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.

Best Practices for a Novel EMS-Based Naloxone Leave behind Program.

BACKGROUND: Increasing naloxone access has been identified as a primary strategy to reduce opioid overdose deaths. To supplement community naloxone training and distribution access points, EMS systems have instituted public safety-based naloxone leave behind (NLB) programs that allow emergency medical responders to distribute "leave behind" naloxone kits on the scene of an overdose. This model presents an opportunity to expand naloxone access for individuals at high risk for future overdoses. Objectives: To evaluate the preliminary outcomes of a novel EMS-based NLB program in Howard County, Maryland. Methods: This exploratory study involved analysis of data from the Howard County NLB Program. Basic statistical analysis of program performance metrics and participant demographic characteristics were performed. Results: From June 2018 to June 2019, Howard County Department of Fire and Rescue Services responded to 239 overdose calls and distributed 120 naloxone kits to individuals on the scene of an overdose, a 50.21% distribution rate. The HCNLB program connected 143 patients (59.83%) to peer recovery specialists. Among the 143 patients linked to peer recovery support specialist services, 87 (60.84%) had accepted an NLB kit from EMS. The fully adjusted logistic regression model revealed that those whose kit was left with a family member on the scene were 5.16 times more likely to be connected to peer support specialists (OR = 5.16, CI= 2.35 - 11.29, p = 0.000) while those whose kit was left with a friend or given directly to the patient were 3.69 times (OR = 3.69, CI= 1.13 - 12.06, p < 0.05) and 2.37 times (OR = 2.37, CI= 1.10 - 5.14, p < 0.05) more likely, respectively, to be connected to follow up services as compared to those who did not accept a kit, controlling for other variables in the model. Conclusion: This study highlights the importance of engaging an individual's family and social network when offering connections to treatment and recovery resources. NLB initiatives can potentially augment existing community-based naloxone training structures, thus widening the scope of the life-saving drug and reaching those most at risk of dying from an opioid overdose.

Diagnosis Prevalence and Comorbidity in a Population of Mobile Integrated Community Health Care Patients.

INTRODUCTION: Frequent calls to 911 and requests for emergency services by individuals place a costly burden on emergency response systems and emergency departments (EDs) in the United States. Many of the calls by these individuals are non-emergent exacerbations of chronic conditions and could be treated more effectively and cost efficiently through another health care service. Mobile integrated community health (MICH) programs present a possible partial solution to the over-utilization of emergency services by addressing factors which contribute to a patient's likelihood of frequent Emergency Medical Services (EMS) use. To provide effective care to eligible individuals, MICH providers must have a working understanding of the common conditions they will encounter. OBJECTIVE: The purpose of this descriptive study was to evaluate the diagnosis prevalence and comorbidity among participants in the Queen Anne's County (Maryland USA) MICH Program. This fundamental knowledge of the most common medical conditions within the MICH Program will inform future mobile integrated health programs and providers. METHODS: This study examined preliminary data from the MICH Program, as well as 2017 Maryland census data. It involved secondary analysis of de-identified patient records and descriptive statistical analysis of the disease prevalence, degree of comorbidity, insurance coverage, and demographic characteristics among 97 program participants. Diagnoses were grouped by their ICD-9 classification codes to determine the most common categories of medical conditions. Multiple linear regression models and chi-squared tests were used to assess the association between age, sex, race, ICD-9 diagnosis groups, and comorbidity among program enrollees. RESULTS: Results indicated the most prevalent diagnoses included hypertension, high cholesterol, esophageal reflux, and diabetes mellitus. Additionally, 94.85% of MICH patients were comorbid; the number of comorbidities per patient ranged from one to 13 conditions, with a mean of 5.88 diagnoses per patient (SD=2.74). CONCLUSION: Overall, patients in the MICH Program are decidedly medically complex and may be well-suited to additional community intervention to better manage their many conditions. The potential for MICH programs to simultaneously improve patient outcomes and reduce health care costs by expanding into larger public health and addressing the needs of the most vulnerable citizens warrants further study.ScharfBM, BissellRA, TrevittJL, JenkinsJL.Diagnosis prevalence and comorbidity in a population of mobile integrated community health care patients.Prehosp Disaster Med. 2019;34(1):46-55.