This study aims to establish a multi-agent system model to provide accurate suggestions for the policy proposal of controlling the unreasonable growth of medical expenses charged by public hospitals in China.A multi-agent system model was employed in this study. Agents of this model were divided into patients, doctors, medical institutions, the government, and medical insurance agencies. The model was composed of two subsystems: the disease and medical-seeking subsystem, and the medical expenses subsystem. Policy intervention experiments were conducted on patients’ medical-seeking preferences, doctors’ public welfare behaviors, and the government’s financial investment.At present, medical expenses in China are unreasonable and keep increasing, and the proportion of medicine and physical examination expenses to total medical expenses for public hospitals is unreasonable. Intervention experiments suggested that expanding the promotion and application of the community first-visit system could rationalize patients’ medical-seeking preferences, increasing doctors’ incomes and reducing workload could significantly restrict doctors’ over-prescription behaviors. Also, improving the government’s financial investment could guide public hospitals to strengthen their commitment to public welfare responsibilities. These interventions could decrease the unreasonable growth of medical expenses of public hospitals. The combined intervention effects on suppliers, demanders, and the government were better than the effect of these agents independently.The main reasons for the unreasonable increase in patient medical expenses at public hospitals could be attributed to patients’ unreasonable medical-seeking preferences, doctors’ weak public welfare incentives, and the government’s inadequate financial investment. Policy-makers should consider proposals to restrict and guide the behaviors of suppliers, demanders, and the government, simultaneously. The government should consider the feasibility, response speed, and implementation cost of policies as well. Since the reform of public hospitals in China in 2009, the issue of unreasonable growth in medical expenses has gradually become the focus of reform. The Chinese government issued the “Notice on Certain Opinions on Controlling Unreasonable Growth of Medical Expenses in Public Hospitals” , clearlyThe problem of unreasonable growth in medical expenses is related to the behaviors of multiple agents, including the government, suppliers, and demanders. Studies in OECD countries and the United States also demonstrated that factors that influence healthcare expenditure are complicated an span all aspects of the health system, such as prices, volumes, supply, demand, and market processes –11. In CControlling the unreasonable growth of medical expenses is therefore key to China’s healthcare reform. Many scholars have explored the unreasonable growth of medical expenses with the majority focused on the medical expenses of a certain disease and its influencing factors –24. OtheTherefore, MAS modeling is an appropriate method to explore how the unreasonable growth of medical expenses are controlled in public hospitals, which enables the prediction of proposal results by implementing intervention experiments for relevant policies. The purpose of the study is to use MAS modeling to explore how the agents influence medical expenses and, based on the results, to provide suggestions for controlling the unreasonable growth of medical expenses, and to improve the accuracy of policies.The unreasonable medical-seeking behavior of patients , excessiThe model includes five categories of agents: patients, doctors, medical institutions, the government, and medical insurance agencies. Patient agents are randomly generated based on the characteristics and patterns of various diseases. According to the patients’ medical-seeking preferences , togetheIn addition to the specific characteristics of diseases, medical expenses are affected by the preferences of patients for the type of medical institution, behavior of doctors, policy orientation of the government, and reimbursement by the medical insurance agency. Jointly, these five types of agents determine medical expenses through their own characteristics and their mutual associations. The model was built by AnyLogic software  Fig. .Fig. 1MThis model is used to simulate how medical expenses are generated. Based on the law of objective facts, and considering the simplification and abstraction of the model, this study carried out the following necessary logical assumptions that respect objective law Table S:China Health and Family Planning Statistical Yearbook. Patients with different diseases were generated randomly by computer. However, due to complexity and considering that this model does not focus on disease transmission, this study assumed that all populations are distributed statically according to Shanghai’s population density in different administrative districts, regardless of the population’s mobility and the impacts of disease transmission.(1) Because there are many different types of diseases, considering the comprehensive coverage of all diseases and for reasons of simplification, this study classified diseases into 30 types based on national statistics. Patients were identified according to two-week prevalence rates , 35 of 3(2) Many doctors’ behaviors affect medical expenses and one of the most important is over-prescription . To quan(3) Though the effect was not obvious, previous publications have demonstrated that the development of primary healthcare institutions could affect patients’ medical-seeking preferences and reduce medical expenses. Moreover, that the Chinese government is making great efforts to support the community first-visit system and is investing heavily in primary healthcare institutions , 41. The(4) Considering that this study aims to discuss the rationalization of medical expenses in public hospitals from the perspective of behaviors of the government, suppliers, and demanders, the model assumed that the effect of medical insurance agencies on patients’ medical-seeking preferences and medical expenses was solely achieved through the reimbursement proportion of medical insurance. The effect of the reimbursement proportion of medical insurance was realized by different proportions in different levels of healthcare institutions . For exaBased on the logic of generating medical expenses, the MAS model developed for controlling the unreasonable growth of medical expenses in public hospitals contained two subsystems: the disease and medical-seeking subsystem, and the medical expenses subsystem.As shown in Fig. In addition, in this subsystem, government initiatives influenced patients’ medical-seeking preferences as well. The government agent guided patients with common diseases or minor illnesses to visit community health service centers first, through policies such as the community first-visit system, dual-referral system, and family doctor contracting system. However, during this stage, these initiatives had not played an obvious role in shifting the flow of patients from high-level institutions to primary healthcare institutions . TherefoAs shown in Fig. However, the final medical expenses of each patient were influenced by many other factors. First, over-prescription by doctors increased the medical expenses. Whether doctors over-prescribed was determined by the gap between their actual and expected incomes, and the probabilities and degree of over-prescription in different situations , as calculated from the expert consultations. The actual income of a doctor was determined by their professional title, as reported by publications and the Chinese physicians White Book –46, whilChina Health and Family Planning Statistical Yearbook, “Shanghai 2010 National Census Main Data Bulletin,” the “China Physician White Paper”; field and literature research; and expert consultations. The output variables of the model included different medical expense values. Initial input values of parameters are listed in Table SThe initial values of the input variables were derived from the These included the total population, population distribution, two-week prevalence rates of 30 different diseases gender, age, occupation, marital status, income, education level, medical-seeking preferences, and adherence rate of prescriptions.These included the number, name, category, and geographical location (latitude and longitude) of tertiary comprehensive hospitals, specialized hospitals, district hospitals, and community health service centers.These included the doctor’s professional title, income, annual growth rate of income, weekly hours worked, annual change rate for weekly hours worked, and the probability of over-prescription.These included the proportion of the government’s financial subsidies to public hospitals and the promotion degree of the community first-visit system.These included the composition of basic medical insurance for urban workers, basic medical insurance for urban and rural residents, and proportion of non-medical insurance residents.These included basic outpatient medical, medicine, and physical examination expenses; and basic inpatient medical, medicine, physical examination, treatment, surgery expenses, and medical material expenses for 30 diseases in four types of medical institutions; annual growth rate of different expenses; and probabilities of outpatient visits, hospitalization, surgery, and physical examinations.China Health and Family Planning Statistical Yearbook.The model validation was tested by comparing the simulated and real values. If the difference is between − 10 and 10%, the model can be considered to be correct and credible . In the The results showed that the gap between the simulated and actual values was between − 10 and 10%. The model was thus correct and credible Table .Table 2This study carried out intervention experiments on patients’ medical-seeking behaviors, doctors’ public welfare behaviors, and the government’s financial investment in public hospitals. The control group was the baseline situation without any intervention, and the simulation time was 3 years.Degree of promotion and application of the community first-visit system was reduced by 50%, and patients preferred tertiary comprehensive hospitals.Degree of promotion and application of the community first-visit system increased by 50%, and patients’ preferences were rationalized.Degree of promotion and application of the community first-visit system increased by 100%, and patients’ preferences were rationalized.Doctors’ income decreased by 50%, income growth rate decreased by 50%, weekly working hours were maximized (60 h), and growth rate of hours worked weekly increased by 50%.Doctors’ income increased by 100%, income growth rate increased by 50%, weekly working hours decreased by 25%, and growth rate of hours worked weekly decreased by 50%.Doctors’ income increased by 200%, income growth rate increased by 100%, weekly working hours decreased by 50%, and growth rate of hours worked weekly decreased by 80%.Annual growth rate of financial investment for tertiary comprehensive, specialized, and district hospitals, and the rate for community health service centers decreased by 50%.Annual growth rate of financial investment for tertiary comprehensive, specialized, and district hospitals increased by 100%, and the rate for community health service centers increased by 75%.Annual growth rate of financial investment for tertiary comprehensive, specialized, and district hospitals increased by 200%, and the rate for community health service centers increased by 100%.Based on the independent intervention experiments on patients, doctors, and the government (the three group experiments mentioned above), a combination of thresholds for each group of experiments was performed to intervene in the behaviors of patients, doctors, and the government, simultaneously.Within the three-year simulation, the outpatient medical, medicine, and physical examination expenses all showed a small increasing trend. The ratio of outpatient medicine to total medical expenses decreased slightly , while the ratio of outpatient physical examination expenses increased slightly. The inpatient medical and medicine expenses, and the ratio of medicine to total medical expenses showed a downward trend; however, inpatient physical examination expenses and their ratio to total inpatient medical expenses both increased.Most government investment was in community health service centers. Government financial subsidies for tertiary comprehensive public and specialized hospitals showed a small downward trend, while financial subsidies in district hospitals and community health service centers showed an increasing trend.Patients’ medical-seeking preferences for the four types of public medical institutions did not show obvious changes. Patients who preferred district and tertiary comprehensive hospitals accounted for the largest percentage.The probability of over-prescription fluctuated slightly. About half of doctors over-prescribed. The increase in medicine and physical examination expenses caused by doctors’ over-prescriptions showed a gradual downward trend Table .Table 3Expanding the promotion and application of the community first-visit system could effectively control total medical, physical examination expenses, and their proportions. However, there was no effect on controlling medicine expenses and their proportions. When the promotion and application of the community first-visit system was expanded, more patients were guided to visit community health service centers and specialized hospitals first. More patients would, on the contrary, prefer tertiary comprehensive hospitals. However, when the degree of promotion and application of the community first-visit system increased to 1.5 times the current level, the effect of continuing to increase promotion and application on controlling medical expenses and optimizing patients’ medical-seeking preferences was not obvious, which indicated a marginal value Fig. .Fig. 4RThe adjustment of doctors’ income and workloads were two independent interventions. By simultaneously increasing doctors’ income and reducing their workloads, it could effectively control total medical expenses, medicine expenses and their proportion, and physical examination expenses; however, regulating the proportion of physical examination expenses was invalid. Moreover, this could weaken doctors’ incentives for over-prescription. It is worth noting that, when doctors’ income increased twofold and their working time decreased to 75% of the current level, marginal values appeared (Fig. Increasing the government’s financial investment to medical institutions could effectively reduce total medical expenses, medicine expenses, proportion of inpatient medicine to total expenses, physical examination expenses, and proportion of inpatient physical examinations to total expenses, while regulating the proportion of outpatient medicine and physical examination expenses was not obvious. Moreover, the greater the proportion of the government’s financial investment, by encouraging medical institutions to undertake public welfare responsibilities, the more effective the effect on controlling medical expenses would be. However, when the government’s financial investment to community health service centers increased to 175% of the current degree, public welfare responsibilities would be undertaken perfectly, which suggests that the government’s financial investment in community health service centers should not exceed this level Fig. .Fig. 6RBased on the marginal values of the above three groups of experiments, the combined experimental interventions would be on patients, doctors, and the government, simultaneously. The scenario was the degree of promotion and application of the community first-visit system increased by 50% and patients’ preferences were rationalized; the doctor’s income increased by 100%, the growth rate of income increased by 50%, weekly working hours decreased by 25%, and the growth rate of weekly working hours decreased by 50%; the annual growth rate of financial investment for tertiary comprehensive, specialized, and district hospitals increased by 100%, and the annual growth rate of financial investment for community health service centers increased by 75%.The intervention experiment results suggested that combined intervention could significantly reduce total medical expenses, medicine expenses and their proportions, physical examination expenses, and the proportion of outpatient physical examination expenses. The effect of combined intervention was better than that of independent experiments Fig. .Fig. 7RAt present, the medical expenses charged by public hospitals are unreasonable and keep increasing. The proportion of both medicine expenses and physical examination expenses to total medical expenses are also unreasonable. The intervention experiments conducted suggest that this could be attributed to patients’ unreasonable medical-seeking preferences, doctors’ weak public welfare incentives, and the government’s inadequate financial investment. Therefore, to control the unreasonable growth of medical expenses with the best effect, our findings indicated that interventions conducted simultaneously on suppliers, demanders, and the government, achieve better results when compared with isolated interventions on these agents.First, expanding the degree of promotion and application of the community first-visit system could guide patients into community health service centers by rationalizing their medical-seeking preferences. It could thus achieve a reasonable diversion of patients, and effectively reduce outpatient and inpatient medical expenses. However, the promotion and application of the community first-visit system should be appropriate—expanding to 1.5 times the current degree was the maximum degree of effectiveness. In addition, considering the feasibility of this policy, it must be pointed out that the community health service centers have yet to play a gate-keeping role , 49, 50.Second, increasing doctors’ income and reducing their workload could significantly restrict doctors’ over-prescription behaviors; this would decrease outpatient and inpatient medical expenses by reducing extra expenses due to over-prescription. It is worth noting that increasing doctors’ income and reducing their workload disproportionately could lead to doctors’ inefficiencies. When their income increased twofold and working hours reduced to 75% of the current level, it reached the most significant effect. However, it should be noted that it was not easy to increase doctors’ incomes and reduce workload simultaneously. In high-level healthcare institutions, doctors face excessive work intensity because of too many patients; progressively more sudden deaths of Chinese doctors were reported globally in recent years , 55. HowThird, improving the government’s financial investment could guide public hospitals to strengthen their commitment to public welfare responsibilities, thereby reducing medical expenses effectively. However, the program had no significant effect on regulating the proportions of outpatient medicine and physical examination expenses. When investment into community health service centers increased to 175% of the current level, it achieved the best controlling effect. However, the threshold for the other three types of medical institutions was not reached, which suggests that the government’s financial investment into tertiary comprehensive, specialized, and district hospitals was extremely insufficient with much room for improvement. Since the implementation of China Health Reform in 2009, the Chinese government has continually increased the investment in public hospitals , 57. HowFourth, simultaneously rationalizing the patients’ medical-seeking preferences, increasing doctors’ income and reducing their workload, and increasing government financial investment achieved the best results for controlling the unreasonable growth of medical expenses. Policy makers should comprehensively examine the combined effects of various agents on medical expenses when formulating policy proposals. In addition, the feasibility, potential problems, and cost of such policies mentioned above should also be given full consideration before implementation.China Health and Family Planning Statistical Yearbook, consultation of medical staff in Shanghai public hospitals, and related experts. Although the extracted data performed well in verifying the model against the real system, it needs to be refined further in future research. Second, due to the complex simulation of the population’s mobility and the impact of disease transmission, this model assumed a statistically static populations distribution. Although the reasonable assumption could be understood, this assumption is far from the real world. Thus, it still needs to be revised in the next step. Third, although the “Opinions of the General Office of the State Council on Strengthening the Performance Appraisal of Tertiary Public Hospitals,” issued on January 30, 2019, noted that rational medicine use should be employed as the assessment indicator, rather than solely using the proportion of medicine expenses to total medical expenses, a reasonable indicator system has not yet been demonstrated. Therefore, this study used the proportion of medicine expenses to total medical expenses as an indicator to determine whether the medicine expenses were reasonable. A follow-up study should further discuss the rationality of medicine expenses. Fourth, although it was a reasonable simplification to some extent that the annual growth rate for doctors’ incomes in different types of hospitals did not differ based on previous national research and existing studies, it was a limitation that the differences among tertiary, specialized, district, and community-level hospitals were unspecified, especially the specialty of community health service centers. Therefore, further research on the different annual growth rates for doctors’ incomes in different types of hospitals and subsequent optimization of the model should be conducted.This study had several limitations. First, due to the lack of complete statistics relating to medical expenses, the medical expense data in the model were measured according to the In conclusion, the current medical expenses of public hospitals continue to show a trend of unreasonable growth. This phenomenon of the unreasonable growth of expenses charged by public hospitals was affected mainly by patients’ unreasonable medical-seeking preferences, doctors’ weak public welfare motivation, and a lack of government public welfare guidance. Controlling the growth of these expenses can be mitigated effectively by comprehensively implementation of the community first-visit system, increasing doctors’ income and reducing their workload, and increasing government financial subsidies. However, the feasibility of these policies, underlying problems, and cost of such policies should be carefully examined before implementation.Additional file 1 Table S1. Initial input values of parameters.Additional file 2 Table S2. Assumptions of model.


Background: This article examines whether connection to digital technologies helps connect young Indigenous people in Australia to culture, community and country to support good mental health and well-being and protect against indirect and potentially long-term effects of COVID-19. (2) Method: We reviewed literature published between February and November 2020 and policy responses related to digital strategies. We searched PubMed, Google Scholar, government policy websites and key Indigenous literature sources, identifying 3460 articles. Of these, 30 articles and 26 policy documents were included and analysed to identify existing and expected mental health outcomes among Indigenous young people associated with COVID-19 and more broadly. (3) Results: There are inequities in affordable access to digital technologies. Only 63% of Indigenous people have access to internet at home. Digital technologies and social media contribute to strong cultural identity, enhance connections to community and country and improve mental health and social and emotional well-being outcomes. (4) Discussion: Access to digital technologies can facilitate healing and cultural continuity, self-determination and empowerment for young people to thrive, not just survive, in the future. (5) Conclusion: More targeted policies and funding is urgently needed to promote digital technologies to enhance Indigenous young people’s access to mental health and well-being services, maintain cultural connections and evaluate the effectiveness of these initiatives using Indigenous well-being indicators.(1)  This paper aims to examine whether utilising digital technologies helps connect young Indigenous people in Australia to culture, community and country to support good mental health and well-being as well as protect against indirect and potentially long-term effects of COVID-19. Since the first case of COVID-19 was reported in Australia in February 2020 there have been over 28,800 COVID-19 cases, 66 active cases and 909 deaths recorded in Australia, one of the least impacted countries in the world [While Australia appears to have avoided the worst of the COVID-19 pandemic, there remains the looming threat of a second (and in some states a third) wave of infections and associated deaths as well as associated disabilities referred to as ‘long COVID’ ,3. In adThis is especially relevant in the Australian context, where a range of distal social determinants that form part of a complex colonial legacy have contributed significantly to these adverse circumstances and issues for Indigenous peoples. These determinants include unequal access to health services, education and employment, and persistent experiences of institutional and interpersonal racism ,9,10, asIt is estimated that prior to colonisation there were over 500 different Indigenous nations with distinctive cultures, beliefs and languages across Australia . In 2016Many Indigenous communities, like many non-Indigenous communities in Australia, are experiencing a sense of disconnection. There is an urgent need for strategies to support vulnerable communities experiencing uncertainty associated with the pandemic as well as with the social and lifestyle restrictions imposed in order to halt the spread of the infection. Young Indigenous people face elevated population-level risks of psychological distress, suicide and health-harming behaviours . There hLocally, the strength of these communities and importance of connection to culture and country has also been displayed in powerful “place-based” COVID-19 responses, highlighting Indigenous self-determination and resilience. Several studies demonstrate how digital technologies and social media contribute to strong cultural identity; enhance connections to community and country and promote health and social and emotional well-being (SEWB) outcomes ,25,29. IWhile this review examines the potential positive impacts of digital technology and social media on enhancing cultural connections and addressing social inequities, several studies also highlight the negative impacts. For instance, a study by Indigenous researcher, Bronwyn Carlson raises concerns about the likely trauma experienced by Indigenous young people due to the frequent exposure to untimely deaths, suicide, deaths in custody, violence and funerals being shared on social media . CarlsonA systematic review examining the positive and negative impacts of Indigenous young people’s use of digital technologies and social media found that “cyber bullying, cyber racism and the exchange of sexually explicit content between minors are common with limited approaches to dealing with this at the community level” , digital technology  and SEWB , AND COVID-19 as an additional parameter of interest. We also scanned relevant media, government, academic and Indigenous-specific websites, Australian Policy Online and YouTube adding the additional search terms Indigenous, barriers AND communication to the previous terms.Given the issues around mental health and given that inequitable access to services for Indigenous communities has escalated and become more obvious since COVID-19, we initially focused on peer-reviewed articles, grey literature including government and scientific research committee reports, working papers and policy documents published in 2020 between February and November and then searched relevant policy documents as well as additional publications referred to in the literature citations.Inclusion criteria included articles referring to the use of digital technologies by Indigenous young people in the Australian context. The Lowitja PubMed search produced 580 relevant articles, and the Google Scholar search for articles during 2020 produced 2880 results. From these, 50 relevant articles were initially selected. We screened the titles and abstracts, and following removal of duplicates, reviewed 30 complete articles that discussed Indigenous young people’s use of the internet and/or social media for either social connection or for access to mental health services or tools for further assessment. A further extended search of relevant media, government, academic and Indigenous-specific websites, Australian Policy Online, YouTube and a scan of references resulted in 26 government policy reports, Indigenous committee reports and statistics that discussed strategies to address digital inequities and/or mental health impacts due to COVID and 32 relevant peer-reviewed articles examining the benefits and risks of social media for Indigenous young people and its role in connecting young people to culture. We grouped the issues into overall themes, all authors agreed on the main themes identified in this paper.A total of, 88 full texts were analysed . The resSeveral studies highlight the social and environmental inequities associated with existing health conditions, including food insecurity; poor access to water, sanitation and health services; and lack of adequate housing to support larger family groups, which increases COVID-19 risk ,8,21. CoThe review confirmed there is growing concern regarding mental health impacts of the COVID-19 outbreak  includinIt has been recognised for several years now that the internet is an important source of information, knowledge and access to health support, including mental health support for Indigenous young people. For instance, a Melbourne study found Indigenous young people were over represented in phone calls to Kids Helpline related to suicide and self-harm . AnotherThe association between good mental health outcomes and access to digital technologies, including computers, the internet, smartphones and mobile applications (apps), has been identified in several national studies ,48,49. OIndigenous young people have also reported increasing acceptability of e-mental health resources that have potential to improve mental health and well-being if they are well supported and integrated through existing services structures . HoweverSeveral articles reveal that 20 Aboriginal and two Torres Strait Islander leaders, including scholars and practitioners from Universities and Indigenous health, mental health, allied health and psychology peak bodies around Australia have worked with the Australian Government Department of Health throughout the pandemic to ensure that public health responses, communication and containment strategies are sensitive to the diverse cultural contexts of Indigenous Australians ,58,59. TA national COVID-19 working party comprised of Indigenous leaders from around Australia was also convened by the Group of Eight Australian universities to provide advice to the government. The working party has produced an independent report for the government, addressing the specific mental health and SEWB needs of Indigenous people in Australia .This repThe report also asserts the need for Indigenous governance to manage the coordination of COVID-19 recovery in communities “through equitable, needs-based funding to support strengths-based, place-based, Indigenous-led, and community-led initiatives that address the social and cultural determinants of health and well-being” (p. 1 ). While The Australian Government allocated funding through the Better Access to Mental Health initiative, which commenced in November 2017 to provide e-mental health for all Australians living in rural and remote areas . The AusThe review identified four current initiatives that the ADHA is implementing in partnership with representatives from State and Territory Aboriginal and Torres Strait Islander health services and NACCHO. The ADHA meet quarterly to monitor strategic digital health priorities designed to contribute to the Australian Government’s Closing the Gap commitment . On 4th In Western Australia, the trial of a new tool to help Indigenous people manage their healthcare via the GoShare digital platform has recently been launched . HoweverOver the past months, social distancing measures and social isolation have severely limited opportunities for social engagement among young people. For many Indigenous young people, these connections are being maintained and sustained through the use of modern technologies to access mental health services and technologies (including apps), call lines and information as well as to maintain access to friend and families .. A South Australian study confirmed that positive family and peer relationships together with activities that facilitate “optimism and self-esteem” were associated with resilience and positive mental health outcomes [Several studies have shown that the use of a range of digital technologies and social media contribute to strong cultural identity, enhance connections to community and country and improve mental health and SEWB outcomes . The impoutcomes . ConnectThe answers to some of these questions are already being explored by Indigenous academics, digital experts and technicians. For instance, the National Centre of Indigenous Excellence (NCIE) with Telstra Foundation have produced the first strategy for driving Indigenous digital excellence, based on a three-year consultation process with Indigenous digital makers, organisations and communities. The road map sets out the principles, goals and areas of focus and priority actions for an Indigenous Digital Excellence (IDX) future. During COVID-19, the NCIE IDX team successfully ran On Country Camps over five days with 30 participants from 11 communities via zoom. The team have developed culturally responsive resources operating across a range of platforms to keep young people linked together and connected with Elders, their families and communities. As participant, Elder Aunty Beryl said, “Modern technology is the way for us to keep going and keep connected” . For exaSeveral studies and reports confirm the highly innovative ways in which young people share information and transformative ideas using digital technologies and social media to create and sustain virtual communities and networks ,76. TheyExisting socioeconomic and health inequalities between Aboriginal and non-Aboriginal young people may be compounded by disparities in access to the internet. There is the potential for this disadvantage to be experienced by young people living in urban settings as well as in rural and remote settings. Census data reveal only 63% of Aboriginal young people aged under 25 years lived in a household with an internet connection compared with 91% of non-Aboriginal young people ,79. In 2The first wave of the pandemic revealed great strengths in terms of the Indigenous leadership, self-determination and resourcefulness of the Aboriginal Community Controlled Health Services (ACCHS) sector, as well as in the Australian health system and its commitment to support and be directed by the ACCHS in this time of crisis . At the Our current research, Young Indigenous People’s Resilience and Well-being  focuses Several studies in the review confirm that many Indigenous young people living in areas outside of urban sites are using the internet and social media. However, access to and use of the internet varies across groups and areas. Indigenous young people are no different. It is important that we develop a better understanding of these issues in order to support the development of policies that may assist young people to have better access to the internet and other digital platforms in times of crises.There is a crucial need to develop and support digital initiatives to strengthen the mental health and SEWB of Indigenous young people in Australia. This requires the provision of adequate long-term funding to Aboriginal community controlled organisations in order to empower and learn from communities at this critical juncture in our history. Bringing together digital technologies with traditional customs and wisdom is testament to the innovation and leadership of Indigenous young people and the stewardship of Aboriginal Community Controlled Health Services.We urge governments to adopt a trauma-informed, culturally responsive, integrated strength-based approach in the provision of mental health and well-being services including digital health solutions to support young people’s health, mental health and SEWB. For Indigenous young people, having a sense of social and cultural connectedness and a sense of control and mastery over their own lives is crucial to their well-being and resilience . It is p


Lipid droplets (LDs) and mitochondria are essential organelles involved in cellular lipid metabolism and energy homeostasis. Accumulated studies have revealed that the physical contact between these two organelles is important for their functions. Current understanding of the contact between cellular organelles is highly dynamic, fitting a “kiss-and-run” model. The same pattern of contact between LDs and mitochondria has been reported and several proteins are found to mediate this contact, such as perilipin1 (PLIN1) and PLIN5. Another format of the contact has also been found and termed anchoring. LD-anchored mitochondria (LDAM) are identified in oxidative tissues including brown adipose tissue (BAT), skeletal muscle, and heart muscle, and this anchoring between these two organelles is conserved from mouse to monkey. Moreover, this anchoring is generated during the brown/beige adipocyte differentiation. In this review, we will summarize previous studies on the interaction between LDs and mitochondria, categorize the types of the contacts into dynamic and stable/anchored, present their similarities and differences, discuss their potential distinct molecular mechanism, and finally propose a working hypothesis that may explain why and how cells use two patterns of contact between LDs and mitochondria. The lipid droplet (LD) is a specialized cellular organelle with a neutral lipid core covered by a monolayer phospholipid membrane and associated proteins . StartinThe LD is an ancient organelle with a new face and a recent recognition of its importance has attracted great attention in the fields of biology and life science. The newly discovered fact that LDs exist in some bacteria extends our view of the origin of membrane-bound organelles. The finding that LDs contain not only triacylglycerol (TAG), but also cholesterol ester, retinal ester, and monoalk(en)yl diacylglycerol in animal cells  suggestsThe unique property of LDs in their sequestration of neutral lipids led to a perception of them merely as “a drop of oil,” negatively impacting scientific interest and slowing down its research. However, the description of their proteome and lipidome and their linkage to metabolic syndromes impacting human health provoked a renaissance in research interest and activity . The LD The LD is integrated with other organelles in maintaining lipid homeostasis , which iMitochondria are the site of β-oxidation, converting hydrophobic substrates into usable cellular energy and reducing potential. The fuel for this reaction is stored in the hydrophobic interior of LDs, necessitating a mechanism for the transfer of FAs between these two organelles. Free transfer of FA (or coenzyme A ligated FA) is restricted by the hydrophobic character of the molecules. In fact, the accumulation of FA or acyl-CoA under certain stress conditions leads to cellular toxicity (lipotoxicity). To facilitate the transfer, cells developed a specific interaction between these two organelles. An understanding of this interaction was initiated by the visualization of the physical contact between LDs and mitochondria. The best images depicting this interaction were electron micrographs taken by George Palade, in which the physical contact was clearly shown between LDs and mitochondria in guinea pig pancreas . Since tDespite early, clear visual evidence of the contact, it has been a long journey toward a biochemical understanding of the interaction. Investigations were hampered by underdeveloped techniques for biochemical isolation and a lack of molecular tools. The discovery of LD marker proteins perilipin (PLIN1) and adipocyte differentiation-related protein (ADRP/PLIN2) in the early 1990s  permitteThis review summarizes the evidence supporting the contact between LDs and mitochondria using morphological, biochemical, and biophysical data and focuses on interactions which cannot be separated by ultracentrifugation. This review brings forward a new point of view, proposing a distinction between stable and dynamic contact which can describe and explain some recent experimental findings. We propose that the stable interaction between LDs and mitochondria is maintained by rivet-like protein structures that prevent the separation between them during ultracentrifugation.The potential trafficking capability of LDs was revealed through the visualization of LDs moving along microtubules, mediated by the protein Klar  and othein vitro assays confirmed that LD is a site for cellular lipid synthesis (The discovery of hormone-sensitive lipase (HSL) and PLIN1 on LDs, and the identification of the mechanism of activation and LD targeting of HSL via phosphorylation of both proteins, identified the catalytic function of this organelle. Additional proteomic studies found lipid synthetic enzymes on isolated LDs, pointing to an anabolic role . In addiynthesis .Thus, the LD is a site of neutral lipid storage, but is also metabolically active, can move rapidly throughout the cell, and possesses the molecular machinery to regulate interactions with other organelles. Collectively, these observations point to a central role for LDs in cellular lipid homeostasis.The interaction between LDs and mitochondria was first observed more than a half-century ago. George E. Palade was one of the major contributors who visualized the physical contact between LDs and mitochondria in guinea pig pancreas using transmission electron microscopy (TEM) . EM alsoAdvances in biological dyes, such as JC-1 and MitoTracker for mitochondria and Nile red, Bodipy, Oil Red O, and LipidTOX for LDs, have permitted the application of fluorescence microscopy to the study of LD-mitochondrion interactions . The disMorphological studies have described highly dynamic interactions between LDs and mitochondria. For example, it was observed by EM that endurance exercise training enhances the physical contact between LDs and mitochondria in muscle cells. This finding is fully consistent with the upregulation of FA β-oxidation in mitochondria to meet the energetic needs during exercise . In anotA wide range of terminology has been applied to direct the contact between LDs and mitochondria. These include, but are not limited to, approximation, association, interaction, targeting, tethering, contact, binding, and anchoring. In one instance, the interaction site was called recognition site . Table 1Saccharomyces cerevisiae  from strong contact (stable binding/anchoring). Therefore, this experimental approach can be used to classify types of contact.in vitro assays  are key players governing the physiological binding between early endosomes and LDs . The term peridroplet mitochondria (PDM) was proposed to describe these loosely associated mitochondria , including BAT (BAT), heart (Heart), and muscles (MG and MS)  .Another fundamental question remaining to be answered for this anchoring hypothesis , is whet2 bomb)  stringency of homogenization and (2) centrifugal force of floatation. Three homogenization methods that have been applied on BAT and brown adipocytes are listed by stringency (low to high): Nitrogen Cavitation technology (N2 bomb) , grindin2 bomb) , and dou2 bomb) . The ceniciently . TherefoFinally, based on previous studies from ours and other laboratories, the working hypothesis is proposed that there are two types of contact (dynamic and stable) between LDs and mitochondria in oxidative cells . The co-PL conceived the project. LC carried out the experiments and data analysis. LC and PL wrote the manuscript. Both authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


A recent survey conducted by the World Health Organization (WHO) from June to August 2020 around the globe has clearly highlighted how the COVID-19 pandemic has disrupted or halted critical mental health services in 93% of the 130 countries under study despite the demand for mental health is increasing [Specifically, 45 countries reported disruption of emergency interventions such as those for people experiencing severe substance use withdrawals syndromes. On the other hand, over 60% of countries reported disruption for vulnerable people, including children and adolescents (72%), the elderly (70%), and women requiring antenatal or postnatal services 61%). Also, around three out of four countries under study reported at least partial disruption of school and workplace mental health services [%. Also, The WHO Eastern Mediterranean Region, which comprises 21 Member States  and Palestine (West Bank and Gaza Strip), with a population of around 680 million people, hosts some of the most important protracted crises on earth that resulted in major population movement due to forced displacement and migration.Conflicts in the Eastern Mediterranean Region are severely impacting human well-being, including mental health of displaced populations and host communities. One peculiar feature is represented by the fact that countries neighbouring those in conflict are under stress because of the large numbers of people seeking shelter. At the very beginning of 2019, 32.1 million out of the globally 70.8 million displaced persons originated from the Middle East area and 25.4 million continued to reside in the region [Isolation, loss of income and fear due to the COVID-19 pandemic are exacerbating existing mental health conditions: common and severe mental disorders are more prevalent in humanitarian crises, especially among women and children, and those exposed to violence and forcible displacement. Specifically, estimates suggest that more than one in five people in post-conflict settings have depression, anxiety disorder, posttraumatic stress disorder, bipolar disorder, or schizophrenia .To note how the current context may also worsen stigmatization of displaced people, often accused of bringing crime and disease, leaving them more vulnerable to mental health and psycho-social problems.To give some examples, in Lebanon, multiple incidents of suicide were reported among refugees in April and there was a spike in instances of threats to self-harm and harm to others amidst domestic violence and family disputes. On the other hand, the Multi-sectoral Rapid Needs Assessment jointly conducted by WFP, UNICEF and UNHCR in Jordan in the same time-period showed that 41% of all respondents witnessed a negative impact on their children’s well-being because of the COVID-19 crisis. Finally, it is important to underline the devastating compounded effect of the current crisis on contexts like Yemen and Libya with their weak national health systems and the shortage of qualified mental health staff; the Libyan context in particular deserves close observation and action due to additional distress aspects like detention centres .While more than 80% of high-income countries reported deploying telemedicine and teletherapy to bridge gaps in mental health, this proportion becomes far lower (50%) in low-income countries and is likely to be even lower in setting experiencing protracted conflicts .as integration must be carefully taken into consideration: despite the fact 89% countries reported that mental health was part of their COVID-19 response plans, only 17% revealed full additional funding for covering these activities [As emphasized by the WHO, monitoring changes and disruption of services and prompt addressing of these issues should be an integral part of response and recovery plans along with the other components related to maintaining essential health services. The financial aspects of such As framed by the Inter-Agency Standing Committee (IASC), establishing a mental health and psycho-social strategy is critical and should be inclusive of targeted actions towards COVID-19 cases, survivors, contacts, family members, frontline workers and the broader community, with special attention to the needs of vulnerable groups . Fear, sThe need to support mental health assistance for vulnerable populations can include a series of innovative interventions like telemedicine, which could be directly financed by the richer countries via recruiting the mental health specialists from the same language group and from around the world to try to give support and follow ups. Other possible solutions include the coordinated connection with facilities and clinics that have better and more specialized personnel. Indeed, a political solution at a higher level for stabilizing and developing the entire region is the most important factor.


Conceptual frameworks of fiscal space for health have traditionally considered health system efficiency improvements as a means to free up resources for the sector. However, there has been no comprehensive review of the evidence to confirm the relationship between efficiency and fiscal space.We conducted a systematic review to synthesize evidence on whether efficiency gains increase fiscal space for health. We searched bibliographic databases for specific keywords – namely, fiscal space, efficiency and health – and identified 22 articles that examined links between efficiency gains and fiscal space for health. The articles, which encapsulated 28 case studies, were included in the analysis.The 28 case studies varied widely with regard to how efficiency was evaluated, the extent to which efficiency was explored, and how efficiency gains could be achieved. Half of the studies assessed both technical and allocative efficiency, and the other half assessed technical efficiency only. The indicators to examine potential inefficiencies varied substantially among studies. The most frequently cited inefficiencies stemmed from public financial management  and governance issues, even though these were characterized in various ways. The second most cited set of inefficiencies that caused health systems to function poorly were those related to health service delivery. Procurement and delivery of input factors was also mentioned in some studies as a source of inefficiency. Though most studies conceded that efficiency gains were a potential means to improve fiscal space for health, very few quantified the potential gains or explored practical mechanisms to translate efficiency gains into fiscal space for health.While the conceptual link between efficiency gains and fiscal space for health may be assumed, there is no direct empirical evidence proving that efficiency gains translate into more resources for the health sector. Mechanisms to translate efficiency gains into fiscal space are barely explored in the fiscal space literature. Public financial management rules and related rules for reallocating funds within the sector need to be further examined to guide countries in the transformation of efficiency gains into more resources for health. There is a growing recognition of the importance of creating fiscal space for health in many low- and middle-income countries (LMICs) in order to achieve universal health coverage (UHC) and health-related Sustainable Development Goals (SDGs). In the 2010 World Health Report, strengthening health system financing was highlighted as a means to achieve UHC ,4.Fiscal space refers to budgetary flexibility that allows a government to provide additional resources for a particular public purpose without impacting fiscal sustainability . PreviouThe fiscal space for health framework was developed in 2010 . Since tA more systematic examination of efficiency in the fiscal space for health literature is necessary, especially given the increasingly prominent role that efficiency gains as a tool for generating fiscal space now plays in policy dialogues and given the diversity of approaches used in fiscal space analyses examining the relationship between efficiency gains and fiscal space . This stThis review concentrates on the relationship between efficiency and fiscal space for health. It builds on existing frameworks to identify causes of inefficiencies in health systems and uses a systematic approach to classify potential causes of inefficiencies and efficiencies that have already been identified in the fiscal space for health literature. In the last few years, several frameworks to identify efficiencies and inefficiencies have emerged, including the health system framework  and inpuOur review initially followed the input-output-outcome framework, in which factors beyond inputs and outputs –what are called external factors or environmental determinants of the performance – are suggested to be examined to identify efficiencies and inefficiencies. We thus added two sets of external factors as potential causes of efficiencies and inefficiencies: (1) procurement and delivery of input products as well as supply and demand factors influencing input factors, and (2) supply and demand factors on access to care using the care utilization framework . These tThe red boxes in To identify articles for review, we searched four major electronic bibliographic databases on public health and economics for combinations of three terms: (1) fiscal space; (2) efficiency; and (3) health. The initial search was conducted on 22 September 2018 on PubMed, EconLit, Academic Search Premier, and Web of Science, and updated on 25 October 2018. We also conducted a search for grey literature through the POPLINE database and Google Scholar. All searches were conducted in English. The initial search identified 6248 non-duplicate publications that were eligible for title and abstract screening, including 14 articles shared by the World Health Organization (WHO). The research team reviewed all records from the Google Scholar search, checked their eligibility and compared them to those obtained from electronic databases. No additional articles were included from the Google Scholar search.The search records were uploaded in Endnote X8 and independently screened by two reviewers. After eliminating duplicate records, the titles and abstracts of the remaining studies were reviewed to assess their relevance based on four criteria: (1) studies examining fiscal space for health in a country or a region; (2) studies examining efficiency as a means to increase fiscal space; (3) studies assessing fiscal space using the World Bank framework; and (4) studies conducted in LMICs. Articles that met or possibly met the criteria were included in the full-text review. Articles were excluded if they met any of the following exclusion criteria: (1) studies not related to health, including social protection; (2) studies that provided no analysis of fiscal space; (3) studies that did not address efficiency of health systems; (4) studies synthesizing previous fiscal space analyses; and (5) studies published prior to 2000. The full text review, which included 53 articles, was conducted independently by Wu Zeng and Yao Yao. Thirty-three articles were excluded based on the exclusion criteria. The data collected from each article included the basic characteristics of each study , as well as which components of efficiency and fiscal space the articles addressed . The data was collected in an Excel spreadsheet. For each article, the above-mentioned information was extracted. Data extraction was carried out primarily by one researcher. A second researcher reviewed and checked the collected data.The analysis of the data collected in the Excel spreadsheet  focused on two dimensions. The first dimension was related to the characteristics of the overall study, including the efficiency assessment methods and the type of efficiency. Researchers often distinguish between two types of efficiency, technical and allocative. Technical efficiency refers to achieving maximum output  for a given level of inputs , while allocative efficiency refers to choosing the appropriate mix of inputs to achieve desired outputs ,15,17.The second dimension was related to specific findings on efficiency and fiscal space, including the efficiency indicators used in the assessment, the key inefficiency identified, the proposed approaches to address inefficiencies, the feasibility and scope for fiscal space, and the estimated fiscal space for health gains from efficiencies. Efficiency indicators were grouped into three categories: (1) general efficiency indicators that capture a country’s health outcomes, such as life expectancy, infant mortality rate and overall mortality rate; (2) allocative efficiency indicators that provide information on the allocation of resources; and (3) technical efficiency indicators that concern the outputs produced for given inputs, such as bed occupancy rate, average length of stay and efficiency scores from data envelopment analysis (DEA) or stochastic frontier analysis (SFA). At times, it was hard to draw a clear line between the efficiency indicator categories. Key inefficiencies were grouped into four categories, based on the approach described in Twenty-two articles with 28 case studies were deemed eligible for this review, based on our database search, our desktop research, and consultations with the WHO. The flow diagram in Of the 28 selected case studies from the 22 articles identified, five were obtained from peer review articles, and the rest were grey reports. Twenty-seven of the case studies were published after 2010; one had unknown publication dates. Twenty-five of the case studies were conducted for specific countries: two studies were conducted in Ghana, Indonesia, and Uganda, respectively, and one study was conducted in each of the following countries, Afghanistan, Bangladesh, Bhutan, Cambodia, Cote d’Ivoire, Guinea, India, Kenya, Liberia, Nepal, Nigeria, Peru, Rwanda, South Africa, Sudan, United Republic of Tanzania, Tonga, Ukraine, and Zimbabwe. The three remaining studies were regional, two focused on a group of sub-Saharan Africa countries and one on a group of countries in the Americas. Geographically, there were 16 studies conducted in Africa, two in the Americas, eight in Asia, one in Oceania, and one in Eastern Europe. Half of the 28 case studies (14) assessed both technical and allocative efficiency, the other half assessed technical efficiency (TE) only, and none focused solely on allocative efficiency (AE). There were four studies that used both quantitative and qualitative approaches to assess efficiencies, 19 studies used a qualitative assessment only, and five studies used only a quantitative approach. The selected studies used a variety of indicators to quantify inefficiencies in health systems and health service delivery. High-level efficiency indicators tended to be health outcome indicators, such as life expectancy, healthy life years, infant mortality rate (IMR), and maternal mortality rate (MMR). Some studies examined variations in these indicators across countries, regions, or districts, which were used as evidence of existing inefficiencies. There were also studies that investigated variations in health outputs, not outcomes, across different geographic areas, which served as an indicator of technical inefficiencies in health systems. The most common output indicators were: immunization coverage, skilled birth attendance, and unmet need for contraceptives. At the hospital level, common efficiency indicators were average length of stay, bed occupancy rate, and bed turnover rate. Other technical efficiency indicators included absenteeism rate, staff vacancy rate, health personnel density, and availability of drugs and equipment, each of which also quantifies the availability and adequacy of input factors. A few studies used either DEA or SFA, and at times both, to estimate health system and health service delivery efficiency scores; these scores were then used as a technical efficiency indicator. One study used costs per hospital stay and costs per hospital day as an efficiency indicator. Allocative efficiency indicators mostly measured the allocation of budget by type of service, level of care, function of input factors , and disease burden.Table S1 in the The second most cited source of health system malfunctions was inefficiency in health service delivery. Of the 28 case studies, 16 (57.1%) addressed inefficiencies in health service delivery. These inefficiencies were often related to the availability and use of inputs, including human resources, medical products, pharmaceuticals, equipment, and health information, as well as the way inputs were organized and how the referral system functioned. The most common inefficiency concerns related to service delivery were: absenteeism , ghost workers , understaffing , and shortage of drugs and equipment . Other inefficiency concerns included excessive use of resources, such as extended hospital stays in Ukraine, and an oversupply of staff, for example in Liberia and Afghanistan.Only four of the 28 studies mentioned issues with the procurement and delivery of inputs as a source of inefficiency . Low procurement capacity was one of the reasons cited as a cause of poor health system performance. In Bhutan, the drug market was identified as a source of inefficiency, with small pharmaceutical markets and a heavy reliance on imported medicines leading to high drug prices and creating vulnerability in the drug supply chain. The studies included little exploration of inefficiencies related to the supply and demand of health services, such as accessibility, affordability, acceptability of health services, or quality of care.Some studies proposed interventions to address efficiency concerns. According to our assessment, nine (32.1%) of the 28 studies described potential interventions to tackle health system inefficiencies in detail. Half of the studies (14), provided directional or generic recommendations, which may not be useful guidance for policy-makers seeking to improve the performance of their health systems or to create fiscal space for health. Five studies (17.8%) did not provide any recommendation.The proposed interventions could be grouped under the same four categories as the inefficiencies themselves: 1) PFM, strategic purchasing and governance; (2) procurement and delivery of input factors; (3) service delivery (use and organization of input factors); and (4) demand and supply factors of health services. The key proposed PFM and governance interventions included performance-based payments, provider payment reforms, and streamlined budget preparation, allocation and execution. The Nepal study, for example, highlighted provider payment reforms as a means to strengthen health system performance.S1 in the The studies were generally optimistic about the possibility of creating fiscal space through efficiency gains. Of the 28 case studies, half (14) indicated that countries could free up sizable resources for health by addressing inefficiencies. The Guinea study, for example, described significant potential for the country to create fiscal space through efficiency gains. Two (7.1%) studies  pointed to moderate potential for efficiency gains to generate fiscal space for budgeting, while three (10.7%) studies  indicated limited scope for efficiency gains in those countries. The nine (32.1%) remaining studies did not assess the scope of efficiency gains for creating fiscal space (see TableOnly seven studies (25%) quantified the financial gains that could be generated by addressing inefficiencies. The remaining 21 studies (75%) provided no estimate of potential gains that could be potentially used for health. In the seven studies which attempted to quantify gains, most failed to provide complete estimates of the potential gains of addressing key inefficiencies. Some estimates were based on addressing absenteeism or length of stay only. Others focused on service delivery inefficiencies only. The potential savings estimates were expressed in monetary units, as a share of gross domestic product, or as a share of government budget or expenditure , which are a result of both allocative and technical efficiencies. The second focuses on resource allocation organized by different characteristics . The third focuses on technical efficiency, such as the production of outputs for a given set of resources or the level or number of inputs for a given level of outputs . Not all of the studies which assess the scope of fiscal space gained through efficiency improvements examine all three types of efficiencies. Many examine technical efficiency only. Some concentrate on the technical efficiency of health service delivery only, as opposed to the health system as a whole. The indicators for each type of efficiency also vary across studies. For example, in the South Africa study, the general indicators used are IMR and MMR . WhereasThe most appropriate methods with which to measure health care and health system efficiency are unaddressed in the assessments, as well as how efficiency metrics could be used to inform policy and managerial decisions. Most studies (19/28 case studies) use qualitative descriptions of health statistics to demonstrate inefficiencies in the health system or to synthesize prior studies. Only one study conducted focus group discussions or stakeholder informant interviews to systematically and qualitatively assess efficiency concerns . Most quOnly a handful of inefficiencies are explored in the existing fiscal space for health literature. Those that are examined tend to be related to PFM and health service delivery. The WHO estimated that 20%-40% of health resources are wasted . The samNot all studies in this review included recommendations to address specific inefficiencies. Those that did often did not always match recommendations to the causes of health system inefficiencies. The failure to provide recommendations may be a result of the initial scope of work agreed upon as part of the fiscal space analysis. In the future, all fiscal space analyses should include space for recommendations, which could then be used to help design targeted interventions and evidence-based policies. Although many studies state that efficiency gains could generate substantial scope for fiscal space, only seven of the 28 studies in this review estimated budgetary space in monetary terms . None of the studies systematically and comprehensively quantified potential budgetary space. Modelling gains in fiscal space requires specific sets of data on each identified inefficiency. For inefficiencies that are common across countries and prevalent in LMICs, a uniform model to quantify efficiency gains in monetary terms would help to standardize fiscal space estimates. Though the scope of work of fiscal space analyses will vary substantially from country to country, it would be useful for all analyses to include data collection that would help quantify potential budgetary space. This would, in turn, provide policy-makers with more detailed and accurate information.The most important omission in the studies reviewed is the lack of direct evidence on how fiscal space would be expanded by addressing inefficiencies, making more funds available for reinvestment in the health sector. No study provided information on whether financial gains actually translated into fiscal space for the health sector. Instead, the studies remained theoretical, assessing potential but not actual gains and failing to explore how funds transform into fiscal space or expanded financial room . While the link between fiscal space and efficiency is conceptually valid, there is increasing empirical evidence showing that the link is not automatic. The fiscal space analysis from efficiency gains seems to assume that (1) improved efficiency results in more money for the health sector; (2) money generated through technical efficiency gains will stay in the health sector; and (3) identifying sources of inefficiency will automatically lead to more fiscal space. However, in practice, efficiency improvements do not necessarily mean spending less and, therefore, don’t guarantee that more resources will be made available for the health sector. This is the result of a number of factors: (1) addressing inefficiencies may require additional investments ; (2) somWe must acknowledge that health system efficiency does not necessarily expand fiscal space for health. This is critical for LMICs to understand as they endeavour to create fiscal space and move towards UHC. Health system efficiency should be examined more thoroughly and systematically, especially how to ensure that efficiency gains lead to an increase in fiscal space instead of leading to budget cuts for the health sector. Despite the lack of direct evidence, efficiency improvements remain an important element of every country’s effort to enhance their health system. In some countries, addressing efficiency concerns could be a starting point for raising financial resources within the health sector or advocating for a greater share of the overall budget. Improving health system efficiency could not only save resources, which could be reinvested in the health sector, but it could also strengthen the relationship between finance and health authorities and help trigger broader health system reform.