Browsing by Subject "Health systems"

BACKGROUND: This study describes the prehospital transport of traumatic brain injury (TBI) patients and its impact on TBI outcome to inform quality improvement for the existing trauma system. Data was collected over 4 months at a major referral hospital in Moshi,Tanzania.

METHODS: Patient demographics, mechanism of injury, injury severity (Glasgow Coma Score), and vitals were recorded on presentation to the Casualty Department. Prehospital factors recorded include time, distance and cost. Multivariable regression analyses evaluated the effect of prehospital factors on unfavourable patient TBI outcome, in-hospital factors and demographics were controlled for. Unfavorable outcome was defined as Glasgow Outcome Score<5 on discharge or death.

RESULTS: Road traffic injuries were the most common mechanism of injury (67.1%). The majority of patients were referred from other facilities in and around the region (62.3%), with 23% from the local public hospital There was no evidence of prehospital care available in this region. Average prehospital duration was more than 1 hour, a third of this was spent in prehospital transit for a majority of the patients. A minority used Ambulances. Predictors of unfavourable outcome (GOS<5) were: prehospital time greater than 60 minutes, multiple physical transfers during the prehospital course and being referred from another hospital.

CONCLUSION: The lack of prehospital care calls for further research into prehospital interventions for this setting. Further analysis should be conducted with a larger sample size to increase accuracy of the findings.

Background

Epilepsy is a chronic neurological disorder characterized by recurrent seizure activity caused by abnormal electrical activity in the brain. Over 80% of all cases globally occur in Low- and Middle-Income countries. A high treatment gap exists in LMICs, including Uganda, with 80% of people with epilepsy never receiving treatment. Studies have shown that even with existing medical services, a lack of skilled workforce, medication stock-outs, and long distances to health facilities contribute to the high treatment gap. This study describes the capacity, distribution of health facilities, and referral patterns between facilities that care for epilepsy patients in Uganda.

Methods

We conducted a cross-sectional survey adapted from the WHO Tool for Situational Analysis to Assess Emergency and Essential Surgical Care. It was modified to include WHO Mental Health Gap Action Program (mhGAP) resources for epilepsy and the Tool for Situational Analysis to Assess Epilepsy Care. Data collection occurred between July and August 2022. Our sample included all regional and general hospitals and a sample of randomly selected Health Centers in Southwestern Uganda. We used probability proportional to size sampling to determine which Health Centers to include in our sample. We had only public health facilities in our sample. Data were collected through in-person interviews conducted by trained research assistants. A three-tiered categorical score (full, intermediate, and low capacity) was used to describe epilepsy capacity. For scoring, hospitals were stratified into three groups/facility levels: tertiary care (regional referral hospitals), secondary care (district hospitals/health center IVs), and primary care (health center IIIs), as we hypothesized that available resources would differ between the groups. We did geospatial mapping to show the distribution of facilities.

Ethical approval was obtained from the Makerere School of Public Health Research Ethics Committee (Protocol 1104), the Uganda National Council of Science and Technology (Protocol HS2344ES), and Duke University’s Institutional Review Board (Protocol 00110747).

Results63 facilities were surveyed, with 100% completion in all facilities. 63 (100%) facilities provide care for epilepsy patients. None of the facilities surveyed had full capacity to treat epilepsy patients. Most of our sampled facilities had a low capacity to treat epilepsy: 100% of tertiary care facilities, 77.3% of secondary care facilities, and 83.8% of primary care facilities. Overall capacity was weakest in medication, equipment, and human resources and highest in infrastructure and guidelines. Conclusion While epilepsy services are present in Uganda’s southwestern region, a lack of vital medicines, staff shortages, and technology can limit service delivery. Task shifting and sharing have been widely implemented to address workforce shortages. The findings of this study can help inform policy to improve service delivery for epilepsy patients.

Background: Emergency care sensitive conditions are defined as those for which rapid diagnosis and early intervention improve patient outcomes. This thesis aimed to develop a list of important pediatric conditions in low- and middle-income countries (LMIC) to be used for further studies on pediatric epidemiology and resource utilization. Methods: A survey of 79 conditions was sent to LMIC physicians, who rated each condition on three categories (time sensitivity, preventability, and commonality) on a scale of 1-9. Responses were matched to Brazil pediatric hospitalization, ambulatory, and mortality data from 2015-2020. Results: 17 physicians completed the first Round of the survey, and 3 of these (17.65%) completed the second Round. Overall, 67 of the 79 (84.21%) were rated as highly time-sensitive and 26 (32.91%) highly preventable. Survey conditions with the highest ratings overall or country overlap (n=11), that were country-specific but highly rated in all three categories (n=8), or that comprised ~1%+ of hospitalizations (n=9), ~0.5%+ of ambulatory visits (n=6), and ~0.5%+ of mortality cases (n=8) were combined with the most common acute non-elective causes of hospitalizations (n=7) and mortality (n=9) into a list of 29 consolidated conditions overall (excluding overlap). These 29 accounted for 37.83% of hospitalizations, 8.97% of ambulatory visits, and 29.17% of mortality cases. 31 of the 79 survey conditions were age-specific and 32 context-specific. Conclusions: These 29 should be targeted in future health system utilization and burden studies. The modified Delphi approach is important in reaching provider consensus.