Patient demographics demonstrate that a majority of MSI cases were male and younger than 35 years of age . Major mechanisms of trauma included RTAs , falls , and assault . Of those involved in RTAs, a substantial proportion involved motorcycles while over one-quarter of accidents involved a pedestrian being struck . The majority of patients were transported from another health facility , while other patients were transported from the street or from home . Clinical characteristics of this cohort in Table 1 demonstrate approximately equal numbers of open and closed fractures . The most common anatomical regions of these fractures and injuries included the lower extremity , upper extremity , craniofacial , abdomen-pelvis , and thorax . The most common abnormal vital signs included tachycardia , hypotension , and tachypnea . Approximately 1 in 10 patients had a Glasgow Coma Scale score of 12 or below, with 24 patients’ scores ranging from 9-12 and 14 patient scores ranging from 3-8 . Care delivery metrics divided between ED outcomes and in-hospital outcomes are shown in Table 2. In the ED, a trauma intervention was performed for approximately three out of every four patients . Most common trauma interventions included traction or splinting , wound care , and hemorrhage control . Antibiotics and tetanus antitoxin were also commonly administered for fractures , although they were more frequently given in the case of open fractures . Other common emergency procedures included analgesic medication , intravenous liquid infusion , and endotracheal intubation , along with less common interventions such as transfusion of blood products and oxygen supplementation.In over four out of every five cases, an emergency consultation was obtained ,cannabis grow equipment most commonly from orthopedics , acute care surgery , and neurosurgery.

In a majority of cases, laboratory tests and imaging tests were ordered . Nearly three of every four patients were admitted to the hospital , with the most common admitting wards comprising orthopedics , surgical , and neurosurgery . As seen in Table 2, analysis of in-hospital care and outcomes showed that a majority of patients required operative management . Most common procedures included open reduction , wound debridement , and closed reduction with external fixation . A lesser percentage of the in-hospital patients required intensive care after admission or suffered from hospital complications . Patient outcomes varied from discharges to transfers to deaths in hospital . Baseline characteristics in Table 3 highlight the similarities and differences among the total of 674 patients seen prior to and following the implementation of the EMTP. Several patient characteristics did not differ between the pre-EMTP and post-EMTP cohorts, including age, gender, proportion of open fractures, proportion of RTAs, heart rate, and systolic blood pressure. Overall, there was significant improvement in ED outcomes after the implementation of EM training at UTH-K. Results demonstrate improvement in the three outcomes of interest. Specifically, there was a decrease in the ED mortality prevalence in patients with MSI by 89.9%, from 2.51% to 0.25% . In the population of patients seeking emergency care for MSI, this study found significant improvements in mortality and complication rates, length of stay, and an array of secondary outcomes in association with the implementation of EMTP. The training curriculum taught by EM faculty is thought to have played a key role in the improvement of these outcomes. This curriculum included specific longitudinal educational trainings on the diagnosis and treatments of MSI provided through lectures and workshops that all residents completed. These findings help to demonstrate the potential importance of investing in the training of formal EM specialists to address the large burden of morbidity and mortality associated with MSI in LMICs.

It has been previously proposed that relatively simple interventions in areas such as emergency triage, communication, and education and supervision could lead to reductions in LMIC mortality in the ED, where up to 10-15% of all deaths occur.The study demonstrates a temporal association between MSI outcomes in the ED and the inception of an EMTP, underlining the importance of developing such programs. While many LMIC governments do not list EM in their medical education priorities, they could consider doing so to tackle the treatment of such a high volume of patients with acute health problems.Understanding the patient population, anatomical distribution of fractures, and mechanisms of injury could allow for more practical incorporation into the EMTP’s future MSI curriculum. This understanding may also aid in proper diagnosis and treatment of the growing burden of MSI cases, a critical step for improving patient outcomes. Moreover, these epidemiological results, to an extent, confirm those of another research team that studied traumatic injuries in Rwanda’s pre-hospital service, an epidemiological profile that showed nearly one-fourth of injured patients suffered from a fracture.3 Most importantly, the epidemiological patterns and EMTP results suggest the need for reducing MSI morbidity and mortality through expanding emergency care training programs. Although this evidence suggests an association with improved outcomes among patients with MSI with Rwanda’s first EM residency program, further prospective evaluation of cases with MSI are needed to demonstrate reliability of these improvements over time. Moreover, similar epidemiological and training evaluation studies are needed in other African countries to effectively understand and develop scale MSI treatments.Although we used formalized protocols, the design resulted in an inability to identify a proportion of cases due to incomplete medical records and some missing data among included cases, which could have biased the results.

Overall, it appears that some intervention data was prioritized and thus better collected in comparison to other interventions. For example, the fact that oxygen supplementation was recorded as less used than intubation, demonstrates an inherent bias in recording interventions that are now more commonplace in the EM setting. In another example, although the GCS and vital signs in the pre-EMTP group are slightly different, it is worth noting that preliminary results show both GCS and vital signs were better recorded in the post-EMTP group vs pre-EMTP group . As better documentation practices were emphasized during EMTP implementation, this improvement demonstrates the inherent differences between provider training in each group, which may have led to more accurate GCS scores and vital signs in the post-EM group. The present study was performed at a single tertiary-care hospital, which may limit the generalizability of the findings to health delivery venues with less resource availability. Furthermore,cannabis cultivation technology due to lack of detailed information on prehospital and interfacility care provided for patients transported from various origins, controlling for prehospital interventions was not possible. Future studies should attempt to account for such variables, especially given that a majority of patients presented from other facilities. Future studies should also attempt to differentiate patients based on varying levels of acuity, as this study’s inclusion of transfer patients likely led to a higher-acuity patient population. Additionally, general medical, technological, and other secular advances over the course of the study cannot be ignored, as healthcare does not occur in a vacuum. Many advances in Rwanda’s healthcare system have occurred in the last several years as previously noted, and the EMTP’s impact cannot be isolated due to the observational nature of this study.However, it is worth noting from the results that changes to patient outcomes in the ED setting outperformed those same outcomes in the in-hospital setting over the same course of years, minimizing the role that technological advances played in improving outcomes. Lastly, the inclusion of patients with life-threatening injuries who also have fractures had the potential to confound results. Future research might exclude patients who require operative intervention for indications external to musculoskeletal trauma.Short-term outcomes – including return emergency department visits – after discharge from the ED are used as internal quality metrics, as short-term revisits might represent medical errors or failures in care.Although interventions to reduce return visits have largely been unsuccessful,it is possible that these efforts did not adequately target high-risk patients.The ability to accurately identify which patients are more likely to revisit the ED could improve treatment and disposition decisions, and also allow EDs and health systems to develop more focused interventions. Previous work has identified some predictors of return visits,although these studies are limited by investigating only a subset of patients, restriction to one or few sites,focus on non-U.S. hospitals,reliance on complicated instruments,focus on medical errors,focus on admissions, or use of overly-broad definition of discharge failure.We used a unique dataset with encounter-level data to evaluate the predictors of return visits. Our goal was to identify which patient demographics and medical conditions were most associated with short-term revisits.

In addition, we hypothesized that frequency of recent previous visits – specifically, number of visits within the previous six months – would have a stronger association with return visits than other patient characteristics , and that this pattern would be observed even after controlling for hospital and community characteristics. Data were recorded in the medical record at each hospital. Vituity collects this data through monthly electronic data feeds by its medical billing company, Med America Billing Systems, Inc, which stores records in Application System / 400 and PostgreSQL. Patient visits were linked through Medical Person Identification number – a unique patient identifier derived by an algorithm taking into consideration patient name, date of birth, Social Security number, and address. This methodology allowed for linkage across sites, although visits at non-Vituity sites were not observable. Any visit had the potential to be defined as an index visit. Patient characteristics included age, sex, insurance type , and the number of ED visits they had in the six months prior to the index visit. We reduced previous ED visits to an indicator variable for two or more previous visits in order to identify a characteristic that was easily observed and easy to apply to patients in real time. Visit characteristics included acuity level, primary diagnosis, and Charlson comorbidity index. Primary diagnoses were categorized using International Classification of Diseases, 9th and 10th revisions Clinical Categorization Software categories. These categories were developed and defined by the Healthcare Cost and Utilization Project , under the AHRQ, and this scheme has been used in a number of studies.Because of the large number of categories, we further restricted diagnoses to the diagnoses that had at least 10,000 observations and were associated with 14-day revisits in bivariate analysis; among these, we included the five most common diagnoses for index visits and for revisits. Charlson comorbidity index was calculated for all visits based on up to 12 separate ICD codes per visit .Hospital characteristics included size , and turnaround time to discharge for 2015. TAT-D is a quality metric measuring the median time between patient arrival and discharge at the hospital level for a given year. Volume was broken into four categories as defined by the Centers for Medicare & Medicaid Services: fewer than 20,000 encounters = low volume; 20,000 – 39,999 encounters = medium volume; 40,000 – 59,999 encounters = high volume; and greater than or equal to 60,000 encounters = very high volume. Community characteristics were comprised of zip code and county-level characteristics: median household income for zip code, number of hospitals per 1000 population in the county, and county.We excluded from the study providers working for the firm for fewer than 60 days within the study period or accounting for fewer than 60 encounters. To test whether there was a different likelihood in return visit according to acuity level, we included interaction terms between MD/DO and acuity level; given the difference in scope of practice for APP, interactions between APP and acuity level were not modeled. Over the study period, there were 8,334,885 index encounters. After excluding visits resulting in a disposition other than discharge and excluding visits with missing data, the total sample size was 6,699,717 . Table 1 shows the patient, visit, hospital, and physician characteristics at index visit for all encounters, and stratified by discharge vs admission. These descriptive statistics are also shown for encounters resulting in a 14-day return and for those who returned and were admitted to the hospital. In the multivariate model including patient, hospital, and community characteristics , the highest predictor of return visit within 14 days was whether or not the patient had two or more visits in the previous six months: OR = 3.06 .