Krishna D. Rao

Human resources for health in India

India has a severe shortage of human resources for health. It has a shortage of qualified health workers and the workforce is concentrated in urban areas. Bringing qualified health workers to rural, remote, and underserved areas is very challenging. Many Indians, especially those living in rural areas, receive care from unqualified providers. The migration of qualified allopathic doctors and nurses is substantial and further strains the system. Nurses do not have much authority or say within the health system, and the resources to train them are still inadequate. Little attention is paid during medical education to the medical and public health needs of the population, and the rapid privatisation of medical and nursing education has implications for its quality and governance. Such issues are a result of underinvestment in and poor governance of the health sector--two issues that the government urgently needs to address. A comprehensive national policy for human resources is needed to achieve universal health care in India. The public sector will need to redesign appropriate packages of monetary and non-monetary incentives to encourage qualified health workers to work in rural and remote areas. Such a policy might also encourage task-shifting and mainstreaming doctors and practitioners who practice traditional Indian medicine (ayurveda, yoga and naturopathy, unani, and siddha) and homoeopathy to work in these areas while adopting other innovative ways of augmenting human resources for health. At the same time, additional investments will be needed to improve the relevance, quantity, and quality of nursing, medical, and public health education in the country.

Insured yet vulnerable: out-of-pocket payments and India's poor

Protecting households from high out-of-pocket (OOP) payments for health care is an important health system goal. High OOP payments can push households into poverty and make them vulnerable to catastrophic health expenditures. This study, based in India, aims to: (a) estimate OOP payments for health and related impoverishment across economic groups; (b) decompose OOP payments and relate the contribution of their components to impoverishment; and (c) examine how well recently introduced national insurance schemes meant for the poor are able to provide financial protection. The analysis of nationally representative data from India shows that 3.5% of the population fall below the poverty line and 5% households suffer catastrophic health expenditures. The poverty deepening impact of OOP payments was at a maximum in people below the poverty line in comparison with those above (Rs. 10.45 vs. Rs. 1.50, respectively). Medicines constitute the main share (72%) of total OOP payments. This share reaches 82% for outpatient care, compared with 42% for inpatient care. Removing OOP payments for inpatient care leads to a negligible fall in the poverty headcount ratio and poverty gap. However, if OOP payments for either medicines or outpatient care are removed then only 0.5% people fall into poverty due to spending on health. These findings suggest that insurance schemes which cover only hospital expenses, like those being rolled out nationally in India, will fail to adequately protect the poor against impoverishment due to spending on health. Further, issues related to identifying the poor and their targeting also constrain the schemes impact. A broader coverage of benefits, to include medicines and outpatient care for the poor and near poor (i.e. those just above the poverty line), is necessary to achieve significant protection from impoverishment.

A cross-sectional study of the microeconomic impact of cardiovascular disease hospitalization in four low- and middle-income countries.

Objective To estimate individual and household economic impact of cardiovascular disease (CVD) in selected low- and middle-income countries (LMIC). Background Empirical evidence on the microeconomic consequences of CVD in LMIC is scarce. Methods and Findings We surveyed 1,657 recently hospitalized CVD patients (66% male; mean age 55.8 years) from Argentina, China, India, and Tanzania to evaluate the microeconomic and functional/productivity impact of CVD hospitalization. Respondents were stratified into three income groups. Median out-of-pocket expenditures for CVD treatment over 15 month follow-up ranged from 354 international dollars (2007 INT

Guidance on priority setting in health care (GPS-Health): the inclusion of equity criteria not captured by cost-effectiveness analysis

, Tanzania, low-income) to INT

Client perceptions of the quality of primary care services in Afghanistan

2,917 (India, high-income). Catastrophic health spending (CHS) was present in >50% of respondents in China, India, and Tanzania. Distress financing (DF) and lost income were more common in low-income respondents. After adjustment, lack of health insurance was associated with CHS in Argentina (OR 4.73 [2.56, 8.76], India (OR 3.93 [2.23, 6.90], and Tanzania (OR 3.68 [1.86, 7.26] with a marginal association in China (OR 2.05 [0.82, 5.11]). These economic effects were accompanied by substantial decreases in individual functional health and productivity. Conclusions Individuals in selected LMIC bear significant financial burdens following CVD hospitalization, yet with substantial variation across and within countries. Lack of insurance may drive much of the financial stress of CVD in LMIC patients and their families.

So many, yet few: Human resources for health in India

This Guidance for Priority Setting in Health Care (GPS-Health), initiated by the World Health Organization, offers a comprehensive map of equity criteria that are relevant to health care priority setting and should be considered in addition to cost-effectiveness analysis. The guidance, in the form of a checklist, is especially targeted at decision makers who set priorities at national and sub-national levels, and those who interpret findings from cost-effectiveness analysis. It is also targeted at researchers conducting cost-effectiveness analysis to improve reporting of their results in the light of these other criteria.The guidance was develop through a series of expert consultation meetings and involved three steps: i) methods and normative concepts were identified through a systematic review; ii) the review findings were critically assessed in the expert consultation meetings which resulted in a draft checklist of normative criteria; iii) the checklist was validated though an extensive hearing process with input from a range of relevant stakeholders.The GPS-Health incorporates criteria related to the disease an intervention targets (severity of disease, capacity to benefit, and past health loss); characteristics of social groups an intervention targets (socioeconomic status, area of living, gender; race, ethnicity, religion and sexual orientation); and non-health consequences of an intervention (financial protection, economic productivity, and care for others).

Which doctor for primary health care? Quality of care and non-physician clinicians in India.

OBJECTIVE To identify factors associated with client perceptions of the quality of primary care services in Afghanistan. DESIGN Cross-sectional survey of outpatient health facilities, health workers, patients and caretakers. SETTING Primary health care facilities in every province of Afghanistan. Main outcome measure Numerical scale of client perceptions of service quality. RESULTS Clients report relatively high levels of perceived quality in Afghanistan. Most of the variation that is explained relates specifically to the patients interaction with the health worker and not to other health facility characteristics, such as cleanliness, infrastructure, service capacity and the presence of equipment or drugs. The strongest determinants of client-perceived quality identified are health worker thoroughness in taking patient histories, conducting physical examinations and communicating with patients. Being seen by a doctor and being from a household in the poorest quintile are also associated with higher perceived quality. For female patients, being seen by a female provider is associated with higher perceived quality, while for male patients time and money spent for travel to the health facility are negatively associated with perceived quality. CONCLUSIONS Clinical quality and client perceived quality appear to be mutually reinforcing, and efforts to improve health worker performance in taking histories, conducting exams and communicating with patients are likely to increase client perceived quality in this setting. Client perceptions of service quality assume additional importance in Afghanistan, where the perceived legitimacy of the government may depend partially on its ability to convince the population that it can deliver essential health services.

Embedding health policy and systems research into decision-making processes in low- and middle-income countries

BackgroundIn many developing countries, such as India, information on human resources in the health sector is incomplete and unreliable. This prevents effective workforce planning and management. This paper aims to address this deficit by producing a more complete picture of India’s health workforce.MethodsBoth the Census of India and nationally representative household surveys collect data on self-reported occupations. A representative sample drawn from the 2001 census was used to estimate key workforce indicators. Nationally representative household survey data and official estimates were used to compare and supplement census results.ResultsIndia faces a substantial overall deficit of health workers; the density of doctors, nurses and midwifes is a quarter of the 2.3/1000 population World Health Organization benchmark. Importantly, a substantial portion of the doctors (37%), particularly in rural areas (63%) appears to be unqualified. The workforce is composed of at least as many doctors as nurses making for an inefficient skill-mix. Women comprise only one-third of the workforce. Most workers are located in urban areas and in the private sector. States with poorer health and service use outcomes have a lower health worker density.ConclusionsAmong the important human resources challenges that India faces is increasing the presence of qualified health workers in underserved areas and a more efficient skill mix. An important first step is to ensure the availability of reliable and comprehensive workforce information through live workforce registers.

Progress towards universal health coverage in BRICS: translating economic growth into better health

The scarcity of rural physicians in India has resulted in non-physician clinicians (NPC) serving at primary health centers (PHC). This study examines the clinical competence of NPCs and physicians serving at PHCs to treat a range of medical conditions. The study is set in Chhattisgarh state, where physicians (medical officers) and NPCs: Rural Medical Assistants (RMA), and Indian system of medicine physicians (AYUSH Medical Officers) serve at PHCs. Where no clinician is available, Paramedics (pharmacists and nurses) usually provide care. In 2009, PHCs in Chhattisgarh were stratified by type of clinical care provider present. From each stratum a representative sample of PHCs was randomly selected. Clinical vignettes were used to measure provider competency in managing diarrhea, pneumonia, malaria, TB, preeclampsia and diabetes. Prescriptions were analyzed. Overall, the quality of medical care was low. Medical Officers and RMAs had similar average competence scores. AYUSH Medical Officers and Paramedicals had significantly lower average scores compared to Medical Officers. Paramedicals had the lowest competence scores. While 61% of Medical Officer and RMA prescriptions were appropriate for treating the health condition, only 51% of the AYUSH Medical Officer and 33% of the prescriptions met this standard. RMAs are as competent as physicians in primary care settings. This supports the use of RMA-type clinicians for primary care in areas where posting Medical Officers is difficult. AYUSH Medical Officers are less competent and need further clinical training. Overall, the quality of medical care at PHCs needs improvement.

An experiment with community health funds in Afghanistan

Attention is increasingly directed to bridging the gap between the production of knowledge and its use for health decision-making in low- and middle-income countries (LMICs). An important and underdeveloped area of health policy and systems research (HPSR) is the organization of this process. Drawing from an interdisciplinary conception of embeddedness, a literature review was conducted to identify examples of embedded HPSR used to inform decision-making in LMICs. The results of the literature review were organized according to the World Health Organization’s Building Blocks Framework. Next, a conceptual model was created to illustrate the arrangement of organizations that produce embedded HPSR and the characteristics that facilitate its uptake into the arena of decision-making. We found that multiple forces converge to create context-specific pathways through which evidence enters into decision-making. Depending on the decision under consideration, the literature indicates that decision-makers may call upon an intricate combination of actors for sourcing HPSR. While proximity to decision-making does have advantages, it is not the position of the organization within the network, but rather the qualities the organization possesses, that enable it to be embedded. Our findings suggest that four qualities influence embeddedness: reputation, capacity, quality of connections to decision-makers, and quantity of connections to decision-makers and others. In addition to this, the policy environment (e.g. the presence of legislation governing the use of HPSR, presence of strong civil society, etc.) strongly influences uptake. Through this conceptual model, we can understand which conditions are likely to enhance uptake of HPSR in LMIC health systems. This raises several important considerations for decision-makers and researchers about the arrangement and interaction of evidence-generating organizations in health systems.