Evaluation of Prior Authorization in Medicare Nonemergent Ambulance Transport.

Importance: Some Medicare-reimbursed services are overused or improperly used, resulting in payments for unnecessary services. Objective: To determine if prior authorization of services vulnerable to improper use is associated with reduced use and costs without changing patient access or health outcomes. Design Setting and Participants: This study involved repeated cross-sectional evaluation with a state-level matched control group construction and inverse propensity score weighting at the Medicare beneficiary level. Eight states plus the District of Columbia requiring prior authorization were compared with 13 matched comparison group states not subject to prior authorization. Observations on approximately 1.7 million Medicare beneficiaries spanned January 2012 through December 2019. Depending on their state of residence, this included 3 or 4 preintervention years and 4 or 5 postintervention years. Data analysis was performed from September 2020 to July 2021. Intervention: Ambulance suppliers were directed to request prior authorization for Repetitive, Scheduled, Non-Emergent Ambulance Transport (RSNAT) services; failure to do so resulted in prepayment claim review. The goal of prior authorization is to reduce use of nonemergency ambulance transports that do not meet Medicare coverage criteria. Main Outcomes and Measures: Primary outcomes included total cost of care, RSNAT use rates and expenditures, unplanned hospital admission, emergency department admission, and emergency ambulance use per beneficiary-year. All measures were constructed from Medicare claims. Results: Approximately 1.7 million Medicare beneficiaries were observed in the study (mean [SD] age, 71 [15] years; 50% female beneficiaries; 30% Black beneficiaries, 64% White beneficiaries; 20% rural residence; 35% dually eligible for Medicare and Medicaid; 58% with end-stage renal disease; and 44% with severe [stage 3 or 4] pressure ulcers). After controlling for covariates, the results showed that prior authorization was associated with a 2.4% reduction in total annual expenditures for a total of $1530 per beneficiary-year (95% CI, -$1775 to -$1285; P < .001); a 61% reduction in the probability of RSNAT use for a total of 4.1 percentage points per beneficiary-year (95% CI, -4.26 to -3.94; P < .001); a 77% reduction in RSNAT expenditures for a total of $1136 per beneficiary-year (95% CI, -$1179 to -$1093; P < .001); a 1.4% reduction in the probability of emergency department use by 0.99 percentage points per beneficiary-year (95% CI, -1.17 to -0.81; P < .001); no change in the probability of emergency ambulance use (0.07 percentage points, 95% CI, -0.15 to 0.29; P = .50); a 2.6% reduction in the probability of unplanned hospital admission for a total of 1.53 percentage points per beneficiary-year (95% CI, -1.71 to -1.35; P < .001); and a 19% annual increase in the probability of emergency dialysis use for a total of 1.4 percentage points per beneficiary with end-stage renal disease (95% CI, 1.28 to 1.60; P < .001). Conclusions and Relevance: In this difference-in-differences analysis of Medicare beneficiaries, the results suggest that the RSNAT Prior Authorization Model was associated with reduced costs with little or no change in the quality or access indicators examined. Targeted approaches to prior authorization may be an appropriate control measure for Medicare services vulnerable to improper use.

Using Predictive Analytics for Early Identification of Short-Term Disability Claimants Who Exhaust Their Benefits.

Purpose Early interventions can help short-term disability insurance (STDI) claimants return to work following onset of an off-the-job medical condition. Accurately targeting such interventions involves identifying claimants who would, without intervention, exhaust STDI benefits and transition to longer-term support. We identify factors that predict STDI exhaustion and transfer to long-term disability insurance (LTDI). We also explore whether waiting for some claims to resolve without intervention improves targeting efficiency. Methods We use a large database of STDI claims from private employer-sponsored disability insurance programs in the United States to predict which claims will exhaust STDI or transition to LTDI. We use a split sample approach, conducting logistic regressions on half of our data and generating predictions for the other half. We assess predictive accuracy using ROC curve analysis, repeating on successive subsamples, omitting claims that resolve within 2, 4, and 6 weeks. Results Age, primary diagnosis, and employer industry were associated with the two outcomes. Rapid attrition of short-duration claims from the sample means that waiting can substantially increase the efficiency of targeting efforts. Overall accuracy of classification increases from 63.2% at week 0 to 82.9% at week 6 for exhausting STDI benefits, and from 63.7 to 83.0% for LTDI transfer. Conclusions Waiting even a few weeks can substantially increase the accuracy of early intervention targeting by allowing claims that will resolve without further intervention to do so. Predictive modeling further narrows the target population based on claim characteristics, reducing intervention costs. Before adopting a waiting strategy, however, it is important to consider potential trade-offs involved in delaying the start of any intervention.

Barriers to evidence-based physician decision-making at the point of care: a narrative literature review.

We conduct a narrative literature review using four real-world cases of clinical decisions to show how barriers to the use of evidence-based medicine affect physician decision-making at the point of care, and where adjustments could be made in the healthcare system to address these barriers. Our four cases constitute decisions typical of the types physicians make on a regular basis: diagnostic testing, initial treatment and treatment monitoring. To shed light on opportunities to improve patient care while reducing costs, we focus on barriers that could be addressed through changes to policy and/or practice at a particular level of the healthcare system. We conclude by relating our findings to the passage of the Medicare Access and Children's Health Insurance Program Reauthorization Act in April 2015.

Impact of Increasing Coverage for Select Smoking Cessation Therapies With no Out-of-Pocket Cost Among the Medicaid Population in Alabama, Georgia, and Maine.

Prevalence of smoking is particularly high among individuals with low socioeconomic status and who may be receiving Medicaid benefits. This study evaluates the public health and economic impact of providing coverage for nicotine replacement therapy with no out-of-pocket cost to the adult Medicaid population in Alabama, Georgia, and Maine, in 2012. We estimated the increase in the number of quitters and the savings in Medicaid medical expenditures associated with expanding Medicaid coverage of nicotine replacement therapy to the entire adult Medicaid population in the 3 states. With an expansion of Medicaid coverage of nicotine replacement therapy from only pregnant women to all adult Medicaid enrollees, the state of Alabama might expect 1873 to 2810 additional quitters ($526,203 and $789,305 in savings of annual Medicaid expenditures from both federal and state funds), Georgia 2911 to 4367 additional quits ($1,455,606 and $2,183,409 savings), and Maine 1511 to 2267 additional quits in ($431,709 and $647,564 savings). The expansion of coverage for smoking cessation therapy with no out-of-pocket cost could reduce Medicaid expenditures in all 3 states.

Barriers to and Facilitators of Evidence-Based Decision Making at the Point of Care: Implications for Delivery Systems, Payers, and Policy Makers.

Introduction: Physicians vary widely in how they treat some health conditions, despite strong evidence favoring certain treatments over others. We examined physicians' perspectives on factors that support or hinder evidence-based decisions and the implications for delivery systems, payers, and policymakers. Methods: We used Choosing Wisely® recommendations to create four clinical vignettes for common types of decisions. We conducted semi-structured interviews with 36 specialists to identify factors that support or hinder evidence-based decisions. We examined these factors using a conceptual framework that includes six levels: patients, physicians, practice sites, organizations, networks and hospital affiliations, and the local market. In this model, population characteristics and payer and regulatory factors interact to influence decisions. Results: Patient openness to behavior modification and expectations, facilitated and hindered physicians in making evidence-based recommendations. Physicians' communication skills were the most commonly mentioned facilitator. Practice site, organization, and hospital system barriers included measures of emergency department throughput, the order in which test options are listed in electronic health records (EHR), lack of relevant decision support in EHRs, and payment incentives that maximize billing and encourage procedures rather than medical management or counseling patients on behavior change. Factors from different levels interacted to undermine evidence-based care. Most physicians received billing feedback, but quality metrics on evidence-based service use were nonexistent for the four decisions in this study. Conclusions and Implications: Additional research and quality improvement may help to modify delivery systems to overcome barriers at multiple levels. Enhancing provider communication skills, improving decision support in EHRs, modifying workflows, and refining the design and interpretation of some quality metrics would help, particularly if combined with concurrent payment reform to realign financial incentives across stakeholders.

Economic Impact of Tobacco Price Increases Through Taxation: A Community Guide Systematic Review.

CONTEXT: Tobacco use is a leading cause of preventable death in the U.S. and around the world. Increasing tobacco price through higher taxes is an effective intervention both to reduce tobacco use in the population and generate government revenues. The goal of this paper is to review evidence on the economic impact of tobacco price increases through taxation with a focus on the likely healthcare cost savings and improvements in employee productivity. EVIDENCE ACQUISITION: The search covered studies published in English from January 2000 to July 2012 and included evaluations of national, state, and local policies to increase the price of any type of tobacco product by raising taxes in high-income countries. Economic review methods developed for The Guide to Community Preventive Services were used to screen and abstract included studies. Economic impact estimates were standardized to summarize the available evidence. Analyses were conducted in 2012. EVIDENCE SYNTHESIS: The review included eight modeling studies, with seven providing estimates of the impact on healthcare costs and three providing estimates of the value of productivity gains. Only one study provided an estimate of intervention costs. The economic merit of tobacco product price increases through taxation was determined from the overall body of evidence on per capita annual cost savings from a conservative 20% price increase. CONCLUSIONS: The evidence indicates that interventions that raise the unit price of tobacco products through taxes generate substantial healthcare cost savings and can generate additional gains from improved productivity in the workplace.

A Review of Tools to Calculate the Cost of Health Conditions and Common Health Risk Factors.

A cost calculator is a software tool that calculates the monetary cost associated with a disease, condition, or risk factor within a population group. We attempted to identify all available public health cost calculators using adapted systematic review methodology and performed a qualitative and a quantitative review on each included calculator. We first abstracted each calculator to ascertain its subject, target user, methodology, and output. We also developed a novel set of scoring criteria and evaluated each calculator for transparency and customizability. We found a wide variety of existing calculators in terms of subject area, target user, and analytic methodology. Furthermore, using our rating criteria, we found large differences in transparency with respect to the assumptions and parameter inputs driving results.