Global access to surgical care: a modelling study

Background More than 2 billion people are unable to receive surgical care based on operating theatre density alone. The vision of the Lancet Commission on Global Surgery is universal access to safe, aff ordable surgical and anaesthesia care when needed. We aimed to estimate the number of individuals worldwide without access to surgical services as defi ned by the Commission’s vision. Methods We modelled access to surgical services in 196 countries with respect to four dimensions: timeliness, surgical capacity, safety, and aff ordability. We built a chance tree for each country to model the probability of surgical access with respect to each dimension, and from this we constructed a statistical model to estimate the proportion of the population in each country that does not have access to surgical services. We accounted for uncertainty with oneway sensitivity analyses, multiple imputation for missing data, and probabilistic sensitivity analysis. Findings At least 4·8 billion people (95% posterior credible interval 4·6–5·0 [67%, 64–70]) of the world’s population do not have access to surgery. The proportion of the population without access varied widely when stratifi ed by epidemiological region: greater than 95% of the population in south Asia and central, eastern, and western sub- Saharan Africa do not have access to care, whereas less than 5% of the population in Australasia, high-income North America, and western Europe lack access. Interpretation Most of the world’s population does not have access to surgical care, and access is inequitably distributed. The near absence of access in many low-income and middle-income countries represents a crisis, and as the global health community continues to support the advancement of universal health coverage, increasing access to surgical services will play a central role in ensuring health care for all

Projected impact of COVID-19 mitigation strategies on hospital services in the Mexico City Metropolitan Area

Evidence-based models may assist Mexican government officials and health authorities in determining the safest plans to respond to the coronavirus disease 2019 (COVID-19) pandemic in the most-affected region of the country, the Mexico City Metropolitan Area. This study aims to present the potential impacts of COVID-19 in this region and to model possible benefits of mitigation efforts. The COVID-19 Hospital Impact Model for Epidemics was used to estimate the probable evolution of COVID-19 in three scenarios: (i) no social distancing, (ii) social distancing in place at 50% effectiveness, and (iii) social distancing in place at 60% effectiveness. Projections of the number of inpatient hospitalizations, intensive care unit admissions, and patients requiring ventilators were made for each scenario. Using the model described, it was predicted that peak case volume at 0% mitigation was to occur on April 30, 2020 at 11,553,566 infected individuals. Peak case volume at 50% mitigation was predicted to occur on June 1, 2020 with 5,970,093 infected individuals and on June 21, 2020 for 60% mitigation with 4,128,574 infected individuals. Occupancy rates in hospitals during peak periods at 0%, 50%, and 60% mitigation would be 875.9%, 322.8%, and 203.5%, respectively, when all inpatient beds are included. Under these scenarios, peak daily hospital admissions would be 40,438, 13,820, and 8,650. Additionally, 60% mitigation would result in a decrease in peak intensive care beds from 94,706 to 23,116 beds and a decrease in peak ventilator need from 67,889 to 17,087 units. Mitigating the spread of COVID-19 through social distancing could have a dramatic impact on reducing the number of infected people and minimize hospital overcrowding. These evidence-based models may enable careful resource utilization and encourage targeted public health responses

Assessment of diagnostics capacity in hospitals providing surgical care in two Latin American states

Background: Diagnostic services are an essential component of high-quality surgical, anesthesia and obstetric (SAO) care. Efforts to scale up SAO care in Latin America have often overlooked diagnostics capacity. This study aims to analyze the capacity of diagnostic services, including radiology, pathology, and laboratory medicine, in hospitals providing SAO care in the states of Chiapas, Mexico and Amazonas, Brazil. Methods: A stratified cross-sectional evaluation of diagnostic capacity in hospitals performing surgery in Chiapas and Amazonas was performed using the Surgical Assessment Tool (SAT). National data sources were queried for indicators of diagnostics capacity in terms of workforce, infrastructure and diagnosis utilization. Fisher's exact tests and chi-square tests were used to compare categorical variables between the private and public sector in Chiapas while descriptive statistics are used to compare Amazonas and Chiapas. Findings: In Chiapas, 53% (n = 17) of public and 34% (n = 20) of private hospitals providing SAO care were assessed. More private hospitals than public hospitals could always provide x-rays (35% vs 23.5%) and ultrasound (85% vs 47.1%). However neither sector could consistently perform basic laboratory testing such as complete blood counts (70.6% public, 65% private). In Amazonas, 30% (n = 18) of rural hospitals were surveyed. Most had functioning x-ray machine (77.8%) and ultrasound (55.6%). The majority of hospitals could provide complete blood count (66.7%) but only one hospital (5.6%) could always perform an infectious panel. Both Chiapas and Amazonas had dramatically fewer diagnostic practitioners per capita in each state compared to the national average capacity. Interpretation: Facilities providing SAO care in low-resource states in Mexico and Brazil often lack functioning diagnostics services and workforce. Scale-up of diagnostic services is essential to improve SAO care and should occur with emphasis on equitable and adequate resource allocation

Genetics workforce: distribution of genetics services and challenges to health care in California

PurposeAccess to genetics health-care services is often complicated by the distance to hospitals, workforce shortages, and insurance coverage. Despite technological advances and decreasing costs of genetic sequencing, the benefits of personalized medicine may be inaccessible to many patients. To assess potential disparities in care, we examined the genetics workforce in California and geographical issues that people encounter in seeking care.MethodsData on all board-certified genetics providers were analyzed including medical geneticists (MGs) and genetic counselors (GCs) in California. To assess distance traveled for care, we computed the distance patients traveled for n = 288 visits to University of California-San Francisco (UCSF) Medical Genetics. We performed geographic optimization to minimize the distance to genetics providers.ResultsThe provider-to-patient ratio in California is 1:330,000 for MGs, 1:100,000 for GCs, and 1:1,520,000 for biochemical MGs. Genetics providers are concentrated in major metropolitan areas in California. People travel up to 386 miles for genetics care within the state (mean = 76.6 miles).ConclusionThere are substantial geographic barriers to genetics care that could increase disparities. Our findings highlight a challenging genetics workforce shortage. The shortage may be even greater due to care subspecialization or lack of full-time equivalency and staffing. We are currently promoting efforts to increase remote health-care options, training, and modified models of care

Global access to surgical care: a modelling study

Background: More than 2 billion people are unable to receive surgical care based on operating theatre density alone. The vision of the Lancet Commission on Global Surgery is universal access to safe, affordable surgical and anaesthesia care when needed. We aimed to estimate the number of individuals worldwide without access to surgical services as defined by the Commission's vision. Methods: We modelled access to surgical services in 196 countries with respect to four dimensions: timeliness, surgical capacity, safety, and affordability. We built a chance tree for each country to model the probability of surgical access with respect to each dimension, and from this we constructed a statistical model to estimate the proportion of the population in each country that does not have access to surgical services. We accounted for uncertainty with one-way sensitivity analyses, multiple imputation for missing data, and probabilistic sensitivity analysis. Findings: At least 4·8 billion people (95% posterior credible interval 4·6–5·0 [67%, 64–70]) of the world's population do not have access to surgery. The proportion of the population without access varied widely when stratified by epidemiological region: greater than 95% of the population in south Asia and central, eastern, and western sub-Saharan Africa do not have access to care, whereas less than 5% of the population in Australasia, high-income North America, and western Europe lack access. Interpretation: Most of the world's population does not have access to surgical care, and access is inequitably distributed. The near absence of access in many low-income and middle-income countries represents a crisis, and as the global health community continues to support the advancement of universal health coverage, increasing access to surgical services will play a central role in ensuring health care for all. Funding: None