Introduction Reduction of forearm and wrist fractures is a common practice in the Emergency Centre (EC). EC doctors must be familiar with the appropriate management thereof. The standard treatment of a fracture involves reduction and immobilization. This study aims to describe the diagnostic and management accuracy of EC clinicians using validated vignettes (also used as the reference standard) of adult patients with closed fractures of the forearm or wrist. Methods This is a prospective, cross-sectional study in the form of an electronic questionnaire to address the study aim. A set of vignettes were created and then validated to serve as the control for the study participants. The study was open to emergency medicine consultants, emergency medicine trainees/registrars, medical officers, and community service medical officers employed at a secondary-level public hospital EC in the Cape Town metropole. Comparison is made by the number and proportions of correct and incorrect answers using the vignette reference standard. Data were analysed using ChiSquare (X2). Results For the diagnosis of forearm and wrist fractures, EC clinicians present 86,8% (1309/1508) correct responses (p=0.68) and, for the course of action, 78% (278/354) correct responses (p=0.09). For the overall management of the fractures (diagnostic and course of action), EC clinicians answered correctly to 84,9% (1585/1866) and incorrectly to 15,1% (281/1866), although the difference by each EC clinician group.was not significant (p=0.72). Conclusion In Western Cape, EC doctors appear to fare better than reported in the literature. However, this can not be shown definitively with this dataset. Regular training is necessary for all clinicians working in EC to improve their skills in managing forearm and wrist fractures, including the interpretation of X-ray imaging. Clear and good notes in the patient folder, top-quality X-ray images, good EC work environment, and improvement between doctors communication are other sets of requirements important to help to avoid errors in fracture management.

Background Despite privacy and legal concerns, social media is used to provide real-time clinical support to emergency care providers. It can be particularly beneficial for those in Africa, who might lack adequate training or access to information. This PhD aimed to describe the use of social media as a point-of-care telemedicine tool in facility-based emergency care in Africa, to further inform its use. Methods A scoping review was conducted to map available literature on use, benefits, and risks associated with social media as a point-of-care platform. A mixed methods approach was then taken using a cross-sectional survey and semi-structured interviews to obtain a comprehensive description of use of social media as a point-of-care tool in facility-based emergency care in Africa. Results The scoping review identified 13 publications describing use of social media as a point-of-care tool in emergency medical settings. No studies were located in low-income countries. All studies evaluated WhatsApp use for real-time consultations, and those that assessed reliability found it to be highly reliable for consultations. A total of 70 emergency care providers in African facilities responded to the survey; nearly all worked in low- or lower-middle-income countries. Responses showed that clinicians use social media multiple times each day, primarily to share and receive advice. The majority felt social media positively impacts patient and provider experiences and improves speed and safety. Finally, eight African emergency care providers were interviewed to gain an in-depth understanding of how social media use impacts emergency care. All participants noted routine use for a range of professional purposes, including consultations, administrative tasks, and education. Concerns were mentioned by all participants, including legality, privacy, and lack of employer regulations. Conclusions This dissertation provides insight into social media use of African emergency care physicians, showing that social media use in this group is ubiquitous. Most clinicians use social media multiple times each day for a range of point-of-care purposes, and many feel social media is positively impacting both the patient and provider experiences. Post-doctoral work will focus on developing a framework to guide use of social media in facility-based emergency care in the African setting.

Background The COVID-19 pandemic has profoundly impacted some of the most vulnerable populations in low-resource settings (LRS) across the globe. These settings tend to have underdeveloped healthcare systems that are exceptionally vulnerable to the strain of an outbreak such as SARS-CoV-2. LRS-based clinicians are in need of effective and contextually appropriate triage and assessment tools that have been purpose-designed and validated to aid in evaluating the severity of potential COVID-19 patients. In the context of the COVID-19 crisis, a low-input severity scoring tool could be a cornerstone of ensuring timely access to appropriate care and justified use of critically limited resources. Machine learning was used on data from a retrospective cohort of Sudanese COVID-19 patients to derive a contextually appropriate mortality scale for COVID-19, the African Federation for Emergency Medicine COVID-19 Mortality Scale (AFEM-CMS) model. This MSc aimed to validate the AFEM-CMS, to assist frontline providers in rapidly predicting severe COVID-19 disease in LRS emergency units (EUs) in Sudan. Methods A retrospective quantitative analysis of data collected on adult patients aged 18 years and older screened as potentially positive for COVID-19 was undertaken to validate the AFEMCMS in the same Sudanese setting from which it was derived. Data for this study were collected retrospectively by non-clinical personnel from four government referral hospitals in Sudan's Khartoum State from 01 September 2020 and 31 January 2021. This study's primary outcome was in-hospital mortality due to SARS-CoV-2 infection. A set of predictor variables was collected for all patients based on the requisite inputs for the AFEMCMS tool. The predictor variables comprise demographic and historical data (age and sex), the number of existing comorbidities a patient has on presentation, and a number of clinical inputs (GCS, systolic blood pressure, respiratory rate, heart rate, and pulse oximetry). The AFEM-CMS was validated using C-index measurements (area under the receiver operator curve (AUROC)) in the validation dataset. All analyses were performed in R (version 4.1.0, © The R Foundation) with the dplyr, finalfit, glmnet, mice, pROC, rmda, and tidyverse packages. 4 Missing datapoints were managed using multiple imputation by chained equations (MICE), which imputed values for predictor variables with less than 33% of data points missing. Ethical approvals for this study were obtained from the University of Cape Town and the Sudanese Ministry of Health. Results In this study, the AFEM-CMS was validated against a 936-patient cohort, all of whom All of these included cases met the WHO definitions for suspected, probable, or confirmed SARSCoV-2 infection. Similar to initial derivation outcomes, the tool was found to have reasonable discriminatory power in identifying those at greatest risk of death from COVID-19: The model including pulse oximetry had a C-statistic of 0.732 (95% CI: 0.687-0.777) and the model excluding pulse oximetry had a C-statistic of 0.696 (0.645-0.747). Conclusions This dissertation establishes what is, to our knowledge, the validation of the first COVID-19 mortality prediction tool intentionally designed for frontline providers in LRS. The validation of the AFEM-CMS highlights the feasibility and potential impact of real-time development of clinical tools to improve patient care, even in times of surge in LRS. This study is just one of hundreds of efforts across all resource levels suggesting that rapid use of machine learning methodologies holds promise in improving responses to pandemics and other emergencies. It is our hope that, in future health crises, LRS-based clinicians and researchers can refer to these techniques to inform contextually and situationally appropriate clinical tools and reduce morbidity and mortality.

Thesis (M.Fam. Med.)--University of the Witwatersrand, Faculty of Health Sciences, 2013.

No description available.

Introduction: Emergency Medical Services (EMS) are ideally placed to provide relief of acute pain and discomfort. EMS frequently follow locally prescribed guidelines and have a variety of qualifications each with differing capabilities and scopes of practice. The objectives of this study are to describe prehospital pain management practices by EMS in the Western Cape, South Africa. Methods: A retrospective descriptive survey was undertaken of analgesic drug administration by advanced life support (ALS) paramedics. Patient care records (PCRs) generated in t he City of Cape Town during an 11 month period containing administrations of Morphine, Ketamine, Nitrates and 50% Nitrous Oxide/Oxygen were randomly sampled. Variables studied were drug dose, dose frequency, and route of administration, patient age, gender, disorder and call type as well as qualification and experience level of the provider. Results: A total of 530 PCRs were included (N=530). Morphine was administered in 70% (95% CI 66 - 74, n=371) of cases, Nitrates in 37 %(95% CI 33 - 41, n=197) and Ketamine in 1.7% (95% CI 1 - 3, n=9) of cases. A total of 5mg or less of Morphine was administered in 75% (95% CI 70 - 79, n=278), with the mean dose being 4mg (IQR 3 - 6). Single doses were administered in 72.2% (95% CI, 67 - 77, n=268) of Morphine administrations, 56% (95% CI, 21 - 86, n=5) of Ketamine administrations and 82% (95% CI, 76 - 87, n=161) of Nitrate administrations. Chest pain was the reason for pain management in 43% (n=226) of cases. ALS providers have a median experience level of 2 years (IQR2 - 4). Conclusion: ALS providers in the Western Cape appear to use low doses of Morphine, with most analgesia administered as a single dose. Chest pain is an important reason for drug administration in acute prehospital pain. Paramedics do not appear to be using a weight based nor a titration based strategy.

Background: Acute respiratory failure is becoming a frequent phenomenon in the emergency department due to increasing life expectancy, and in the last two decades the number of presentations has more than doubled. Non-invasive ventilation has become the treatment modality of choice in selected patients, with a significant reduction of mortality in these cases. However, adequate monitoring of clinical and blood gas parameters is crucial to ensure treatment targets are met. Objective: This study aims to evaluate monitoring of respiratory physiological parameters in patients treated with non-invasive ventilation (NIV) in the ED in Sligo University Hospital. As a secondary objective, the study aims to evaluate how monitoring data influence treatment modification. Methodology: This was a retrospective chart review of 50 patients who presented to the ED in acute respiratory failure and were treated with non-invasive ventilation between September 2017 and March 2019. Results: A total of 50 charts were analysed, 62% female and 38% male. The average age for both genders was 76 years. Results showed that initial and ongoing monitoring of vital signs remained guideline compliant throughout the entire duration of NIV in the ED. All but one patient out of 50 had an initial blood gas analysis done prior to initiation of NIV treatment, while repeat blood gas analysis was inconsistent with 38% (n= 19) who did not have blood gas repeated. Conclusion: The study highlights the discrepancy between monitoring of vital signs and arterial blood gas during treatment of acute respiratory failure patients with non-invasive ventilation in the emergency department. A proforma may help bridge this gap to ensure a standardised care in order to improve treatment outcomes.

Includes abstract. Includes bibliographical references.

Includes bibliographical references / Anecdotally incidents of inappropriate refusal of treatment or transportation by patients referred to hospital under the Mental Healthcare Act of 2002 have been noted. There is little documented about the knowledge and understanding of prehospital providers of the mental healthcare act, their responsibilities and the issues around patient competence and refusal of care. The transportation of patients presenting with a suicide attempt who have not yet been formally assessed for involuntary admission poses a particular problem. Aim: To determine the knowledge of prehospital providers with respect to the transport of patients presenting with suicide attempts and the mental health act and to describe their management of cases where these patients may refuse treatment. Methods: A cross-sectional survey and including open ended questions of 100 prehospital providers in the Western Cape both public and private. The questionnaire will include knowledge testing, vignettes describing patient management and open-ended questions regarding their opinions on suicidal patients. Simple descriptive statistics will be used for the knowledge test. Qualitative data will be coded using a grounded theory approach. Discussion: The findings of the study will be used to determine provider knowledge and attitudes regarding the prehospital management of patients presenting with suicide attempts. Recommendations will be made for provincial EMS guidelines and the results will be disseminated in an article for publication.

Background: Much emphasis has been placed on Quality Measurements or Key Performance Indicators in Emergency Medicine. Internationally, KPI's are used to measure and improve quality of care, with a major emphasis on waiting times, measured as time-based KPI's. These times are related to the various stages of a patient journey through the Emergency Center. In South Africa this has not been routinely done. The Western Cape has conducted audits in recent years to measure these. This study aims to provide a snapshot of waiting times (specifically time to triage, time to doctor, time to disposition decision and time to departure from the EC) within Cape Town public sector Emergency Centres. Methods: This is a retrospective descriptive study of waiting times for all patients presenting to Emergency Centres in the Western Cape in 2013-2014, as per six monthly waiting times audits conducted by the Western Cape Department of Health. A wide variety of emergency centers were audited, from 24 hour clinics to larger acute hospital based ECs. Results: The proportional acuity difference between hospitals and CHC for the first random 100 folders were statistically no different. Arrival to triage times were universally longer than internationally accepted as safe. The mean time for all-comers across all facilities was just under an hour, the higher acuity patients were triaged significantly faster (half an hour) than the lower acuity patients (hour or more). This difference was significant for hospitals, with a non-significant trend for CHCs. At hospital ECs, green patients were triaged significantly faster than yellow patients; this was not the case at CHCs. The mean time from triage to clinician consultation for all-comers across all facilities (over two hours) was significantly longer at hospitals as compared to clinics. Time from triage to clinician consultation, per triage category, were longer than the SATS guide times, although higher acuity cases were seen faster than lower acuity cases in a stepwise fashion. Red patients waited nearly an hour on average, with no significant difference between hospitals and CHCs. Orange patients had to wait one to two hours; this was significantly longer at hospitals. The mean time from assessment and management to a disposal decision for all-comers was significantly longer at hospitals as compared to CHCs across all priorities. Green patients took a lot longer at hospital compared to CHCs. A similar pattern was seen for the disposition decision to leaving time. The mean total time was significantly longer at hospitals as compared to clinics. Orange and yellow cases stayed significantly longer at hospitals as compared to CHCs; red and green cases also stayed longer at hospitals as compared to CHCs, though this was not significant. Red cases appeared to stay the longest at CHCs. Conclusions: Patients attending CHCs and hospitals are of similar illness acuity, despite policies dictating that sicker patients should be seen at hospitals not CHC level. CHCs have limited packages of care (decision making investigations, management options and expertise), and can only manage patients to a defined level. Thus, it takes longer for patients who are moderately or very ill to be seen and sorted in a CHC than a hospital, as at a CHC they are generally referred onwards to a hospital. Their journey through the EC will then begin again, so that for sicker patients the time spent in ECs in this study is underestimated. Models need to be explored so that patients receive care at point of contact as far as possible. Since CHC-based ECs see as many patients who are as ill as those in hospitals, these should have similar resources to hospitals, so that only those requiring definite admission need to be referred onwards. Point of care testing, bedside ultrasound, appropriate medications and EM skills should all be available at facilities closest to the patients with emergency conditions. Green patients, the lowest acuity, also take longer to be seen and sorted at hospitals versus CHCs, because investigations are available that are then done as an emergency versus outpatient basis. Efficient and timely outpatient appointments would help mitigate this.