IntroductionIn the world, the health policies are necessary to satisfy with efficiency the requirements of the quality management in the health sector. The laboratory of the academic clinics of Lubumbashi in Africa was inspired by the EFQM model to improve its performance and the quality of its services offered to the community. The aim of this survey is to evaluate the level of job satisfaction of the healthcare providers after implementation of the model.MethodsQualitative study used an anonymous questionnaire consisted of 16 semi directional dichotomous and 12 according to four modality of the Likert's scale; to evaluate the job satisfaction of the healthcare providers. 40 workers are concerned and their informed consent is obtained. Epi Info 3.5.3 and SPSS 19.0 software, the Student t test and Chi-square test and the threshold set at p ≤ 0.05 were used. The mean score was calculated. Cronbach's ‘ coefficient and principal component analysis allowed the validity measurement of the questionnaire, and the correlations has been calculated.ResultsThis survey had a rate of answer of 80% on a set of all questionnaires. The Cronbach's coefficient of reliability is 0.72 on 40 complete observations with 12 questions. The Kaiser Meyer Olkin (0.564) and the Bartlett test is significant (χ2= 57, 30, p=0.001). The Physicians are very dissatisfied (2.363) against the nurses, and the biologists who are moderately dissatisfied (3 and 3.312). The relative results to the global satisfaction of the workers show a meaningful difference between the workers satisfied versus those non satisfied (p = 0.003). More of the half of the workers is satisfied after the setting up of the EFQM model.ConclusionA certain number of the factors act together and simultaneously on the satisfaction of the workers particular in the health sector. The EFQM model permits the job satisfaction in the hospital because it combines several factors acting on the individuals.

IntroductionThis article analyses the composition of healthcare costs for HIV/AIDS infected patients in a country with limited resources and attempts to identify the factors that influence these costs. The aims are to calculate medical care costs, analysing how they vary depending on patients’ income, and to evaluate the factors explaining healthcare consumption.MethodsThis is a prospective cohort study focusing on patients who were admitted to hospital for a short stay between January 2010 and June 2011, before their integration into a specialised program. The patients were selected randomly. Free consent was obtained from all participants. Data were analysed using the SPSS 19.0 software. The significance threshold was set at 5% and the CI (Confidence Interval) at 95%. We used Kruskal-Wallis tests, Fisher's exact test and multiple linear regression.ResultsWe monitored 209 patients. Their average age was 36.37 years (SD: 8.72). The sex ratio was 0.58 and the women patients were generally younger than the male ones (p=0.011). The overall cost of healthcare amounted to $US 41,922. The cost of Antiretroviral Therapy represented 21.6% ($US 9,045). The price of para-clinical examinations represented 46% ($US 19,136) of the overall cost. The patient's average monthly income was $US 157.40 whereas the average direct cost per patient was$US 201.45. Both monthly income (t=4.385; p=0.0000) and education level (t=3.703 p=0.0003) were statistically significant predictive factors for healthcare consumption. The medical care costs for patients with opportunistic infections were nine times higher than those for patients who presented none. The presence of opportunistic infections increased healthcare consumption by approximately 31$ US (CI 95%: 15-46.9).ConclusionThe average direct cost for patients on each short-term stay was higher than the average monthly income. To be able to access the necessary services, the patients need additional resources, which are derived from various sources. Monthly income and the level of education were both statistically significant predictors for healthcare consumption. The analysis allows us to extend the study by using different analytical accounting approaches such as by case and by pathology.