Background
Equitable access to surgical care service is still unreachable for billions of people. According to the Lancet Commission on Global Surgery (LCoGS), about five billion people lack access to timely, safe and affordable surgical and anesthesia care services globally [
1]. However, the inaccessibility of surgical care disproportionately high in low-and middle-income countries (LMICs), where nine of ten people cannot access basic surgical care. Of the 313 million surgical procedures undertaken globally per year, only 6% were performed in the poorest countries, where over a third of the world’s population lives. The lion share of unmet surgical needs appear in sub-Saharan Africa and South Asia [
1]. Regarding the type of procedures, 80% of the practices are indicated to be elective, whereas, in sub-Saharan Africa major proportion of the practice is on emergency and essential surgeries. This requires instantaneous attention [
2]. Improving access to safe and affordable emergency and essential surgical and anesthesia care reduces premature death and disability, and also boosts welfare, economic productivity, capacity, and freedoms, contributing to long-term development [
1].
The World Health Organization (WHO) Global Initiative for Emergency and Essential Surgical Care launched in 2005, galvanized global commitment for strengthening access to Emergency and Essential Surgical Care (EESC) in LMICs through successful advocacy efforts for the inclusion of EESC as an integral component of the Universal Health Coverage (UHC) packages. In 2015, the World Health Assembly (WHA) Resolution on EESC had motivated countries to prioritize surgical and anesthesia care in their national surgical plans and develop a national surgical plan [
3,
4].
Measuring surgical care in terms of capability, capacity, timeliness, safety, and affordability is essential to access the services. In line with this, the LCoGS put forth the following targets to be achieved by 2030. The targets include 80 percent coverage of essential surgical and anesthesia services per country; at least 20 surgical, anesthesia, and obstetric physicians per 100,000 population; 5,000 procedures annually per 100,000 population, and 100 percent protection against catastrophic expenditure from out-of-pocket payments for surgical and anesthesia care [
1].
In Ethiopia, former study findings showed a substantial unmet need for surgical care in the country. For instance, in 2015 the surgical volume and specialist surgical workforce per 100,000 population were 43/100,000 population and 0.35 surgeons/100,000 population, respectively [
5]. In alignment with global commitment, the Ministry of Health (MOH)-Ethiopia launched Saving Lives through Safe Surgery I (
SaLTS I) Strategic Plan 2016–2020 as the national flagship initiative. The
SaLTS initiative was designed to improve access to safe surgical care at all levels of the Ethiopian health care delivery system with special emphasis in expanding EESC service in the primary level healthcare units (PHCUs) [
6,
7].
Ethiopian health care operates on the basis of a three-tier healthcare delivery system. The first level comprises the PHCUs, which include health posts, health centers, and primary hospitals, while levels two and three comprise general hospitals and specialized hospitals including teaching hospitals, respectively [
8]. The private for-profit sectors are supplementing the health service coverage at various levels of the healthcare system [
9]. However, after the
SaLTS initiative has been launched, there is no adequate information about surgical care access status across levels of the health system in Ethiopia. Understanding the surgical care access status will be a springboard for the subsequent planning and inform the strategies to achieve universal access to surgical care in the nation. The aim of this study was to assess the status of surgical care access in terms of capability, capacity, and timeliness in different levels of health care including public and private health care facilities in Ethiopia.
Methods
Study design and setting
Health facility based cross-sectional study with retrospective data review was conducted in public and private health facilities of Ethiopia from December 30, 2020 to June 10, 2021. Ethiopia is an east African country with estimated population of more than 117 million people in 2021 [
10]. A total of 282 government health facilities and 45 private hospitals were providing surgical care in the country during the study period.
Sampling procedure and sample size
A multi-stage stratified random sampling method was used to select study sites (public and private health care facilities). First, lists of all health care facilities providing surgical care were obtained from MOH of Ethiopia’s District Health Information System 2 (DHIS 2) report. Accordingly, 282 government hospitals (26 specialized hospitals, 75 general hospitals, and 181 primary hospitals) were providing EESC during the study period. The required sample size for the study was estimated using a single population proportion formula with a 95% level of confidence, a 5% margin of error, and an assumed proportion of surgical care accessibility (P = 0.5); therefore, the sample size was estimated to be 163 public hospitals. As we used a stratified sampling method, the sample size for each stratum of primary hospitals (np), general hospitals (ng), and specialized hospitals (ns) was calculated using the proportional allocation method and it was 105, 43, and 15 hospitals, respectively. In addition, to assess the status of surgical care in the private health sector, private health facilities providing safe surgical care services were included. According to DHSI 2 report, 45 private health facilities were providing surgical care. Thus, the sample size for private hospitals was estimated to be 40. This makes a total of 203 study sites. Each hospital from each stratum was selected by a simple lottery method. However, due to internal conflict and limited transport accessibility in some parts of Ethiopia, we could not be able to access all health facilities that were selected randomly, and we decided to replace some health facilities which were convenient assuming that hospitals in the same strata are homogeneous. A total of 172 sampled health facilities were evaluated in the study, which hold 84.7% of the estimated sample size.
Data sources and collection
Routine DHIS 2 surgical care services database and pre-admission and admission register were reviewed using the Harvard Program in Global Surgery and Social Change and the WHO Surgical Assessment Tool [
11], which was adopted in the context of Ethiopia. Thirteen trained data collectors reviewed the data from December 30, 2020-June 10, 2021. Data collectors were trained about the entire process of data collection including quality control measures such as: completeness, correctness, consistency, and synchronizing and archiving data with RedCap. The data we reviewed includes data dating back to September 2020 to May 2021; specifically, for total numbers of surgical procedures with the intention to capture the volume of procedures done in the past 90 days prior to data collection, therefore, this data reflects the volume of procedures done in a 90-day interval of the time from September 2020 to May 2021. Precaution measures including wearing a face mask, using hand sanitizers, and physical distancing were implemented to prevent Coronavirus disease 2019 (COVID-19) transmission during data collection.
Quality assurance
To ensure the quality of data, the data were cleaned and checked for completeness, correctness, and consistency. Regular supervision and follow-up were made throughout the data collection period.
Operational definition of variables
Surgical care: provision of perioperative and operative management for surgical conditions.
Surgical volume: number of minor and major surgical procedures performed during the study period.
Major surgery: surgeries that require general or regional anesthesia, involve opening great body cavities, have risk of severe hemorrhage, put the patient’s life at risk and needs postoperative care and require special anatomical knowledge, manipulative skills,and specific equipment.
Minor Surgery: surgeries in which short surgical techniques are applied on superficial tissues, usually with local anesthesia and minimal complications that usually do not require postoperative resuscitation and need minimal equipment.
A Bellwether procedure: any procedure involving laparotomy, cesarean section, or treatment of an open long bone fracture.
Physical access for surgical care: Surgical health facilities that can be accessed within two hours of travel.
Surgical referrals out: number of patients referred out of the hospitals/health center operation room (OR) blocks for surgical services after an on-site assessment by a medical professional in the reporting period.
Surgical workforce: total number of available surgical workforces including Surgeons (General, neurosurgeons, and orthopedic surgeons), Anesthesiologists or anesthesia care providers, Obstetrician-gynecologist, Integrated Emergency Surgical Officers (IESO), and Nurse Anesthetists.
Data management and analysis
The reviewed data were cleaned, checked for consistency, and entered into the Redcap database, and the data collectors archived cleaned data on a regular basis, every week. Then the cleaned data were exported into STATA Version 15 statistical software package for statistical analysis.
Descriptive statistics: frequency, proportion, and median with interquartile range (IQR) were computed. As the data were skewed, non-parametric tests (Mann–Whitney/Kruskal–Wallis) were employed to compare the median number of surgical volumes performed by health care facilities level. Kruskal–Wallis test was used for comparing the surgical volume performed among public specialized hospitals, public general hospitals, and public primary hospitals, and the Mann–Whitney test was used for comparing the surgical volume between public and private health facilities. A p-value of < 0.05 was considered statistically significant.
Ethical consideration
The study was approved by Armauer Hansen Research Institute (AHRI) ethical review board in Addis Ababa, Ethiopia. Additionally, the Ethiopia MOH issued a letter of support to conduct data review at the selected health facilities. Additionally, letters of support and permissions were obtained from the local health offices authorities to conduct data review at the selected health facilities.
Discussion
In this study, more than half (58%) of the surgical procedures were major surgeries, and about 41% of which were performed in public specialized hospitals where capacity in terms of human resources, infrastructure, equipment, and supplies are relatively better. On the other hand, public primary hospitals performed a small proportion (13.3%) of major surgical procedures. This is in line with a study in three East African countries that reported low rates of major surgery at district hospitals, ranging from 50 to 450 surgical procedures per 100,000 population [
12]. In Ethiopia, more than 80% of the total population lives in rural areas of the country where they get health services from the PHCUs [
13,
14]. This implies that there is a substantial unmet need for major surgical services for the majority of the population in Ethiopia.
Despite the fact that only 18.6% of the study facilities were private surgical facilities, the private sector contributed to 17.3% of both minor and major surgical volume for the study period. Although, the median number of major surgical procedures was significantly high in public specialized hospitals as compared to public primary and general hospitals (Kruskal–Wallis test;
p < 0.001), however, the median number of major surgical procedures which were performed in 32 private health facilities was higher than 136 public health facilities performed during the period. Furthermore, more than a third of open fracture management was undertaken in private hospitals. This may indicate the demand for surgical care services from private health facilities and the significant contribution of private hospitals in reducing the surgical burden. Nevertheless, the private sector in Ethiopia is relatively small (approximately 20% of the total health market share) compared to other countries in the region. For instance, 46% and 65% of all health facilities are managed by Private Sectors in the Democratic Republic of Congo and in Kenya, respectively [
15]. Moreover, SaLTS I strategy has not been implemented in the private hospitals. Our finding underscores the importance of scaling up surgical care services in the private sector.
In this study, nearly half (45.3%) of the bellwether surgical procedures were performed in specialized hospitals. This is consistent with findings of a study in KwaZulu
-Natal Province of South Africa which showed that the majority of non-obstetric bellwether operations were performed at regional and tertiary hospitals [
16]. The Lancet commission recommends that all first-level hospitals should be able to perform laparotomy, cesarean delivery, and treatment of open fractures as bellwether procedures [
1]. The procedures have been proposed as proxy metrics for surgical systems that are functioning at a level of complexity advanced enough to provide most other surgical procedures [
16,
17]. However, in the current study, first-level health care units (primary hospitals and health center OR blocks) performed a small proportion (12.8% and 3.1%) of all the bellwether procedures, respectively. Likewise, a study from KwaZulu
-Natal Province reported that the non-obstetric bellwether operations that were performed at district hospitals of South Africa were small to negligible, with 2.1% laparotomies and 1.8% open reduction of fractures, and this study highlighted that the imbalance performance has major implications for strategic planning around the delivery of surgical care [
16].
Our study showed the surgical volume of 289 /100,000 population, 37/100,000 population, and 33/100,000 population over a 90-day interval in PHCUs, general hospitals, and specialized hospitals, respectively. This indicates that the surgical volume in Ethiopia’s public health facilities falls far below the LCoGS target of 5000 surgeries per 100,000 population/year which has been set to be achieved by the year 2030 [
1]. Likewise, findings of studies from other African countries showed low surgical volume to population ratios such as Uganda (145/100,000 population) [
17] and Rwanda (429/100,000 population) [
18].
The study revealed that patients traveled about 28Hrs, 21Hrs, and 11Hrs to access surgical services in public specialized hospitals, private hospitals, and public generalized hospitals, respectively. This is still far from the LCoGS recommendation that patients should access a facility capable of performing the Bellwether procedure within two hours [
1]. The relatively long-distance travel observed in our study may be related to the reason that majority of specialist surgical workforce is available in these health facilities. Likewise, studies in other sub-Saharan African countries showed that a significant proportion of people lack timely access to surgical care. For instance, a study conducted in Zambia showed that only 20% of the population lives within two hours of facilities providing essential and emergency care [
19]. Another study from Ghana revealed that about 30% of Ghanaians don’t have access to essential surgery within two hours [
20]. Long-distance was one of the major factors that affect timely access to health care services in these studies [
19,
20].
On the other hand, our study showed that patients have taken less than one hour to reach the health centers OR blocks. This may be related to the reason that all health center OR blocks are located in Addis Ababa where with relatively better transport access. However, a small proportion, 2.4% of minor surgeries and 3.1% of bellwether procedures were performed in health centers OR blocks for the period. This may be related to the gap in the deployment of IESO at the health center level.
The average pre-admission waiting time for patients, who need essential surgical care, was 38 days in general hospitals and 36 days in specialized hospitals. This is longer than the findings of studies from other countries. For instance, a study from Zambia showed that the pre-admission waiting time for surgical patients, who need elective surgery, in teaching hospitals was 9 days [
21]. Another study from India revealed a pre-admission waiting time of 12 days for surgical patients in teaching hospital [
22]. Moreover, generalized and specialized hospitals reported longer pre-admission waiting times compared to private hospitals and public primary hospitals reported. Long pre-admission time in generalized and specialized hospitals observed in this study might be related to the high burden of surgical cases requiring more advanced surgical care. The pre-admission waiting time reported in these health facilities was also longer than the country’s target of less than 30 days [
8]. Prolonged pre-admission waiting time worsens surgical outcome, pre-operative anxiety score, and depression [
23,
24]. Moreover, it may also result in post-operative complications, mortality and increased hospitalization stay, and catastrophic costs [
25].
This study showed that public primary hospitals referred nearly two-fifths (41%) of surgical patients. Nonetheless, higher levels of health facilities including generalized and specialized hospitals also referred significant proportion of patients who need surgical interventions. Lack of skilled professionals, lack of equipment/instrument, lack of blood, and lack of supplies or medications were the most frequent reasons for patient referrals at all levels of the health system. Likewise, a study from Tanzania showed that the lack of essential equipment, infrastructure, and human resources were significant gaps to provide EESC in first-referral health facilities [
26].
Lack of skilled professionals accounts for about one-third of the reasons for surgical referral out and which may likely indicate shortages of surgical workforce in the country. Our study also showed a considerably low surgical workforce to population ratio which was about 1/100,000 population served in higher levels of health facilities. However, the surgical workforce per 100,000 population served in PHCUs (10.8/100,000 pop in Health center OR blocks and 7.5/100,000 pop in primary hospitals) was higher compared to in higher levels of health facilities. This might be related to that PHCUs are supposed to serve nearby communities and lower catchment populations [
8]. Shortage of surgical workforce has an impact on the service delivery, patient satisfaction, and finical burdens on the patients [
27]. Unless the country designs a strategy like surgical task shifting programs it will be unlikely to achieve the LCoGS target of 20 surgical workforces per 100,000 populations by 2030 in general and accessing the surgical care service at PHCUs level in particular.
The study also has strengths. As far as our literature review is concerned, this is the first study in Ethiopia that attempted to assess surgical care access in terms of capability, capacity, and timeliness across levels of the health care system. The study highlighted the surgical care access gap within the health system of the country; therefore, we believe that the results would inform a crucial input for the surgical care strategic plane of Ethiopia and provide a foundation for evidence-based decision-making and evidence-informed policy making. Moreover, the study may be used as baseline data for future studies.
Our study has limitations. Although we could collect data from 85 percent of sampled health facilities, because of security situations related to the existing conflict at different places of the country, the data were not collected from all sampled health facilities. Moreover, the study was conducted in the COVID-19 era when the pandemic has been affecting health services provision including surgical care. Therefore, the pandemic might have affected the performance of surgical care services, particularly the surgical volume. This study may share the inherent limitation of secondary data such as inconsistency, incompleteness, and inaccuracy; however, extensive efforts have been made by the research team to ensure the data quality.
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