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Objectives: This study aims to explore factors that influence progression of Diabetes complications among Medicare non-dual beneficiaries. Three Diabetes complications explored are retinopathy, nephropathy and neuropathy. A second objective of this study is to explore the impact that various patient management programs have on reducing the risk of development of Diabetes complications. Three patient management programs are explored, including total cost of treatment (for payer), total patient cost share and physician factors (rural vs. urban and primary care vs. specialist). Methods: Predictive and descriptive logistic regression models are used with each Diabetes complication as the outcome variable. For predictive models, the risk factors are obtained using stepwise logistics regression. For explanatory models, the risks factors are included with each of the analytical factors in order to risk adjust the impact of the analytical factors on the development of Diabetes complications. Results: Nephropathy is found to be the most predictive of the three Diabetes complications. For nephropathy, both total cost of treatment and total patient cost share show negative statistical relation with nephropathy development. For physician factors, rural and specialist physicians are found to be associated with lower rate of nephropathy development among beneficiaries. Conclusions: There is evidence that prediction and management of Diabetes complications can lead to improved outcomes among Medicare beneficiaries. Total cost of treatment, total patient cost share and physician factors (rural vs. urban and primary care vs. specialist) all appear to play a role in improved outcomes in nephropathy development among beneficiaries.

Objectives: U.S. Medicaid expansion has added over 11 Million new enrollees since 2010 and U.S. states are attempting to integrate the increased population as well as addressing fiscal constraints. Account based plans (such as Health Savings Accounts) have been successfully used to control utilization while providing enrollee flexibility. We suggest that a portion of the 55 million Medicaid beneficiary population can be enrolled in account based plans and assist state and federal Health Insurance Exchanges with the ‘churn’ that occurs between the two systems while controlling costs. Methods: We use publicly available per capita Medicaid spending in each state to estimate the population that could be enrolled in an account based plan and apply factors from previous private market research in estimating the reduction in utilization trend and spend for the selected population. Results: We find that using conservative enrollment and utilization trend assumptions that states could collectively see a reduction in spend of over $800 million to over $1 billion in a fiscal year. Conclusions: States can enroll select Medicaid populations that could benefit from having a potentially seamless product that would allow individuals to transition between Medicaid plans and state and federal Health Insurance Exchange products while reducing utilization and spend.

Objectives: Physician payments from public and private payers are still largely paper-based, so significant payment lags are prevalent across all reimbursement systems. Electronic Medical Record use has the potential to reduce payment lag and improve health system performance. Methods: We use a claims data set of 100,000 covered lives from a national employer to examine mean accounts receivable (AR) payment times by provider type, physician specialty, and state. Eleven physician specialty disciplines are included in the analysis of mean AR and days of payment lag. We also include a coefficient of variation (CV) of physician claims processed by place of delivery and correlation (R2: r-squared) values between mean days of AR and mean CV. Results: We find significant variation in mean AR days by provider type and physician specialty. There is also a great deal of variation in payment processing lags by state. We find a range of correlations between mean AR days and mean CV by provider type of service (R2=0.6288), physician specialties (R2=0.662), and the state of service (R2=0.1247). Conclusions: Low EMR adoption rates impact how all payer types pay physicians. The elimination of paper-based claims (and their associated lag times) could be achieved through the adoption of basic practice management systems bundled with EMRs. There is sufficient health savings from shortening the AR lag time period for insurer payment to providers to finance EMR adoption even with without federal HITECH incentives to practices.