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BackgroundDischarge delays for non-medical reasons put patients at unnecessary risk for hospital-acquired infections, lead to loss of revenue for hospitals and reduce hospital capacity to treat other patients. The objective of this study was to determine prevalence of, and patient characteristics associated with, delays in discharge at an urban county trauma service.MethodsWe performed a retrospective cohort study with data from Zuckerberg San Francisco General Hospital (ZSFGH), a level-1 trauma center and safety net hospital in San Francisco, California. The study included 1720 patients from the trauma surgery service at ZSFGH. A 'delay in discharge' was defined as days in the hospital, including an initial overnight stay, after all medical needs had been met. We used logistic and zero-inflated negative binomial regression models to test whether the following factors were associated with prolonged, non-medical length of stay: age, gender, race/ethnicity, housing, disposition location, type of insurance, having a primary care provider, primary language and zip code.ResultsOf the 1720 patients, 15% experienced a delay in discharge, for a total of 1147 days (median 1.5 days/patient). The following were statistically significant (p<0.05) predictors of delays in discharge in a multivariable logistic regression model: older age, unhoused status or disposition to home health or postacute care (compared with home discharge) were associated with increased likelihood of delays. Having private insurance or Medicare (compared with public insurance) and discharge against medical advice or absent without leave (compared with home discharge) were associated with reduced likelihood of delays in discharge after all medical needs were met.DiscussionThese results suggest that policymakers interested in reducing non-medical hospital stays should focus on addressing structural determinants of health, such as lack of housing, bottlenecks at postacute care disposition destinations and

BACKGROUND:The United States is the only high-income nation without universal, government-funded or -mandated health insurance employing a unified payment system. The US multi-payer system leaves residents uninsured or underinsured, despite overall healthcare costs far above other nations. Single-payer (often referred to as Medicare for All), a proposed policy solution since 1990, is receiving renewed press attention and popular support. Our review seeks to assess the projected cost impact of a single-payer approach. METHODS AND FINDINGS:We conducted our literature search between June 1 and December 31, 2018, without start date restriction for included studies. We surveyed an expert panel and searched PubMed, Google, Google Scholar, and preexisting lists for formal economic studies of the projected costs of single-payer plans for the US or for individual states. Reviewer pairs extracted data on methods and findings using a template. We quantified changes in total costs standardized to percentage of contemporaneous healthcare spending. Additionally, we quantified cost changes by subtype, such as costs due to increased healthcare utilization and savings due to simplified payment administration, lower drug costs, and other factors. We further examined how modeling assumptions affected results. Our search yielded economic analyses of the cost of 22 single-payer plans over the past 30 years. Exclusions were due to inadequate technical data or assuming a substantial ongoing role for private insurers. We found that 19 (86%) of the analyses predicted net savings (median net result was a savings of 3.46% of total costs) in the first year of program operation and 20 (91%) predicted savings over several years; anticipated growth rates would result in long-term net savings for all plans. The largest source of savings was simplified payment administration (median 8.8%), and the best predictors of net savings were the magnitude of utilization increase, and savings on administrati

BackgroundDischarge delays for non-medical reasons put patients at unnecessary risk for hospital-acquired infections, lead to loss of revenue for hospitals and reduce hospital capacity to treat other patients. The objective of this study was to determine prevalence of, and patient characteristics associated with, delays in discharge at an urban county trauma service.MethodsWe performed a retrospective cohort study with data from Zuckerberg San Francisco General Hospital (ZSFGH), a level-1 trauma center and safety net hospital in San Francisco, California. The study included 1720 patients from the trauma surgery service at ZSFGH. A 'delay in discharge' was defined as days in the hospital, including an initial overnight stay, after all medical needs had been met. We used logistic and zero-inflated negative binomial regression models to test whether the following factors were associated with prolonged, non-medical length of stay: age, gender, race/ethnicity, housing, disposition location, type of insurance, having a primary care provider, primary language and zip code.ResultsOf the 1720 patients, 15% experienced a delay in discharge, for a total of 1147 days (median 1.5 days/patient). The following were statistically significant (p<0.05) predictors of delays in discharge in a multivariable logistic regression model: older age, unhoused status or disposition to home health or postacute care (compared with home discharge) were associated with increased likelihood of delays. Having private insurance or Medicare (compared with public insurance) and discharge against medical advice or absent without leave (compared with home discharge) were associated with reduced likelihood of delays in discharge after all medical needs were met.DiscussionThese results suggest that policymakers interested in reducing non-medical hospital stays should focus on addressing structural determinants of health, such as lack of housing, bottlenecks at postacute care disposition destinations and

BACKGROUND:The United States is the only high-income nation without universal, government-funded or -mandated health insurance employing a unified payment system. The US multi-payer system leaves residents uninsured or underinsured, despite overall healthcare costs far above other nations. Single-payer (often referred to as Medicare for All), a proposed policy solution since 1990, is receiving renewed press attention and popular support. Our review seeks to assess the projected cost impact of a single-payer approach. METHODS AND FINDINGS:We conducted our literature search between June 1 and December 31, 2018, without start date restriction for included studies. We surveyed an expert panel and searched PubMed, Google, Google Scholar, and preexisting lists for formal economic studies of the projected costs of single-payer plans for the US or for individual states. Reviewer pairs extracted data on methods and findings using a template. We quantified changes in total costs standardized to percentage of contemporaneous healthcare spending. Additionally, we quantified cost changes by subtype, such as costs due to increased healthcare utilization and savings due to simplified payment administration, lower drug costs, and other factors. We further examined how modeling assumptions affected results. Our search yielded economic analyses of the cost of 22 single-payer plans over the past 30 years. Exclusions were due to inadequate technical data or assuming a substantial ongoing role for private insurers. We found that 19 (86%) of the analyses predicted net savings (median net result was a savings of 3.46% of total costs) in the first year of program operation and 20 (91%) predicted savings over several years; anticipated growth rates would result in long-term net savings for all plans. The largest source of savings was simplified payment administration (median 8.8%), and the best predictors of net savings were the magnitude of utilization increase, and savings on administrati