Factors associated with mortality among inpatients at Koidu Government Hospital, Sierra Leone: A Secondary data analysis

Ivan Augustine Barrie^1,2, Solomon Aiah Sogbeh^2,3, Babatunde Duduyemi⁴, Umaru Sesay^2,3, Amara Alhaji Sheriff^2,3, Anna Jammeh^2,3, Adel Hussein Elduma^2,3,&, Gebrekrstos Negash Gebru^2,3

 

¹Minisry of Health, Freetown Sierra Leone, ²Sierra Leone Field Epidemiology Training Program, Freetown, Sierra Leone, ³Africa Field Epidemiology Network, Freetown, Sierra Leone, ⁴University of Sierra Leone Teaching Hospital Complex, Freetown, Sierra Leone

 

 

^&Corresponding author
Adel Hussein Elduma, Sierra Leone Field Epidemiology Training Program, National Public Health Agency, Wilkinson Road Freetown, Sierra Leone.

 

 

 

 

Sierra Leone Sample Registration System (SLRS) has been conducting verbal autopsies of community deaths since 2018 in 637 enumeration areas in the country. As a result of the advanced form of scientific data being collected, it is not part of the Civil Registration and Vital Statistics System by the National Civil Registration Authority [1]. The National Civil Registration usually conducts a passive registration of births and deaths in Sierra Leone [2].

 

Globally, there were an estimated 58.7 million deaths in 2020 from various causes across different regions. Ischemic heart disease and stroke remained the leading global causes of death, accounting for a combined 15.6 million deaths in 2020 and have been the leading cause of death worldwide for the last two decades [3]. The Global Burden of Disease Study 2021 reported ischemic heart disease, stroke, and neonatal disorders among the top causes of premature mortality [4].

 

A stark contrast persists in mortality patterns between developing and developed nations. Developing countries continue to shoulder a higher proportion of deaths due to infectious diseases, maternal causes, and conditions arising during pregnancy and childbirth. Conversely, non-communicable diseases such as cardiovascular diseases, cancers, and chronic respiratory diseases account for the majority of deaths in the developed world [5]. Crucially, many developing countries still lack comprehensive population-based data on morbidity and mortality patterns, making hospital-based records the best available source to estimate disease burden in these settings [6, 7].

 

The Minimal Invasive Tissue Sampling (MITS) procedure used by Child Health Mortality Prevention Surveillance (CHAMPS) was developed to reduce the uncertainty regarding the causes of death of children in Sierra Leone[8]. Most deaths in Sierra Leone that occur in the community are determined by verbal autopsy. Most morbidity and mortality reviews in Sierra Leone are for maternal and infant deaths, and there is minimal documented information about hospital-based morbidity and mortality patterns in Sierra Leone [1]. Despite Partners in Health's (PIH) efforts to train monitoring, evaluation, and quality officers in data collection and analysis for providing critical health information to authorities. The absence of an annual documented admission and mortality report at Koidu Government Hospital represents a critical gap in systematic healthcare documentation and performance monitoring. These statistics are critical indicators of hospital quality of care and will serve as inputs for national and subnational health policy and planning in Sierra Leone.

 

This study analyzed the morbidity and mortality data among inpatients and determined factors associated with mortality at the Koidu government hospital from 2020 to 2022. This study will provide information on the causes of morbidity and factors associated with mortality which can guide authorities to implement necessary measures that can reduce both morbidity and mortality among inpatients at the Koidu government hospital.

 

 

Study design and setting

 

A retrospective cross-sectional study using secondary data was conducted in Koidu Government Hospital 2020-2022 and adopted a quantitative approach. Koidu Government Hospital serves as a secondary referral facility for Kono District and neighboring areas in Eastern Sierra Leone. Kono District is a vibrant mining and industrial area, with fishing and agriculture as additional economic activities (Figure 1). The district has an estimated population of 620,703 (Ministry of Health projected population, 2023).

 

In 2023, the hospital had an annual caseload of over 2,500 deliveries in the maternity unit. The hospital provides care for patients with diseases of epidemic potential, with a focus on early detection and response. With a daily patient turnover of around 150, the facility offers general and specialist medical care on both an outpatient and inpatient basis, along with comprehensive diagnostic services. The hospital, which serves as a major healthcare provider, has a total capacity of 237 beds and 12 inpatient wards; and a workforce of 399 staff comprising 15 doctors, 227 nurses and community health officers, and 157 other allied health professionals. The hospital receives support from Partners in Health to provide patient care and meet the demands of the community.

 

Study participants

 

All patients who were admitted or died (whilst on admission) between 2020 and 2022, and their information captured in the hospital database were included in the study including cases admitted for labour and delivery. Patients who died before arrival at the hospital were excluded from this study.

 

Data collection

 

Data on demographics, disease conditions, events, and length of hospital stay was extracted from the Strategic Health Information System Unit database of the Koidu Government Hospital. The data are usually updated daily via outgone and returning patient case notes and are compiled into quarterly reports submitted to the Strategic Health Information System unit.

 

Operational definition

 

Verbal Autopsy (VA); is a method of determining an individual´s causes of death and cause-specific mortality fractions in a population without a complete vital registration system.

 

Morbidity: is the state of being unhealthy for a particular disease.

 

Mortality: refers to the number of deaths that have occurred due to a specific illness or condition

 

Inpatient: a patient admitted to a hospital for treatment

 

Minimal Invasive Tissue Sampling (MITS): is a procedure that allows the extraction of tissue specimens and body fluids from a predefined set of organs without the need to open the body.

 

Data management and analysis

 

In this study, the data generated were entered and analyzed using MS Excel 2013 and Epi Info Version 7.2.0. Descriptive statistics, including frequencies, percentages, mean, and standard deviation, were calculated to summarize the data Annual hospital-based mortality rate and age-specific mortality rates were calculated using the total inpatients during the study period. This allowed the researchers to determine trends and variations in mortality over time and across different age groups.

 

The causes of death were classified based on the International Classification of Disease version 11 (ICD-11) and the Startup Mortality List for Low-Resource Countries[9]. This standardized coding system ensures consistency and comparability of data across different settings. To assess the relative importance of different causes, the researchers calculated the proportional morbidity, mortality, and case fatality rates. These measures provide insights into the frequency of specific causes relative to the overall morbidity and mortality patterns observed in the study population.

 

Bivariate analysis was conducted to explore the association between the outcome variable (death) and independent variables. A significant level of p-value 0.2 was used to determine variables included in the multiple logistic regression model. Variables retained at the bivariate analysis , ignoring interaction, were included in the multiple logistic regression model Adjusted Odds Ratios (aORs) and 95% Confidence Intervals (CI) was computed to determine the association between the independent variables and the outcome variable (death). Variables with a p-value less than 0.05 were considered statistically significant.

 

Ethical considerations

 

Ethical approval from the Sierra Leone Ethics and Scientific Review Committee was not sought as the study was part of the routine programmatic activity using secondary data analysis. However, permission to access data was granted by the Medical Superintendent Kono District and the data was made available by the Research Director at Partners in Health. To maintain patients´ confidentiality, any personally identifiable information will not be disclosed to the public.

 

 

Demographic characteristics of in-patients at the Koidu government hospitals, 2020 - 2022

 

From 2020 to 2022, Koidu Government Hospital recorded a total of 48,579 inpatient admissions and 4,589 associated deaths. The mean age of admitted patients was 18.4 ±17.65 years while the mean age of patients who died was 43 ± 19.40 years. Out of the total admissions, 51.5% (25,027) were female patients. Among the inpatient cases, 9.4% (45889) died, and 56% (2,550) were male admitted patients. Regarding admission categories, 6.8% (3,285) of patients were admitted for accidental and emergency causes, while 93.2% (45,276) were admitted through other wards. Of those admitted due to accidents or emergencies, 56% (1,843) were male patients (Table 1).

 

The annual hospital-based mortality rate per 10,000 , 33 in 2020, 39 in 2021, and 32 in 2022. Age-specific hospital based mortality rates (per 1,000 population) were highest among inpatients aged 60 years and above, with 21 in 2022, 25 in 2021, and 19 in 2020. The second-highest age-specific mortality rate was observed in the 45-59 years age group, with 6 in 2022, 7.9 in 2021, and 5 in 2020. For children under 5 years, the age-specific mortality rate (per 1,000 live births) was 6 in 2022, 7 in 2021, and 6 in 2020. The age group with the lowest age-specific mortality rate was 5-14 years, with 1 per 1,000 population in both 2022 and 2021, and 1.0 per 1,000 population in 2020 (Table 1).

 

Description of the morbidity and mortality patterns of inpatients at Koidu Government Hospital, 2020 - 2022

 

From our study, the pediatric ward recorded the highest number of patients 26.5% (12,876/48579), followed by the female medical ward 15.5% (7515/48579) and the male medical ward 15.0% (7266/48579). However, the Intensive care unit recorded the highest proportion of inpatient deaths at 25.0% (89/350), followed by male surgical ward 17.0% (437/2567) and pediatric rhesus 16% (630/3736). Moreover, the intensive care unit had the least proportion of inpatients 0.7% (350/48579) and the labor ward recorded the least proportion of mortalities 3.8% (121/3207). The paediatric ward had the highest number of deaths and contributed most to the overall mortality 24.3% (1113/4588) followed by the pediatric rhesus ward 13.7% (630/4588), the least contributor was the postnatal ward 0.7% (32/4588) (Table 2).

 

Main causes of diseases diagnosed and death among the inpatients at Koidu Government Hospital 2020 - 2022

 

A comprehensive analysis revealed 43 different causes of morbidity and mortality among patients admitted to the hospital. However, a notable finding was that 10 specific diseases accounted for 77.3% of total admissions: The top ten causes of hospital admission among the 48,579 cases were: Malaria - 34.4% (16,687 cases), Respiratory Diseases - 15.2% (7,407 cases), Anemia - 7.3% (3,529 cases), Cardio-circulatory Diseases - 4.6% (2,258 cases), Septicemia - 4.6% (2,239 cases), Diabetes - 4.2% (2,062 cases),HIV/AIDS - 3.7% (1,790 cases), Tuberculosis - 3.5% (1,697 cases), Injuries - 3.4% (1,667 cases) and Diarrhea diseases 2.81% (1,365) (Figure 2).

 

These same 10 diseases also accounted for 71.8% (3126/4589) of all deaths among hospitalized patients. The top ten diseases or conditions related to In-hospital mortality are: Malaria - 12.9% (591/4,589), respiratory diseases - 12.4% (570/4,589), Septicemia - 10.7% (489/4,589), Diabetes - 9.2% (422/4,589), Anemia - 7.8% (356/4,589), Cardio-circulatory Diseases - 7.3% (336/4,589),Neonatal Disorders - 6.7% (306/4,589), HIV/AIDS - 5.3% (244 deaths/4,589); Injuries - 2.6% (121/4,589), and Tuberculosis - 2.5% (117/4,589). While malaria, respiratory diseases, septicemia, and non-communicable diseases like diabetes were the leading cause of death, the following conditions exhibited exceptionally high case fatality rates: poisoning/intoxication 66% (21/32cases), congenital anomalies 62% (21/34 cases), and brain diseases 49% (17/35 cases. In contrast, diarrheal diseases had the lowest case fatality rate at merely 1% (21/1365 cases) (Table 3).

 

Age-specific mortality rate per 1,000 population of inpatients at the Koidu government hospital 2020 -2022

 

The age-specific mortality rate was high among inpatients 60+ years was 21/1000 people in 2022, 25/1000 people in 2021, and 19/1000 people in 2020, respectively. The second highest age-specific mortality rate was the age group 45-59 years, which was 6 /1000 people in 2022, 8 /1000 people in 2021, and 5 /1000 people in 2020. The age-specific mortality rate for the age group 0-4 years was 6 /1000 live births in 2022, 7 /1000 live births in 2021, and 6 /1000 livebirth in 2020. The age group with the lowest age-specific mortality rate was the age group 5-14 years, with 1.0/1,000 population in each year (Figure 3).

 

Factors associated with inpatient mortality at Koidu Government Hospital, 2020 -2022

 

At bivariate level the odds of death among male inpatients was 1.3 times compared to female, (cOR = 1.3, 95% CI: 1.229, 1.389, P<0.001). The odds of death among inpatients under the age of 15 years was 5.9 times compared to those who aged 15 years or older (cOR = 5.9, 95% CI: 5.41, 6.47, P<0.001). The odds of death among inpatients with primary education was 19 times compared with those have tertiary education (cOR = 18.7, 95% CI: 16.68, 21.00 P<0.001). Inpatients who had attained a secondary education had less odds of death compared to inpatients with tertiary education (cOR = 0.9, 95% CI: 0.79, 1.08, P<0.001). The odds of death among inpatients with an extended hospital stay exceeding 5 days was 1.5 compared to those with stay less than 5 days (cOR = 1.5, 95% CI: 1.34, 1.77, P<0.001).

 

After adjusting for confounding factors in the multiple logistic regression model, the odds of death among male inpatients was 0.3 as compared to female inpatients (OR: 0.3, 95% CI: 0.253, 0.301). Additionally, the odds of death among inpatients with primary education 53 times as compared to those with tertiary education, (aOR= 53.1, 95% CI: 42.62, 66.23, p-value<0.001). Moreover, the odds of death among inpatients with secondary education 3 times compared to those with tertiary education (aOR= 3.0, 95% CI: 2.47, 4.02; p-value<0.001). Also, the odds of death among inpatients that have extended hospital stay of more than five days was 12 times as compared to those who were hospitalized for five days only (aOR 12.4, 95% CI: 9.58, 16.06,p-value<0.001). Furthermore, the odds of death among inpatients less than 15 years was 8 times compared to inpatients aged 15+ years (aOR 8.0, 95% C I: 7.21, 9.07;p-value<0.001) at Koidu Government Hospital (Table 4).

 

 

This study found that malaria was the main cause of inpatients admission at Koidu Government Hospital (KGH). These findings align with the broader health landscape in Sierra Leone, where malaria remains a significant health challenge. The high prevalence of malaria-related admissions and deaths at KGH reflects the national trend, where malaria accounts for 38% of hospital admissions and 17.6% of inpatient deaths [10]. Our results are consistent with other studies in Sierra Leone, such as the one conducted at Bo Government Hospital, which reported higher mortality rates among adults with severe malaria [11], it's important to consider potential confounding factors. The high prevalence of malaria diagnoses may be partially attributed to misdiagnosis of other acute febrile illnesses as malaria, particularly in settings with limited diagnostic capabilities. Furthermore, the possibility of co-infections, where malaria occurs alongside other infectious diseases, may complicate both diagnosis and treatment outcomes. These factors could potentially inflate malaria-attributed morbidity and mortality rates.

 

A comparative study revealed that Sierra Leone had a significantly higher malaria mortality rate (42.9%) among children aged 1-50 months compared to Kenya (31.4%), Mozambique (18.2%), Mali (6.7%), and South Africa (0.3%) [12]. This underscores the urgent need for enhanced malaria control and treatment strategies in Sierra Leone, especially given that the WHO African region accounts for 94% of global malaria cases and 95% of malaria deaths [13].

 

Our study revealed an association between inpatient death and certain demographic factors (being female, aged 15 years and above, having primary or secondary education level) and clinical factors (length of hospital). These findings provide valuable insights for targeting interventions and improving inpatient care at KGH. The overall mortality rate at KGH was higher compared to a similar study in Nigeria [14], probably due to differences in the sociodemographic structure, environmental factors and geographical factors.

 

Contrary to our findings, a study in Southern Nigeria reported a higher proportion of deaths among males compared to females admitted to the hospital. The higher admission and mortality rates among females in our study could be attributed to various factors, including maternal health issues, gender-based disparity in healthcare utilization and cultural barriers to seeking medical treatment. Sierra Leone continues to face challenges in maternal health, particularly in rural areas [15].

 

Our study revealed higher admission rates and mortality among children under five and young patients less than 15 years. This could be due to lower immunity in young children, making them more susceptible to infectious diseases. Other contributing factors may include delays in seeking healthcare, possibly due to referral system issues, cultural beliefs, socioeconomic factors, and population movement related to mining activities in Kono district.

 

The high percentage of admissions in pediatric wards likely reflects the demographic profile of our district. While Sierra Leone has a young population, it's important to consider that factors beyond population structure, such as disease prevalence and healthcare-seeking behaviors, contribute to admission patterns.

 

Extended hospital stays were associated with higher mortality in our study. This was consistent with a study that analyzed data from 26 hospitals and found that hospitals with high mortality rates had a higher proportion of long hospital stays [16]. This could be due to increased exposure to hospital-acquired infections or development of additional complications.

 

Our findings also indicated higher mortality among patients with lower education levels compared to those with higher education. This disparity might be attributed to better health literacy and treatment compliance among more educated patients. A study in the United States reported lower annual mortality rates among highly educated adults compared to those with less education [17].

 

These findings highlight the need for targeted interventions to address the specific health needs of different demographic groups and to improve overall healthcare delivery at Koidu Government Hospital.

 

Limitations

 

This study relied on secondary data analysis, which can be impacted by missing variables, potentially affecting the accuracy of the results. To investigate the associations between dependent and independent variables, we employed multiple logistic regression models. However, it is important to note that the cross-sectional nature of this study does not allow for the establishment of causal relationships between the dependent and independent variables. Furthermore, the determination of the exact causes of death was based on clinical assessments and ancillary investigations rather than postmortem examinations (autopsies). This approach introduces the possibility of misclassification of the underlying cause of death, as autopsies provide more definitive insights into the pathological processes leading to mortality.

 

Also, the lack of a comprehensive, nationwide system for tracking and reporting deaths limits our ability to capture a complete picture of mortality patterns and trends across the country. This gap in data collection may result in underreporting or misrepresentation of certain causes of death.

 

Without robust mortuary surveillance practices and adequate laboratory diagnostic capabilities, it is often difficult to ascertain the precise cause of illness and death. This limitation may lead to: a) Misclassification of causes of death b) Under-diagnosis of certain conditions c) Inability to identify emerging health threats in a timely manner

 

These limitations collectively hinder our capacity to accurately determine the true burden of various diseases and health conditions, potentially impacting the effectiveness of public health interventions and policy decisions.

 

It is crucial to acknowledge the limitations of secondary data analysis and the cross-sectional study design. While the findings provide valuable insights into patterns and associations, caution should be exercised in drawing firm conclusions about causality. Future research employing prospective study designs and incorporating postmortem examinations could enhance the accuracy and robustness of the findings related to the causes of morbidity and mortality in this setting. This statement accurately highlights the limitation of cross-sectional studies in establishing causal relationships, as they capture data at a single point in time and cannot account for the temporal sequence of events necessary to infer causality.

 

 

This study found a high mortality among inpatients in Kono Government Hospital. We found high proportion of mortality in the intensive care unit, and the leading cause of morbidity and mortality was malaria. Risk factors of mortality included inpatients who is female, less than 15 years, stay at the hospital for more than five days, and with lower education level. We recommend that the Ministry of Health implement the following specific interventions to reduce the burden of malaria:

 

1. Enhance vector control measures:

 

- Increase distribution and use of long-lasting insecticide-treated bed nets (LLINs)

 

- Expand indoor residual spraying (IRS) programs in high-risk areas

 

- Implement larval source management in urban and peri-urban settings

 

2. Improve access to rapid diagnostic tests (RDTs) and artemisinin-based combination therapies (ACTs):

 

- Ensure consistent supply of RDTs and ACTs at all health facilities

 

- Train community health workers in malaria diagnosis and treatment

 

3. Strengthen malaria surveillance systems:

 

- Implement real-time data reporting using mobile health technologies

 

- Enhance capacity for data analysis and response at district and national levels

 

4. Scale up seasonal malaria chemoprevention (SMC) for children under five in high-transmission areas

 

5. Increase public awareness through targeted health education campaigns:

 

- Focus on malaria prevention, early symptom recognition, and prompt treatment-seeking behavior For patients under 15 years and those with extended hospital stays, we recommend:

 

a) Develop specialized pediatric care protocols for malaria and other common childhood illnesses

 

b) Implement rigorous infection control measures to prevent hospital-acquired infections

 

c) Establish a system for regular reassessment of long-stay patients to identify and address complications early

 

d) Provide enhanced nutritional support for pediatric and long-stay patients

 

e) Create dedicated follow-up care programs for patients after discharge to reduce readmission rates These targeted interventions aim to address the specific challenges identified in our study and improve overall health outcomes at Koidu Government Hospital.

 

 

Authors declare no competing interest.

 

 

Conceptualization and design: Ivan Augustine Barrie, Solomon Aiah Sogbeh; Data Collection: Ivan Augustine Barrie; Analysis, and Interpretation: Ivan Augustine Barrie, Solomon Aiah Sogbeh, Babatunde Duduyemi, Adel Hussein Elduma; Drafting and Review of Manuscript: Ivan Augustine Barrie, Solomon Aiah Sogbeh, Adel Hussein Elduma, Amara Alhaji Sheriff, Umaru Sesay, Anna Jammeh, Gebrekrstos Negash Gebru. The final approval was made by all authors

 

 

Table 1: Sociodemographic characteristics of inpatients at the Koidu government hospitals, 2020 - 2022

Table 2: Description of the morbidity and mortality patterns of inpatients at Koidu Government Hospital, 2020 - 2022

Table 3: The main causes of morbidity and mortality of inpatients at Koidu Government Hospital 2020 - 2022

Table 4: Bivariate and multivariate analysis of factors associated with inpatient mortality at Koidu Government Hospital, 2020 - 2022

Figure 1: Map of Kono District, Sierra Leone

Figure 2: Percentage of the top ten diseases and conditions of Hospital Admission among inpatients at the Koidu government hospital 2020 -2022

Figure 3: Age-specific mortality rate per 1,000 population of inpatients at the Koidu government hospital 2020 - 2022

 

 

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