In the past twenty years, CMS has conducted demonstrations aimed at enhancing the quality of health care and improving the efficiency of health care delivery in Medicare’s fee-for-service program. However, a recent Congressional Budget Office report shows mixed results for previously deployed demonstration projects attempting to improve the quality or efficiency of care for beneficiaries. The CBO report states that “For many of the programs, the estimated effects on hospital admissions and spending are quite imprecise because they had so few enrollees. On average, the 34 care coordination and disease management programs had little or no effect on hospital admissions or regular Medicare spending.”

The CBO report identified attributes of demonstrations that translated to better program outcomes. Demonstrations that retrieved and utilized timely data on the use of care, especially hospital admissions, were able to employ more relevant practices based on more current and accurate information. Programs that focused on transitions in care settings by providing additional patient education and support were able to more significantly reduce hospital admissions. Notably, the CBO reported that interventions that promoted team-based coordination across the care continuum were more successful in improving patient outcomes and establishing a care community support system. Targeting high risk enrollees for interventions enabled successful demonstrations to generate more measurable results by selecting a differentiated population representing the largest opportunity for improvement. Loopback Analytics has developed a tool for case managers and hospital/post-acute care partnerships that meets all the CBO’s suggested criteria by organizing, through an integrated web-based data platform, a cross-setting community effort to improve care transitions for discharged patients.

Other determinants of a well-designed program, as outlined by the Congressional Budget Office, revolve around a program’s ability to quickly and accurately gauge and react to results. The CBO indicates that “rigorous evaluations that use randomized designs or well-matched comparison groups” are imperative to evaluating the success of the program and the reproducibility of the program’s results. Additionally, programs designed to lead “quickly to concrete answers” and “facilitate rapid-cycle learning by showing where strategies are or are not working effectively” have the best chances of implementing a successful strategy and adjusting to new information.

Loopback Analytics supports a technology and workforce governance model to coordinate care across health systems, post-acute care providers, and social service agencies. The Loopback Analytics platform uses advanced data analytics to match high risk patients with a portfolio of post-acute care interventions and provide continuous measurement and feedback on economic and clinical effectiveness. The platform also includes a secure, cloud-based workflow system enabling care coordinators to manage, track, and communicate with patients as they progress through evidence-based programs. Care coordinators and program managers use the platform’s embedded feedback loop to assess program efficacy and inform adjustments to the model for optimal results. Loopback’s integrated data platform is a scalable model that engages a large enough population to achieve statistical significance in a relatively short period of time and promotes a continuous feedback loop to support quick program adjustments made actionable by timely evaluation.
Many of the demonstration projects evaluated by the CBO failed to produce anticipated cost reductions, health improvements, or care improvements because they lacked a developed system to support current data access, targeted patient care delivery, continuous evaluation and process improvement, and cross-setting teamwork- features Loopback Analytics has integrated into Loopback Navigator, the latest technology in patient intervention program management.

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