Evaluation of the Adequacy between the Workload and the Number of State Midwives and Maieuticians Practicing in the Gynecology-Obstetrics Departments of the University Hospitals of Burkina Faso ()
1. Introduction
The 2030 Global Strategy for Health Human Resources [1] aims to accelerate progress towards Universal Health Coverage. This requires universal access to health workers. It is, therefore, essential to have an evidence-based planning method to estimate the necessary staffing of health care facilities, in order to help to provide and manage the required workforce where it is needed. The traditional methods used to determine staffing standards are based on the ratio of practitioners to the population. These ratios have limitations in determining the staffing requirements for a health care facility such as University Hospital.
To do this, we used the workload assessment method proposed by the WHO, which is the WISN (Worckload Indicators Staffing Need) tool.
2. Methodology
This is a descriptive and analytical retrospective study, using a quantitative approach in which a set of operations recommended by the WISN (Worckload Indicators Staffing Need) method or indicators of staffing needs in relation to workload, was used.
The study period extended from1May, 2018 to 30 April 2019. The data collection took place from 25 to July, 2020. The study, all midwives and maïeuticians practicing in the Gynecology-Obstetrics departments of a University Hospital Center in Burkina Faso during the study period and providing care. The study did not include midwives and maïeuticians working in the services of university hospitals that did not offer free care during the study period. A literature review grid was used to collect data. It included the following items: a first item to quantify service activities and determine the standard of these activities; a second item to determine the quantity of support activities and determine the standard of these activities; a third item to quantify additional activities and determine the standard of these activities; a fourth item to evaluate the number of spare days in relation to sick leave and other leaves (personal leaves, training leaves, etc.). The sources of data were consultation registers, personnel administrative files, monthly activity reports, and task allocation sheets. Our study was carried out in strict compliance with the confidentiality of information. We received the agreement of the Ministry of Health for the use of the statistical yearbooks of the various university hospitals.
3. Results/Discussion
Dystocic delivery was the activity that took the most time. Inpatient activities were the most performed in terms of volume (Table 1).
The following table summarizes not only all the activities of each hospital, but also the volume and time spent on each.
Tables 2-5 show us the procedure that leads to the estimation of the need for midwives and maïeuticians in each hospital.
In University Hospital A, the WISN estimate of required staff was 62 midwives
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Table 1. Volume and time spent on service activities in four university hospital.
a = Volume of activity; b = Volume of activity in %; c = Average time to complete an activity (in minutes); d = Time spent on one activity; e = Time spent in %.
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Table 2. Estimated need for midwives and maïeuticians in university hospital A.
and maïeuticians (Table 2)against available staff of 57, meaning a shortage of 05 health workers.
During our study period, 75 midwives and maïeuticianswere on duty in University Hospital B. The estimated need for midwives and maïeuticiansby the WISN method was 75 midwives and maïeuticians (Table 3). The WISN ratio was 1.
University Hospital C had 87 midwives and maïeuticians staff. According to the WISN method, the required staff was estimated at 41 midwives and maïeuticians (Table 4).
There were 46 midwives and maïeuticians available in University Hospital D. According to the WISN method, the required staff was 24midwives and maïeuticians (Table 5).
Table 6 shows the number of staff and the WISN ratio per hospital. It allows us to appreciate the workload pressure in each hospital.
We note that it is only in hospital A that we find a lower workload pressure.
University A WISN ratio was 0.92, meaning a low work pressure of 8% (Table 6). Govule et al. [2] in Cameroon and Musau et al. [3] in Kenya, also found a shortage of midwives in their hospitals. In 2011, Ly et al. [4] reported a WISN ratio of 0.68 at Yalgado University Hospital and 0.79 at the Bogodogo medical center with surgical branch. From 2011 to 2019, there was a decrease in the work pressure of midwives and maïeuticians. This could be explained by the opening of two University Hospital in the city of Ouagadougou: the University Hospital of Bogodogo and the University Hospital of Tengandgo.
This workload pressure is relative since non-official staff (for example students,
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Table 3. Estimated need for midwives and maïeuticians in university hospital B.
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Table 4. Estimated need for midwives and maïeuticians in university hospital C.
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Table 5. Estimated need for midwives and maïeuticians inuniversity hospital D.
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Table 6. Staffing and workload pressure analysis.
doctors in specialization) perform all the service activities of the midwives and maïeuticians.
In univesity hospital B, WISN ratio was 1. N’Guessan in Dakar [5] found a similar result for midwives in the principal hospital (ratio 1).
In 2011, Ly et al. [4] found a ratio of 0.79 for midwives and in amedical center with surgical branch. This shortage may be possible by a massive recruitment of health personnel during the transformation of the medical center with surgical branch into a university hospital in 2017.
In some African countries, there is a very uneven distribution between urban areas, which have a higher ratio of health professionals, and rural areas [6] [7] [8]. The University Hospital B is located in the second largest city in the country. When staff is assigned to an area, they tend to stay in the urban area of the region.
In univesity hospital C, the WISN ratio calculated was 2.12 (Table 6). There would therefore be an overstaffing of nearly 112%. This rate is comparable to that of Ly et al. [5] who found an overstaffing of 100% (WISN ratio = 2) at Kaya Regional Hospital. Our results are contrary to those of Shivam et al. [9] who reported a shortage of midwives in rural hospitals in India.
The calculated WISN ratio is 1.93 in University Hospital D. The University Hospital D has an overstaffing of 93% of midwives and maïeuticians. Thus, there is no workload pressure. In India, Das et al. [10] noted a ratio of 1.38. Namaganda et al. in Uganda [6] had an overstaffing of midwives and maïeuticians of 25%.
This low ratio of the need for staff could be explained by an erroneous result of the actual volume of activities of the midwives and maïeuticians. In fact, during our data collection, we noted under-reporting of activities in the monthly activity reports. Under-reporting leads to an underestimation of the health care institution’s staffing needs.
In addition, the University Hospital D receives only patients from the North region and sometimes from the Mouhoun loop region.
Non-attendace could also play an important role in workload. Although we did not investigate this aspect, it remains a real problem in public institutions. In Burkina Faso, Non-attendace affects 7% to 10% of health personnel (Ministerial Sector Board of Directors).
4. Conclusion
WISN allows evaluating the adequacy between the workload and the existing staff. When applied to the midwives and maïeuticians in the university hospitals of Burkina Faso, it revealed an over-staffing of midwives and maïeuticians in the two university hospitals of the country. A regional analysis of midwives and maïeuticians needs is advisable in order to allow for an equitable redeployment of midwives and maïeuticians through out Burkina Faso.