For exploratory purposes, no interactions were detected between each demographic and clinical factor with time period in their relationship with mortality (all P ≥ .20). After pooling the 2 cohorts, the adjusted analysis found that ASA-PS score (III or IV versus I or II) and emergency status were significantly associated with intraoperative mortality (imputed sample: OR, 4.4; 95% CI, 1.5–12.5; P = .006; and OR, 7.7; 95% CI, 2.5–23.6; P < .001, respectively). This finding was consistent with the model utilizing the observed sample (Table 3).
This study describes the case mix and intraoperative mortality rate for patients undergoing surgery at a Central Referral Hospital of Malawi. Overall, in combining the early and late cohorts, we found that intraoperative mortality in the study hospital is high (76 deaths per 100,000 surgeries) and did not change between the 2 time periods. Despite the inaccessibility of data between 2007 and 2014 to model the relationship over time, the high overall intraoperative mortality suggests a substantial need for improvements in surgical and anesthetic care in this region.
With increasing recognition of the role of surgery in improving population health,4 several metrics have been proposed to monitor and evaluate health care systems and processes of care delivery,5–7 but these metrics have rarely been applied in Sub-Saharan Africa. These metrics are also broad in scope and do not necessarily indicate which specific parts of the health care system should be targeted to increase access to quality care (eg, health care providers, infrastructure, anesthesia services). The perioperative mortality rate (POMR) is likely the most generalizable metric for use in low- and middle-income countries because it captures the continuum of surgical care and is applicable to patients of all ages undergoing all types of surgical procedures. However, it can be manipulated by the use of different denominators or time points for survival (eg, 24-hour vs 7-day mortality),8 and it requires reliable follow-up by clinical staff or research personnel, which may not be feasible in low-income or low-resource settings.
In areas of Sub-Saharan Africa with maturing surgical and anesthesia delivery systems, more precise details about surgical and anesthetic care, stratified by the preoperative, intraoperative, and postoperative periods, may more efficiently direct quality improvement efforts. Intraoperative mortality serves this purpose, in part, by reflecting the preoperative and intraoperative care. It is also easily measured without postoperative follow-up, making it more feasible for low-resource settings.
The overall intraoperative mortality of 76 (95% CI, 44–124) per 100,000 surgeries at this study site is higher than recent reports describing the POMR from Rwanda and Kenya.9,10 It is important to understand that intraoperative mortality is an underestimation of overall perioperative mortality, and this suggests an even higher POMR for Malawi. While the precise differences between surgical care in Malawi and Rwanda or Kenya are beyond the scope of this article, it is well known that in the past 2 decades since the Rwandan genocide, Rwanda has received foreign investments for the development of quality health care that are not likely generalizable to the region. The study from Kenya was also conducted at a hospital that has had substantial external investments over the past decade. Our study, although limited by the absence of cause-of-death data or a true POMR, provides an important benchmark for efforts to improve surgery in Malawi, and it may be more generalizable to regions where significant investments in surgical care delivery have not yet been made.
Factors associated with intraoperative death at this study site included ASA-PS score of III or IV and emergency status. While these factors are well-known predictors of perioperative mortality in high-income regions,11 there is a paucity of data describing perioperative mortality in Sub-Saharan Africa, and this study is one of the largest of its kind to provide clinical data confirming these associations. While the association of emergency status with intraoperative death is not unexpected,9,12 the OR for intraoperative mortality with emergency surgery in this study (imputed sample adjusted OR, 7.7; 95% CI, 2.5–23.6) is higher than that found in both high-income settings13 and in recent data from Kenya.10 The proportion of emergent surgeries at this site (46%) is striking and may be due to several factors. Given the increase in the unweighted proportion of male patients, orthopedic cases, and patients with ASA-PS status III or IV, this may be attributable to an increased burden of traumatic injuries over time. Alternatively, elective case cancellation is common in this region because of infrastructural limitations,14–16 and this may be associated with the volume of emergency surgery. Increased efforts at surgical care rollout in this region may have also led to more patients seeking surgery, but staffing and equipment may not have risen to meet the demand. Finally, in 2011, the financial aid to Malawi from the United Kingdom decreased dramatically, which may have affected the health care budget and available services.17 Surgical volume at this site increased only marginally over the study period and does not necessarily explain a high emergency case volume. Identifying the precipitating factors for emergency surgery and improving access to timely surgical care may be an important first step toward improving surgical safety in this region.
Improvements in quality surgical and anesthetic care in Malawi, and the region as a whole, will have to address infrastructural limitations. Although this study was performed at a Central Referral Hospital with some of the best staffing and resources in the country, the practice of anesthesia and surgery in Malawi is different than the standard in high-income settings. Anesthetic equipment such as ventilators, supplemental oxygen, end-tidal carbon dioxide monitoring or capnography, and warming devices is routinely absent. Available equipment is often old and cannot provide more modern interventions such as positive end-expiratory pressure or a titratable fraction of inspired oxygen. Medications used daily in high-income countries (eg, propofol, phenylephrine, fentanyl) are not routinely available. Outside the central hospital level, equipment and medications are even more scarce. For example, although every district hospital provides general anesthesia, only about half of hospitals in Malawi have a functioning anesthesia machine.18 Thus, the intraoperative mortality rate reported in this study likely represents the low range for intraoperative mortality nationwide and cannot reasonably be expected to improve without addressing these limitations.
Improvements will also have to take into account the differences in health care provider structure. Nonphysician clinical officers provide >90% of surgery and anesthetic care in Malawi.18 The current training for specialty clinical officers in anesthesiology or surgery is an 18-month course, after which the officers independently provide anesthesia, surgery, and critical care. This strategy has allowed the country to develop a cadre of trained health care providers while avoiding brain drain, but this training alone cannot prepare officers to manage all intraoperative complications. The high intraoperative mortality may indicate the need for improved education to address higher acuity patients and emergency cases. This may include simulation training and continuing education programs developed especially for clinical officers. Recruitment and retention of consultant physicians trained in anesthesia and surgery for oversight of the clinical officer workforce are other strategies to improve nationwide care.
This study has several limitations. First, because this was a secondary analysis of an existing database, we could not account for readmissions or repeat operations, which would reasonably be expected to be higher risk than initial procedures. Second, we did not have more granular data describing the operative interventions, intraoperative vital signs and events, or the proximate cause of death. Therefore, we could not assess the specific treatment modalities that may prevent further intraoperative events. The ASA-PS data may also be a potential source of bias because the pattern of its missingness may have been related to other variables such as surgical type or patient age. Finally, the daily case data from 2007 to 2014 were unavailable, so we were unable to assess trends in intraoperative mortality over that time period.
In summary, intraoperative mortality is an easily measurable indicator for surgical care quality in low-resource settings that focuses attention on a critically important time period for improving patient safety. Intraoperative mortality is high in Malawi and is not decreasing. This may be attributable to many factors, including a higher proportion of emergency surgery and/or changes in case mix. Efforts at improving safe surgery should focus on decreasing the need for emergency surgical care.
Name: Meghan Prin, MD, MS.
Contribution: This author helped to conceive and design the project, to perform data analysis, to write the manuscript, and had full access to all the data in the study.
Name: Stephanie Pan, MS.
Contribution: This author helped with statistical analysis and manuscript preparation.
Name: Janey Phelps, MD.
Contribution: This author helped to collect data and to write the manuscript.
Name: Godfrey Phiri, CO.
Contribution: This author helped to collect the data and to write the manuscript.
Name: Guohua Li, MD, DrPH.
Contribution: This author helped with the statistical analyses and writing the manuscript.
Name: Anthony Charles, MD, MPH.
Contribution: This author helped to conceive and design the project, and to write the manuscript.
This manuscript was handled by: Angela Enright, MB, FRCPC.
1. Debas HT, Gosselin R, McCord C, Thind A. Jamison DT, Breman JG, Measham AR, et al. Surgery. In: Disease Control Priorities in Developing Countries. 2006:2nd ed. Washington, DC: Oxford University Press; 1–26.
3. Liu Y, De A. Multiple imputation by fully conditional specification for dealing with missing data in a large epidemiologic study. Int J Stat Med Res. 2015;4:287–295.
4. Ozgediz D, Riviello R. The “other” neglected diseases in global public health: surgical conditions in Sub-Saharan Africa. PLoS Med. 2008;5:e121.
5. Watters DA, Hollands MJ, Gruen RL, et al. Perioperative mortality rate (POMR): a global indicator of access to safe surgery and anaesthesia. World J Surg. 2015;39:856–864.
6. Hughes CD, McClain CD, Hagander L, et al. Ratio of cesarean deliveries to total operations and surgeon nationality are potential proxies for surgical capacity in central Haiti. World J Surg. 2013;37:1526–1529.
7. Samuel JC, Tyson AF, Mabedi C, et al. Development of a ratio of emergent to total hernia repairs as a surgical capacity metric. Int J Surg. 2014;12:906–911.
8. Ariyaratnam R, Palmqvist CL, Hider P, et al. Toward a standard approach to measurement and reporting of perioperative mortality rate as a global indicator for surgery. Surgery. 2015;158:17–26.
9. Rickard JL, Ntakiyiruta G, Chu KM. Associations with perioperative mortality rate at a major referral hospital in Rwanda. World J Surg. 2016;40:784–790.
10. Sileshi B, Newton MW, Kiptanui J, et al. Monitoring anesthesia care delivery and perioperative mortality in Kenya utilizing a provider-driven novel data collection tool. Anesthesiology. 2017;127:250–271.
11. Koo CY, Hyder JA, Wanderer JP, Eikermann M, Ramachandran SK. A meta-analysis of the predictive accuracy of postoperative mortality using the American Society of Anesthesiologists’ physical status classification system. World J Surg. 2015;39:88–103.
12. Glance LG, Lustik SJ, Hannan EL, et al. The surgical mortality probability model: derivation and validation of a simple risk prediction rule for noncardiac surgery. Ann Surg. 2012;255:696–702.
13. Whitlock EL, Feiner JR, Chen LL. Perioperative mortality, 2010 to 2014: a retrospective cohort study using the National Anesthesia Clinical Outcomes Registry. Anesthesiology2015;123:1312–1321.
14. Chalya PL, Gilyoma JM, Mabula JB, et al. Incidence, causes and pattern of cancellation of elective surgical operations in a university teaching hospital in the Lake Zone, Tanzania. Afr Health Sci. 2011;11:438–443.
15. Bhuiyan MM, Mavhungu R, Machowski A. Provision of an emergency theatre in tertiary hospitals is cost-effective: audit and cost of cancelled planned elective general surgical operations at Pietersburg Hospital, Limpopo Province, South Africa. S Afr Med J. 2017;107:239–242.
16. Prin M, Eaton J, Mtalimanja O, Charles A. High elective surgery cancellation rate in Malawi primarily due to infrastructural limitations. World J Surg2018;42:1597–1602.
17. Tran M. Britain suspends aid to Malawi. The Guardian. 2011.London, UK: Guardian Media Group.
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18. Henry JA, Frenkel E, Borgstein E, Mkandawire N, Goddia C. Surgical and anaesthetic capacity of hospitals in Malawi: key insights. Health Policy Plan. 2015;30:985–994.