AfDB 2014 www.afdb.org E c o n o m i c B r i e f Summary p.2 CONTENTS What policies should be implemented to address inequalities in health care in Tunisia? 1 General Introduction p.4 2 Indicators of Health Status and Use of Health Care Services p.5 3- Territorial Inequalities in Health Care Facilities p.9 4- Trend in inequalities in health spending in Tunisia between 2000 and 2010 p.27 5- General Conclusion p.41 Bibliography p.42 Annexes p.44 Zondo Sakala Vice President z.sakala@afdb.org Jacob Kolster Director ORNA j.kolster@afdb.org +216 7110 2065 Key Messages Despite the progress achieved, health inequalities remain considerable and relatively little known in Tunisia. In light of the analysis conducted, there is significant elbow room for reducing these inequalities. In Tunisia, there are significant inequalities in care consumption between governorates for similar needs (those related to reproductive health, for example). There are also significant differences in the health status of the population of these governorates. The life expectancy of 74.5 years in 2009 does not exceed 70 years in Kasserine and Tataouine, but reaches 77 years in the governorates of Tunis and Sfax. The analysis indicates that: - The overall inequality in health spending declined from 2000 to 2010. The breakdown of the Gini index shows that this movement is almost entirely explained by the decrease in inequality in pharmaceuticals spending, which accounted for 42.2% of health spending in 2010. This trend can be attributed to a greater availability of pharmacies throughout the national territory. - The items where inequality has worsened and that had an inertia effect were long-term illnesses (17% of expenditure), hospital stay and medical surgery (8.6%) and radio and scans (8% of health spending). Such spending is related to the demographic and epidemiological transition. - Dental care is characterized by unusually high levels of inequality and lack of access for the disadvantaged classes. The main recommandations in this context are as follow: - From the supply side: (i) In the public sector, it is necessary to revitalize primary health care by improving the operation (ii) It is also important to strengthen Level II which seems to be the weak link in the system. Better coverage of the territory in terms of Level II beds should necessarily go hand-in-hand with the provision of more specialized physicians for the poorest regions in light of the demographic and epidemiological transition. (iii) Efforts should be made to ensure that at each level the system performs its assigned tasks under the best possible conditions. These tasks should be clearly defined. Each hospital institution should have a scheme of work that allows for coherent strategic management. (iv) The specific incentives that were introduced to encourage physicians to settle in deserted areas should be evaluated. Public-public and possibly private-public partnerships should be instituted. Also, it is important to negotiate with corporations an institutional framework to better regulate the opening of private practices. (v) It is necessary to determine measures that should be implemented to enhance health care delivery at local or regional level, as part of an overall regional development policy. - On the demand side: (i) It is important to reduce financial barriers to health care access by better targeting the poor who benefit from free medical assistance. (ii) Pharmaceuticals are a significant drain on the budgets of the poorest households and it is necessary to reduce this weight by ensuring good governance of public pharmacies. (iii) There is a need to ensure a better collective coverage of longterm illness, hospital stay and medical surgery, x-rays and scans. Knowing the profile of households that incur these expenses will make it possible to better target them, if need be. (iv) Dental care continues to be characterized by extremely high inequalities in expenses. Improved coverage of the territory in terms of availability of dental practices and greater public awareness of the importance of dental health should curb one of the causes of the inequality. Similarly, a special processing of reimbursement for dental expenses by health insurance, apart from the recurrent expenses, should contribute to reducing inequalities in dental care access. - On the institutional side: (i) It is necessary to aim at reducing social and regional inequalities in health care. (ii) There is a need to produce and monitor indicators for assessing the progress of specific categories not only at the national level but also at the local level. It is important to conduct periodic surveys on the status of health, health care use, or the failure to seek health care for financial reasons. This paper was prepared by Salma Zouari, Ines Ayadi and Yassine Jmal, under the supervision of Vincent Castel (ORNA) and Sahar Rad (ORNA) et Laurence Lannes (OSHD). Overall guidance was received from Jacob Kolster (Director, ORNA). Ahmed Rekik and Chokri Arfa suggested improvements to the preliminary version of this research. Asma Baklouti, Mariem Ellouze, Rahim Kallel and Abdessalem Gouider each made an input.
AfDB E c o n o m i c B r i e f Summary In Tunisia, there are significant inequalities in care consumption between governorates for similar needs (those related to reproductive health, for example). There are also significant differences in the health status of the population of these governorates. The life expectancy of 74.5 years in 2009 does not exceed 70 years in Kasserine and Tataouine, but reaches 77 years in the governorates of Tunis and Sfax. Three hypotheses were then made: Therefore, there is clearly a need to develop a strategy for strengthening and revitalizing primary health in the country as well as enhancing Level II. 1-2- Regarding human resource allocations, the inequality between governorates has decreased, except for physicians whether in the public or private sector. Although there has been a significant drop in the number of inhabitants per physician from 2002 to 2010, the gaps have widened between the better endowed governorates and the less endowed ones, while the variation coefficients have increased. l l l Households, whatever the level of their resources and even when they benefit from social security coverage, have unequal access to care because of inequities in the provision of health care services in their immediate environment. Despite the importance of social coverage, households assume an average of 41% of health spending in the form of out-of-pocket expenditures. Therefore, households have unequal access to care arising from inequalities in income distribution and illustrated by unequal health spending. Due to the importance of out-of-pocket health care spending, the regressive (or progressive) nature of care spending and its inelasticity compared to income, can give them a potentially catastrophic and impoverishing character that makes unequal access to care even more acute. These hypotheses were tested on the basis of available statistical data. Health policy recommendations have been made. 1- On the assumption that the availability of care provision, whether public or private, and good coverage of the national territory in health infrastructure contribute to the decline in inequality in access to care, we analysed the trend of provision indicators by governorate and the dispersion of these indicators through the use of cross-sectional data of the 2010 health map and various longitudinal indicators published in the Statistical Yearbook of the National Institute of Statistics for the period 1997-2010. Three aspects were analysed: infrastructure, the availability of beds and the provision of human resources. 1-1- With regard to infrastructure and bed availability, it turned out that only the availability of PHCs declined over the last decade. Level II, which is the reference for Level I, would not be very effective because it lacks adequate technical equipment and specialized physicians. We suspect that patients are referred to Level III which takes the place of Level II, thus causing inefficiencies. The availability of free medical practitioners is characterized by high levels of inequality; the relationship between the most endowed and the least endowed governorates is 14.3. This is followed by dental practices (ratio of 11.3) and hospital beds (10.7). The most evenly distributed resources are pharmacies and paramedical staff. It would be advisable to review the criteria for opening positions of public health physician at regional level and the institutional framework governing private practices. Like the practice of pharmacy, the practice of dentistry and medicine on a free basis should be better regulated. Similarly, public-private and especially public-public partnerships (such as agreements between academic physicians and regional hospitals) that may make disadvantaged areas more attractive as is being considered for specialists could be a solution. However, the implementation of such partnerships should be accompanied by measures to ensure their effectiveness for all stakeholders. 1-3- Lastly, since the status of health care facilities in a governorate cannot be analysed by reference to a single determinant, all the components of the sector and the complementarity between different providers should be taken into account simultaneously. For this purpose, we have integrated the various determinants of facilities (by category and overall) in order to arrive at relatively homogeneous groups (called clusters) and calculated for each governorate, a composite indicator of care provision that measures its position compared to other governorates as well as the progress that may be achieved over time. Among the three components of health care facilities, the geographic distribution of medical human resources stands out as the most unequal, with a significant concentration on the coast. Despite an increase in the density of physicians, regional disparities have widened. Qualitatively, the inequalities are even more blatant and more than 2/3 of specialists are found on the coast as regards not only rare specialties but also the most common such as gynaecology and paediatrics. 2
E c o n o m i c B r i e f AfDB Three governorates constantly fall within the most favoured cluster whatever the aspect considered. They are Tunis, Sousse and Monastir. Conversely, four governorates always fall within the most disadvantaged cluster: Jendouba, Kairouan, Kasserine and Sidi Bouzid. Between these two groups, the various governorates show more or less substantial deficits depending on the nature of the resources analysed. The scope of intervention required by each governorate may then be defined. Government intervention is necessary when there is a build-up of inequalities. However, the choices related to the health sector and efforts to better allocate resources to priority areas can only be effective if they form part of a comprehensive local development strategy in these areas. The reduction of economic, cultural and social differences between the governorates can only facilitate and strengthen health reforms. 2- Working from the assumption that inequalities in access to health are linked to income inequalities, we assessed the inequality of out-ofpocket household health expenditure and analysed the trends thereof and training through inequality indicators and their breakdown by expenditure category. For this purpose, we referred to the individual data of the national surveys on household budget and consumption in 2000, 2005 and 2010. This data provides information on total health spending per person per year (SPY) and the various expenditure categories: routine medical care, special medical care, pharmaceuticals and medical devices or expenditure sub-categories (medical consultations; dental care; radio, scanner and medical analysis; medical stay and surgery; special dental care; special radiology expenditure; childbirth; long-term diseases; drugs; other pharmaceuticals, etc.). This approach gave information about: l l Overall inequality in health spending and its trends; inequality of SPY in each care spending item and sub-item; l l the contribution of inequality in each SPY category or sub-category to total health spending inequality; the marginal effect - equalizer or non-equalizer of the variation of a particular SPY on total health spending inequality. 2-1- The overall inequality in health spending declined from 2000 to 2010. The breakdown of the Gini index shows that this movement is almost entirely explained by the decrease in inequality in pharmaceuticals spending, which accounted for 42.2% of health spending in 2010. This trend can be attributed to a greater availability of pharmacies throughout the national territory. 2-2- The items where inequality has worsened and that had an inertia effect were long-term illnesses (17% of expenditure), hospital stay and medical surgery (8.6%) and radio and scans (8% of health spending). Such spending is related to the demographic and epidemiological transition. The reduction of the corresponding inequality requires specific government policies that target the most vulnerable groups. The collective management of these expenditures still seems insufficient. Knowing the profile of households that incur these expenditures will help to better target them. 2-3- Dental care is characterized by unusually high levels of inequality and lack of access for the disadvantaged classes. Improved coverage of the territory by dental practices and greater awareness of people about the importance of oral and dental health should curb one of the causes of this inequality. Similarly, a specific treatment for reimbursement made by health insurance that is nonconcurrent with current spending should contribute to the reduction of inequalities in access to dental care. 3
AfDB E c o n o m i c B r i e f 1. General Introduction Since 1956, the foundations for a universal system of health care delivery have been established in Tunisia. For three decades, the resulting benefits have been improved over time and a social security system has been put in place for employees. However, public expenditure on the health sector has slowed since the 1990s, and private practices have gradually substituted public health services that have experienced some decline in their quality and availability. Household health spending has risen sharply, sometimes leaving a heavy dent on the household budget. The most vulnerable segments are not spared (Arfa, ElGazzar, 2013). Since January 2011, there is heightened awareness of inequalities in the health status of the population and health care use. More attention is paid to issues of equity in access to care and there is more concern about a more egalitarian distribution of health services throughout the country. Indeed, although health infrastructure covers almost the entire country 1, there are inequalities in availability between the different regions. The health system is predominantly public, with 87% of bed capacity in public hospitals and 13% in private clinics. On average, Tunisia has 123 physicians per 100 000 inhabitants. However, physician density is much lower in the poorest regions where most of the beneficiaries of free health care are found. 2 With regard to the financing of the demand for care, the National Health Insurance Fund (CNAM) covers about 68% of the total population. It covers both public and private health care services in the country. The majority of physicians, laboratories, dentists and pharmacists are contracted with CNAM. There are three branches: the public branch, the private branch and the reimbursement branch. The public branch is heavily subsidized or free for the beneficiaries of free health coverage who are estimated at 27% of the population. Despite the important size of community coverage of medical care by insurance or by the State budget, private spending still remains very high and is increasing. In 2010, health care was financed by public budgets to the tune of 23.8%, by health insurance resources (CNAM with 27.7% and private insurance with 7%) and out-of-pocket household spending that covered 41.2%. Thus, the health system faces many challenges, and it is important to: l l l Reduce regional disparities in the provision of health care services; reduce inequalities in household health spending; limit the amount of out-of-pocket household spending. Therefore, it is necessary to better define the situation of health inequalities and its recent trend, and to identify policies that can help address the above challenges. We will begin by recalling some household health status indicators and the use of health services (Section I). We will then analyse the inequities in health care provision (Section II). Lastly, we will also address the spending inequalities and their sources (Section III). In this respect, we will mainly use data from the 2010 Tunisia Health Map published by the Ministry of Health as well as data relating to the health sector published by the National Institute of Statistics (INS) in the Statistical Yearbook of Tunisia between 1997 and 2010. We will further use the individual databases of the National Surveys on Household Budget and Consumption conducted by the INS in 2000, 2005 and 2010. 1 The health system includes: (a) primary health centres or primary health centres and local or district hospitals; (b) regional hospitals; and (c) university teaching hospitals. 2 Medical density in Tunisia is lower than the European average, which is more than 300 physicians per 100 000 people. It is the highest in the Maghreb (Algeria and Libya 120, Morocco 60, Mauritania 10) and occupies the ninth place in the EMRO region behind Lebanon (330), Bahrain (300), Qatar (280), Jordan (260), Egypt (240), Kuwait and Oman (180), Saudi Arabia (160) and ahead of Iran (90), Pakistan (80), Syrian Arab Republic and Iraq (50 ), Sudan and Yemen (30) (MH, Tunisia Health Map 2010). 4
E c o n o m i c B r i e f AfDB 2. Indicators of Health Status and Use of Health Care Services 3 There are few studies and statistics on this issue. However, we will refer to data known for their relevance and published regularly by the INS. The health status will be assessed through life expectancy and the infant mortality rate (IMR). These two indicators are particularly suited to the health inequalities study (Jusot, 2003). However, they are published in a systematic way only at the national level. The mortality rate, which is a poor indicator of health status because it is sensitive to the structure of the population by age, is however available at the governorate level. It will only be used to assess the evolution of its variation coefficient. 4 Health service use will be analysed through the data on reproductive health because of their availability and because reproductive health concerns the entire population in the same manner. 1- Health status indicators Differences in life span may be seen as a synthetic indicator of social differences affecting health throughout the life cycle (Aïach, 2000). There has been a remarkable increase in life expectancy at birth in Tunisia (Figure 1). From only 58 years in 1956, life expectancy has risen to 74.9 years in 2011. The continuous improvement of this indicator is applicable to both men and women. Figure 1: Life expectancy by gender (1990-2011) 78 76 74 72 70 68 66 64 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Male Female The increase in life expectancy is due to a decrease in mortality rates in general, and the sharp decline in infant mortality in particular. The mortality rate showed a decreasing trend. From 19.1 per thousand in 1960, it dropped to 5.5 per thousand in 2011 (Figure 2). The infant mortality rate fell from 120 per thousand births in 1966 to 14 per thousand in 2011 (Figure 2). 3 All the statistics in this section are derived from Tunisian Statistical Yearbooks published by the National Institute of Statistics. 4 For a Y distribution of mortality rates with average Y, the coefficient of variation, noted CV, is derived from the variance. It is defined as the ratio of the standard deviation σ to the mean mortality rates: CV = σ / Y where σ 2 = 1/ N (Yi - Y)2 CV is used to compare the dispersions of distributions with different averages. The higher the CV the more dispersed the distribution will be. 5
AfDB E c o n o m i c B r i e f Figure 2: Mortality rate Figure 3: Infant mortality rate 25.0 20.0 15.0 10.0 5.0 0.0 200 150 100 50 0 1990 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2001 2008 1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008 Infant mortality is an indicator widely used in international comparisons. It is an indicator of robust health, revealing a country s development level and the quality of its health care system. It depends on several factors, including income, maternal educational level and the effectiveness of preventive care provided to mother and child (Bouchoucha and Vallin, 2007). The decline in infant mortality rate may be attributed to both factors inherent in the health system (modernization and better coverage of the country) and the evolution of Tunisian society (improvement in the quality of life and an increase in the living standards and the educational level of the population). The life expectancy of 74.5 years in 2009 did not exceed 70 years in Kasserine and Tataouine, but reached 77 years in the Tunis or Sfax governorates (Map 1). Similarly, the decline in infant mortality has not been equally beneficial to all children regardless of their place of birth (Map 1). In 2009, the infant mortality rate was 17.8 at the national level. In the South, it was 21, while in the Midwest it rose to 23.6 (Ministry of Regional Development, 2011). Map 1 shows two groups of governorates at odds with each other: the first (Tunis, Sousse, Monastir and Sfax) recorded the lowest infant mortality rates (IMR), while the second (Kasserine, Sidi Bouzid and Kairouan) had the highest rates. However, this overall positive trend hides significant disparities between rural and urban areas as well as between socioeconomic groups and between the various governorates. We will focus on the regional aspect of inequality and health status indicators. Lastly, the mortality rate by governorate (indicator sensitive to the age structure of the population) shows contrasting trends and especially an increase in the variation coefficient, indicating a rise in inter-governorate inequality and greater heterogeneity of living conditions prevailing there (Figure 4). Figure 4: Coefficient of variation in mortality rates by governorate (1978-2010) 0.25 0.20 0.15 0.10 0.05 0.00 1997 1998 1999 2000 2000 2001 2002 2003 2004 2005 2007 2008 2009 2010 6
E c o n o m i c B r i e f AfDB 2- Health care use indicators In general, health care use is related to health condition and inequality in health care use primarily reflects unequal needs. Hence it is not necessarily unfair. It is therefore necessary to analyse the inequalities observed only when facing the same need. As such, the indicators related to reproductive health are well suited for such an analysis. They help to identify women who give birth and analyse inequalities between them. Tunisian Statistical Yearbooks each year publish statistics on the use of reproductive health care. We will try to see to what extent the use of such care is egalitarian. However, it is important to note that reproductive health care use reflects women s perception of health and medicine, and it depends on the alternative care available to them and their medical environment. However, it is often subject to social and family control (Gastineau, 2003). Belonging to a family or community group, social habits and the environment are likely to influence women's choices in this matter. With reference to the number of deliveries by governorate, we calculated three indicators: the home delivery rate, the hospital delivery rate and the clinic delivery rate. 5 In 2010, the home delivery rate (or rate of medically unassisted childbirth) was 7.6%. It varied greatly between governorates. Governorates with high home delivery rates include Monastir, Nabeul and Mahdia, all of which have relatively good health infrastructure (Figure 5). Figure 5: Home delivery rate in 2010 by governorate 50% 40% 30% 20% 10% 0% Zaghouan Kasserine Manouba Sidi Bouzid Kairouan Siliana Mahdia Nabeul Monas r TUNISIA Medenine Tataouine Gaafsa Ben Arous Kebili Sousse Ariana Tozeur Sfax Gabes Le Kef Jendouba Beja Bizerte Tunis Clinic delivery rate was 12.3%. With the exception of Monastir, it was generally higher in the major urban centres of the coast which have private health infrastructure (Figure 6). Figure 6: Clinic delivery rate in 2010 by governorate 50% 40% 30% 20% 10% 0% Ben Arous Sfax Nabeul Sousse Tunis Ariana TUNISIA Bizerte Médenine Le Kef Mahdia Monas r Gabes Kairouan Beja Gafsa Jendouba Manouba Sidi Bouzid Siliana Touzeur Kasserine Kebili Zaghouan Tataouine 5 The sum of these three rates is not a unit because some women do not report the place where they gave birth. 7
AfDB E c o n o m i c B r i e f Lastly, hospital delivery is the dominant standard in Tunisia. On average, 67.5% of women give birth in hospital. Governorates where the propensity to give birth in hospitals is lower (Figure 7) are those where the private sector is important (Sfax, Tunisia...) or where the use of medicine is relatively limited (Sidi Bouzid, Kasserine ). Figure 7: Hospital delivery rate in 2010 by governorate 100% 80% 60% 40% 20% 0% Jendouba Beja Tozeur Kebili Tataouine Gabes Le Kef Siliana Bizerte Gafsa Ariana Medenine Sousse Mahdia Kairouan TUNISIA Sfax Nabeul Tunis Manouba Sidi Bouzid Ben Arous Kasserine Monas r Zaghouan By comparing the number of antenatal or postnatal visits in the public sector to the total number of births registered in a year (assisted or unassisted, in hospital or private clinic), the frequency of these procedures may be determined. There is an average of three antenatal visits per delivery. Only Tunis, Sousse, Sfax, Monastir and Mahdia governorates show a lower frequency rate for these procedures. These governorates are better off in private infrastructure, and many women consult their gynaecologist. The number of public postnatal visits is much lower (0.57 in 2010), but it is just as unevenly distributed among the governorates as the number of antenatal visits (Figures below). Figure 8: Antenatal visits per delivery Figure 9: Postnatal visits per delivery 8 6 4 2 0 Tozeur Kebili Zaghouan Kasserine Gabes Sidi Bouzid Gafsa Le Kef Bizerte Siliana Tataouine Ariana Beja Nabeul Kairouan Ben Arous Jendouba Medenine TUNISIA Mahdia Monas r Sfax Sousse Tunis 1.5 1.0 0.5 0.0 Kebili Gabes Zaghouan Kasserine Ariana Ben Arous Sidi Bouzid Nabeul Tozeur Mahdia Bizerte Jendouba Tataouine Gafsa Beja Siliana TUNISIA Le Kef Sfax Monas r Medenine Kairouan Sousse Tunis More generally, the various governorates do not fall in the same category for the two indicators, reflecting the importance of community and social determinants in health care use. It would be interesting to consider the factors that explain these differences in order to assess the fairness of the system (Fleurbaey and Schokkaert, 2011). The use of health care which determines the health status of individuals is mainly due to the interaction of three determinants: Existence of demand related to the expression of a need for health (disease prevention, disease treatment, reproduction, etc.); availability of funding or means of support to make the demand effective; existence of an offer or several offers to meet the need. When one of the last two elements is absent, access to care becomes impossible and care will not be provided at the risk of leading to serious vital and economic consequences. Disease causes a loss of income and can propel the individual into poverty. As such, these two dimensions deserve special attention because they have a determinant impact on access to care. We will devote the following sections to them. 8
E c o n o m i c B r i e f AfDB 3. Territorial Inequalities in Health Care Facilities The availability of a health service whether public or private and good coverage of the national territory in health infrastructure contribute significantly to the reduction of inequality in access to health care (Gold Zeynep et al., 2009). After an overview of Tunisia s health care system, we will analyse the availability of public and private health resources in the 24 governorates and try to build a composite indicator of health care facilities that can help to assess inter-regional inequalities and to monitor their trend. 1- Overview of the health care system in 2010 6 In Tunisia, the health care delivery system is primarily public although there is a growing private sector (Arfa, 2007). Nationally, more than 86% of hospital beds are in the public sector. 7 The leading care provider is the Ministry of Health. The public provision of health services is structured in three levels of care. Primary health care 8 is provided by 2 085 primary health centres (PHC), with 2 923 district hospital beds (consisting of small facilities with an average of 27 beds per facility) and maternity centres, which together account for about 15% of public sector bed capacity. This care level implements preventive health policy. It handles 60% of public sector medical outpatients and more than 1.3 million reproductive health visits (perinatal consultations, contraception, STI, screening for female cancers, etc.). It manages the health activities of all pupils and students at all levels (pre-school, primary, secondary, university, vocational training and others). Level II health care is provided by 33 regional hospitals (RH), which account for 35% of total bed capacity and medical specialists in the public sector. Level III health care consists of a network of 24 hospitals and academic institutions with an average size of 405 beds. These hospitals represent approximately 50% of all public sector beds. The health system further includes the polyclinics of the National Social Security Fund, hospitals under the Ministry of National Defence and the facilities of the Ministry of the Interior and Local Development (Arfa and Elgazzar, 2013). In Tunisia, access to the various levels is open and not by referral. Hence, the first line may start at the primary, secondary or tertiary level. The intense activity of emergency services in hospitals is an example. The private health care sector has grown significantly: it accounts for about 14% of total bed capacity and 70% of advanced technology services. In terms of human resources, it employs 48.3% of physicians (55.6% of specialists and 42% of general practitioners), 77.5% of dentists and 81.5% of pharmacists. Private clinics are mostly concentrated in major coastal urban areas (Arfa and Elgazzar, 2013). Despite an equalizing trend and geographical accessibility deemed acceptable for front-line facilities, the distribution of health services in the country is characterized by a certain inequality that should be evaluated and corrected. 2- Trend in the distribution of health facilities To study the trend in the distribution of health facilities in the country, we will analyse the allocations of the 24 governorates in primary health centres and hospital beds over the past decade. These two indicators characterize public health provision. 9 We will complete them with human resource indicators (public sector physicians and paramedical staff). We will also analyse the availability of private practices, pharmacies and dental offices in governorates. These three indicators characterize private health provision. 6 The main source is the 2010 Health Map of Tunisia (Ministry of Health). 7 In 2010, the theoretical public bed capacity is 19 565 beds, while private clinics account for only 3 029 beds. 8 When people need health care, they turn most often to primary health care services, which are the first point of contact with the system. In general, primary health care has a double function. First, it provides preventive and curative support for common diseases. Then it acts as an interface and when necessary, refers patients to higher levels; it facilitates their movement within the health system when more specialized care is needed. 9 We will not discuss any issues related to the efficient use of the infrastructure, (World Bank, 2008). Overall, the potential of district hospitals has been under-utilized because of the weakness of their technical facilities, which limits the scope of diagnostic and therapeutic care management. Regarding regional hospitals, despite generally satisfactory technical facilities, productivity is affected by the lack of specialists, who are more attracted to university hospital careers or private practice. Lastly, UTHs control most of the heavy equipment in the public sector. Skill levels are high, but the sector suffers from consultation congestion, due to the weakness of the second level, as well as an increasingly strong tendency for brain drain to private practice that offers significantly higher income levels (WHO, 2010). 9
AfDB E c o n o m i c B r i e f For each indicator, we will refer to the per capita endowment or its inverse (the number of inhabitants per unit). We will see if, on average, the indicator improves. In addition, the use of the coefficient of variation 10 will reveal whether, overall, the distribution of health resources has become more or less unequal. Comparing the values of the indicator at the beginning of the last decade and at its end, for each governorate, will allow description of the trend of the governorate. The data used are drawn from the Tunisian Statistical Yearbook for 2006-2010 (Serial No. 53). 2-1 Trend in the distribution of public health care facilities 2-1-1. Primary Health Centres (PHCs) The number of inhabitants by PHC globally reflects a reversal trend from 2003 (Figure 10). It increased from 4 795 in 2003 to 5 051 in 2010. This trend could mean a more efficient use of PHCs for the benefit of a denser population. It may also indicate less easy access to these centres. In the latter case, the PHC facility, as the access point of the population to the health system, is fulfilling its role of health prevention and curative treatment of common diseases less than before. However, the coefficient of variation of the number of inhabitants per PHC according to the governorate shows a downward trend indicating a reduction in inter-governorate inequality (Figure 10). The decrease in inequalities is due primarily to the deterioration of the situation in governorates such as Monastir, Bizerte, Sfax, Sousse, Nabeul, Ben Arous, Ariana and Tunis, as shown in Figure 12. These governorates are relatively well served by Level III and PHCs providing consultations almost daily. Figure 10: Inhabitants per PHC (1998-2010) Figure 11: CV inhabitants per PHC (1998-2010) 5100 5000 4900 4800 4700 4600 5100 5000 4900 4800 4700 4600 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Figure 12: Inhabitants per PHC by governorate 25 000 20 000 15 000 10 000 5 000 0 2000 2010 Tataouine Kebili Siliana Le Kef Tozeur Beja Zaghouan Mahdia Sidi Bouzid Gafsa Jendouba Kasserine Medenine Gabes Kairouan Ensemble Monas r Bizerte Sfax Sousse Nabeul Manouba Ben Arous Ariana Tunis 10 For a Y expenditure distribution with average Y, the coefficient of variation (CV) is derived from the variance. It is defined as the ratio of the standard deviation σ to the average of expenses: CV = σ / Y where σ 2 = 1/ N (Yi - Y)2 CV is used to compare the dispersions of distributions with different averages. The higher the CV the more dispersed the distribution will be. 10
E c o n o m i c B r i e f AfDB In this respect, it should be noted that this indicator does not allow proper assessment of the availability of health services in regions because it does not take into account the pace of consultations in the PHC. Indeed, primary health centres differ in their type and the pace of medical consultation observed there. In 2010, 1040 of the 2085 PHCs provided at most one day of consultation per week. The 2 085 primary health centres are in fact equivalent to 870 full-time centres. 11 In addition, the pace of consultations is not equally distributed among the PHCs. The proportion of PHCs providing medical consultation six days per week is only 4.4% in Medenine, 4.8% in Tataouine, 9.3% in Tozeur, 8% in Mahdia, 8.6% in Kébili, 8.9% in Sidi Bouzid and 9.6% in Beja. Thus, in these governorates, most of the population does not have daily access to mobile, community primary health care services. Accordingly, efforts should focus more towards Figure 13: Bed availability rate (1998-2010) 1.9 1.8 1.7 1.6 1.5 1.4 improving the frequency of primary health care consultations rather than the multiplication of small health centres. 12 2-1-2. Hospital beds Unlike the first indicator, the bed equipment rate or number of public beds per 1000 inhabitants shows a significant increasing trend in the public provision of care (Figure 13). The number of public beds per 1000 inhabitants increased from 1.74 in 2001 to 1.85 in 2010. Similarly, the coefficient of variation of the bed rate in governorates decreased (Figure 13). This therefore means reduced inter-governorate inequality. Despite these positive developments, the public bed equipment rate varied in 2010 from 0.4 in Ben Arous to 4 in Tunis (Figure 15). Figure 14: CV bed availability rate 0.60 0.50 0.40 0.30 0.20 0.10 0.00 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 1998 1999 2000 2001 2002 2004 2005 2006 2007 2008 2009 2010 4.50 4.00 3.50 3.00 2.50 2.00 1.50 1.00 0.50 0.00 Figure 15: Public hospital beds per 1 000 inhabitants by governorate Ben Arous Ariana Sidi Bouzid Kairouan Kasserine Nabeul Jendouba Mahdia Bizerte Medenine Siliana Gabes Tataouine Beja Sfax Kebili Tunisie entère Le Kef Gafsa Monas r Sousse Manouba Zaghouan Tozeur Tunis 2000 2010 11 The 2010 Health Map can be used to calculate for each governorate the number of PHC full-time equivalent and the number of inhabitants per PHC full-time equivalent, but this statistic is not available for earlier years. 12 Three evaluations of the primary health care system (1997, 2000 and 2004) were carried out by the Ministry of Health as part of the Health Districts National Development Programme. It is a programme developed since 1994 by the Directorate of Primary Health Care. The overall objective of PNDCS is to make all health units in the country able to manage the health status of the population through a set of preventive, curative, promotional and rehabilitation activities, and ensure coordination within and between sectors involving all health stakeholders. The PNDCS has two specific objectives: firstly, improving the (technical and relational) quality and efficiency of care at the primary health centres (PHC) and the district hospital and secondly, strengthening and involving the population in health management. The main recommendations were: (i) optimizing health delivery by moving from a logic of coverage with infrastructure (number of hospital beds, number of DHCs) to an approach of coverage with effective services (number of medical consultation days offered, range of hospital services with appropriate technical facilities); (ii) improving the dimensions of care quality, for example by adapting opening hours to the rhythm of the patient population. 11
AfDB E c o n o m i c B r i e f Reducing inequality reflects both: l l An improvement in bed equipment in many governorates among the least well off, notably: Sidi Bouzid, Kasserine, Siliana, Tataouine, Beja, Kébili, Le Kef, Gafsa, Tozeur... a worsening situation in other governorates. The number of beds per 1 000 population decreased in Ariana, Sfax, Monastir, Sousse, Manouba and Zaghouan. These governorates are experiencing strong population growth induced in particular by migration. Almost ten years of stagnation of the bed equipment rate in Tunis or the reduction thereof in large cities such as Sfax, Monastir, Sousse, Ariana and Manouba are all the more disturbing trends since these cities are university teaching hospital centres. The quality of training at the patient s bedside may be affected by the increasingly less favourable conditions in which it takes place. As such, there is the risk of a vicious circle that reproduces mediocrity. To decongest level III and allow it to devote more time to training and research missions, level II should be developed. Indeed, the bed equipment rate analysed below takes into account beds at the three levels. It therefore hides disparities within levels. In the absence of detailed statistics for the study period, it was not possible for us to appraise the paces of matching developments. However, interviews with stakeholders led us to conclude that the weak link in the system is level II. Often this level is ineffective or non-existent and therefore needs to be strengthened. Finally, the quest for greater equity in the health system should not result in levelling from the bottom, or in a substantial carrying forward of activities from a certain level to a higher one. The system should be able to ensure that at each of its levels, the tasks assigned are carried out in the best conditions. These missions should be clearly specified. Each hospital institution should have a roadmap that allows strategic management consistent with the whole system. 2-1-3. Public sector physicians There has been a significant decrease in the number of inhabitants per physician in the public sector in all governorates with the exception of Ariana. This decrease reflects an increase in public health care provision. Overall, the number of inhabitants per physician dropped from 2176 in 2002 to 1569 in 2010 (Figure 16). Until 2008, this trend increased inequality between governorates. However, since 2008, the inequality gap is closing but is still significant (Figure 16). The number of inhabitants per physician in the public sector varied, in 2010, between 493 in Tunis and 3377 in Kasserine, a ratio of 1 to 6.8. There is a clear improvement in physician availability in many governorates (Figure 18). However, at the same time, the situation has changed very little in governorates like Kasserine, Medenine, Nabeul and Kébili. Yet these governorates were initially less endowed with physicians. Five governorates are better provided with public health physicians than the country as a whole. The number of inhabitants per physician there is less than 1569. They are Tunis, Sousse, Monastir, Sfax (which enjoy level III services) and Tozeur. Conversely, five governorates have twice less the number of physicians; the number of physicians per inhabitant is higher than 3 000 in Kairouan, Jendouba, Sidi Bouzid, Medenine and Kasserine. Figure 16: Inhabitants per public health physician 3000 2500 2000 1500 1000 500 0 Figure 17: CV Inhabitants per public health physician 0.37 0.36 0.35 0.34 0.33 0.32 0.31 0.30 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2002 2003 2004 2005 2006 2007 2008 2009 2010 12
E c o n o m i c B r i e f AfDB Figure 18: Inhabitants per public health physician by governorate 5000 4500 4000 3500 3000 2500 2000 1500 1000 500 0 2002 2010 Tunis Sousse Monas r Sfax Tozeur Ensemble Zaghouan Manouba Mahdia Tataouine Ariana Siliana Bizerte Beja Gafsa Kebili Gabes Le Kef Ben Arous Nabeul Kairouan Jendouba Sidi Bouzid Medenine Kasserine The overall improvement in the availability of physicians veils significant deficits in medical specialists (surgery, obstetrics, ophthalmology, orthopaedics, anaesthesiology...). Better coverage of the national territory in level II beds is necessarily concomitant with better provision of these regions with physicians in general and specialist physicians in particular. 2-1-4. Public sector paramedical staff The number of inhabitants per senior technician is a clear indication of the increase in public health care provision (Figure 19). It went from 341 in 2002 to 308 in 2010. The indicator has improved in all governorates except Sousse, Monastir and Ariana. The trend of the coefficient of variation across governorates indicates a gradual reduction of intergovernorate inequalities (Figure 19). However, there are still significant inequalities. The number of inhabitants per public sector paramedical staff varied in 2010 between 150 in Tunis and 720 in Ariana, a ratio of 1 to 4.8. The six governorates best equipped with paramedical staff are Tunis, Tozeur, Sousse, Monastir, Gafsa and Kef. The six governorates least equipped are Zaghouane, Nabeul, Kasserine, Sidi Bouzid, Ben Arous and Ariana, as shown in Figure 21. Figure 19: Inhabitants per paramedical staff Figure 20: CV Inhabitants per paramedical staff 360 340 320 300 280 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 0.60 0.50 0.40 0.30 0.20 0.10 0.00 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 13
AfDB E c o n o m i c B r i e f 1200 1000 800 600 400 200 0 Figure 21: Inhabitants per paramedical staff by governorate 2002 2010 Tunis Tozeur Sousse Monas r Gafsa Le Kef Kebili Beja Ensemble Tataouine Sfax Mahdia Bizerte SIliana Gabes Jendouba Manouba Kairouan Medenine Zaghouane Nabeul Kasserine Sidi Bouzid Ben Arous Ariana Once more, better coverage of the territory with level II beds will involve better provision of these regions with senior health technicians and nurses. 2.2 Trend in the distribution of private health care facilities 2-2-1. Private practice offices The number of private practice offices has increased considerably throughout the past two decades such that the number of inhabitants per office has on average been divided by 1.66 in 10 years (Figure 22). Inequalities between governorates declined until 2004, but have since increased (Figure 22). Between 2004 and 2010, the situation improved in all governorates except Siliana, Sidi Bouzid and Tataouine. In 2004, the ratio between the governorate best provided with private practice offices (Tunis) and the least provided governorate (Siliana) was 1 to 11.6. In 2010, this ratio rose to 14.3 (Figure 24). This problem is not specific to Tunisia; the same situation prevails in several developed countries, including France where it is called medical desert (Potvin Moquet, Jones, 2010; High Council of Public Health, 2009 and Senate 2013). Thus, in a context where physicians are free to choose their location, there was a craze for major urban centres and areas where the purchasing power of the patient base is higher and the quality of life better. In these areas, even when the number of inhabitants per physician is already low, this number has continued to decrease. By contrast, in the hinterland and in the least developed governorates, the propensity of physicians to settle there was low and the number of inhabitants per physician remained high and/or was on the increase. To counteract this spontaneous location of physicians, it is important to negotiate with the medical corps to revise the institutional framework governing the opening of private practice offices and/or to grant special incentives to physicians who settle in priority areas. The Order of 24 December 2009 in part enshrined the idea by providing for compensation for medical specialists 13 practising in the private sector and contracted with health facilities in priority areas (defined by the Order of 1 March 1995 issued by the Prime Minister laying down priority health areas for the granting of certain benefits). The effects could be assessed. 14 In France, a solution to the medical desert phenomenon was the establishment of medical home, that is to say, a structure whose main advantage is that of bringing together in one place many practitioners and several specialties with the purpose of saving by pooling and sharing certain costs. However, these structures instead resulted in the creation of a wider geographical network of rural and desert areas. Proposals have been made to hamper the freedom of installation of physicians rather than encourage them to open offices in areas where medical facilities are scarce. In particular, this means excluding from health insurance physicians who choose to settle in already saturated areas. As a result, since their patients are not reimbursed by social security, it would be impossible for a young physician to build a patient base (Senate, 2013). 13 TND 500 for specialists in surgery and obstetrics and gynaecology, TND 400 for all other specialties. 14 There is concern that physicians may abuse this situation by diverting patients from the hospital to their private practice or by using hospital equipment for private purposes. Ethical standards and rules of governance should be enacted. Very strict controls must be implemented. 14
E c o n o m i c B r i e f AfDB Figure 22: Inhabitants per private practice office Figure 23: CV Inhabitants/Private practice office 4 000 3 000 2 000 1 000 0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 0.70 0.60 0.50 0.40 0.30 0.20 0.10 0.00 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Figure 24: Number of inhabitants per private practice office by governorate 16000 14000 12000 10000 8000 6000 4000 2000 0 2001 2010 Tunis Sfax Ariana Sousse Ben Arous Ensemble Nabeul Medenine Monas r Bizerte Manouba Gabes Mahdia Beja Gafsa Zaghouan Le Kef Kairouan Kebili Jendouba Tozeur Tataouine Sidi Bouzid Kasserine Siliana 2-2-2. Dental offices The number of dental offices has increased significantly over the last two decades to the extent that the number of inhabitants per office was divided on average by 1.76 between 2001 and 2009 (Figure 25). Inequalities between governorates have significantly decreased, as shown by the trend of the variation coefficients (Figure 25). Figure 25: Inhabitants per dental office Figure 26: CV Inhabitants per dental office 14 000 12 000 10 000 8 000 6 000 4 000 2 000 0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 0.80 0.60 0.40 0.20 0.00 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 15
AfDB E c o n o m i c B r i e f 60000 50000 40000 30000 20000 10000 0 Figure 27: Number of inhabitants per dental office by governorate 2004 2009 Tunis Ariana Sousse Sfax Ben Arous Nabeul Bizerte Ensemble Monas r Manouba Mahdia Medenine Gafsa Le Kef Gabes Ensemble Jendouba Kairouan Beja Siliana Zaghouan Kebili Sidi Bouzid Tataouine Kasserine Tozeur Between 2001 and 2009, the situation improved in all governorates and is particularly striking in Zaghouan, Siliana, Sidi Bouzid and Kasserine (Figure 27). In 2004, the ratio between the governorate most provided with dental offices (Tunis) and the least provided governorate (Zaghouan) was 1 to 30. In 2009, this ratio dropped to 11 (between Tunis and Kebili). So there are still margins to reduce inequalities in dental office availability. 2-2-3. Pharmacies Overall, the number of pharmacies has increased faster than the country s population, such that the number of inhabitants per pharmacy has been divided by 1.2 in 10 years (Figure 28). Accordingly, the inequalities between governorates decreased significantly as shown by the variation coefficient (Figure 28). The situation improved in all governorates between 2001 and 2010 (Figure 30). Figure 28: Inhabitants per pharmacy 8 000 6 000 4 000 2 000 0 Figure 29: CV Inhabitants per pharmacy 0.50 0.40 0.30 0.20 0.10 0.00 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 60000 50000 40000 30000 20000 10000 0 Figure 30: Inhabitants per pharmacy by governorate 2004 2009 Tunis Ariana Sousse Sfax Ben Arous Nabeul Bizerte Ensemble Monas r Manouba Mahdia Medenine Gafsa Le Kef Gabes Ensemble Jendouba Kairouan Beja Siliana Zaghouan Kebili Sidi Bouzid Tataouine Kasserine Tozeur 16
E c o n o m i c B r i e f AfDB The improvement has been very significant in governorates that were less provided with pharmacies. 15 Despite this, in 2010, the governorate most provided with pharmacies (Tunis) had per capita 2.63 times more pharmacies than that least provided (Kasserine). It should be noted that the inequalities in the number of pharmacies nationwide are much lower than inequalities in private practice offices due to very strict regulations. 2.3 Summary The analysis shows a generally favourable trend that however hides internal distortions (Table 1 below). The availability of PHCs is declining. Level II, which is the reference for Level I, would not be very effective because it is poorly resourced. Therefore, there is an important carry over to Level III, which thus replaces Level II, thereby causing inefficiencies. Obviously, there is a need to develop a strategy that strengthens and revitalizes primary health care in the country and enhances Level II. Similarly, it has been shown that the trend of all dispersion indicators is favourable, with the exception of the indicator for physicians, whether in the public or private sector. Although the number of physicians per inhabitant witnessed a significant drop between 2002 and 2010 (28.5% for the public health sector and 21% for private practice), the gaps have widened between the better endowed and less endowed governorates, and the variation coefficients have increased. Hence, it is necessary to develop an appropriate strategy for addressing this challenge. It would be advisable to review the criteria for opening positions of public health physician at regional level and the institutional framework governing practices at the private level. Similarly, public-public partnerships (such as agreements between academic physicians and regional hospitals) or, failing that, public-private partnerships likely to make disadvantaged areas more attractive, could be considered for medical specialists. The availability of private medical practitioners is characterized by high levels of inequality; the ratio between the most endowed and the least endowed governorates is 14.3. They are followed by dental offices (ratio of 11.3) and hospital beds (10.7). The most fairly distributed resources are pharmacies and paramedical staff. Like in pharmacy, the private practice of dentistry and medicine should be better regulated. Lastly, the status of health care facilities in one governorate cannot be analysed by reference to a single determinant. As such, all components of the sector and complementarity between the various providers should be considered simultaneously. Consequently, it seems worthwhile to conduct an analysis of health care provision that integrates all the determinants of the provision so as to end up with relatively homogeneous groups. It would further be interesting to develop for each governorate a composite indicator of health care facilities so that a governorate could gauge its position in relation to other governorates as well as the progress it may achieve over time. 15 The operation of pharmacies is strictly subject to a numerus clausus, which is established on the basis of five areas according to delegations. It is regularly reviewed to adapt to the new realities of the profession and demographics. 17
AfDB E c o n o m i c B r i e f Table 1: Level and distribution of major health care provision indicators Indicator Statistics 2002 2010 2010/2002 Appraisal Disadvantaged governorates Average 4807 5051 +5% Unfavourable Tunis Inhabitants /PHC CV 0.94 0.89 Favourable Max/min 8.63 8.66 Moderate Ariana Ben Arous Hospital beds/ 1 000 inhabitants Inhabitants/ Physician (public sector) Inhabitants/ Paramedical staff Inhabitants/ Private practice (2004-2010) Inhabitants/ Dental office (2002-2009) Inhabitants/ Pharmacy Average 1.7 1.85 +8.8% Favourable Ben Arous CV 0.49 0.41 Favourable Ariana Max/min 47.4 10.7 High Sidi Bouzid Average 2196 1569-28.5% Favourable Kasserine CV 0.32 0.35 Unfavourable Medenine Max/min 5.27 6.85 Moderate Sidi Bouzid Average 341 308-8.7% Favourable Ariana CV 0.44 0.3 Favourable Ben Arous Max/min 6.68 4.8 Low Sidi Bouzid Average 2128 1681-21% Favourable Siliana CV 0.5 0.6 Unfavourable Kasserine Max/min 11.6 14.3 High Sidi Bouzid Average 8847 5774-34.7% Favourable Tozeur CV 0.66 0.58 Favourable Kasserine Max/min 24 11.3 High Tataouine Average 6756 5604-17% Favourable Tozeur CV 0.39 0.27 Favourable Kasserine Max/min 4.4 2.6 Low Tataouine 3- Health care facilities in 2010: cluster analysis 3.1 Indicators To analyse the distribution of health care facilities between the 24 governorates in Tunisia, we will refer to a broad set of indicators that characterize such facilities. These are indicators relating to health infrastructure, human resources in public and private health facilities, and equipment. These indicators are drawn from the Tunisia 2010 Health Map published by the Ministry of Health and/or from the Tunisia Statistical Yearbook published by the INS. 3-1-1. Health infrastructure indicators These are indicators on: 1. Average distance to get to a regional hospital 2. Average distance to get to a general hospital 3. Inhabitants by PHC 4. Proportion of PHCs providing medical consultation 6 days of 6 5. Inhabitants per PHC full-time equivalent (FTE) 6. Inhabitants per primary care physician 7. Frontline bio-medical laboratory unit per 100 000 inhabitants 8. Frontline radiology unit per 100 000 inhabitants 9. Frontline dental chairs per 100 000 inhabitants 10. Inhabitants per day pharmacy 11. Inhabitants per night pharmacy 12. Private bio-medical laboratories per 100 000 inhabitants 13. Haemodialysis machines per 100 000 inhabitants (public and private) 18
E c o n o m i c B r i e f AfDB 3-1-2. Common equipment indicators 16 1. Hospital bed equipment rate (public and private) 2. Public hospital bed equipment rate 3. Private bed equipment rate (in clinics) 4. General surgery bed equipment rate 5. Gynaecology and obstetrics bed equipment rate 6. Paediatric bed equipment rate 7. Ophthalmology bed equipment rate 8. ENT bed equipment rate 9. Orthopaedic bed equipment rate 10. Cardiology bed equipment rate 11. Anaesthesiology bed equipment rate 12. Psychiatric bed equipment rate 3-1-3. Human resource indicators 1. Density of physicians (per 100 000 inhabitants) 2. Density of general practitioners (per 100 000 inhabitants) 3. Density of general practitioners in the public sector (per 100 000 inhabitants) 4. Density of general practitioners in the private sector (per 100 000 inhabitants) 5. Density of specialists (per 100 000 inhabitants) 6. Density of public sector specialists (per 100 000 inhabitants) 7. Density of private sector specialists (per 100 000 inhabitants) 8. Medical density per specialty (all physicians) 9. Density of pharmacists (per 100 000 inhabitants) 10. Density of dentists (per 100 000 inhabitants) 11. Density of nurses, nursing aides and senior technicians (per 100 000 inhabitants). 3-2 Heath Infrastructure Distribution Based on health infrastructure indicators in the 24 governorates observed in 2010 (Tables 15, 16, 17 and 18 in Annex 1), a dynamic clusters analysis 17 was conducted in four clusters (Map 3). 3-2-1- The first cluster (Table 13 in Annex 1) includes the Tunis, Ariana, Ben Arous, Manouba, Sousse, Monastir, Sfax and Médenine governorates. This cluster covers 626 PHCs, 21 district hospitals (341 beds), 13 regional hospitals (1 315 beds) 22 university hospitals (92% of the overall with 9 032 beds) and 4 590 private medical practices out of 6 273 (general practitioners and specialists). It is characterized by good positioning in terms of access to hospitals and backed by sustained availability of alternative types of infrastructure and also by poor positioning in terms of the number of inhabitants per Primary Health Centre (PHC). Hence, we have: l l l l l l l The best location in terms of access to regional hospitals and general hospitals (except Médenine due to its low density); The largest proportion of PHC providing medical consultation 6 days a week; The highest number of inhabitants per PHC on average; The highest number of inhabitants per PHC in full time equivalent; A moderate number of inhabitants per primary care physician; The lowest number of primary biomedical laboratory units for 100 000 inhabitants; The lowest number of primary radiology units for 100 000 inhabitants; l The lowest number of primary health care dental chairs for 100 000 inhabitants; l l The highest number of inhabitants per day-time pharmacy; Moderate number of inhabitants per overnight pharmacy; l The highest number of medical analysis laboratories for 100 000 inhabitants; l The highest number of haemodialysis machines for 100 000 inhabitants. Besides Médenine, this cluster is composed of university hospital cities. 18 It can be observed that there is a predominance of tertiary care, including emergency services that are particularly in demand and are overriding the PHC. 19 The question then is not so much whether or not to increase the density of PHCs but also to understand the motives underlying the people's preference for emergency room services to PHCs. Should it be blamed on the overly broad primary health network or the discrepancy between its temporal accessibility and the quality of care it provides? 20 These two aspects certainly deserve special consideration and it is appropriate to both standardize the availability of infrastructure and upgrade the operation of all structures at all levels. The certification of hospitals would be entirely appropriate. In this context, an agency for the accreditation and 16 We did not consider indicators for equipment that has a regional scope and serves several governorates, such as the equipment rate for public beds with university status by major region (north, centre and south); the MRI equipment rate by major region; the scanner equipment rate and the equipment rate for other heavy equipment. 17 The method for classifying dynamic clusters is essentially based on the distribution of a population into homogeneous groups (classes or clusters) using the core concept associated with each class. It may involve, as in our study, for example, discovering the main governorates with the closest health facilities. 19
AfDB E c o n o m i c B r i e f certification of health services was established by Decree No. 2012-1709 of 06/09/2012. 3-2-2- The second cluster (Table 14 in Annex 1) includes the Bizerte, Nabeul and Kebili governorates. This cluster is characterized by a very average positioning with respect to all criteria relating to public infrastructure (hospitals, PHC...) or private facilities (pharmacies, dental offices, laboratories, etc.). It includes 273 PHC, 9 CH and 6 RH (2 135 beds i.e. 11% of the overall nominal capacity), 709 private practices, 286 pharmacies, 221 dental offices... 3-2-3- The third cluster (Table 15 in Annex 1) includes the Béja, Gabès, Gafsa, Le Kef, Mahdia, Siliana, Tataouine, Tozeur and Zaghouan governorates. These nine governorates have a rather low hospital access rate (due to low population density) and limited availability of various types of infrastructure, especially those that are private-owned. This shortcoming is partly offset by proper positioning in terms of the number of inhabitants per PHC and per primary care physician. Yet these governorates have 46 district hospitals out of a total of 109, 10 regional hospitals (about 33 throughout Tunisia) and two university hospitals (in Mahdia and Zaghouan), with a nominal capacity of 4 133 beds (21 % of national capacity). However, while a hospital should have at least one surgical ward and an intensive care unit, with the technical equipment needed to support different types of emergencies, district hospitals currently perform only a single real hospital function: carrying out eutocic deliveries. Regional hospitals that are supposed to provide Level II care, lack specialists (the cluster is very poorly staffed with specialist physicians) and equipment. Furthermore, quality certification will help bring these structures up to standard. Lastly, it would be appropriate to develop specific incentives to induce private stakeholders to settle in these governorates. 3-2-4- The fourth cluster (Table 16 in Annex 1) includes the Jendouba, Kairouan, Kasserine and Sidi Bouzid governorates. This cluster is characterized by even low rate of access to hospitals and available basic infrastructure (with 27 CH, 470 PHC and only 4 RH). Furthermore, the most reduced availability of private facilities can be observed (350 private practices). The shortfall of private health services is probably due to the low standard of living in these governorates and the lack of effective demand for health services. Hence, this fourth cluster comprises all priority governorates in terms of infrastructure wherein an intervention to enhance public health coverage would allow coverage similar to the rest of the country, and seems to be a necessary step to boost private coverage through the ripple effect. In this regard, it would be wise to develop specific incentives to induce private stakeholders to settle in these governorates. The table below summarizes the specificities of each cluster with respect to health infrastructure. 18 Tunis, Sousse, Monastir and Sfax. 19 In a study on the reasons for recourse to the emergency services of major hospitals in Greater Tunis (Ben Gobrane et al., 2012), the major reasons given by patients are quick and easy access to emergency services, the availability of equipment as compared to PHCs and, for the populations, inappropriate working hours of primary care facilities that work only in the morning. Hence, recourse to emergency services is partly due to the shortcomings of primary care medicine. 20 In most of these structures, consultations are carried out only in the morning. In rural areas, the length of consultations is notoriously reduced given the number of consultations conducted. In urban areas, opening hours do not match the time users are available for consultation. The result is threefold: either unwarranted recourse to hospital emergency services at different levels, or delay in recourse or forced and costly recourse to private primary care facilities. 20