Supply of human resources for rehabilitation
Our investigation revealed wide cross-national disparities in the supply of allied health professionals associated to rehabilitation (except medical practitioners). Lower income countries tend to have the lowest densities: less than 0.5 workers per 10,000 inhabitants in many countries of sub-Saharan Africa (Burundi, Cameroon, Central African Republic, Chad, Congo, Gabon, Guinea, Niger, Burkina Faso, Cote d'Ivoire, Gambia, Senegal, Tanzania, Madagascar, Mali, Ghana, Uganda) but also in several across Asia (Bangladesh, Nepal, Pakistan, Myanmar, India) and the Eastern Mediterranean (Iran, Yemen). Many high income countries - including Finland, Japan, the United States, the United Kingdom and Canada - have workforce densities several times higher (Figure 1) [19]. This finding is not surprising: large differences across countries in overall HRH density and critical shortages of highly skilled professionals in low-income countries have been well documented internationally [15].
It is important to note that HRH data disaggregated for allied health occupations associated to rehabilitation were found for only 38% of WHO's 193 Member States. In the Americas, information was even scarcer: only 7 (20%) of the countries in the region had relevant data (Bolivia, Brazil, Canada, Costa Rica, Panama, Paraguay and the United States). Data coverage was higher in the African region, with 32 (70%) of 46 countries reporting statistics on rehabilitation personnel. This does not necessarily mean no data at all were available in other countries, but that data were not being collated and publicly disseminated through national government health or statistical channels and captured in the international database. Coverage for the African region may have been relatively high due to the results of a special data collection exercise conducted by WHO among health ministries and other partners to feed the empirical analysis of the World health report 2006 [25]. Coverage was surprisingly low for high income countries, but is expected to increase in coming years following expansion of a joint data collection exercise by the WHO European Regional Office and the Organization for Economic Cooperation and Development on health workforce statistics including more non-medical occupations [26].
Among countries with available data, differences were found in the number of occupations related to rehabilitation for which data were disseminated. South Africa had the largest number of categories at 16, counting those subject to national regulation and reported by the Health Professions Council of South Africa: medical orthotists and prosthetists, occupational therapists, occupational therapy technicians, orthopaedic footwear technicians, physiotherapists, speech therapists and others (results not shown). Elsewhere, in Bolivia and Costa Rica two types of allied rehabilitative personnel ("physiotherapists and related associate professionals" and "speech therapists") could be distinguished according to the harmonized occupational classification applied to the public use microdata release of the national population census of 2001 and of 2000, respectively. Likewise, only physiotherapists and speech pathologists were retained from the Australia 2001 census. In the United States, five types of therapists (occupational, physical, respiratory, speech and "other") were captured with the occupation variable of the internationally released Current Population Survey microdata file. For over half (44 or 60%) of the countries with available data, only information on numbers of physiotherapists (including sometimes related professions as per the applied occupational classification) was collected - e.g. for Benin, Cameroon, Egypt, Kenya, Iraq, Myanmar, Nigeria, Oman and Sri Lanka, among others.
Because the Global Atlas had very limited data on medical practice areas, we conducted further reviews of government publications to gather relevant information. Data from countries with published statistics on the distribution of the medical workforce teasing out specialists in physical and rehabilitation medicine are presented in Figure 2 [27–32]. There is no global standard or norm for the minimum density of rehabilitation specialists or for their ratio to other categories of personnel [6], and this is reflected in the observed differences across countries. While in general the percent of the medical workforce specializing in rehabilitation medicine is low, less than 3% of all physicians, relatively large differences were found among the few countries with available data: the proportion was sixty times greater in Portugal than in Sudan, for example. This may be a reflection, in part, of the overall medical workforce distribution among generalist versus specialist practitioners, which is also subject to wide cross-national differences.
Given the variability in the nature of the underlying national information sources, comparability of the data remains uncertain, even under the application of a common occupational classification. Comparability may be hampered when it is not possible to ascertain whether the source of data covers health workers in all sectors (public facilities, private facilities, community-based service delivery, academic training, research, etc.) and types of activity (paid employment, self-employed, unemployed, retired...) [21]. For instance, occupation data from a population census usually cover individuals active in the national labour force over a given time period, as classified according to the nature of their main work activity, regardless of sector. Data from health professional regulatory bodies generally include individuals who have met certain qualifications and have registered with the appropriate body, regardless of current work activity or physical location in the country. Data from ministry of health administrative records oftentimes only cover public sector employees or posts.
An attempt was made to triangulate data from two different sources to better understand the potential differences in reporting. We compared data for physiotherapists, the profession with the largest number of data points, according to findings from official sources collated in the WHO's Global Atlas against those obtained from national professional associations. The latter are based on voluntary memberships, and so may either underestimate or overestimate actual supply of physiotherapists in a given country. For example, in Finland, both licensed physiotherapists and physiotherapy students may apply to become members of the Finnish Association of Physiotherapists [33], whereas official HRH statistics count all persons registered with the National Authority for Medicolegal Affairs [34] regardless of current practice. In Costa Rica, official data from the census refer to the main type of work in the week preceding enumeration [35] and may include professions performing similar types of rehabilitation work but with different professional titles, such as kinesiologists or ergotherapists, in addition to physiotherapists [36].
While our analysis did not enable us to quantify a "true" value for physiotherapists density, we did find relatively low variability (R
2= 0.74) across the two information sources among the sub-set of countries with comparable data, with densities reported from professional associations tending to be less than official statistics, especially at higher density levels (Figure 3).
Supply-need relationship
Baseline findings suggest that 92% of the burden of disease in the world (measured in terms of attributable years of life lost, or YLL) is related to causes that require assistance of health professionals associated to rehabilitation (e.g. physiatrists, physical therapists, audiologists, occupational therapists, orthotists, prosthetists, speech-language pathologists and others). A plot of supply of selected categories of health professionals against selected causes of YLL shows a strong and negative relationship, suggesting that countries with the highest burden of disability-related health conditions simultaneously tend to be those with the lowest supply of health workers skilled in rehabilitation services (Figure 4).
Disentangling the analysis by geographical region, a similar pattern emerges among low- and middle-incomes countries (Figure 5). Within regions, countries with higher rehabilitation needs tend to have lower numbers of skilled health workers. At the same time, the fit of the relationship varies across regions: a closer supply-need predictive link in the region of the Americas (R
2= 0.73), less obvious in the South-East Asian/Western Pacific regions (R
2= 0.26).
The picture is more ambiguous among the grouping of high and upper-middle income countries, where there is a lack of a clear supply-need relationship (Figure 6). This grouping includes a heterogeneous collection of countries across the Americas, European and Western Pacific regions, characterized by relatively higher overall levels of HRH supply but varying health system organizations, workforce mixes and disease burdens, especially with regard to the transitional Eastern European countries. However, not counting the latter from the analysis does not necessarily result in a clearer view: no strong monomial relationship is observed among the remaining high income countries with developed market economies, even when excluding the outlier point for Finland (results not shown).