concordantes con las opciones terapéuticas sugeridas por "Watson for Oncology" (Watson para la oncología), un sistema de apoyo a la decisión clínica.Estudio observacional retrospectivo de concordancia entre el tratamiento real y las opciones terapéuticas de Watson para oncología.Un centro oncológico de primer nivel en China.Datos de tratamiento postoperatorio de registros de salud electrónicos de 306 pacientes con adenocarcinoma de colon en estadio II de alto riesgo.Patrones de tratamiento más supervivencia global y libre de enfermedad a 3 y 5 años para casos concordantes y no concordantes.La concordancia general fue del 90%. La mayoría de la atención no concordante resultó del uso de quimioterapia adyuvante (en lugar de vigilancia) en pacientes de alto nivel con inestabilidad de microsatélites y pacientes ≥70 años. No se observaron diferencias en la supervivencia global (p = 0,56) o la supervivencia libre de enfermedad (p = 0,19) entre los grupos de concordancia. Los pacientes que recibieron quimioterapia adyuvante tuvieron una supervivencia global a los 5 años significativamente más alta que los que fueron sometidos a vigilancia (94% frente a 84%, p = 0,01).Uso de casos retrospectivos extraídos de pacientes que se presentan para cirugía, falta de datos de seguimiento completos para el 58% de los pacientes que no pudieron ser incluidos en el análisis, y análisis de supervivencia que asume que no exite una correlación no medida entre supervivencia y censura.Watson para Oncología produjo opciones terapéuticas altamente concordantes con las decisiones humanas en un centro oncológico de primer nivel en China. Los patrones de tratamiento sugieren que Watson para Oncología puede guiar a los médicos para minimizar el sobretratamiento de pacientes con cáncer de colon en estadio II de alto riesgo con quimioterapia. Los análisis de supervivencia sugieren la necesidad de realizar mas investigaciónes para evaluar específicamente la asociación entre la vigilancia, la quimioterapia con uno solo o múltiples agentes y los resultados de supervivencia en esta población. Consulte Video Resumen en http://links.lww.com/DCR/B291. (Traducción-Dr. Gonzalo Hagerman).

Elimination of the Out-of-Pocket Charge for Children's Primary Care Visits: An Application of Value-Based Insurance Design.

OBJECTIVE: To evaluate the impact of a value-based insurance design for primary care among children. STUDY DESIGN: A retrospective analysis of health care claims data on 25 950 children (<18 years of age) was conducted. Individuals were enrolled in a large employer's health plans when zero out-of-pocket cost for primary care physician visits was implemented. A rigorous propensity score matching process was used to generate a control group of equal size from a database of other employer-sponsored insurees. Multivariate difference-in-differences models estimated the effect of zero out-of-pocket cost on 21 health services and cost outcomes 24 months after intervention. RESULTS: Zero out-of-pocket cost for primary care was associated with significant increases (P < .01) in primary care physician visits (+32 per 100 children), as well as decreases in emergency department (-5 per 100 children) and specialist physician visits (-12 per 100 children). The number of prescription drug fills also declined (-20 per 100 children), yet medication adherence for 3 chronic conditions was unaffected. The receipt of well child visits and 4 recommended vaccinations were all significantly (P < .05) greater under the new plan design feature. Employer costs for primary care increased significantly (P < .01) in association with greater utilization ($29 per child), but specialist visit costs declined (-$12 per child) and total health care costs per child did not exhibit a statistically significant increase. CONCLUSION: This novel application of value-based insurance design warrants broader deployment and assessment of its longer term outcomes. As with recommended preventive services, policymakers should consider exempting primary care from health insurance cost-sharing.

Financial Incentives, Workplace Wellness Program Participation, and Utilization of Health Care Services and Spending.

This paper analyzes data from a large employer that enhanced financial incentives to encourage participation in its workplace wellness programs. It examines, first, the effect of financial incentives on wellness program participation, and second, it estimates the impact of wellness program participation on utilization of health care services and spending. The Patient Protection and Affordable Care Act of 2010 (PPACA) allows employers to provide financial incentives of as much as 30 percent of the total cost of coverage when tied to participation in a wellness program. Participation in health risk assessments (HRAs) increased by 50 percentage points among members of unions that bargained in the incentive, and increased 22 percentage points among non-union employees. Participation in the biometric screening program increased 55 percentage points when financial incentives were provided. Biometric screenings led to an average increase of 0.31 annual prescription drug fills, with related spending higher by $56 per member per year. Otherwise, no significant effects of participation in HRAs or biometric screenings on utilization of health care services and spending were found. The largest increase in medication utilization as a result of biometric screening was for statins, which are widely used to treat high cholesterol. This therapeutic class accounted for one-sixth of the overall increase in prescription drug utilization. Second were antidepressants, followed by ACE inhibitors (for hypertension), and thyroid hormones (for hypothyroidism). Biometric screening also led to significantly higher utilization of biologic response modifiers and immunosuppressants. These specialty medications are used to treat autoimmune diseases, such as rheumatoid arthritis and multiple sclerosis, and are relatively expensive compared with non-specialty medications. The added spending associated with the combined increase in fills of 0.02 was $27 per member per year--about one-half of the overall increase in prescription drug spending from those who participated in biometric screenings.

Sinking, Swimming, or Learning to Swim in Medicare Part D.

Under Medicare Part D, senior citizens choose prescription drug insurance offered by numerous private insurers. We examine nonpoor enrollees' actions in 2006 and 2007 using panel data. Our sample reduced overspending by $298 on average, with gains by 81 percent of them. The greatest improvements were by those who overspent most in 2006 and by those who switched plans. Decisions to switch depended on individuals' overspending in 2006 and on individual-specific effects of changes in their current plans. The oldest consumers and those initiating medications for Alzheimer's disease improved by more than average, suggesting that real-world institutions help overcome cognitive limitations.

Impact of direct-acting antiviral use for chronic hepatitis C on health care costs in Medicaid: economic model update.

Curative direct-acting antivirals for chronic hepatitis C provide a net economic benefit to Medicaid in less than 1 year. Cumulative savings to date have exceeded $15 billion.

Endoscopic Ultrasound-Guided Botox Injection for Refractory Anal Fissure.

Background: Anal fissures cause severe pain and can be difficult to treat. Medical therapy is initially used, followed by sigmoidoscopy-guided botox injections if the medical therapy is not successful. With this technique, however, it is not clear whether botox is injected into the muscle layer or submucosa. Aim: To evaluate the efficacy of EUS-guided botox injection directly into the internal sphincter. Methods: Consecutive patients with chronic anal fissure refractory to conventional endoscopic botulinum toxin type A injection were enrolled in the study. EUS was performed using a linear array echoendoscope, and a 25 G needle was used to inject botox. All patients were followed up at one- and two-month intervals. Results: Eight patients with chronic anal fissures were included in the study. Six patients had an excellent response to botox at the two-month interval using a visual analog pain scale, while one patient had a moderate response with a pain score reduction of 40%. One patient had no response. No complications were noted. An improvement in visual analog scale (pre-score > post-score) was statistically significant at the p < 0.01 level. Conclusion: EUS-guided botox injection into the internal sphincter appears to be a promising technique for patients with refractory anal fissure with pain.

Accuracy of an Artificial Intelligence System for Cancer Clinical Trial Eligibility Screening: Retrospective Pilot Study.

BACKGROUND: Screening patients for eligibility for clinical trials is labor intensive. It requires abstraction of data elements from multiple components of the longitudinal health record and matching them to inclusion and exclusion criteria for each trial. Artificial intelligence (AI) systems have been developed to improve the efficiency and accuracy of this process. OBJECTIVE: This study aims to evaluate the ability of an AI clinical decision support system (CDSS) to identify eligible patients for a set of clinical trials. METHODS: This study included the deidentified data from a cohort of patients with breast cancer seen at the medical oncology clinic of an academic medical center between May and July 2017 and assessed patient eligibility for 4 breast cancer clinical trials. CDSS eligibility screening performance was validated against manual screening. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for eligibility determinations were calculated. Disagreements between manual screeners and the CDSS were examined to identify sources of discrepancies. Interrater reliability between manual reviewers was analyzed using Cohen (pairwise) and Fleiss (three-way) κ, and the significance of differences was determined by Wilcoxon signed-rank test. RESULTS: In total, 318 patients with breast cancer were included. Interrater reliability for manual screening ranged from 0.60-0.77, indicating substantial agreement. The overall accuracy of breast cancer trial eligibility determinations by the CDSS was 87.6%. CDSS sensitivity was 81.1% and specificity was 89%. CONCLUSIONS: The AI CDSS in this study demonstrated accuracy, sensitivity, and specificity of greater than 80% in determining the eligibility of patients for breast cancer clinical trials. CDSSs can accurately exclude ineligible patients for clinical trials and offer the potential to increase screening efficiency and accuracy. Additional research is needed to explore whether increased efficiency in screening and trial matching translates to improvements in trial enrollment, accruals, feasibility assessments, and cost.

Prescription drug costs and the generic dispensing ratio.

BACKGROUND: The generic dispensing ratio (GDR)-the number of generic fills divided by the total number of prescriptions-is a standard performance metric on which pharmacy benefit designs and their managers are routinely evaluated. Higher GDRs are considered important because they consistently produce lower prescription drug costs. OBJECTIVE: To (a) quantify the relationship between GDR and gross pharmacy expenditures and (b) distinguish pharmacy cost savings realized from brand-to-generic conversion from those due to brand drug utilization decreases. METHODS: This study was a longitudinal, retrospective analysis of paid pharmacy claims and insurance eligibility information for 548 employers covering nearly 14 million members. Data were from the period January 1, 2007, through December 31, 2009, aggregated quarterly. In a linear fixed effects model controlling for plan membership demographics and time trends, percentage changes in gross pharmacy expenditures per member per quarter (PMPQ) were associated with changes in GDR. A second model estimated the association of GDR with gross pharmacy cost, holding total drug utilization constant. All claims counts were adjusted to 30-day equivalents, and expenditures were log--transformed. RESULTS: Mean generic claims PMPQ increased by 18.4% during the study period, from 2.01 in 2007 Q1 to 2.38 in 2009 Q4. Conversely, brand claims PMPQ decreased by 21.0%, from 1.76 in 2007 Q1 to 1.39 in 2009 Q4. As a result, mean GDR per plan increased by 9.8 percentage points or a relative change of 18.2%, from 53.9% in 2007 Q1 to 63.7% in 2009 Q4. Over the 3 years, average gross pharmacy costs PMPQ increased by 14.0% from $242 to $276. The relationship between GDR and gross pharmacy expenditures, estimated in the linear fixed effects multivariate models, varied depending upon whether or not total utilization was controlled. In the first model, which did not control for total utilization, each percentage point increase in GDR was associated with a 2.5% reduction in gross pharmacy expenditure. Holding total utilization constant, the reduction in gross pharmacy expenditure for each percentage point increase in GDR was 1.3%. CONCLUSION: Prescription drug cost savings are realized with increases in GDR. During 2007-2009, each 1 percentage point increase in GDR was associated with a drop of 2.5% in gross pharmacy expenditures. Slightly more than one-half of the savings was derived from the lower drug prices enjoyed with brand-to-generic conversions. The remaining savings, however, were attributed to reduced brand drug utilization. Pharmacy benefit managers and plan sponsors should exercise care to ensure that increases in GDR do not represent reductions in appropriate medication use.

Artificial Intelligence Tool for Optimizing Eligibility Screening for Clinical Trials in a Large Community Cancer Center.

PURPOSE: Less than 5% of patients with cancer enroll in clinical trials, and 1 in 5 trials are stopped for poor accrual. We evaluated an automated clinical trial matching system that uses natural language processing to extract patient and trial characteristics from unstructured sources and machine learning to match patients to clinical trials. PATIENTS AND METHODS: Medical records from 997 patients with breast cancer were assessed for trial eligibility at Highlands Oncology Group between May and August 2016. System and manual attribute extraction and eligibility determinations were compared using the percentage of agreement for 239 patients and 4 trials. Sensitivity and specificity of system-generated eligibility determinations were measured, and the time required for manual review and system-assisted eligibility determinations were compared. RESULTS: Agreement between system and manual attribute extraction ranged from 64.3% to 94.0%. Agreement between system and manual eligibility determinations was 81%-96%. System eligibility determinations demonstrated specificities between 76% and 99%, with sensitivities between 91% and 95% for 3 trials and 46.7% for the 4th. Manual eligibility screening of 90 patients for 3 trials took 110 minutes; system-assisted eligibility determinations of the same patients for the same trials required 24 minutes. CONCLUSION: In this study, the clinical trial matching system displayed a promising performance in screening patients with breast cancer for trial eligibility. System-assisted trial eligibility determinations were substantially faster than manual review, and the system reliably excluded ineligible patients for all trials and identified eligible patients for most trials.

Effect of an Artificial Intelligence Clinical Decision Support System on Treatment Decisions for Complex Breast Cancer.

PURPOSE: To examine the impact of a clinical decision support system (CDSS) on breast cancer treatment decisions and adherence to National Comprehensive Cancer Center (NCCN) guidelines. PATIENTS AND METHODS: A cross-sectional observational study was conducted involving 1,977 patients at high risk for recurrent or metastatic breast cancer from the Chinese Society of Clinical Oncology. Ten oncologists provided blinded treatment recommendations for an average of 198 patients before and after viewing therapeutic options offered by the CDSS. Univariable and bivariable analyses of treatment changes were performed, and multivariable logistic regressions were estimated to examine the effects of physician experience (years), patient age, and receptor subtype/TNM stage. RESULTS: Treatment decisions changed in 105 (5%) of 1,977 patients and were concentrated in those with hormone receptor (HR)-positive disease or stage IV disease in the first-line therapy setting (73% and 58%, respectively). Logistic regressions showed that decision changes were more likely in those with HR-positive cancer (odds ratio [OR], 1.58; P < .05) and less likely in those with stage IIA (OR, 0.29; P < .05) or IIIA cancer (OR, 0.08; P < .01). Reasons cited for changes included consideration of the CDSS therapeutic options (63% of patients), patient factors highlighted by the tool (23%), and the decision logic of the tool (13%). Patient age and oncologist experience were not associated with decision changes. Adherence to NCCN treatment guidelines increased slightly after using the CDSS (0.5%; P = .003). CONCLUSION: Use of an artificial intelligence-based CDSS had a significant impact on treatment decisions and NCCN guideline adherence in HR-positive breast cancers. Although cases of stage IV disease in the first-line therapy setting were also more likely to be changed, the effect was not statistically significant (P = .22). Additional research on decision impact, patient-physician communication, learning, and clinical outcomes is needed to establish the overall value of the technology.

Assessing the burden of illness of chronic hepatitis C and impact of direct-acting antiviral use on healthcare costs in Medicaid.

OBJECTIVES: To quantify the burden of illness of chronic hepatitis C virus (HCV) infection and estimate the impact of interferon-free direct-acting antiviral treatment on healthcare costs in Medicaid. STUDY DESIGN: Observational, retrospective analysis. METHODS: Medicaid claims data from 2012 for nonelderly adult enrollees with chronic HCV in 16 states were used to estimate the burden of HCV in Medicaid. Annual measures of health services utilization and cost for patients with HCV were compared with a control group of patients without HCV exactly matched on a robust set of individual characteristics and stratified according to liver disease severity, Medicaid eligibility group, and plan type. Subsequently, HCV burden-of-illness estimates were used in a separate analysis of Medicaid State Drug Utilization Data on interferon-free drug utilization and expenditures to estimate the annual and cumulative impact of these curative medications on national Medicaid costs from 2013 through 2022. RESULTS: Annual per-person Medicaid healthcare costs attributed to HCV infection were estimated to range from $10,561 for noncirrhotic disabled adults to $46,263 for nondisabled adults with end-stage liver disease. The costs were due mainly to inpatient hospitalizations and outpatient hospital visits, prescription drug utilization, outpatient physician's office/clinic visits, and laboratory tests. By 2014, the first full year following the approval of interferon-free treatment, an estimated 12,175 adults with HCV were cured in Medicaid nationwide, each avoiding an estimated $15,907 per year in healthcare costs associated with the disease. As more patients in Medicaid are treated and net savings continue to grow year after year-due to recurring avoidance of health services use and declining drug prices-total cumulative treatment costs since 2013 are expected to be fully offset by total cumulative healthcare expenditure reductions by the end of 2019. By 2022, the recurrent annual avoidance of healthcare costs will have delivered an estimated $12 billion in total cumulative savings to Medicaid, net of DAA drug expenditures. CONCLUSIONS: The introduction of interferon-free HCV treatments enables the avoidance of significant healthcare costs previously associated with treating the disease year after year, producing annual cumulative Medicaid savings beginning in 2019. A main finding from this study is that the cost of a complete DAA treatment course, at 2018 estimated net prices, can be expected to be fully offset by healthcare cost savings after only 16 months, on average, on a per-person basis. Given the tremendous value provided by these curative drugs, Medicaid policies aimed toward restricting access to these treatments based on disease severity or other requirements would be shortsighted.

Artificial Intelligence Treatment Decision Support For Complex Breast Cancer Among Oncologists With Varying Expertise.

PURPOSE: The aim of the current study was to assess treatment concordance and adherence to National Comprehensive Cancer Network breast cancer treatment guidelines between oncologists and an artificial intelligence advisory tool. PATIENTS AND METHODS: Study cases of patients (N = 1,977) who were at high risk for recurrence or who had metastatic disease and cell types for which the advisory tool was trained were obtained from the Chinese Society for Clinical Oncology cancer database (2012 to 2017). A cross-sectional observational study was performed to examine treatment concordance and guideline adherence among an artificial intelligence advisory tool and 10 oncologists with varying expertise-three fellows, four attending physicians, and three chief physicians. In a blinded fashion, each oncologist provided treatment advice on an average of 198 cases and the advisory tool on all cases (N = 1,977). Results are reported as rates and logistic regression odds ratios. RESULTS: Concordance for the recommended treatment was 0.56 for all physicians and higher for fellows compared with chief and attending physicians (0.68 v 0.54; 0.49; P = .001). Concordance differed by hormone receptor subtype-TNM stage, with the lowest for hormone receptor-positive human epidermal growth factor receptor 2/neu-positive cancers (0.48) and highest for triple-negative breast cancers (0.71) across most TNM stages. Adherence to National Comprehensive Cancer Network guidelines was higher for oncologists compared with the advisory tool (0.96 v 0.82; P < .003) and lower for fellows compared with attending physicians (0.93 v 0.98; 0.96; P = .04). CONCLUSION: Study findings reflect a complex breast cancer case mix, the limits of medical knowledge regarding optimum treatment, clinician practice patterns, and use of a tool that reflects expertise from one cancer center. Additional research in different practice settings is needed to understand the tool's scalability and its impact on treatment decisions and clinical and health services outcomes.

Economic cost of the therapeutic workplace intervention added to methadone maintenance.

Therapeutic workplace is a novel intervention that uses access to paid training and employment to reinforce drug abstinence within the context of standard methadone maintenance. We used the Drug Abuse Treatment Cost Analysis Program as a standard method of estimating the economic costs of this intervention. In a 1-year period, the therapeutic workplace served 122 methadone maintenance clients who had a median length of stay of 22 weeks. The workplace maintained a mean daily census of 48 clients. The combined cost of methadone maintenance and the therapeutic workplace was estimated at US$362 per week. This cost is less than that of other treatments that might be used to promote abstinence in individuals who continue to use drugs during methadone treatment. Given prior evidence of effectiveness, these cost data may be useful to policy makers, social service agencies, and researchers interested in using or further developing the therapeutic workplace intervention.

Brief physician advice for problem drinking among older adults: an economic analysis of costs and benefits.

OBJECTIVE: Problem alcohol use among elderly persons can have a variety of health-related consequences, complicating management of chronic illnesses and increasing health care utilization and costs. This study evaluates the economic cost and benefits of brief intervention for at-risk drinking older adults. METHOD: A controlled clinical trial with 24-month follow-up tested effectiveness of brief physician advice in reducing alcohol use, health care utilization and other consequences among older (age 65 or older) adult problem drinkers. Of 6,073 patients screened for problem drinking in 24 community-based primary care practices in Wisconsin, 158 patients met inclusion criteria and were randomized into control (n = 71) or intervention (n = 87) groups. Intervention group patients received two 10- to 15-minute physician-delivered counseling sessions including professional advice, education and contracting using scripted workbooks. RESULTS: The intervention group demonstrated significant reductions in alcohol use (p = 0.001) and frequency of excessive drinking (p = 0.03) compared with the control group over 24 months, but no significant differences emerged in economic outcomes, including hospital days, emergency department visits, office visits, medications, lab and x-ray procedures, injuries, legal events or mortality. CONCLUSIONS: Although the clinical benefits of brief alcohol interventions with older adults are clear, the economic results in this age group are less certain. Older adult problem drinkers may require more intensive and costly interventions to achieve economic benefits similar to those seen in younger adult problem drinkers. Methodological issues, such as statistical power, outcome measures, outlier cases and follow-up periods, are identified for future evaluations.

Increased Use Of Prescription Drugs Reduces Medical Costs In Medicaid Populations.

We used data on more than 1.5 million Medicaid enrollees to examine the impact of changes in prescription drug use on medical costs. For three distinct groups of enrollees, we estimated the effects of aggregate prescription drug use-and, more specifically, the use of medications to treat eight chronic noncommunicable diseases-on total nondrug, inpatient, outpatient, and other Medicaid spending. We found that a 1 percent increase in overall prescription drug use was associated with decreases in total nondrug Medicaid costs by 0.108 percent for blind or disabled adults, 0.167 percent for other adults, and 0.041 percent for children. Reductions in combined inpatient and outpatient spending from increased drug utilization in Medicaid were similar to an estimate for Medicare by the Congressional Budget Office. Moving forward, policy makers evaluating proposed changes that alter medication use among the nearly seventy million Medicaid recipients should consider the net effects on program spending to ensure that scarce federal and state health care dollars are allocated efficiently.