The Revolution Will Be Hard to Evaluate: How Co-Occurring Policy Changes Affect Research on the Health Effects of Social Policies.

Extensive empirical health research leverages variation in the timing and location of policy changes as quasi-experiments. Multiple social policies may be adopted simultaneously in the same locations, creating co-occurrence that must be addressed analytically for valid inferences. The pervasiveness and consequences of co-occurring policies have received limited attention. We analyzed a systematic sample of 13 social policy databases covering diverse domains including poverty, paid family leave, and tobacco use. We quantified policy co-occurrence in each database as the fraction of variation in each policy measure across different jurisdictions and times that could be explained by covariation with other policies. We used simulations to estimate the ratio of the variance of effect estimates under the observed policy co-occurrence to variance if policies were independent. Policy co-occurrence ranged from very high for state-level cannabis policies to low for country-level sexual minority-rights policies. For 65% of policies, greater than 90% of the place-time variation was explained by other policies. Policy co-occurrence increased the variance of effect estimates by a median of 57-fold. Co-occurring policies are common and pose a major methodological challenge to rigorously evaluating health effects of individual social policies. When uncontrolled, co-occurring policies confound one another, and when controlled, resulting positivity violations may substantially inflate the variance of estimated effects. Tools to enhance validity and precision for evaluating co-occurring policies are needed.

Outcomes after ultramassive transfusion in the modern era: An Eastern Association for the Surgery of Trauma multicenter study.

BACKGROUND: Despite the widespread institution of modern massive transfusion protocols with balanced blood product ratios, survival for patients with traumatic hemorrhage receiving ultramassive transfusion (UMT) (defined as ≥20 U of packed red blood cells [RBCs]) in 24 hours) remains low and resource consumption remains high. Therefore, we aimed to identify factors associated with mortality in trauma patients receiving UMT in the modern resuscitation era. METHODS: An Eastern Association for the Surgery of Trauma multicenter retrospective study of 461 trauma patients from 17 trauma centers who received ≥20 U of RBCs in 24 hours was performed (2014-2019). Multivariable logistic regression and Classification and Regression Tree analysis were used to identify clinical characteristics associated with mortality. RESULTS: The 461 patients were young (median age, 35 years), male (82%), severely injured (median Injury Severity Score, 33), in shock (median shock index, 1.2; base excess, -9), and transfused a median of 29 U of RBCs, 22 U of fresh frozen plasma (FFP), and 24 U of platelets (PLT). Mortality was 46% at 24 hours and 65% at discharge. Transfusion of RBC/FFP ≥1.5:1 or RBC/PLT ≥1.5:1 was significantly associated with mortality, most pronounced for the 18% of patients who received both RBC/PLT and RBC/FFP ≥1.5:1 (odds ratios, 3.11 and 2.81 for mortality at 24 hours and discharge; both p < 0.01). Classification and Regression Tree identified that age older than 50 years, low initial Glasgow Coma Scale, thrombocytopenia, and resuscitative thoracotomy were associated with low likelihood of survival (14-26%), while absence of these factors was associated with the highest survival (71%). CONCLUSION: Despite modern massive transfusion protocols, one half of trauma patients receiving UMT are transfused with either RBC/FFP or RBC/PLT in unbalanced ratios ≥1.5:1, with increased associated mortality. Maintaining focus on balanced ratios during UMT is critical, and consideration of advanced age, poor initial mental status, thrombocytopenia, and resuscitative thoracotomy can aid in prognostication. LEVEL OF EVIDENCE: Prognostic, level III.

The DISTANCE study: Determining the impact of social distancing on trauma epidemiology during the COVID-19 epidemic-An interrupted time-series analysis.

BACKGROUND: The large-scale social distancing efforts to reduce SARS-CoV-2 transmission have dramatically changed human behaviors associated with traumatic injuries. Trauma centers have reported decreases in trauma volume, paralleled by changes in injury mechanisms. We aimed to quantify changes in trauma epidemiology at an urban Level I trauma center in a county that instituted one of the earliest shelter-in-place orders to inform trauma care during future pandemic responses. METHODS: A single-center interrupted time-series analysis was performed to identify associations of shelter-in-place with trauma volume, injury mechanisms, and patient demographics in San Francisco, California. To control for short-term trends in trauma epidemiology, weekly level data were analyzed 6 months before shelter-in-place. To control for long-term trends, monthly level data were analyzed 5 years before shelter-in-place. RESULTS: Trauma volume decreased by 50% in the week following shelter-in-place (p < 0.01), followed by a linear increase each successive week (p < 0.01). Despite this, trauma volume for each month (March-June 2020) remained lower compared with corresponding months for all previous 5 years (2015-2019). Pediatric trauma volume showed similar trends with initial decreases (p = 0.02) followed by steady increases (p = 0.05). Reductions in trauma volumes were due entirely to changes in nonviolent injury mechanisms, while violence-related injury mechanisms remained unchanged (p < 0.01). CONCLUSION: Although the shelter-in-place order was associated with an overall decline in trauma volume, violence-related injuries persisted. Delineating and addressing underlying factors driving persistent violence-related injuries during shelter-in-place orders should be a focus of public health efforts in preparation for future pandemic responses. LEVEL OF EVIDENCE: Epidemiological study, level III.