No abstract

Hospital readmissions are common and costly; this has resulted in their emergence as a key target and quality indicator in the current era of renewed focus on cost containment. However, many concerns remain about the use of readmissions as a hospital quality indicator and about how to reduce hospital readmissions. These concerns stem in part from deficiencies in the state of the science of transitional care. A conceptualization of the “ideal” discharge process could help address these deficiencies and move the state of the science forward. We describe an ideal transition in care, explicate the key components, discuss its implications in the context of recent efforts to reduce readmissions, and suggest next steps for policymakers, researchers, health care administrators, practitioners, and educators.

Objectives Hospital discharges to post-acute care (PAC) facilities have increased rapidly. This increase may lead to more hospital readmissions from PAC facilities, which are common and poorly understood. We sought to determine the risk factors and timing for hospital readmission from PAC facilities and evaluate the impact of readmission on patient outcomes. Design Retrospective analysis of Medicare Current Beneficiary Survey (MCBS) from 2003–2009. Setting The MCBS is a nationally-representative survey of beneficiaries matched with claims data. Participants Community-dwelling beneficiaries who were hospitalized and discharged to a PAC facility for rehabilitation. Intervention/Exposure Potential readmission risk factors included patient demographics, health utilization, active medical conditions at time of PAC admission, and PAC characteristics. Measurements Hospital readmission during the PAC stay, return to community residence, and all-cause mortality. Results Of 3246 acute hospitalizations followed by PAC facility stays, 739 (22.8%) included at least 1 hospital readmission. The strongest risk factors for readmission included impaired functional status (HR 4.78, 95% CI 3.21–7.10), markers of increased acuity such as need for intravenous medications in PAC (1.63, 1.39–1.92), and for-profit PAC ownership (1.43, 1.21–1.69). Readmitted patients had a higher mortality rate at both 30 days (18.9 vs. 8.6%, p<0.001) and 100 days (39.9 vs. 14.5%, p<0.001) even after adjusting for age, comorbidities, and prior health care utilization (30 days: OR 2.01, 95% CI 1.60–2.54; 100 days: OR 3.79, 95% CI 3.13–4.59). Conclusions Hospital readmission from PAC facilities is common and associated with a high mortality rate. Readmission risk factors may signify inadequate transitional care processes or a mismatch between patient needs and PAC resources.

BackgroundSystematic attempts to identify best practices for reducing hospital readmissions have been limited without a comprehensive framework for categorizing prior interventions. Our research aim was to categorize prior interventions to reduce hospital readmissions using the ten domains of the Ideal Transition of Care (ITC) framework, to evaluate which domains have been targeted in prior interventions and then examine the effect intervening on these domains had on reducing readmissions.MethodsReview of literature and secondary analysis of outcomes based on categorization of English-language reports published between January 1975 and October 2013 into the ITC framework.Results66 articles were included. Prior interventions addressed an average of 3.5 of 10 domains; 41% demonstrated statistically significant reductions in readmissions. The most common domains addressed focused on monitoring patients after discharge, patient education, and care coordination. Domains targeting improved communication with outpatient providers, provision of advanced care planning, and ensuring medication safety were rarely included. Increasing the number of domains included in a given intervention significantly increased success in reducing readmissions, even when adjusting for quality, duration, and size (OR per domain, 1.5, 95% CI 1.1 - 2.0). The individual domains most associated with reducing readmissions were Monitoring and Managing Symptoms after Discharge (OR 8.5, 1.8 - 41.1), Enlisting Help of Social and Community Supports (OR 4.0, 1.3 - 12.6), and Educating Patients to Promote Self-Management (OR 3.3, 1.1 - 10.0).ConclusionsInterventions to reduce hospital readmissions are frequently unsuccessful; most target few domains within the ITC framework. The ITC may provide a useful framework to consider when developing readmission interventions.Electronic supplementary materialThe online version of this article (doi:10.1186/1472-6963-14-423) contains supplementary material, which is available to authorized users.

PRISM is useful to identify contextual factors that influence implementation, modification, uptake, and evaluation of health services programs.

BackgroundMany health outcomes and implementation science studies have demonstrated the importance of tailoring evidence-based care interventions to local context to improve fit. By adapting to local culture, history, resources, characteristics, and priorities, interventions are more likely to lead to improved outcomes. However, it is unclear how best to adapt evidence-based programs and promising innovations. There are few guides or examples of how to best categorize or assess health-care adaptations, and even fewer that are brief and practical for use by non-researchers.Materials and methodsThis study describes the importance and potential of assessing adaptations before, during, and after the implementation of health systems interventions. We present a promising multilevel and multimethod approach developed and being applied across four different health systems interventions. Finally, we discuss implications and opportunities for future research.ResultsThe four case studies are diverse in the conditions addressed, interventions, and implementation strategies. They include two nurse coordinator-based transition of care interventions, a data and training-driven multimodal pain management project, and a cardiovascular patient-reported outcomes project, all of which are using audit and feedback. We used the same modified adaptation framework to document changes made to the interventions and implementation strategies. To create the modified framework, we started with the adaptation and modification model developed by Stirman and colleagues and expanded it by adding concepts from the RE-AIM framework. Our assessments address the intuitive domains of Who, How, When, What, and Why to classify and organize adaptations. For each case study, we discuss how the modified framework was operationalized, the multiple methods used to collect data, results to date and approaches utilized for data analysis. These methods include a real-time tracking system and structured interviews at key times during the intervention. We provide descriptive data on the types and categories of adaptations made and discuss lessons learned.ConclusionThe multimethod approaches demonstrate utility across diverse health systems interventions. The modified adaptations model adequately captures adaptations across the various projects and content areas. We recommend systematic documentation of adaptations in future clinical and public health research and have made our assessment materials publicly available.

Medicare's payment reforms in the 1990s significantly affected hospital length of stay and post-acute care (PAC) (eg, skilled nursing or rehabilitation) facility use. 1 , 2 H o w e v e r , f e w s t u d i e s d e s c r i b e c o nt e m p o r a r y length of stay and postdisc h a rge c a r e t r e n d s i n a nationally representative sample of Medicare and non-Medicare patients. We sought to understand these trends using the National Hospital Discharge Survey (NHDS) from 1996 to 2010.Methods | The NHDS is a nationally representative annual probability sample of discharges from hospitals in all 50 states. 3 We included all hospital discharges of patients 18 years or older, excluding patients transferred to other hospitals, discharges against medical advice, discharges without a destination coded, or hospital lengths of stay more than 31 days (together, <7% of all discharges). We used NHDS definitions for discharge to home or a care facility.We evaluated trends in discharges to PAC facilities as well as length of stay over the 15-year period, then calculated relative percentage changes for each year, using 1996 rates as a baseline. To account for the aging of the population, all trends were age-adjusted by the US Census population in 2003 (www.census.gov). The derived age-specific estimates for each individual year were weighted to reflect the age distribution in 2003, the midpoint of our analysis. Analyses were conducted using SAS statistical software (version 9.

No abstract