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1.
Artigo em Inglês | IMSEAR | ID: sea-178853

RESUMO

Background & objectives: The evidence-base of the impact of community-based health insurance (CBHI) on access to healthcare and financial protection in India is weak. We investigated the impact of CBHI in rural Uttar Pradesh and Bihar States of India on insured households’ self-medication and financial position. Methods: Data originated from (i) household surveys, and (ii) the Management Information System of each CBHI. Study design was “staggered implementation” cluster randomized controlled trial with enrollment of one-third of the treatment group in each of the years 2011, 2012 and 2013. Around 40-50 per cent of the households that were offered to enroll joined. The benefits-packages covered outpatient care in all three locations and in-patient care in two locations. To overcome self-selection enrollment bias, we constructed comparable control and treatment groups using Kernel Propensity Score Matching (K-PSM). To quantify impact, both difference-in-difference (DiD), and conditional-DiD (combined K-PSM with DiD) were used to assess robustness of results. Results: Post-intervention (2013), self-medication was less practiced by insured HHs. Fewer insured households than uninsured households reported borrowing to finance care for non-hospitalization events. Being insured for two years also improved the HH’s location along the income distribution, namely insured HHs were more likely to experience income quintile-upgrade in one location, and less likely to experience a quintile-downgrade in two locations. Interpretation & conclusions: The realized benefits of insurance included better access to healthcare, reduced financial risks and improved economic mobility, suggesting that in our context health insurance creates welfare gains. These findings have implications for theoretical, ethical, policy and practice considerations.

2.
Artigo em Inglês | IMSEAR | ID: sea-170287

RESUMO

Background & objectives: Despite remarkable progress in airborne, vector-borne and waterborne diseases in India, the morbidity associated with these diseases is still high. Many of these diseases are controllable through awareness and preventive practice. This study was an attempt to evaluate the effectiveness of a preventive care awareness campaign in enhancing knowledge related with airborne, vector-borne and waterborne diseases, carried out in 2011 in three rural communities in India (Pratapgarh and Kanpur-Dehat in Uttar Pradesh and Vaishali in Bihar). Methods: Data for this analysis were collected from two surveys, one done before the campaign and the other after it, each of 300 randomly selected households drawn from a larger sample of Self-Help Groups (SHGs) members invited to join community-based health insurance (CBHI) schemes. Results: The results showed a significant increase both in awareness (34%, p<0.001) and in preventive practices (48%, P=0.001), suggesting that the awareness campaign was effective. However, average practice scores (0.31) were substantially lower than average awareness scores (0.47), even in post-campaign. Awareness and preventive practices were less prevalent in vector-borne diseases than in airborne and waterborne diseases. Education was positively associated with both awareness and practice scores. The awareness scores were positive and significant determinants of the practice scores, both in the pre- and in the post-campaign results. Affiliation to CBHI had significant positive influence on awareness and on practice scores in the post-campaign period. Interpretation & conclusions: The results suggest that well-crafted health educational campaigns can be effective in raising awareness and promoting health-enhancing practices in resource-poor settings. It also confirms that CBHI can serve as a platform to enhance awareness to risks of exposure to airborne, vector-borne and waterborne diseases, and encourage preventive practices.

3.
Artigo em Inglês | IMSEAR | ID: sea-137372

RESUMO

Background & objectives: In 2008, India’s Labour Ministry launched a hospital insurance scheme called Rashtriya Swasthya Bima Yojana (RSBY) covering ‘Below Poverty Line’ (BPL) households. RSBY is implemented through insurance companies; premiums are subsidized by Union and States governments (75 : 25%). We examined RSBY’s enrolment of BPL, costs vs. budgets and policy ramifications. Methods: Numbers of BPL are obtained by following criteria of two committees appointed for this task. District-specific premiums are weighted to obtain national average premiums. Using the BPL estimates and national premiums, we calculated overall expected costs of full roll-out of the RSBY per annum, and compared it to Union government budget allocations. Results: By March 31, 2011, RSBY enrolled about 27.8 per cent of the number of BPL households following the Tendulkar Committee estimates (37.6% following the Lakdawala Committee criteria). The average national weighted premium was ` 530 per household per year in 2011. The expected cost of premium to the union government of enrolling the entire BPL population in financial year (FY) 2010-11 would be ` 33.5 billion using Tendulkar count of BPL (or ` 24.6 billion following Lakdawala count), representing about 0.3 per cent (or 0.2%, respectively) of the total union budget. The RSBY budget allocation for FY 2010-11 was only about 0.037 per cent of the total union budget, sufficient to pay premiums of only 34 per cent of the BPL households enrolled by March 31, 2011. Interpretation & conclusions: RSBY could be the platform for universal health insurance when (i) the budget allocation will match the required funds for maintenance and expansion of the scheme; (ii) the scheme would ensure that beneficiaries’ rights are legally anchored; and (iii) RSBY would attract large numbers of premiumpaying (non-BPL) households.


Assuntos
Administração Financeira/economia , Política de Saúde/economia , Índia , Seguro Saúde/economia , Pobreza/economia , Saúde Pública
4.
Artigo em Inglês | IMSEAR | ID: sea-136318

RESUMO

Background & objectives: Against the backdrop of insufficient public supply of primary care and reports of informal providers, the present study sought to collect descriptive evidence on 1st contact curative health care seeking choices among rural communities in two States of India - Andhra Pradesh (AP) and Orissa. Methods: The cross-sectional study design combined a Household Survey (1,810 households in AP; 5,342 in Orissa), 48 Focus Group Discussions (19 in AP; 29 in Orissa), and 61 Key Informant Interviews with healthcare providers (22 in AP; 39 in Orissa). Results: In AP, 69.5 per cent of respondents accessed non-degree allopathic practitioners (NDAPs) practicing in or near their village; in Orissa, 40.2 per cent chose first curative contact with NDAPs and 36.2 per cent with traditional healers. In AP, all NDAPs were private practitioners, in Orissa some pharmacists and nurses employed in health facilities, also practiced privately. Respondents explained their choice by proximity and providers’ readiness to make house-calls when needed. Less than a quarter of respondents chose qualified doctors as their first point of call: mostly private practitioners in AP, and public practitioners in Orissa. Amongst those who chose a qualified practitioner, the most frequent reason was doctors’ quality rather than proximity. Interpretation & conclusions: The results of this study show that most rural persons seek first level of curative healthcare close to home, and pay for a composite convenient service of consulting-cum-dispensing of medicines. NDAPs fill a huge demand for primary curative care which the public system does not satisfy, and are the de facto first level access in most cases.


Assuntos
Coleta de Dados/métodos , Atenção à Saúde , Características da Família , Instalações de Saúde , Pessoal de Saúde , Necessidades e Demandas de Serviços de Saúde/estatística & dados numéricos , Humanos , Índia , Médicos , Atenção Primária à Saúde , População Rural
5.
Artigo em Inglês | IMSEAR | ID: sea-19155

RESUMO

BACKGROUND & OBJECTIVE: In India, health services are funded largely through out-of-pocket spendings (OOPS). We carried out this study to collect data on the cost of an illness episode and parameters affecting cost in five locations in India. METHODS: The data were obtained through a household survey carried out in 2005 in five locations among resource-poor persons in rural India. The analysis was based on self-reported illness episodes and their costs. The study was based on 3,531 households (representing 17,323 persons) and 4,316 illness episodes. RESULTS: The median cost of one illness episode was INR 340. When costs were calculated as per cent of monthly income per person, the median value was 73 per cent of that monthly income, and could reach as much as 780 per cent among the 10 per cent most exposed households. The estimated median per-capita cost of illness was 6 per cent of annual per-capita income. The ratio of direct costs to indirect costs was 67:30. The cost of illness was lower among females in all age groups, due to lower indirect costs. 61 per cent of total illnesses, costing 37.4 per cent of total OOPS, were due to acute illnesses; chronic diseases represented 17.7 per cent of illnesses but 32 per cent of costs. Our study showed that hospitalizations were the single most costly component on average, yet accounted for only 11 per cent of total on an aggregated basis, compared to drugs that accounted for 49 per cent of total aggregated costs. Locations differed from each other in the absolute cost of care, in distribution of items composing the total cost of care, and in supply. INTERPRETATION & CONCLUSION: Interventions to reduce the cost of illness should be context-specific, as there is no "one-size-fits-all" model to establish the cost of healthcare for the entire sub-continent. Aggregated expenses, rather than only hospitalizations, can cause catastrophic consequences of illness.


Assuntos
Adolescente , Adulto , Criança , Pré-Escolar , Efeitos Psicossociais da Doença , Doença/economia , Feminino , Gastos em Saúde/estatística & dados numéricos , Humanos , Renda/estatística & dados numéricos , Índia , Masculino , Pessoa de Meia-Idade , Áreas de Pobreza , População Rural/estatística & dados numéricos
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