Policy Flight Simulators: Accelerating Decisions to Adopt Evidence-Based Health Interventions.

EXECUTIVE SUMMARY: In this study, the authors used simulation to explore factors that might influence hospitals' decisions to adopt evidence-based interventions. Specifically, they developed a simulation model to examine the extent to which hospitals would benefit economically from the transitional care model (TCM). The TCM is designed to transition high-risk older adults from hospitals back to communities using interventions focused on preventing readmissions.The authors used qualitative methods to identify and validate simulation facets. Four simulation experiments explored the economic impact of the TCM on more than 3,000 U.S. hospitals: (1) magnitude of readmission penalty, (2) application to specific diagnosis-related groups, (3) level of cost sharing between payer and provider, and (4) capitated versus fee-for-service payments. The simulator projected hospital-specific economic effects. The authors used Monte Carlo methods for the simulations, which were parameterized with public data sets from the Centers for Medicare & Medicaid Services (CMS) and TCM data from randomized controlled trials and comparative effectiveness studies.Under current conditions, the simulation indicated that only 10 of more than 3,000 Medicare-certified hospitals would benefit financially from the TCM. If current readmission penalties were doubled, the number of hospitals projected to benefit would increase to 300. Targeting selected diagnosis cohorts would also increase the number of hospitals to 300. If payers reimbursed providers for 100% of the TCM costs, 2,000 hospitals would benefit financially. Under a capitated payment model, 1,500 hospitals would benefit from the TCM.Current CMS penalties-or reasonable increases-have little economic effect on the TCM. In the current environment, two strategies are likely to facilitate adoption: (1) persuading payers to reimburse TCM costs and (2) focusing on hospitals with higher bed occupancies and higher revenue patients.

Service supply chains for population health: Overcoming fragmentation of service delivery ecosystems.

INTRODUCTION: Population health involves integration of health, education, and social services to keep a defined population healthy, to address health challenges holistically, and to assist with the realities of being mortal. The fragmentation of the US population health delivery system is addressed. The impacts of this fragmentation on the treatment of substance abuse in the United States are considered. Innovations needed to overcome this fragmentation are proposed. APPROACH: Treatment capacity issues, including scheduling practices, are discussed. Costs of treatment and lack of treatment are considered. Models of integrated care delivery are reviewed. Potential innovations from systems science, behavioral economics, and social networks are considered. The implications of these innovations are discussed in terms of information technology (IT) systems and governance. CONCLUSIONS: Enormous savings are possible with more integrated treatment. Based on a range of empirical findings, it is argued that investments of these resources in integrated delivery of care have the potential to dramatically improve health outcomes, thereby significantly reducing the costs of population health.

Developing a Policy Flight Simulator to Facilitate the Adoption of an Evidence-Based Intervention.

While the use of evidence-based interventions (EBIs) has been advocated by the medical research community for quite some time, uptake of these interventions by healthcare providers has been slow. One possible explanation is that it is challenging for providers to estimate impacts of a specific EBI on their particular organization. To address that concern, we developed and evaluated a type of simulation called a policy flight simulator to determine if it could improve the adoption decision about a specific EBI, the transitional care model (TCM). The TCM uses an advanced practice nurse-led model of care to transition older adults with multiple chronic conditions from a hospitalization to home. An evaluation by a National Advisory Committee, made up of senior representatives from various stakeholders in the U.S. healthcare system, found the policy flight simulator to be a useful tool that has the potential to better inform adoption decisions. This paper describes the simulation development effort and documents lessons learned that may be useful to the healthcare modeling community and those interested in using simulation to support decisions based on EBIs.

Learning in the health care enterprise.

INTRODUCTION: The overall enterprise of health care delivery is considered. The 4 levels of the enterprise include clinical practices, processes that provide capabilities and information, structure that includes the business entities involved, and ecosystem that includes Centers for Medicare and Medicaid Services and Congress, as well as societal values and norms. It is argued that the enterprise of health care delivery needs to be transformed to enable high-quality, affordable care for everyone. DISCUSSION: The constructs of enterprise transformation and organizational learning are reviewed. The distinction of single-loop versus double-loop learning is discussed and illustrated for all levels of the health care delivery enterprise. Three health care examples are used to elaborate this distinction-cancer, population health, and health IT. Four strategies are outlined that the health care delivery enterprise can use to more effectively learn at all levels of the enterprise. CONCLUSIONS: This overall line of reasoning suggests several important research issues. The health care delivery enterprise involves much more than treating disease and paying for it. We need to improve our methods and tools for addressing the overall enterprise. Research is also needed on better means for portraying consequences of decisions to the full range of stakeholders in the enterprise. In general, the overall goal should be a healthy, educated, and productive population that is competitive in the global marketplace. We need to better understand the available levers for achieving this goal and how to best portray the intricacies of the overall enterprise to motivate those who can pull these levers to do so.