Abstract
Introduction
Surgery plays a critical role in sustainable healthcare systems. Validated metrics exist to guide implementation of surgical services, but low-income countries (LIC) struggle to report recommended metrics and this poses a critical barrier to addressing unmet need. We present a comprehensive national sample of surgical encounters from a LIC by assessing the National Health Services of Mozambique.
Material and methods
A prospective cohort of all surgical encounters from Mozambique’s National Health Service was gathered for all provinces between July and December 2015. Primary outcomes were timely access, provider densities for surgery, anesthesiology, and obstetrics (SAO) per 100,000 population, annualized surgical procedure volume per 100,000, and postoperative mortality (POMR). Secondary outcomes include operating room density and efficiency.
Results
Fifty-four hospitals had surgical capacity in 11 provinces with 47,189 surgeries. 44.9% of Mozambique’s population lives in Districts without access to surgical services. National SAO density was 1.2/100,000, ranging from 0.4/100,000 in Manica Province to 9.8/100,000 in Maputo City. Annualized national surgical case volume was 367 procedures/100,000 population, ranging from 180/100,000 in Zambezia Province to 1,897/100,000 in Maputo City. National POMR was 0.74% and ranged from 0.23% in Maputo Province to 1.78% in Niassa Province.
Discussion
Surgical delivery in Mozambique falls short of international targets. Subnational deficiencies and variations between provinces pose targets for quality improvement in advancing national surgical plans. This serves as a template for LICs to follow in gathering surgical metrics for the WHO and the World Bank and offers short- and long-term targets for surgery as a component of health systems strengthening.
Introduction
Surgery plays a critical role in sustainable healthcare systems but only recently gained visibility in global health policy [1–4]. In 2015, the Lancet Commission on Global Surgery (LCoGS) estimated that 5 billion people lack timely access to surgical care and that a minimum of 140 million surgical procedures are required annually to address the current unmet need worldwide [5, 6]. Failure to address this critical public health issue will lead to global losses in productivity cumulatively estimated at $12.3 trillion USD by 2030 [7].To expedite the realization of gains in health and economic development, the World Health Organization (WHO) unanimously passed Resolution 68/15 in 2015, calling for meaningful and reliable measures on access to surgical care [8].
Commensurately, the WHO and World Bank (WB) endorsed a suite of indicators for monitoring and evaluation of surgical services [9, 9]. However, large deficiencies exist in the reporting these metrics [10]. Of all United Nations member states, 80% report surgical–anesthesia and obstetric provider densities, 37% report volume of surgery per 100,000 population, 10% report timely access to surgery, 5% report postoperative mortality rate, and no countries report standardized values for catastrophic and impoverishing expenditures [10]. Despite early successes formulating National Surgical, Obstetric, and Anesthesia Plans (NSOAPs), most of these aspirational documents do not build on a foundation of data. Low-income countries (LICs) especially struggle to report recommended metrics and this poses a critical barrier to addressing unmet need where it is needed the most [11, 12].
We present a comprehensive national sample of surgical encounters from a LIC by assessing the National Health Services of Mozambique (NHSM). Mozambique is a LIC situated in the southeast of Africa with a population of 25 million [13–15]. Currently, there are fewer than 35 Mozambican general surgeons (0.14/100,000 inhabitants) and the country relies heavily on nonphysician technicians and expatriate surgeons from Cuba, China, and North Korea [16–18]. As a first step in developing a national surgical plan for Mozambique, we assessed the NHSM hospitals for all provinces using the surgical indicators developed by the LCoGS and adopted by the WB and WHO [2, 9, 9].
Methods
Overview/setting
A prospective cohort of all consecutive surgical encounters from NHSM was gathered from July to December of 2015. The NHSM distributes healthcare facilities comprehensively over the country’s 128 geographic districts, which are organized into 11 Provinces, namely Niassa, Manica, Tete, Inhambane, Gaza, Nampula, Zambezia, Cabo Delgado, Sofala, Maputo Province, and Maputo City [19].(Fig. 1) Hospitals were selected for inclusion based on the presence of an operating room (OR) and the appropriate staffing to carry out basic surgical procedures such as fractures, trauma, exploratory laparotomy, and cesarean section. Surgical providers, health managers, and administrative personnel collected data from daily reports using a predefined data collecting form. All data were sent at monthly intervals to the research team in hard copies or electronically over secure networks. In order to ensure accuracy and reliability, the research team conducted periodic site visits to all health units in the study. Data reports were compared to data sources, and individual patient charts were consulted to confirm deaths and time from operation to death. Data entry was performed in Excel on a secure computer in the capital city, Maputo. The study protocol was granted ethical approval by the Mozambique National Bioethics Committee.
Fig. 1.
Map of Mozambique showing 54 Districts with surgical capacity (in orange) and those without surgical capacity (in green)
Data definitions
Surgical data were collected according to definitions described in the LCoGS [2]. ‘Timely Access’ refers to the proportion of the population with access to Bellwether procedures within 2 hours. Bellwether procedures are defined by LCoGS as cesarean delivery, laparotomy, and open fracture [2]. In Mozambique, road conditions are highly variable due to the rainy season so timely access was defined as the population living in a geographic district with surgical capacity in the local community hospital. Provider density was calculated as the volume of surgeons, anesthesiologists, and obstetricians (SAO) per 100,000 population. Volume of surgery was calculated as the number of surgeries performed in an operating room per 100,000 population. Of note, volume of surgery was also calculated as an annualized density by doubling the six-month values of surgical procedures in the numerator to allow for comparison to other studies where annual values are the accepted standard. Postoperative mortality ratios (POMR) were calculated as the volume of in-hospital deaths after surgery (numerator) divided by the total volume of surgical cases (denominator). Secondary outcomes of nonphysician technician densities (per 100,000 population) were also calculated in a similar fashion for surgical technicians, anesthesia technicians, and obstetric technicians. All calculations were performed at the national level and again by geographic Province. Demographic data and population denominators were taken from the Mozambique’s Ministry of Health [20]. Data definitions are also consistent with the WHO’s Global Reference List of 100 Core Health Indicators and WB’s World Development Indicators [9, 9]. Econometrics data such as catastrophic expenditure and impoverishing expenditure were not collected.
Results
Summary: national demographics and infrastructure
We identified 54 hospitals with surgical capacity with 130 total operating rooms (0.5 OR per 100,000 people) where 47,189 surgical encounters occurred (Table 1). Three of these health facilities were regional hospitals, 12 were provincial hospitals, and 39 were district (aka rural) hospitals. Most of Mozambique’s population (68.2%) resides in rural areas, and the gender distribution is roughly equal (51.7% female, 48.3% male). Patients from all 11 geographic provinces were represented within the study cohort, including rural and urban settings. There are 318 certified SAO providers (1.2/100,000 population) and 343 nonphysician SAO technicians (1.3 per 100,000 population). More than 60% of the geographic districts in Mozambique do not have health facilities with operating rooms (and thus no SAO providers whatsoever), leaving 44.9% of Mozambique’s population without timely access to surgical services (Fig. 1).
Table 1.
Provinces of Mozambique and their characteristics, including population, rurality, gender distribution, operating rooms, timely access, surgical–anesthesia–obstetric technicians, and surgical–anesthesia–obstetric physicians
| Province | Population | Rurality | Gender Distribution | Operating Rooms (Density) | Timely Access | SAO Technicians (Density) | SAO (Density | |||
|---|---|---|---|---|---|---|---|---|---|---|
| Rural (%) | Urban (%) | Female (%) | Male (%) | Without (%) | With (%) | |||||
| Maputo city | 1,241,702 | 0 (0) | 1,241,70 (100) | 644,593 (51.9) | 597,109 (48.1) | 16 (1.3) | 0 (0) | 1,241,70 (100) | 59 (4.7) | 122 (9.8) |
| Maputo province | 1,709,058 | 508,192 (29.7) | 1,200,866 (70.3) | 889,850 (52.1) | 819,208 (47.9) | 6 (0.3) | 518,199 (30.3) | 1,190,859 (69.7) | 27 (1.6) | 14 (0.8) |
| Gaza | 1,416,810 | 1,051,460 (74.2) | 365,350 (25.8) | 770,807 (54.5) | 646,003 (45.6) | 8 (0.6) | 683,861 (48.3) | 732,948 (51.7) | 22 (1.5) | 8 (0.6) |
| Inhambane | 1,499,479 | 1,140,226 (76.0) | 359,253 (24.0) | 826,194 (55.1) | 673,285 (44.9) | 11 (0.7) | 766,027 (51.1) | 733,451 (48.9) | 35 (2.3) | 16 (1.1) |
| Manica | 1,933,522 | 1,472,925 (76.2) | 460,597 (23.8) | 1,000,797 (51.8) | 932,725 (48.2) | 8 (0.4) | 1,115,753 (57.7) | 817,768 (42.3) | 26 (1.3) | 8 (0.4) |
| Sofala | 2,048,676 | 1,311,173 (64.0) | 737,503 (36.0) | 1,053,840 (51.4) | 994,836 (48.6) | 16 (0.8) | 665,545 (32.5) | 1,383,131 (67.5) | 32 (1.5) | 26 (1.3) |
| Tete | 2,517,444 | 2,176,059 (86.4) | 341,385 (13.6) | 1,285,484 (51.1) | 1,231,960 (48.9) | 12 (0.5) | 1,444,193 (57.4) | 1,073,252 (42.6) | 25 (1.0) | 23 (0.9) |
| Zambezia | 4,802,365 | 3,794,084 (79.0) | 1,008,281 (21.0) | 2,482,815 (51.7) | 2,319,550 (48.3) | 13 (0.3) | 2,097,421 (43.7) | 2,704,944 (56.3) | 44 (0.9) | 30 (0.6) |
| Nampula | 5,008,793 | 3,393,495 (67.8) | 1,615,298 (32.2) | 2,535,547 (50.6) | 2,473,246 (49.2) | 19 (0.4) | 2,229,246 (44.5) | 2,779,549 (55.5) | 38 (0.8) | 42 (0.8) |
| Niassa | 1,556,906 | 1,268,704 (76.6) | 388,202 (23.4) | 842,795 (50.9) | 814,111 (49.1) | 7 (0.4) | 1,220,616 (73.7) | 436,290 (26.3) | 11 (0.6) | 14 (0.9) |
| Cabo Delgado | 1,893,156 | 1,430,118 (75.5) | 463,038 (24.5) | 976,175 (51.6) | 916,981 (48.4) | 14 (0.7) | 805,112 (42.5) | 1,088,043 (57.5) | 27 (1.4) | 15 (0.8) |
| Mozambique | 25,727,911 | 17,546,436 (68.2) | 8,181,475 (31.8) | 597,109 (48.1) | 12,419,014 (48.3) | 130 (0.5) | 11,545,973 (44.9) | 14,181,937 | 343 (1.3) | 318 (1.2) |
Key: SAO = Surgical–anesthesia–obstetric, all densities reported as per 100,000 population
Provincial variability in infrastructure
Significant variability exists between provinces with regard to demographics and infrastructure (Table 1). The proportion of the population that lives in a rural setting varies from 0% in Maputo City to 86.4% in Tete Province; however, there is less variability outside of the capital city, Maputo, ranging from 64.0% rural in Sofala to 84.6% rural in Tete. The density of operating rooms ranges by a factor of four from 0.3 per 100,000 population in Zambezia and Maputo Provinces to 1.3 per 100,000 population in Maputo City. The proportion of the population without timely access to surgical services ranges from 0% in Maputo City to 73.7% in Niassa. In 8 of 11 provinces, at least 40% of the population lives in districts without surgical services.
Variability in workforce
Most Mozambican hospitals with surgical services had no accredited anesthesiologist or surgeon (Table1). Accredited SAO densities ranged by a factor of 20 from 0.4/100,000 in Manica Province to 9.8/100,000 in Maputo City. Thirty hospitals (55.5%) were without accredited surgeons, and 40 hospitals (74.1%) were without accredited anesthesiologists and rely strictly on nonphysician surgeon and anesthesiologist technicians (Table2). Nonphysicians provided 39.7% (18,769) of national surgical volume. Nationally, accredited anesthesia providers were fewer (0.1 per 100,000 population) than accredited surgeons (1.1 per 100,000 population). All provincial and regional hospitals had accredited surgeons and anesthesiologists. SAO densities for medical doctors, nonphysician technicians, and combined medical doctors plus nonphysician technicians are compared in Table 2.
Table 2.
Summary of surgical workforce, including physicians and nonphysician technicians
| Province | Surgery (density) | Anesthesia (density) | Obstetrics (density) | Total providers (density) | |||||
|---|---|---|---|---|---|---|---|---|---|
| MD | Technician | MD | Technician | MD | Technician | MD | Technician | Combined | |
| Maputo City | 75 (6.0) | 9 (0.7) | 23 (1.8) | 40 (3.2) | 25 (2.0) | 9 (0.7) | 122 (9.8) | 59 (4.7) | 181 (14.5) |
| Maputo Province | 7 (0.4) | 8 (0.5) | 1 (0.1) | 5 (0.3) | 6 (0.3) | 14 (0.8) | 14 (0.8) | 27 (1.6) | 40 (2.4) |
| Gaza | 5 (0.4) | 7 (0.5) | 0 (0.0) | 12 (0.9) | 3 (0.2) | 3 (0.2) | 8 (0.6) | 22 (1.5) | 30 (2.1) |
| Inhambane | 10 (0.7) | 10 (0.6) | 2 (0.1) | 17 (1.1) | 4 (0.3) | 8 (0.5) | 16 (1.1) | 35 (2.3) | 51 (3.4) |
| Manica | 4 (0.2) | 5 (0.3) | 0 (0.0) | 17 (0.9) | 4 (0.2) | 4 (0.2) | 8 (0.4) | 26 (1.3) | 34 (1.8) |
| Sofala | 19 (0.9) | 6 (0.3) | 2 (0.1) | 24 (1.2) | 5 (0.2) | 2 (0.1) | 26 (1.3) | 32 (1.5) | 58 (2.8) |
| Tete | 17 (0.7) | 8 (0.3) | 1 (0.0) | 12 (0.5) | 5 (0.2) | 5 (0.2) | 23 (0.9) | 25 (1.0) | 48 (1.9) |
| Zambezia | 20 (0.4) | 15 (0.3) | 2 (0.0) | 25 (0.5) | 7 (0.1) | 4 (0.1) | 30 (0.6) | 44 (0.9) | 73 (1.5) |
| Nampula | 30 (0.6) | 12 (0.2) | 3 (0.1) | 24 (0.5) | 9 (0.2) | 3 (0.1) | 42 (0.8) | 38 (0.8) | 80 (1.6) |
| Niassa | 11 (0.7) | 3 (0.2) | 1 (0.1) | 7 (0.4) | 2 (0.1) | 1 (0.0) | 14 (0.9) | 11 (0.6) | 25 (1.5) |
| Cabo Delgado | 10 (0.5) | 9 (0.5) | 2 (0.1) | 13 (0.7) | 3 (0.2) | 5 (0.3) | 15 (0.8) | 27 (1.4) | 42 (2.2) |
| Mozambique | 209 (0.8) | 90 (0.3) | 37 (0.1) | 196 (0.8) | 72 (0.3) | 57 (0.2) | 318 (1.2) | 343 (1.3) | 661 (2.6) |
Key: MD = Medical Doctor. All densities reported per 100,000 population
Surgical output
There were 47,189 surgical procedures performed during the six-month study period (Table 3). Annualized national surgical case volume was 367 procedures/100,000 population and ranged from 180/100,000 in Zambezia Province to 1,897/100,000 in Maputo City. As a measure of resource utilization, annualized case volume per OR was 726 nationally and ranged from 448 in Niassa to 1,472 in Maputo City. There were 99 deaths within 24 h of surgery, with a 24-h POMR of 0.21%. There were 348 total deaths that occurred in the hospital after surgery with a POMR of 0.74%. The inpatient POMR varied by province, ranging from 0.23% in Maputo Province to 1.78% in Niassa Province (Fig. 2).
Table 3.
Summary of surgical output, including surgical case volume, annualized surgical case volume, surgical case volume density (per 100,000), surgical case volume per operating room (OR), deaths within 24 h of surgery, 24-h postoperative mortality rate (POMR), and in-hospital (total) postoperative mortality rate (POMR)
| Province | Case volume | Case volume annualized | Case volume density* | Case volume per OR | Deaths in 24Hrs (POMR, %) | Deaths, Total (POMR, %) |
|---|---|---|---|---|---|---|
| Maputo City | 11,779 | 23,558 | 1897 | 1472 | 5 (0.04) | 46 (0.39) |
| Maputo Province | 1728 | 3456 | 202 | 576 | 3(0.17) | 4 (0.23) |
| Gaza | 1796 | 3592 | 254 | 449 | 3 (0.17) | 13 (0.72) |
| Inhambane | 3664 | 7328 | 489 | 666 | 6 (0.16) | 13 (0.35) |
| Manica | 2305 | 4610 | 238 | 576 | 5 (0.22) | 11 (0.48) |
| Sofala | 4174 | 8348 | 407 | 522 | 12 (0.29) | 32 (0.77) |
| Tete | 3377 | 6754 | 268 | 563 | 11 (0.33) | 30 (0.89) |
| Zambezia | 4324 | 8648 | 180 | 665 | 19 (0.44) | 47 (1.09) |
| Nampula | 8647 | 17,294 | 345 | 910 | 17 (0.20) | 95 (1.10) |
| Niassa | 1569 | 3138 | 189 | 448 | 8 (0.51) | 28 (1.78) |
| Cabo Delgado | 3826 | 7652 | 404 | 547 | 10 (0.26) | 29 (0.76) |
| Mozambique | 47,189 | 94,378 | 367 | 726 | 99 | 348 (0.74) |
case volume density is annualized case volume
Fig. 2.
Summary of key surgical indicators in Mozambique; namely a proportion of population with timely access, b density of surgical, anesthesia, and obstetric (SAO) providers, c density of surgical case volume, and d postoperative mortality rate (POMR). Data are stratified by Province, with national values in blue (dotted) and international targets in green (solid). There is no consensus or international target for POMR
Discussion
Our findings highlight significant shortcomings in the provision of surgical care in Mozambique. The comprehensive nature of this study facilitates the identification of population-level deficiencies at multiple levels of the healthcare system, in both urban and rural settings, and includes all patients undergoing surgery. Adoption of validated global surgery metrics confirms the feasibility and utility of facility-based data collection in austere environments according to recommendations from the WHO and WB.
Infrastructure
Poor access to surgery in Mozambique is directly linked to physical infrastructure. Worldwide, there are 6.2 ORs per 100,000 population [21, 22]. Mozambique’s 0.5 ORs per 100,000 falls substantially below international comparisons, with 10 ORs per 100,000 in high-income countries and 1.2 ORs per 100,000 in Rwanda, a country in a similar economic tier [22, 23]. In Mozambique, 60% of geographic districts do not have ORs whatsoever, leaving 44.9% of the population without timely access to surgical services as they must travel to adjacent districts where surgical services are available. Infrastructural deficiencies reinforce the application of the ‘Three Delays Framework’ originally describing obstetric emergencies [2, 24].The ‘Second Delay’ in reaching care directly reflects physical infrastructure, and our study resonates with findings by Faierman et al. showing that patients seeking surgery traveled longer distances than any other group of (non-surgical) patients in Mozambican hospitals [25, 26].Without significant investment in infrastructure, Mozambique will fall short of the Lancet Commission on Global Surgery’s target of 80% of the population with timely access by 2030 [2, 27].
Workforce
Our assessment of MNHS hospitals illustrates major deficits in the surgical, anesthesia, and obstetric (SAO) workforce in comparison with international targets that are best revealed by data stratification. Based on estimates from 2015 in 154 countries, national SAO density (per 100,000 population) ranges from 68 in high-income countries to 0.7 in low-income countries, and low-income countries are struggling to make progress [10]. Mozambique’s national SAO density of 1.2 per 100,000 is comparable to its low-income peers and far below the international target of 20 [2, 10]. Stratification by province reveals severe disparities as most surgical providers are heavily concentrated in the capital city of Maputo, where the SAO density is 9.8 compared to the median value of 0.84 in the Province of Nampula. Stratification by provider type also reveals densities of 1.1 surgeons and 0.1 anesthesiologists per 100,000 population. While a formal analysis is outside the scope of the current study, there are various possible explanations for the unequal distribution of providers, most notably the comparative luxuries of living in the urban capital setting.
Additionally, most district hospitals rely on nonphysician technicians to perform basic surgery and anesthesia. Traditionally, nonphysician technicians are not counted in international SAO comparisons, but in Mozambique these technicians provide 39.7% of all procedures and it is impossible to neglect their contribution. These technicians are compared in Table2 to demonstrate the effect of inclusion on national and subnational SAO calculations [10, 28]. More intense focus on surgical providers will be required to overcome the current barriers in the provision of safe surgical and anesthetic care [29–32].
Surgical output
Low surgical volume in Mozambique is multifactorial and granular data elucidates possible areas for improvement. Mozambique’s annualized surgical case volume density of 367 per 100,000 falls well below the minimum international target of 5000 cases per 100,000 per year [2]. Stratification by province shows more than a tenfold difference in case volume density between the capital city Maputo and rural areas (i.e., Zambezia, Niassa). This ‘tale of two metrics’ between rural and urban settings is not unique [10, 33]. A study in Mozambique, Tanzania, and Uganda found low rates of major surgeries at district hospitals, ranging from 50 to 450 surgical procedures per 100,000 people, and that the majority of non-obstetric surgery is for emergencies rather than for elective conditions, suggesting that district residents do not receive surgical care for common (non-emergent) surgical conditions in local hospitals [34]. Community-based surveys also show that 17% of people in Mozambique are living with untreated surgical conditions [35, 36]. Our findings confirm that Mozambique will need to significantly boost its health system to reach recommended targets.
Postoperative mortality
Postoperative mortality (POMR) is unique among recommended surgical metrics because it is a marker of quality of surgical care [37–39]. In Mozambique, the national inpatient POMR was 0.74% and quite comparable to the Pacific Region [28]. However, stratification by province reveals substantial disparities between regions of the country, with POMRs spanning a range of roughly a tenfold difference (0.23% in Maputo Province to 1.78% in Niassa, See Table 3). This finding recapitulates the importance of comprehensive population-level datasets. Datasets relying on a convenience sample of self-selected institutions reporting POMR have limited utility in regional or international comparisons because they are not representative of the population outside the study [40–43]. The same is true of datasets limited to a discrete number or type of operations [44, 45]. These limitations of comparability are evident in the largest meta-analysis of POMR to date by Ng-Kamstra et al. [46]. In Mozambique, variation in POMR allows concentrated deeper dives in provinces of concern to disambiguate between the many possible causes of elevated POMR, including pre-hospital care, management of comorbid disease, timeliness of presentation, availability of resources, and quality of surgical care.
Strategies for incremental upscaling
The strength of our findings is most clearly elucidated in the exercise of implementing change. Aspirational targets, such as a surgical procedure volume density of 5000 cases per 100,000 population, seem out of reach from a setting like Mozambique where the starting point is 367 per 100,000. To put that into perspective, Mozambique’s current national surgical volume output (94,378 cases annually) is only 7% of that goal. In order to achieve this goal, Mozambique surgical output would have to perform an additional 1,286,396 surgical procedures each year. Lowering the target to Maputo City’s surgical output, 1897 cases per 100,000, makes the goal more attainable, which would require 393,680 additional surgical procedures each year. A more conservative strategy is to bring all provinces to the national statistic of 367 cases per 100,000 population, in which case efforts could be focused on the seven provinces that fall below this national average, which would require an additional 22,402 procedures each year, or 679 operations per hospital in those seven provinces, which translates to roughly 14 more operations per week. Incremental targets, grounded in subnational data stratifications, allow countries to set concrete short- and long-term goals on a path to upscaling surgical services with neighboring provinces serving as case studies of feasibility.
Our subnational findings also facilitate the development of referral networks within a country’s healthcare system. In high-income countries, a robust body of literature confirms the positive relationship between hospitals with high surgical volume and postoperative outcomes [47]. High-volume centers are known to have lower postoperative mortality and costly complications [48]. For this reason, a logical response to the subnational disparities we report may include preferential triage of complex cases to centers where specialist care is available and ensuring availability of complex services to the frontline where acuity may not allow for immediate transfer without stabilization, such as trauma and obstetric emergency. Using a national dataset of surgical encounters from New Zealand, Hider et al. described a framework of four disease prototypes that allows policy-makers to apportion surgical services within a healthcare system according to disease prevalence and surgical incidence [49].
Weaknesses
The current study does have multiple weaknesses. Regarding access, our calculation is not ideal because we do not utilize available technologies such as ArcGIS, Redivis, or OpenStreetMaps [5, 50, 51]. During the rainy season in Mozambique, road conditions change drastically, leading to significant seasonal variability in access. The authors felt this variability was so great as to render the geospatial mapping without internal validity. Additionally, patient age, procedure type, ASA class, and emergency status might assist in risk adjustment through an efficient tool designed by the authors [52, 53]. Risk adjustment might help to account for differences between hospitals in case mix and disease severity. Lastly, we know that up to 30% of admissions to surgical wards in Mozambique do not undergo a surgical procedure, reflecting the large non-operative component of care by surgical teams that is wholly ignored by the standard metrics [26].
Summary
This is the first national study to address the delivery of surgery in Mozambique. Timely access, SAO provider density, and surgical case volumes in Mozambique fall short of international targets and substantial variation exists between provinces. Training and retaining local anesthesia and surgical physicians are vital to boost surgical services. Abject deficiencies and variations in surgical care pose targets for future interventions in advancing Mozambique’s NSOAP. POMR is low and nonphysician technicians play a large role in this success. This study serves as a template for LMICs to follow in meeting the current mandates for surgical metrics from the WHO and the WB and establishes baseline outcomes for international comparisons and quality improvement.
Acknowledgements
We would like to acknowledge Dr. Ussene Isse and all his team as the National Director of the Medical Assistance Directorate at the Ministry of Health of Mozambique. We also wish to thank our staff and collaborators at the Mozambique Institute for Health Education and Research (MIHER) who gave the institutional and administrative support which made this work possible. A special thanks to my research team, Drs. Adriano Tivane, Amâncio Oliveira, Clotilde Nhatave, Ivandra Magaia, Micail Julaya, Monica Muataco, Nelson Mucopo, Paulo Gudo, Thiago Machado de Oliveira, Tyler Robinson, Jamie Anderson, all the nonphysician surgeons, administrative personnel, and health managers who took part in this work.
Funding
This project was supported by United States National Institutes of Health through the Fogarty International Center and University of California Global Health Institute (UCGHI), grant numbers R25TW009343 and R25TW011216.
Footnotes
The content is solely the responsibility of the authors and does not necessarily represent the official views of theNational Institutes of Health or UCGHI.
Conflict of interest The authors have no conflicts of interest of relevant financial disclosures.
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