"The most prominent example of targeting readmissions for cost and quality reform is the recent establishment of the Hospital Readmissions Reduction Program in the United States, which enacts penalties for hospitals that have above-average hospital readmission rates [10,11]. While this endeavor focuses on certain medical conditions, its development should raise awareness regarding readmissions in all fields . "
[Show abstract][Hide abstract] ABSTRACT: Understanding risk factors that increase readmission rates may help enhance patient education and set system-wide expectations. We aimed to provide benchmark data on causes and predictors of readmission following inpatient plastic surgery.
The 2011 National Surgical Quality Improvement Program dataset was reviewed for patients with both "Plastics" as their recorded surgical specialty and inpatient status. Readmission was tracked through the "Unplanned Readmission" variable. Patient characteristics and outcomes were compared using chi-squared analysis and Student's t-tests for categorical and continuous variables, respectively. Multivariate regression analysis was used for identifying predictors of readmission.
A total of 3,671 inpatient plastic surgery patients were included. The unplanned readmission rate was 7.11%. Multivariate regression analysis revealed a history of chronic obstructive pulmonary disease (COPD) (odds ratio [OR], 2.01; confidence interval [CI], 1.12-3.60; P=0.020), previous percutaneous coronary intervention (PCI) (OR, 2.69; CI, 1.21-5.97; P=0.015), hypertension requiring medication (OR, 1.65; CI, 1.22-2.24; P<0.001), bleeding disorders (OR, 1.70; CI, 1.01-2.87; P=0.046), American Society of Anesthesiologists (ASA) class 3 or 4 (OR, 1.57; CI, 1.15-2.15; P=0.004), and obesity (body mass index ≥30) (OR, 1.43; CI, 1.09-1.88, P=0.011) to be significant predictors of readmission.
Inpatient plastic surgery has an associated 7.11% unplanned readmission rate. History of COPD, previous PCI, hypertension, ASA class 3 or 4, bleeding disorders, and obesity all proved to be significant risk factors for readmission. These findings will help to benchmark inpatient readmission rates and manage patient and hospital system expectations.
Archives of Plastic Surgery 03/2014; 41(2):116-21. DOI:10.5999/aps.2014.41.2.116
"The inclusion of the Hospital Readmission Reduction Program (HRRP) in the Affordable Care Act represents a movement toward high powered incentives to reduce hospital readmission. This has spurred a concomitant rise in research interest on this topic (Kangovi and Grande, 2011; Joynt and Jha, 2013; Williams, 2013). "
[Show abstract][Hide abstract] ABSTRACT: All-cause readmission to inpatient care is of wide policy interest in the United States and a number of other countries (Centers for Medicare and Medicaid Services, in the United Kingdom by the National Centre for Health Outcomes Development, and in Australia by the Australian Institute of Health and Welfare). Contemporary policy efforts, including high powered incentives embedded in the current US Hospital Readmission Reduction Program, and the organizationally complex interventions derived in anticipation of this policy, have been touted based on potential cost savings. Strong incentives and resulting interventions may not enjoy the support of a strong theoretical model or the empirical research base that are typical of strong incentive schemes. We examine the historical broad literature on the issue, lay out a 'full' conceptual organizational model of patient transitions as they relate to the hospital, and discuss the strengths and weaknesses of previous and proposed policies. We use this to set out a research and policy agenda on this critical issue rather than attempt to conduct a comprehensive structured literature review. We assert that researchers and policy makers should consider more fundamental societal issues related to health, social support and health literacy if progress is going to be made in reducing readmissions.
Health Economics Policy and Law 08/2013; 9(2):1-21. DOI:10.1017/S1744133113000340 · 1.33 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.