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Cross Sectional Study

Mixed-method analysis of barriers to surgical care in Uganda

Incorvia, Joseph J. MSa,b; Du, Robin BSc; Tafreshi, Ali R. BAc; Vissoci, Joao R.N. PhDa,b,d; Fuller, Anthony T. MDa,b,d,e; Rice, Henry E. MDf; Kebba, Naomi MDd; Doshi, Pratik BSf; Galukande, Moses MBChBd; Haglund, Michael M. MD, PhD, FAANSa,b,d,e,

Author Information
International Journal of Surgery: Global Health: July 2020 - Volume 3 - Issue 4 - p e21
doi: 10.1097/GH9.0000000000000021


The Lancet Commission on Global Surgery reports that an estimated 5 billion people do not have access to safe, affordable surgical and anesthesia care, with the majority of those residing in low- and middle-income countries (LMICs)1. Only 6% of surgical procedures worldwide occur in LMICs, requiring over 143 million additional surgical procedures to meet the need in those areas1. There exist major barriers preventing patients from obtaining the surgical care they need. In the Lancet Commission, Dr John Meara and colleagues describe the Three Delays framework, which was adapted to assess the different delays experienced by patients when seeking surgical care1. The First Delay is delay in seeking care, the Second Delay is delay in reaching care, and the Third Delay is delay in receiving care, with each limiting access through a variety of factors ranging from financial limits to proximity and location of hospitals to surgical infrastructure, personnel, and capacity1–10. These delays help provide a framework for the many barriers that patients face when attempting to receive surgical care; however, study of self-identified barriers in a surgical context is limited.

Many theoretical frameworks exist regarding health care access and behavioral choices; notable among these are the Health Belief Model, Theory of Reasoned Action, and Theory of Planned Behavior11,12. Health care access, specifically, benefited from the works of Obrist and Peters, who defined access to health care by outlining specific dimensions of care that influence an individual’s access to care13,14. Likewise, Irfan’s Healthcare Barrier Model accurately articulates how to identify the main barriers regarding access to health care, many of which have ample amounts of literature supporting how they obstruct individuals from receiving the care that they need5,15–20. Assessing barriers at 4 levels (patient, environment, health system, and provider) gives this model the ability to show how different barriers in society are related to each other16. However, on its own, it lacks information regarding how these barriers impact overall access. Therefore, for our study design, we chose McIntyre’s Access Evaluation Framework, which utilizes the dimensions of availability, affordability, and acceptability, to be the lens through which we investigate barriers as they relate to access to care21.

Although these theoretical frameworks have their merit, none individually are sufficient to understand the connection between behavior, access, and barriers. In order to shed light on and further investigate these connections, we developed a mixed-method protocol to elucidate the most significant barriers to surgical care among individuals in Uganda. The protocol was based on a need to understand what factors influence individuals to overcome or succumb to barriers.


Ethics approval

Written informed consent was obtained from all study participants prior to the survey. If the participant could not read, the informed consent document was audibly read to the participant. If the participant could not write, his or her thumbprint was used to grant consent, as this method is an accepted form of signature by the Ugandan National IRB. Ethical approval for this study was provided by the Ugandan National IRB Committee.


Mulago National Referral Hospital (MNRH) serves as a teaching hospital and tertiary care referral center, and has the largest catchment area in Uganda due to its location in the capital city of Kampala (1.5 million people), and takes cases from throughout the country22. Jinja Regional Referral Hospital (JRRH) serves the 17th most populated district in Uganda (76,000 people) and has a much smaller catchment area22.

Data collection

This study employed a mixed-method design that used a 3-part data collection tool utilizing concurrent triangulation. The first 2 parts consisted of a quantitative demographic survey and a ranking and rating exercise. This was followed by an in-depth interview, which served to supplement and explain the findings of the demographic survey and ranking and rating exercise; the findings of this portion of the study will be published separately.

Quantitative methods

At both study sites, participants were recruited from a convenience sample within all surgical wards at MNRH and JRRH. Participants were eligible if they were a patient receiving surgical care or a representative family member or attendant that was with the patient throughout the time the patient was in the hospital. The individuals needed to be in the surgical wards and proficient in either English or Luganda, the languages that were comprehensible to the surveyors. Potential participants were excluded if they were identified as incapable of understanding and answering the questions or were very ill and unable to provide answers. Potential participants identified within the wards were approached and once written consent was obtained, a research nurse administered the questionnaire and facilitated the completion of the survey.

The first part of the questionnaire was a basic demographic survey pertaining to information about the individuals, their household, and their background. Next, participants were asked about their surgical experience and what caused them to be in the hospital for the procedure that they either already had or were scheduled to receive. A third section inquired about transportation to the hospital and any prior experiences with alternative medical facilities or local healers regarding their current condition. Finally, the questionnaire concluded with a ranking and rating exercise which adapted a model that is highly used in the literature to provide insight into the significance of multiple variables5,23–26.

In the ranking exercise, the participant ranked 10 predetermined variables that represented barriers to seeking surgical care from most significant to least significant (Appendix, Supplemental Digital Content 1, In the rating exercise, the participant individually indicated the significance of the same barriers one at a time using a Likert scale, ranking each barrier individually from 1, least significant, to 5, most significant. A separate manuscript detailing the methods of the ranking and rating exercise and qualitative interviews is currently being prepared for publication by our team.

The survey questionnaire was adapted from the Surgeon Overseas Assessment of Surgical Need (SOSAS) Version 3.0 and a study on pediatric surgical barriers in Guatemala23,24,27. All paper data was immediately entered into Lighthouse Studio (Version 9; Orem, UT) to aggregate and then exported to an Excel (Redmond, WA) spreadsheet.

Data analysis

Overall, 214 questionnaires and 13 interviews were conducted. Open-ended text answers were coded into numerical categories with surgical procedures assessed by a collaborator at MNRH to determine proper coding. Cost data was converted from Ugandan Shillings (UGX) to United States Dollars (US$) for contextualization. Analysis was performed with Stata Statistical Software (Version 14.2; College Station, TX).

Descriptive statistics were used to describe the demographic and other characteristics of the data. All parametric continuous data were summarized as means and SDs. Nonparametric continuous data were summarized as medians and interquartile ranges (IQR). Median ranks and rates for each of the barriers to surgical care were calculated, along with IQR. The medians of the barriers to surgical care were used to rank each obstacle from most to least significant for both exercises. The medians were also compared between hospital sites and reported to show trends based on the location of the surveyed population.


Overall descriptive results

The participants were evenly split between the 2 surgical sites within Uganda, with 47% (n=101) from MNRH and 53% (n=113) from JRRH (Table 1). Almost half of patients were located within the general surgery wards of the hospitals (48.6%, n=104), with pediatrics contained the second highest percentage of patients (16.8%, n=36). Notably, 38.8% (n=83) of respondents reported that an injury was the reason for which they were there to receive surgery, while 49% (n=105) cited a preexisting medical condition as the reason.

Table 1
Table 1:
Sample demographic characteristics.

The median income for participants in the study was US$5.56 (UGX20,000) per week and US$288.88 (UGX1,000,000 UGX) per year (Table 2). Comparatively, the average total cost incurred by participants was US$10.20 (UGX36713.50). The highest cost that an individual incurred during their time to reach the hospital was US$691.66 (UGX2490,000). Between the 2 hospitals, the difference between the total costs incurred were statistically significant, with patients at MNRH incurring a higher average cost on their way to the hospital.

Table 2
Table 2:
Population economic characteristics.

The number of transportation modes used by subjects had a median of 1 (IQR; 1–2), and ranged from 1 to 7 types of transportation per route to the hospital. MNRH had a median number of transportation modes used of 2 (IQR: 1–2) and JRRH had a median of 1 (IQR: 1–2), which was significantly different between the two study sites with a P-value of 0.048 (Table 3). The most common modes of transportation were by motorcycle, locally referred to as bodas (or boda bodas), and public transport via a taxi known as a mutatu. Of all the participants, 37.2% (n=132) reported using motorcycles and 31.0% (n=110) stated use of public transportation. Only 7.9% (n=28) of participants cited being taken to the hospital by an ambulance. More than half of participants (55.6%, n=119) indicated that their preferred method of transportation to the hospital would be an ambulance.

Table 3
Table 3:
Sample transportation characteristics.

Overall, participants traveled to the hospital an average of 20.6 km, higher for those at MNRH (31.2 km) than those at JRRH (14.2 km) (P-value <0.001). Similarly, total travel time and total wait time for transportation to arrive were higher at MNRH than at JRRH (P-values <0.001 for both). When the time waiting for transportation was subtracted from the total travel time to reach the hospital, there was a decrease of nearly 1 hour overall—2.9 hours with waiting and 2 hours without waiting (Table 3). In terms of cost of transportation, the average amount of money spent on transportation for all respondents was US$4.00 (UGX14406.58), and this number was again significantly higher for MNRH than JRRH (Table 3).

Ranking and rating exercise

The rating and ranking exercise demonstrated differences between the most significant barriers. The rating exercise revealed that cost of surgery (median: 4, IQR: 3–5), distance to the hospital (median: 4, IQR: 2–5), and transportation to the hospital (median: 4, IQR: 2–4) were the most significant barriers to seeking and reaching care (Fig. 1). Language barrier (median: 1, IQR: 1–2) and no control over decision making (median: 1, IQR: 1–3) were the least significant barriers during the rating assessment. The ranking exercise revealed that cost of surgery (median: 1, IQR: 1–3) was the most significant barrier to care (Fig. 2). Second was transportation to the hospital (median: 3, IQR: 2–5). No control over decision making was elucidated as the least significant of the 10 barriers listed (median: 9, IQR: 6.25–10).

Figure 1
Figure 1:
Median rating for each barrier to surgical care (orange) along with interquartile range, Q1 (gray) and Q3 (blue), for all participants. Variables are ordered from highest median ranking (5) to lowest (1).
Figure 2
Figure 2:
Median ranking for each barrier to surgical care (orange) along with interquartile range, Q1 (gray) and Q3 (blue), for all participants. Variables are ordered from most significant median ranking (1) to least (10).


This study demonstrated that Ugandans seeking surgical care risk catastrophic expenditure, are required to travel long distances, and face numerous obstacles before being admitted for surgery, which many cannot afford to begin with. Each of the 10 barriers assessed in our ranking and rating exercises represented a higher order theme that stemmed from 1 of the 3 main categories in McIntyre’s framework21. Our ranking and rating exercises found that cost of surgery, distance to the hospital, and transportation to the hospital were the most significant barriers to accessing surgical care; these belonged to the categories of affordability and availability. Language barriers, not having a caretaker at the hospital, and having no control over the decision-making process were found to be the least significant barriers; all 3 of these barriers belonged to the category of acceptability. Some variation existed in the results obtained using these 2 tools; however, the 3 most significant barriers and the 3 least significant barriers were consistent between the 3, albeit with some differences in the order.

The results of our study reflect the literature for other sub-Saharan Africa studies. Lin and colleagues found that cost was reported as the most significant barrier to surgical care in the Republic of Congo by 73% of their respondents28. A study utilizing SOSAS in Nepal found similar results as well, citing accessibility and affordability as the most significant self-reported barriers to care, which supplements the findings by Fuller and colleagues in Uganda preceding this study29,30.

In many areas of the world, particularly LMICs, out-of-pocket payments remain the primary form of health care financing, which carries a risk of impoverishment31. Catastrophic health expenditure is defined as out-of-pocket spending for healthcare that exceeds a certain percentage of a household’s income, leading to the household suffering the burden of the disease and impoverishment as a result of the costs of obtaining health care32. The literature, consisting of studies of various developing countries, shows that this type of health care expenditure is often a significant barrier to seeking health care due to the potentially devastating socioeconomic consequences of out-of-pocket costs33–39.

In our study, about one-third (36%) of all patients surveyed were unemployed. Median weekly income of participants was US$5.56, compared with an average US$10.20 total cost incurred on the way to the hospital, which has the implication that one trip to the hospital for a surgical intervention could cost 2 weeks’ worth of income for the average patient. Cost incurred was significantly higher at MNRH (US$20.40) than at JRRH (US$5.28) (P-value of <0.001); 1 month’s worth of income was required for the average patient to pay for a surgical intervention at MNRH, including the transportation they took to get there.

Our study demonstrates that with catastrophic expenditure already occurring before the patient arrives at the hospital, revisiting health financing schemes should be made a priority. Whether it be by providing better access and transportation to surgical centers to mitigate the cost of reaching care or by decreasing indirect costs within the hospital, there needs to be a restructuring of the costs that patients need to pay out-of-pocket. If this can be addressed, there would be less stress on patients to be able to reach the hospital and many more people would be able to receive care. Protection against catastrophic health expenditure has become an emerging policy goal within global health, and is 1 of the 6 core indicators for monitoring of universal access to safe, affordable surgical and anesthesia care as outlined in the Lancet Commission1. The World Bank has stated that, “By 2030, no one should fall into poverty because of out-of-pocket healthcare expenses.”40 In order to achieve this, we need greater insight into the various costs incurred, both medical and nonmedical, that lead households to become impoverished in the process of obtaining much-needed health care.

Distance and transportation to the hospital also inherently posed significant challenges to patients attempting to access surgical care, beyond their implications on cost. In order to reach the hospital, the average patient in our study traveled 20.6 km and used a total travel time of 2.9 hours, which includes time spent waiting for transportation. A dichotomy between transportation types taken and preferred transport type was found, as 37.2% of participants traveled by motorcycle and 31% of participants traveled by public transportation to the hospital, but 55.6% of all participants preferred an ambulance as their main means of travel to the hospital; however, only 7.9% of participants were transported via ambulance to the hospital. Although these statistics were obtained from patients who had already arrived at the hospital, they highlight conditions and barriers that may have prevented others from even seeking out necessary surgical care.

In tandem with the recommendations from the Lancet Commission on Global Surgery, this study has important implications for policy. Elucidating the means by which individuals travel to the hospital and the barriers and financial loss incurred during that process is invaluable to a Ministry of Health and administrative personnel within hospitals. To better determine how to decrease the barriers associated with delays in seeking care and delays in reaching care, our study could be used to understand where patients are having the most problems as they attempt to reach the hospital.

The findings of this research indicate that governments and health care providers need to take into consideration and value the input, opinions, and preferences of the patients and caretakers who consume the health care. This is important for all healthcare settings, regardless of country economic classification. Within the 3 dimensions utilized as the lens for this study, acceptability is incredibly important in determining the effectiveness of the health care system21. Interestingly, the 3 least significant self-perceived barriers of care among patients in our study all belonged to the category of acceptability in McIntyre’s Access Evaluation Framework; however, if patients, providers, administrators, and governments do not see eye to eye on expectations for healthcare provision, then the system will fail those who need it the most. These lessons should be applied across settings within Uganda, and ideally throughout many developing countries worldwide.

However, mitigation of barriers to seeking care is not the only answer. Service provision should continue to be invested in as barriers are reduced. Greater accessibility leads to greater demand, and it is the responsibility of the health care system to provide the necessary capacity to address the demand. The Lancet Commission on Global Surgery is a great start to understanding how to address these issues in accordance with the Three Delays framework and the 6 core Lancet indictors and should be utilized as we move forward to help create and invest in quality surgical care for all1.


Limitations of this study include the short timeframe of data collection, small sample size, and the convenience sample utilized in this study. These limitations may lead to selection bias. All participants were able to reach the hospital and therefore may be biased toward the particular obstacles and barriers they faced to reach care. Furthermore, all patients who were very ill or unconscious were excluded, as they were identified as unable to complete the survey. In addition, patients who did not understand either English or Luganda were excluded. It is possible that the patients who were excluded may have had different perceptions and opinions on barriers to surgical care. These reasons, coupled with self-reporting, may limit the generalizability of the data. However, despite these limitations, we are confident in our results and the associations that we could draw. Our sample size of 241 patients was substantial enough to elucidate significant conclusions from the results of this study, our study was inclusive of patients with regards to sociodemographic factors such as age, sex, and income. In addition, our dataset was aggregated from 2 major hospitals in Uganda, which renders it more representative of the country’s patient population than a single-hospital study and further supports the robustness of the conclusions we drew.


This study uses a mixed-method protocol to elucidate the most significant barriers to accessing surgical care in Uganda. Our ranking and rating exercises confirmed that cost is the most significant barrier to surgical care, yet all types of cost should be considered to fully understand the economic burden that surgical patients face as they attempt to seek care. Catastrophic expenditure is not only relevant with regards to direct costs of surgical care; indirect costs provide equally large barriers preventing individuals from accessing surgical care. Distance to the hospital is another significant factor that needs to be addressed, as it manifests not only in large travel costs and delays in initial care-seeking behavior, but also demonstrates the need for proximal surgical sites that can provide surgical care to the most remote patients. Overall, efforts to reduce the cost of surgery and shorten the delay in seeking care and delay in reaching care should be prioritized to impact the most individuals, especially those in impoverished or rural parts of developing countries. Further studies regarding these barriers are necessary to influence the progression of policies that impact access to surgical care and to ensure that surgical provision and quality become priorities for governments and health care administrators.

Ethical approval

Ethical approval for this study was provided by the Ugandan National IRB Committee.

Sources of funding

Funding was provided by Duke Global Health Institute and Duke Division of Global Neurosurgery and Neurology.

Author contribution

All authors contributed to this manuscript.

Conflict of interest disclosures

The authors declare that they have no financial conflict of interest with regard to the content of this report.

Research registration unique identifying number (UIN)



Michael M. Haglund.


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Global surgery; Surgical capacity; Surgical barriers; Surgical access

Supplemental Digital Content

Copyright © 2020 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of IJS Publishing Group Ltd.