Implementation of a prehospital whole blood program: Lessons learned.

Early blood administration by Emergency Medical Services (EMS) to patients suffering from hemorrhagic shock improves outcomes. Prehospital blood programs represent an invaluable resuscitation capability that directly addresses hemorrhagic shock and mitigates subsequent multiple organ dysfunction syndrome. Prehospital blood programs must be thoughtfully planned, have multiple safeguards, ensure adequate training and credentialing processes, and be responsible stewards of blood resources. According to the 2022 best practices model by Yazer et al, the four key pillars of a successful prehospital program include the following: (1) the rationale for the use and a description of blood products that can be transfused in the prehospital setting, (2) storage of blood products outside the hospital blood bank and how to move them to the patient in the prehospital setting, (3) prehospital transfusion criteria and administration personnel, and (4) documentation of prehospital transfusion and handover to the hospital team.  This concepts paper describes our operational experience using these four pillars to make Maryland's inaugural prehospital ground-based low-titer O-positive whole blood program successful. These lessons learned may inform other EMS systems as they establish prehospital blood programs to help improve outcomes and enhance mass casualty response.

Sample size considerations for micro-randomized trials with binary proximal outcomes.

Micro-randomized trials (MRTs) are a novel experimental design for developing mobile health interventions. Participants are repeatedly randomized in an MRT, resulting in longitudinal data with time-varying treatments. Causal excursion effects are the main quantities of interest in MRT primary and secondary analyses. We consider MRTs where the proximal outcome is binary and the randomization probability is constant or time-varying but not data-dependent. We develop a sample size formula for detecting a nonzero marginal excursion effect. We prove that the formula guarantees power under a set of working assumptions. We demonstrate via simulation that violations of certain working assumptions do not affect the power, and for those that do, we point out the direction in which the power changes. We then propose practical guidelines for using the sample size formula. As an illustration, the formula is used to size an MRT on interventions for excessive drinking. The sample size calculator is implemented in R package MRTSampleSizeBinary and an interactive R Shiny app. This work can be used in trial planning for a wide range of MRTs with binary proximal outcomes.

Profile Matching for the Generalization and Personalization of Causal Inferences.

We introduce profile matching, a multivariate matching method for randomized experiments and observational studies that finds the largest possible unweighted samples across multiple treatment groups that are balanced relative to a covariate profile. This covariate profile can represent a specific population or a target individual, facilitating the generalization and personalization of causal inferences. For generalization, because the profile often amounts to summary statistics for a target population, profile matching does not always require accessing individual-level data, which may be unavailable for confidentiality reasons. For personalization, the profile comprises the characteristics of a single individual. Profile matching achieves covariate balance by construction, but unlike existing approaches to matching, it does not require specifying a matching ratio, as this is implicitly optimized for the data. The method can also be used for the selection of units for study follow-up, and it readily applies to multivalued treatments with many treatment categories. We evaluate the performance of profile matching in a simulation study of the generalization of a randomized trial to a target population. We further illustrate this method in an exploratory observational study of the relationship between opioid use and mental health outcomes. We analyze these relationships for three covariate profiles representing: (i) sexual minorities, (ii) the Appalachian United States, and (iii) the characteristics of a hypothetical vulnerable patient. The method can be implemented via the new function profmatch in the designmatch package for R, for which we provide a step-by-step tutorial.

Impacts of an EMS Hospital Liaison Program on Ambulance Offload Times: A Preliminary Analysis.

INTRODUCTION: Ambulance patients who are unable to be quickly transferred to an emergency department (ED) bed represent a key contributing factor to ambulance offload delay (AOD). Emergency department crowding and associated AOD are exacerbated by multiple factors, including infectious disease outbreaks such as the coronavirus disease 2019 (COVID-19) pandemic. Initiatives to address AOD present an opportunity to streamline ambulance offload procedures while improving patient outcomes. STUDY OBJECTIVE: The goal of this study was to evaluate the initial outcomes and impact of a novel Emergency Medical Service (EMS)-based Hospital Liaison Program (HLP) on ambulance offload times (AOTs). METHODS: Ambulance offload times associated with EMS patients transported to a community hospital six months before and after HLP implementation were retrospectively analyzed using proportional significance tests, t-tests, and multiple regression analysis. RESULTS: A proportional increase in incidents in the zero to <30 minutes time category after program implementation (+2.96%; P <.01) and a commensurate decrease in the proportion of incidents in the 30 to <60 minutes category (-2.65%; P <.01) were seen. The fully adjusted regression model showed AOT was 16.31% lower (P <.001) after HLP program implementation, holding all other variables constant. CONCLUSION: The HLP is an innovative initiative that constitutes a novel pathway for EMS and hospital systems to synergistically enhance ambulance offload procedures. The greatest effect was demonstrated in patients exhibiting potentially life-threatening symptoms, with a reduction of approximately three minutes. While small, this outcome was a statistically significant decrease from the pre-intervention period. Ultimately, the HLP represents an additional strategy to complement existing approaches to mitigate AOD.

Gay men's experiences with prostate cancer: Implications for future research.

Gay men's experiences with prostate cancer and its impact on health-related quality of life are poorly understood. This qualitative study explored gay men's experience with prostate cancer with a focus on the emotional, physical, and sexual impact of cancer; support needs; and healthcare interactions. Three semi-structured focus groups of gay men with prostate cancer were conducted. A conventional content analytic approach was used to identify six primary content areas that described poignant aspects of the men's experience with prostate cancer: minority stress, intimacy and sexuality concerns, impact on life outlook, healthcare experiences, social support and the gay community, and intersectional identities.