Macroeconomic trends and practice models impacting acute care surgery

Acute care surgery (ACS) diagnoses are responsible for approximately a quarter of the costs of inpatient care in the US government, and individuals will be responsible for a larger share of the costs of this healthcare as the population ages. ACS as a specialty thus has the opportunity to meet a significant healthcare need, and by optimizing care delivery models do so in a way that improves both quality and value. ACS practice models that have maintained or added emergency general surgery (EGS) and even elective surgery have realized more operative case volume and surgeon satisfaction. However, vulnerabilities exist in the ACS model. Payer mix in a practice varies by geography and distribution of EGS, trauma, critical care, and elective surgery. Critical care codes constitute approximately 25% of all billing by acute care surgeons, so even small changes in reimbursement in critical care can have significant impact on professional revenue. Staffing an ACS practice can be challenging depending on reimbursement and due to uneven geographic distribution of available surgeons. Empowered by an understanding of economics, using team-oriented leadership inherent to trauma surgeons, and in partnership with healthcare organizations and regulatory bodies, ACS surgeons are positioned to significantly influence the future of healthcare in the USA

Surgical Critical Care of Special Populations (Pregnant, Geriatric, Pediatric)

This review covers the specialized care of populations who present different management challenges when critically injured. The text is divided into three sections: pregnant, geriatric, and pediatric patients. For each population, the discussion focuses on the unique diagnostic and treatment algorithms that the surgical intensivist must consider. In addition to management of trauma in these special populations, other common diagnoses warranting surgical intensive care unit (ICU) admission are reviewed. Current guidelines on diagnostic imaging and medication safety are outlined. Injury prevention and outcomes improvement are an essential component of optimizing trauma care. The epidemiology of traumatic injury within each specialized population is included in this review. Outcomes are discussed in depth, particularly with respect to the geriatric ICU patient, including a section on barriers to disposition, decision-making capacity, and end-of-life care in the surgical ICU.   This review contains 2 figures, 4 tables, and 72 references. Key words: end of life in the ICU, geriatric trauma, injury prevention, pediatric trauma, pregnanc

Trauma center care is associated with reduced readmissions after injury.

BackgroundTrauma center care has been associated with improved mortality. It is not known if access to trauma center care is also associated with reduced readmissions. We hypothesized that receiving treatment at a trauma center would be associated with improved care and therefore would be associated with reduced readmission rates.MethodsWe conducted a retrospective analysis of all hospital visits in California using the Office of Statewide Health Planning and Development Database from 2007 to 2008. All hospital admissions and emergency department visits associated with injury were longitudinally linked. Regions were categorized by whether they had trauma centers. We excluded all patients younger than 18 years. We performed univariate and multivariate regression analyses to determine if readmissions were associated with patient characteristics, length of stay for initial hospitalization, trauma center access, and triage patterns.ResultsA total of 211,504 patients were included in the analysis. Of these, 5,094 (2%) died during the index hospitalization. Of those who survived their initial hospitalization, 79,123 (38%) experienced one or more readmissions to any hospital within 1 year. The majority of these were one-time readmissions (62%), but 38% experienced multiple readmissions. Over 67% of readmissions were unplanned and 8% of readmissions were for a trauma. After controlling for patient variables known to be associated with readmissions, primary triage to a trauma center was associated with a lower odds of readmission (odds ratio, 0.89; p < 0.001). The effect of transport to a trauma center remained significantly associated with decreased odds of readmission at 1 year (odds ratio, 0.96; p < 0.001).ConclusionReadmissions after injury are common and are often unscheduled. While patient factors play a role in this, care at a trauma center is also associated with decreased odds for readmission, even when controlling for severity of injury. This suggests that the benefits of trauma center care extend beyond improvements in mortality to improved long-term outcomes.Level of evidenceEpidemiologic study, level III; therapeutic/care management study, level IV

Trauma center care is associated with reduced readmissions after injury.

BackgroundTrauma center care has been associated with improved mortality. It is not known if access to trauma center care is also associated with reduced readmissions. We hypothesized that receiving treatment at a trauma center would be associated with improved care and therefore would be associated with reduced readmission rates.MethodsWe conducted a retrospective analysis of all hospital visits in California using the Office of Statewide Health Planning and Development Database from 2007 to 2008. All hospital admissions and emergency department visits associated with injury were longitudinally linked. Regions were categorized by whether they had trauma centers. We excluded all patients younger than 18 years. We performed univariate and multivariate regression analyses to determine if readmissions were associated with patient characteristics, length of stay for initial hospitalization, trauma center access, and triage patterns.ResultsA total of 211,504 patients were included in the analysis. Of these, 5,094 (2%) died during the index hospitalization. Of those who survived their initial hospitalization, 79,123 (38%) experienced one or more readmissions to any hospital within 1 year. The majority of these were one-time readmissions (62%), but 38% experienced multiple readmissions. Over 67% of readmissions were unplanned and 8% of readmissions were for a trauma. After controlling for patient variables known to be associated with readmissions, primary triage to a trauma center was associated with a lower odds of readmission (odds ratio, 0.89; p < 0.001). The effect of transport to a trauma center remained significantly associated with decreased odds of readmission at 1 year (odds ratio, 0.96; p < 0.001).ConclusionReadmissions after injury are common and are often unscheduled. While patient factors play a role in this, care at a trauma center is also associated with decreased odds for readmission, even when controlling for severity of injury. This suggests that the benefits of trauma center care extend beyond improvements in mortality to improved long-term outcomes.Level of evidenceEpidemiologic study, level III; therapeutic/care management study, level IV

Probabilistic Detection of Short Events, with Application to Critical Care Monitoring

We describe an application of probabilistic modeling and inference technology to the problem of analyzing sensor data in the setting of an intensive care unit (ICU). In particular, we consider the arterial-line blood pressure sensor, which is subject to frequent data artifacts that cause false alarms in the ICU and make the raw data almost useless for automated decision making. The problem is complicated by the fact that the sensor data are averaged over fixed intervals whereas the events causing data artifacts may occur at any time and often have durations significantly shorter than the data collection interval. We show that careful modeling of the sensor, combined with a general technique for detecting sub-interval events and estimating their duration, enables detection of artifacts and accurate estimation of the underlying blood pressure values. Our model¿s performance identifying artifacts is superior to two other classifiers¿ and about as good as a physician¿s