Mortality and morbidity patterns in Yaoundé, Cameroon: an ICD-11 classification-based analysis

Abstract

Background

In Cameroon, like in many other resource-limited countries, data generated by health settings including morbidity and mortality parameters are not always uniform. In the absence of a national guideline necessary for the standardization and harmonization of data, precision of data required for effective decision-making is therefore not guaranteed. The objective of the present study was to assess the reporting style of morbidity and mortality data in healthcare settings.

Methods

An institutional-based cross-sectional study was carried out from May to June 2022 at the Yaoundé Central Hospital. A questionnaire was used to assess the need to set up a standard tool to improve the reporting system. Medical records were used to collect mortality and morbidity data which were then compared to the International Statistical Classification of Diseases and Related Health Problems-11 (ICD-11) codification. Data were analyzed using IBM-SPSS version 26.

Results

Out of 200 patients’ morbidity causes recorded, nearly three-quarter (74.0%) were heterogeneous, and two over five (41.0%) of mortality causes reported were also heterogeneous. Most of respondents stated the need to set up a standard tool for collecting mortality and morbidity data (83.6%). Less than one-fifth (18.2%) of health care providers were able to understand data flow, correctly archived data (36.6%) and used electronic tools for data quality control (40.0%).

Conclusion

There were high levels of heterogeneities of morbidity and mortality causes among patients admitted to the Yaoundé Central Hospital in 2021. It is therefore urgent that Cameroon national health authorities implement the ICD-11 to allow the systematic recording, analysis, interpretation and comparison of mortality and morbidity data collected in Yaoundé Central Hospital at different times; and ensure interoperability and reusability of recorded data for medical decision support.

Background

The global health profile and the forecast of its evolution are based on reliable morbidity and mortality data. Cause of death statistics are an important tool for quality control of the health care system. Morbi-mortality data are essential, as they make it possible to know the epidemiological profile required for the development of health policies in order to reduce the burden of disease in the population [1]. The mortality rate in Cameroon was estimated at 8 per 1000 in 2020 [2]. The health profile remains dominated by communicable diseases such as malaria, complications related to HIV/AIDS which account for approximately 23.3% of the disease burden and 25% of deaths [3, 4].

The management of the COVID-19 pandemic has put the need for quality mortality and morbidity data back on the agenda [5]. The lack of quality data remains a challenge in most African countries where the health surveillance process remains sub-optimal due to insufficient skilled manpower and technical and infrastructural tools [6].

Inadequacy of data systems therefore results in the implementation of inappropriate policies and guidelines [7]. A good measurement of health indicators allows a better understanding of diseases in ways that enable prevention, treatment, and the allocation of resources. To be useful, measurement must be reliable, allow valid comparisons to be made between places and over time, and enable coherent summarization of large volumes of data. A classification of diseases and related things is essential for such measurement. For more than a century, the International Statistical Classification of Diseases and Related Health Problems (ICD) has been the main basis for comparable statistics on causes of death and non-fatal disease [8, 9]. It serves a variety of functions in much of the world and has been translated into 43 languages [10]. Uses of the ICD are diverse and widespread, extending directly to much of the world and indirectly to all populated places [8, 11].

In Cameroon, like in many other resource-limited countries, data generated by health settings including morbidity and mortality parameters are not always uniform and in a context of absence of national guidelines necessary for the standardization and harmonization of data, data precision required for effective decision-making is therefore not guaranteed [12]. The objective of this study was to assess the reporting style of morbidity and mortality data in healthcare settings.

Methods

Study design & period

We conducted an institutional-based cross-sectional study in Yaoundé (the capital of Cameroon) Central Hospital from May to June 2022 with the aim to assess the heterogeneity of mortality and morbidity causes of patients admitted in Yaoundé Central Hospital (YCH) using the ICD tool.

Setting

Yaoundé Central Hospital is a 2nd category public health establishment with a hospital-university character. It concentrates skills, techniques and specialized services and serves as a reference health facility for health establishments of equivalent or lower category. The theoretical capacity for hospitalization is 402 beds and it cumulated 166 139 consultations for illness in 2021 [13]. It is made up of twenty (20) departments divided into five (5) units, namely: (a) Medicine and Specialties Unit (Gastroenterology, Cardiology, Diabetology and Endocrinology, Geriatrics, Hematology-Oncology, Infectiology, Neurology-Physical Medicine, Rheumatology-High Standing, Physio-Physiotherapy, Day Hospital, Outpatient Consultation); (b) The surgery unit (Urology - Andrology, Orthopedics-Traumatology, General and Digestive surgery, Visceral Surgery, Cancer Surgery, Neurosurgery, Ear-Nose-Throat (ENT), Ophthalmology, Pediatric Surgery, Stomatology); (c) The Reception, Anesthesia Resuscitation and Emergency unit (Yaoundé Emergency Reception Coordination Center, Anesthesia Resuscitation Department A, Operating Theatre, and Anesthesia Resuscitation Department B); (d) Gynecology and Obstetrics Unit (Main Maternity Unit) and the Technical Unit (Pharmacy, Radiology Imaging, Pathologic Anatomy, Laboratory, and Blood Bank) [14]. Because access to some departments wasn’t possible, our study took place in Medical emergency, Adult surgery, Pediatric surgery, Urology, Neurology & Neurosurgery, Gastroenterology, Hematology, Obstetrics & gynecology, Intensive care, Infectiology & Traumatology, and Surgical Emergency.

Participant

The study population consisted of patients admitted in selected services during the year 2021 and clinical staff (doctors and nurses) working in those units during the study period.

Inclusion criteria

Patients admitted in selected services from January 1st to December 31st, 2021, with required information on the cause of morbidity or mortality were included in this study. Staffs present in the study departments consenting to participate in the study were included.

Sampling method

An exhaustive sampling method was used to select medical records in selected services during the year 2021 meanwhile clinical staffs were enrolled using a non-probabilistic sampling technique.

Data collection

Medical records were used to collect mortality and morbidity data including the diagnosis or the cause of death (See Questionnaire in the Appendix as supplementary material). Another research tool allowed us to assess the need to set up a standard tool for reporting mortality and morbidity data.

Data processing and analysis

The spelling of morbidity and mortality were compared with the International Statistical Classification of Diseases and Related Health Problems-11 (ICD-11) developed by the World Health Organization [15, 16]. In this study context, the term heterogeneous represented all pathologies or death causes whose spelling did not respect the ICD-11 meanwhile homogeneous represented all pathologies or cause of death spelling that meet ICD-11 standards. Unknown is the set of pathologies that do not appear. All filled questionnaires were entered using CS-PRO software version 7.3; and data were exported and analyzed with IBM-SPSS software version 26. As the study was purely descriptive, variables involved were categorical and were presented as number (percentage).

Ethical approval Statement and consent to participate

The protocol of this study was reviewed and approved by the Institutional Ethics Committee for Research on Human Health of the University of Douala (CEI-UDO) and the ethical clearance N°377CEI-UDo/07/2022/M was issued. Informed consent of all participants was obtained prior to their inclusion in the study, after clearly informing the participants of the benefits, risk, and the voluntary nature of their participation, and the lack of negative consequences should they not participate; and for publication of final results.

Results

A total of 55 health staffs were enrolled in this study among which female (80.0%, 44) and those aged 21–30 (47.3%, 26) were the most represented. They were mainly nursing staffs (56.4%, 31) and participants with less than 10 years of experience (65.4%, 36) (Table 1).

Table 1 Socio-professional characteristics of study participants in Yaoundé Central Hospital, 2021 (n = 55)

Most of respondents (83.6%, 46) stated the need to set up a standard tool for collecting mortality and morbidity data (Table 2). Less than one-fifth (18.2%, 10) of health care providers were able to understand data flow, correctly archived data (36.6%, 20) and used electronic tools for data quality control (40%, 22) (Table 2).

Table 2 Assessment of the need to implement tool necessary to improved electronic reporting system of morbidity and mortality causes in Yaoundé Central Hospital, 2021 (n = 55)

A total number of 200 patients’ diagnoses were recorded. Most of diagnoses were heterogeneous (74.0%, 148) and the highest proportion was observed in the cardiology unit (84.0%, 168) (Table 3).

Table 3 Heterogeneity assessment of morbidity causes at Yaoundé Central Hospital 2021 using the International classification of Disease-11, (n = 200)

Out of 54 reported causes of mortality, four over ten (41.0%, 22) were heterogeneous and all discordant spelling was observed in Cardiology Department (45.8%, 25) (Table 4).

Table 4 Heterogeneity Assessment of mortality causes at Yaoundé Central Hospital in 2021 using the International classification of Disease-11, (n = 54)

Discussions

Study findings allowed us to assess the level of heterogeneity of reported diagnoses and causes of death among patients admitted to the Yaoundé Central Hospital in 2021. The findings of this study might not only apply to the case of Cameroon (or even the Yaoundé Central Hospital), but to several similar settings worldwide; especially in resource-limited settings.

Morbidity heterogeneity evaluation

Most of reported diagnoses were heterogeneous (74.0%). This high rate of heterogeneity of diagnoses compared to the standard ICD could be due to lack of training of clinicians on the notification of diseases. Training and recycling sessions are well known methods to improve data quality reporting in healthcare institutions. In this regard, a study findings shown that a program of repeated assessments, feedback, and training appears to upgrade data quality in a range of practices [17].

Mortality heterogeneity assessment

Four over ten mortality causes were heterogeneous (41.0%). Our result corroborates observations in other settings in Germany and Australia [18, 19]. It is therefore necessary to set up standard data collection tools for morbidity and mortality data and conduct capacities of healthcare workers in the management of morbidity and mortality data. Moreover, Harmonizing ICD coding standards/guidelines should be a common goal to enhance international comparisons of health data. The current international status of ICD data collection highlights the need for the promotion of ICD-11 [20].

Need to implement improved electronic reporting tool

Most of respondents (83.6%) expressed the need to set up a standard tool for collecting mortality and morbidity data. Despite the poor capacity in data archiving and the use of electronic tools for data quality. These findings reflect an unprepared framework for the implementation of the ICD-11 which is the latest edition of disease classification developed by the World Health Organization. The successful implementation of the ICD-11 for morbidity ideally proceeds via the following steps: determining the center of excellence, engaging stakeholders, selecting the setting, building a common understanding of the discharge process in the selected setting, evaluating and preparing information technology infrastructure, ICD-11 training, pre-pilot testing on a small scale, and implementing the pilot while providing on-site support and collecting data for analysis [21]. The first phase involves convincing leaders to support the change using stakeholder-tailored messages. The second phase includes physicians’ experimentation of the ICD-11 in real-life while voicing their opinions using a simple structured feedback mechanism. Training for this phase must be customized to physicians’ needs, interests, language and disseminated using a familiar medium. The final phase, institutionalization, is ultimately reached when the change is accepted and maintained, with the success of the adoption phase being communicated to other hospital departments to scale up implementation, making ICD-11 the routine way for documenting and reporting diagnoses and causes of death [22].

Strengths and limitations

Strengths of this study include its comprehensive assessment of the level of heterogeneity of reported diagnoses and causes of death among patients admitted to the Yaoundé Central Hospital in 2021. However, because of difficulties in accessing some departments, our study was restricted to Medical emergency, Adult surgery, Pediatric surgery, Urology, Neurology & Neurosurgery, Gastroenterology, Hematology, Obstetrics & gynecology, Intensive care, Infectiology & Traumatology, Surgical emergency; this might have caused selection bias; and therefore, the findings may not be generalizable to other departments. However, the selected departments have the highest attendance. Despite these limitations, the study provides important insights by reporting a high level of inadequacy between the hospital reporting style. Future research could consist of covering all the departments at the Yaoundé Central Hospital; conduct this study to other health facilities in Cameroon; and examine barriers to the implementation of ICD-11 in Cameroon.

Conclusions

There were high levels of heterogeneities of morbidity and mortality causes among patients admitted to the Yaoundé Central Hospital in 2021. This study suggests that Cameroon national health authority should set up a more reliable system (ICD) for collecting mortality and morbidity data by involving all the stakeholders of the national health information system. This will allow the systematic recording, analysis, interpretation and comparison of mortality and morbidity data collected in Yaoundé Central Hospital at different times; and ensure interoperability and reusability of recorded data for decision support and resource allocation.