Suche - Dental Aid Project

https://www.paho.org/salud-en-las-americas-2017/?page_id=135

https://www.who.int/bulletin/volumes/89/6/10-084327/en/

Methods
Data source

Data were obtained from drug price and availability surveys conducted using a standard, validated methodology developed by WHO and Health Action International (HAI).26–28 In the survey, the availability of 50 medicines was investigated through visits to public and private sector facilities. Data were collected on standard medicines that enable international comparisons and on medicines selected by each country for their importance nationally (e.g. drugs for high-burden diseases). Availability was determined for: (i) the originator brand first authorized worldwide for marketing (normally as a patented product) on the basis of the documentation of its efficacy, safety and quality, according to requirements at the time of authorization; and (ii) generic equivalents intended to be interchangeable with the originator brand product. Availability is reported as the percentage of facilities where a product was found on the day of data collection. The difference or gap in availability was calculated by subtracting the availability of medicines for chronic conditions from the availability of medicines for acute conditions.
Survey inclusion

All surveys conducted following the WHO/HAI method and included in the HAI database29 on 24 September 2009 were considered for inclusion, with the exception of nine pilot surveys that measured availability using different methods. In countries where repeat surveys were conducted, the most recent data set was used. In countries where multiple surveys were conducted at the state/provincial level, results were averaged without weighting. In total 50 surveys conducted in 40 countries between 2003 and 2008 were included in the analysis, yielding a sample of 2779 medicine outlets (Table 1).

Table 1. Surveys included in secondary analysis of data in study comparing the availability of medicines for chronic and acute conditions in 40 developing countries
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Medicine selection

Any medicine covered in at least one survey was considered for inclusion and was classified as being for either acute or chronic treatment according to its primary indication for use. In accordance with methods published previously,11 the 15 medicines most frequently covered in WHO/HAI surveys for acute and chronic conditions were included in the analysis to maximize the comparability of data across countries. Such medicines are effective based on the evidence, are used to treat high-burden conditions and are widely used internationally.26,27
Data analysis

The per cent availability of each medicine was extracted for both originator brand and generic products in both the public and private sectors. When alternate strengths of the same medicine were included in a survey, the availability of each of the two strengths was combined on a facility-by-facility basis to determine the overall availability of the medicine. Alternate strengths were only combined when used for the same indication; adult and paediatric dosage forms were kept separate.

Availability was analysed for: (i) the originator brand, (ii) the generic equivalent and (iii) any product (brand or generic). For the last category, the availability of originator brands and generics was combined on a facility-by-facility basis to determine the overall availability of each medicine.

The mean availability of each basket of medicines (for acute and chronic conditions) was calculated and, as data were normally distributed, the unpaired t-test was used to test the difference in mean availability between baskets. As availability was measured in the same facilities in each country, confounding factors such as facility type and location were eliminated. To investigate whether the availability of medicines for chronic conditions differed by indication, the mean availability of each therapeutic class represented in this medicines basket was calculated and compared with the mean availability of the 15 medicines in the acute conditions basket.

To examine potential differences in medicine availability by country income status, data were analysed by World Bank country income groups effective from 1 July 2009: low-income countries, lower-middle-income countries, upper-middle-income countries and high-income countries.30 Results were also aggregated by WHO Region: African (AFR), Americas (AMR), European (EUR), Eastern Mediterranean (EMR), South-East Asia (SEAR) and Western Pacific (WPR). Due to the small number of countries in some categories, results are descriptive only. To investigate any relationship between per cent availability of acute and chronic medicine baskets and level of income disparity, availability was analysed as a function of country Gini index, which measures the extent to which income distribution among individuals and households within an economy deviates from being perfectly equal.31
Results

Table 2 shows the 30 medicines included in the analysis. In the basket of medicines used to treat acute conditions, the frequency with which individual medicines were included in WHO/HAI surveys ranged from 24% to 100%; in the basket of medicines for chronic conditions, it ranged from 72% to 100%. This is not an indication of medicine availability at individual facilities, but rather, of greater consistency in the selection of chronic disease medicines for inclusion in individual surveys. With the exception of the combination sulfadoxine plus pyrimethamine, medicines for the treatment of human immunodeficiency virus (HIV) infection and acquired immunodeficiency syndrome (AIDS), tuberculosis and malaria are notably absent. These treatments are usually provided through vertical programmes that address specific health problems and consequently are often excluded from WHO/HAI surveys.

Table 2. Medicines included in secondary analysis of data in study comparing the availability of medicines for chronic and acute conditions in 40 developing countries
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In the public sector, the mean availability of generic medicines was low for both baskets: 53.5% for medicines for acute conditions and 36.0% for medicines for chronic conditions, with medicines for acute conditions significantly more available (P = 0.001) (Table 3). Originator brands of medicines in both the acute and chronic condition baskets were rarely available in the public sector. When product types were combined to yield the availability of any given product (originator brand or generic) at each facility, the difference in availability between the two baskets (14.3%) remained statistically significant (P = 0.009).

Table 3. Mean availability of medicines used for acute and chronic conditions in 40 developing countries
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In the private sector, the mean availability of generics in each basket was higher than in the public sector (66.2% for generics for acute conditions and 54.7% for generics for chronic conditions), but it was still low. The availability of generic products differed significantly between the two baskets (11.5%; P = 0.007), but the availability of originator brands was the same (39.1%). The difference in the availability of any product type (originator or generic) was 5.6% (P = 0.070).

When the availability of medicines for chronic conditions was disaggregated by therapeutic classes, in both the public and the private sector antiulcerants and antidiabetics were the drugs most widely available for the chronic indications studied, with availability comparable to that of the basket of medicines for acute indications (Fig. 1). In fact, in the private sector the average availability of antiulcerants was higher than that of the 15 medicines for acute conditions. Antihypertensives and cardiovascular medicines had the next highest availability among the drugs for chronic indications, but their availability was 8.5% and 21.4% lower than that of medicines for acute conditions in the private and the public sectors, respectively. Antiasthmatics, antiepileptics and antidepressants had similarly low availability (28–30% and 40–45% in the public and private sectors, respectively) and showed the largest difference in availability with respect to the acute conditions basket. The availability of individual medicines in the countries studied can be obtained from the corresponding author upon request.
Fig. 1. Comparison of mean availability of individual medicines for chronic conditions, by therapeutic class, and of 15 medicines for acute conditions, in 40 developing countries
Fig. 1. Comparison of mean availability of individual medicines for chronic conditions, by therapeutic class, and of 15 medicines for acute conditions, in 40 developing countries
CVD, cardiovascular disease.a Availability is expressed as the percentage of facilities where a product was found on the day of data collection.

Mean differences in the per cent availability of the baskets of medicines for acute and chronic conditions in each country are shown by World Bank income group (Fig. 2) and WHO region (Fig. 3). Fig. 2 shows an inverse relationship between income level and the gap in availability between medicines for acute and chronic conditions, particularly in the public sector. In low- and lower-middle-income countries, the mean differences in availability were 33.9% and 12.9%, respectively, while in upper-middle-income countries the availability was nearly equal and in high-income countries medicines for chronic conditions had higher availability. In the private sector the availability gap was smaller than in the public sector in all country income groups. No relationship was found in the public or private sector between the gap in the availability of medicines for acute or chronic conditions and level of income disparity (R2 = 0.0283 and 0.0118, respectively) (data available from the corresponding author upon request).
Fig. 2. Mean difference in the availabilitya of medicines for acute and chronic conditions in 40 developing countries, by World Bank income groupb
Fig. 2. Mean difference in the availability^a of medicines for acute and chronic conditions in 40 developing countries, by World Bank income group^b
a Availability is expressed as the percentage of facilities where a product was found on the day of data collection.b World Bank income groups: HI, high-income; UMI, upper-middle-income; LMI, lower-middle-income; LI, low-income.
Fig. 3. Mean difference in the availabilitya of medicines for acute and chronic conditions in 40 developing countries, by World Health Organization regionb
Fig. 3. Mean difference in the availability^a of medicines for acute and chronic conditions in 40 developing countries, by World Health Organization region^b
a Availability is expressed as the percentage of facilities where a product was found on the day of data collection.b World Health Organization regions: AFR, Africa; AMR, Americas; EMR, Eastern Mediterranean; EUR, European; SEAR, South-East Asia; WPR, Western Pacific.

The African region showed a substantially larger average difference (nearly 40%) than other regions in the availability of medicines for acute and chronic conditions in the public sector (Fig. 3). In the South-East Asia Region, the Region of the Americas and the Eastern Mediterranean Region, medicines for acute conditions were 4% to 14% more available in the public sector, on average, than those for chronic conditions, while in the European Region and the Western Pacific Region medicines for chronic conditions were somewhat more available than those for acute conditions in the public sector. In the private sector, the African region again showed the largest difference in availability between medicines for acute and for chronic conditions (16.7%), but this difference was less pronounced than in the public sector. In the Region of the Americas, the European Region and the South-East Asia Region, medicines for acute conditions were more available than those for chronic conditions in the private sector, while in the Eastern Mediterranean Region two medicine baskets had comparable availability and in the Western Pacific Region medicines for chronic conditions were more available than those for acute conditions.
Discussion

The WHO has set a benchmark of 80% for medicine availability,33 against which the values found in this study were sub-optimal for both the acute and chronic condition medicine baskets, particularly in the public sector. Low public sector availability can result from factors such as inadequate funding, lack of incentives for maintaining stocks, inability to forecast needs accurately, inefficient purchasing/distribution systems or leakage of medicines for private resale.11 The low availability of medicines in the public sector is a general problem, and this study shows that medicines for chronic conditions are even less available than medicines for acute conditions, particularly in low- and lower-middle-income countries. This may be the result of government policies that do not provide for widespread access to medicines for chronic conditions through the public sector, or it could stem from technical and resource-related factors hindering the adaptation of health systems to the changing epidemiological profile of their populations.

The difference in availability between the two medicine categories was consistently smaller in the private sector than in the public sector (11.5% versus 17.5%). This suggests that the current demand for medicines for chronic conditions exceeds what the public sector is providing and that low demand resulting from low diagnostic rates or other factors does not account for the low availability observed in the public sector. However, the availability of generics in the private sector was still low and probably not enough to compensate for the lack of availability in the public sector. Further, in the private sector, medicines for chronic conditions usually cost substantially more than in the public sector and are often unaffordable.11,19–25,34 Chronic disease patients, who need lifelong treatment, may find these medicines even less affordable than other patients. In developing countries, catastrophic health spending (e.g. spending on drugs and health care in excess of 40% of the income remaining after meeting subsistence needs) is common.35 Health policies should therefore be designed to protect people from these expenditures by increasing financial risk protection through health insurance schemes that cover essential medicines for outpatients, including drugs for chronic conditions. The cost of medicines to both patients and health systems can also be reduced by promoting quality-assured, low-cost generic medicines through preferential registration procedures, financial incentives for prescribing and dispensing generics, generic substitution and measures to heighten trust among physicians, pharmacists and patients in the quality of generics.11

In both the public and private sectors, antiasthmatics, antiepileptics and antidepressants, and antihypertensives to a lesser extent, were the drivers of the gaps in the availability of drugs in the acute and chronic condition baskets (Fig. 1). However, as previously reported,19 in some therapeutic classes (e.g. antidiabetics and antihypertensives) substantial variation was observed in the availability of individual medicines. Results may also have been influenced by the treatment options included in each class. For example, the availability of antidiabetics may have been influenced by the exclusion of insulin, whose availability was low in a previous study.23 The reliability of our findings is supported by the fact that the therapeutic classes with the highest to lowest availability followed the same pattern in both the public and private sectors.

As the income level of a country decreases, the difference in availability between medicines for acute and chronic conditions increases, particularly in the public sector (Fig. 2). Priority should therefore be given to improving the availability of medicines for chronic conditions in low- and lower-middle-income countries, where the availability gaps are largest. According to a similar analysis by WHO region, the availability of the two treatment types differs most widely in countries in the African Region (Fig. 3). Since 25% of all deaths in Africa are caused by chronic conditions, current disease patterns do not explain the observed gap. Disease patterns vary by individual country, but the medicines in this study are used to treat very common chronic conditions and should be available in sufficient quantities in any health system.

This analysis improves upon a previous analysis of medicine availability based on data from WHO/HAI surveys11 in that alternate strengths of the same medicine were combined to account for country-level differences in medicine use. However, availability data only apply to the day of data collection and may not reflect average availability over time. Nevertheless, the data were collected in at least 20 facilities per country using a validated sampling frame28 and therefore provide a reasonable estimate of the overall situation. Further, the analysis is more concerned with the relative availability of medicines used for acute and chronic conditions than with their absolute availability. Another limitation is that the availability of individual medicines in the public sector may be influenced by whether or not they are on the national essential medicines list (a government-approved selective list used for procurement or reimbursement) and by the level(s) of care for which they are expected to be available.

The choice of medicines for the secondary analysis, which was restricted to the medicines included in WHO/HAI surveys, may also have limited the results. These surveys comprise both common medicine formulations that enable international comparisons and medicines of national importance, which are selected in accordance with disease burden, medicine usage patterns and recommendations in standard treatment guidelines. The selection process for survey medicines is described in detail elsewhere.26,27 However, country variations in medicine use may limit the comparability of results.

Prior to 2008, when all but two of the surveys were conducted, the WHO/HAI recommended a global list of 30 medicines for inclusion in all surveys, plus 20 medicines selected nationally.26 Among the medicines most frequently surveyed and as such included in the analysis, all 15 of the drugs used to treat chronic conditions were on the global list, versus only 9 (60%) of the drugs used to treat acute conditions. More local adaptations were therefore made for the latter than for the former, perhaps because treatment alternatives for chronic conditions were fewer and the use of these drugs consequently more consistent across countries. In developing the second edition of the WHO/HAI survey manual, Intercontinental Marketing Services Health (IMS Health) consumption data were used to analyse the medicines surveyed and those recommended for chronic conditions were found to be widely used worldwide.27 However, a further limitation is that the lack of a clear distinction between acute and chronic indications for some medicines that are used intermittently over long time periods (e.g. antimalarials) and for medicines used to treat acute episodes of chronic disease (e.g. diazepam). In addition, while all of the medicines studied are off patent, the date of patent expiry may have affected the availability of multisource generic products on the market. Certain products, such as omeprazole, losartan, ciprofloxacin and fluconazole, have been off patent for less than 10 years and the persistence of the originator brand product following patent expiry may have reduced the availability of generics of these products.

Despite these limitations, this study raises important concerns about access to treatment for the millions of people with chronic conditions who live in developing countries. Governments should prioritize the supply of medicines for chronic conditions through their public health systems to ensure that people have access to the treatment they need. Low availability in the public sector can be through improved procurement efficiency and supply chain management as well as adequate, equitable and sustainable financing. In practice this could mean implementing schemes to make medicines for chronic conditions available through the private sector at no cost or at subsidized prices, as is done in Jamaica and in Trinidad and Tobago36,37. International financing can also strongly affect public sector availability. In Kenya, for example, the availability of the antimalarial combination composed of artemether-lumefantrine increased from 4% to 91% the year following a grant from the Global Fund to Fight AIDS, Tuberculosis and Malaria.16 While this study addresses the supply-side barriers to access to treatment for chronic conditions, efforts to address demand-side issues are also required. Supply that remains on the shelf is of little use; conversely, stimulating demand makes no sense if there is no supply. The extent to which a low demand for medicines for chronic conditions affects their availability is outside the scope of this analysis and warrants further investigation. However, our analysis suggests that current demand outweighs supply in the public sector and that no efforts should be made to further increase demand unless an adequate and ongoing supply of medicines can be ensured.

Successes in scaling-up treatment for HIV infection can offer lessons in connection with other chronic conditions. For example, HIV/AIDS treatment programmes in sub-Saharan Africa have shown relatively high patient adherence (77%) to complex antiretroviral regimens.38 Ensuring sustained medicine availability is clearly an essential precondition to achieving high adherence rates. Success in the field of HIV/AIDS stems largely from global and national efforts in the areas of mobilization and advocacy, financing and engagement of civil society.39 Alongside current efforts in connection with communicable diseases, international agencies, governments and other stakeholders should work together to raise the profile of chronic diseases on health and development agendas and to advocate for a balanced approach that addresses both prevention and treatment.

To date, the control of chronic diseases in developing countries has received little international attention.3,40 The UN Summit on Non-communicable Diseases to be held in September 2011 is a positive step towards recognizing the importance of chronic diseases on the global health agenda. Our study shows that reorienting and strengthening health systems to enable a more effective and equitable response to chronic diseases should be a key priority, as recommended in the WHO Action Plan for the Global Strategy for the Prevention and Control of Chronic Diseases. Target 8.E of the Millennium Development Goals deals with access to affordable essential medicines in developing countries.10,12,16 To achieve this target, special efforts will be required to ensure universal and sustained availability of medicines for chronic conditions.
Conclusion

Although the disease burden from chronic conditions in developing countries is large, wide gaps exist in the availability of medicines for chronic conditions. This study shows that such medicines are less available than those for acute conditions, which have traditionally been the focus of health systems in these countries. To ensure equitable access to treatment for different types of diseases, greater national and international attention should be given to chronic disease control, including access to medicines.
Acknowledgements

The authors thank Dele Abegunde, Ala Alwan, Gauden Galea and Belinda Loring; all consultants and all country teams who undertook surveys of medicine prices and availability. They also appreciate the support of the WHO Regional Offices in conducting the surveys.
Funding:

The division of Pharmacoepidemiology and Pharmacotherapy where authors AKM-T and HGML are employed has received unrestricted funding for pharmacoepidemiological research from GlaxoSmithKline, the Top Institute Pharma (www.tipharma.nl, includes co-funding from universities, government and industry), the Dutch Medicines Evaluation Board and the Dutch Ministry of Health
Competing interests:

Methods
Study sample

We used data from the Service Provision Assessment, which is a census survey of health facilities conducted in Haiti in 2013 by the Demographic and Health Survey Program. The census included a facility assessment, a questionnaire for health-care providers, observations of sick child, antenatal care and family planning visits, and exit interviews with observed clients. We limited our analysis to the data collected on outpatient primary care facilities, i.e. dispensaries and health centres with or without beds.22

We also used WorldPop maps to obtain estimates of the 2015 population density of Haiti, at a resolution of 100 m2.23
Measuring primary care quality

We developed metrics of service delivery quality following the Primary Health Care Performance Initiative’s framework. Several modifications were required to adapt the framework for health facility assessment (Fig. 1). We excluded the domain “population health management”, because of a lack of relevant facility-related data. For clarity, we also altered the labels for two of the domains, using “effective service delivery” for the availability of effective services and “primary care functions” for high-quality primary health care.14
Fig. 1. Conceptual framework of quality in primary health care
Fig. 1. <b>Conceptual framework of quality in primary health care</b>
Source: Adapted from the Primary Health Care Performance Initiative’s framework,13 for use in Haiti.
Figure 1 - full screen

We reviewed the data available in the survey and selected 28 indicators that most appropriately matched each of the quality subdomains included in our analysis. For this selection, we were guided by the Primary Health Care Performance Initiative’s method note.13 Each indicator is a proportion or an index that ranges from 0 to 1. For example, the indicator “sick child did not first visit traditional healer” measures first-contact access to a facility as the proportion of sick children who came to the facility for care without first visiting a traditional healer. All selected indicator definitions are available from the corresponding author. Within the survey data, we were unable to find relevant indicators for two of the subdomains that we wished to investigate: geographical access and the organization of team-based care. As people need to be able to access health facilities to benefit from quality care, we used the WorldPop maps to determine geographical access to facilities.

For each primary care facility, we calculated a score for each of four service delivery domains: (i) accessible care; (ii) effective service delivery; (iii) management and organization; and (iv) primary care functions. Each of these scores, which could range from 0 to 1, was the mean of all the indicators under the domain. As we considered the four domains to be equally important elements of quality primary care, we took the mean of the four scores calculated for each facility as the overall measurement of the quality of the facility’s service delivery for primary care.

Although the census covered all but two of the health facilities in Haiti in 2013, two of the survey tools, i.e. clinical observations and patient interviews, were applied only in a selected subset of facilities. For each indicator included in our analysis, we used multiple imputation to generate five versions of a completed data set for all quality indicators. We based the imputation on observed covariates, e.g. management type and urban, and the non-missing indicators.

Finally, we assessed the distribution of indicators across facilities and sought valid groupings of better and worse quality. Given the lack of universally defined minimum quality thresholds and the rudimentary nature of many of the indicators included in our analysis, we divided the facility scores into three categories of quality. Scores of less than 0.50, 0.50–0.74 and at least 0.75 were considered indicative of poor, fair and good quality, respectively.
Covariates

We defined each 100 m2 block of population as an urban or rural population using the census’ urban or rural classification of the facility nearest to the centre of the block. As a sensitivity check, we also defined an urban population as one in which there were at least five people per 100 m2 block.
Analysis

We calculated descriptive statistics of the primary care facilities with non-response weights. We summarized mean values and uncertainty intervals for each indicator, domain and overall quality score for service delivery. As the data we analysed provided a census of the primary care facilities in Haiti in 2013, the uncertainty intervals that we calculated indicate the measurement error attributable to missing data.24 Using inverse distance-weighted interpolation, we mapped, across Haiti, the quality of the primary care available to a nearby population. In the resultant map, the colour of each 100 m2 block indicates whether the quality of the nearest primary care facility was poor, fair or good. We used the global Moran’s I statistic, which tests for the presence of spatial autocorrelation,25 to investigate whether facilities of good or poor quality, in terms of each of the four domains of interest, were clustered geographically. Moran’s I can range from −1 to 1. In our analyses, positive I values would indicate that primary care facilities of similar quality were clustered together. We defined proximity using an inverse-distance weight matrix.26 In keeping with prior research on physical access to care in Haiti,27 we calculated the percentages of the entire Haitian population, rural population and urban population living within 5 km of any facility and within the same distance of a facility with a good overall score. Finally, we mapped the areas that lay within 5 km of any facility and a facility with a good overall care score.

Multiple imputation was conducted in R 3.2 (R Core Team, Vienna, Austria). All other analyses were conducted in Stata version 14.0 (StataCorp, LP, College Station, United States of America). We used QGIS version 2.1228 to map the data.
Ethical approval

The Harvard University Human Research Protection Program categorized this secondary analysis of data as exempt from human subjects review.
Results

The survey obtained detailed data from 905 (99.8%) of the 907 health facilities in Haiti in 2013, 786 of which were primary care facilities and included in the analysis (Table 1). Most primary care facilities were classified as rural, although there was a high concentration of primary care facilities in and around Port-au-Prince. Fig. 2 summarizes the performance of the primary care facilities across the four domains of primary care service delivery. At the average facility, 86% and 94% of clients, respectively, stated that they did not find wait times or the costs of care to be a problem, even though about half of all primary care services required payment and over half of the primary care facilities had mean wait times in excess of one hour. Large gaps in quality were evident in the metrics for the availability of effective services. The indicators for provider motivation and safety were found to be especially low. Basic elements of clinical care were not universally followed. For example, at the average facility only 57% of the providers asked about maternal age at a first visit for antenatal care. Low quality scores for primary care functions were partially attributable to poor provider communication. Under management and organization, only 2% (18) of the primary care facilities had a system for gathering feedback from their clients and nearly three-quarters (577) did not have routine quality assurance processes. For their overall quality of service delivery, the primary care facilities in Haiti achieved a mean score of 0.59.

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