RESUMO
Background: In India, access to medicine in the public sector is significantlyaffected by the efficiency of the drug procurement system and allied processesand policies. This study was conducted in two socioeconomically different states:Bihar and Tamil Nadu. Both have a pooled procurement system for drugs butfollow different models. In Bihar, the volumes of medicines required are pooledat the state level and rate contracted (an open tender process invites biddersto quote for the lowest rate for the list of medicines), while actual invoicing andpayment are done at district level. In Tamil Nadu, medicine quantities are alsopooled at state level but payments are also processed at state level upon receiptof laboratory quality-assurance reports on the medicines.Methods: In this cross-sectional survey, a range of financial and non-financial datarelated to procurement and distribution of medicine, such as budget documents,annual reports, tender documents, details of orders issued, passbook details andpolicy and guidelines for procurement were analysed. In addition, a so-called ABCanalysis of the procurement data was done to to identify high-value medicines.Results: It was observed that Tamil Nadu had suppliers for 100% of the drugson their procurement list at the end of the procurement processes in 2006, 2007and 2008, whereas Bihar’s procurement agency was only able to get suppliersfor 56%, 59% and 38% of drugs during the same period. Further, it was observedthat Bihar’s system was fuelling irrational procurement; for example, fluconazole(antifungal) alone was consuming 23.4% of the state’s drug budget and was beingprocured by around 34% of the districts during 2008–2009. Also, the ratios ofprocurement prices for Bihar compared with Tamil Nadu were in the range of 1.01to 22.50. For 50% of the analysed drugs, the price ratio was more than 2, that is,Bihar’s procurement system was procuring the same medicines at more than twicethe prices paid by Tamil Nadu.Conclusion: Centralized, automated pooled procurement models like that ofTamil Nadu are key to achieving the best procurement prices and highest possibleaccess to medicines
Assuntos
Acessibilidade aos Serviços de Saúde , Preço de MedicamentoRESUMO
Background: In India, household air pollution (HAP) is one of the leading riskfactors contributing to the national burden of disease. Estimates indicate that 7.6%of all deaths in children aged under 5 years in the country can be attributed to HAP.This analysis attempts to establish the association between HAP and neonatalmortality rate (NMR).Methods: Secondary data from the Annual Health Survey, conducted in 284districts of nine large states covering 1 404 337 live births, were analysed. Thesurvey was carried out from July 2010 to March 2011 (reference period: January2007 to December 2009). The primary outcome was NMR. The key exposurewas the use of firewood/crop residues/cow dung as fuel. The covariates were:sociodemographic factors (place of residence, literacy status of mothers,proportion of women aged less than 18 years who were married, wealth index);health-system factors (three or more antenatal care visits made during pregnancy;institutional deliveries; proportion of neonates with a stay in the institution forless than 24 h; percentage of neonates who received a check-up within 24 h ofbirth); and behavioural factors (initiation of breast feeding within 1 h). Descriptiveanalysis, with district as the unit of analysis, was performed for rural and urbanareas. Bivariate and multivariable linear regression analysis was carried out toinvestigate the association between HAP and NMR.Results: The mean rural NMR was 42.4/1000 live births (standard deviation [SD]= 11.4/1000) and urban NMR was 33.1/1000 live births (SD=12.6/1000). Theproportion of households with HAP was 92.2% in rural areas, compared to 40.8%in urban areas, and the difference was statistically significant (P < 0.001). HAPwas found to be strongly associated with NMR after adjustment (β = 0.22; 95%confidence interval [CI] = 0.09 to 0.35) for urban and rural areas combined. Forrural areas separately, the association was significant (β = 0.30; 95% CI = 0.13 to0.45) after adjustment. In univariable analysis, the analysis showed a significantassociation in urban areas (β = 0.23; 95% CI = 0.12 to 2.34) but failed to demonstratean association in multivariable analysis (β = 0.001; 95% CI = –0.15 to 0.15).Conclusion: Secondary data from district level indicate that HAP is associatedwith NMR in rural areas, but not in urban areas in India.
