Data Driven Solutions for Complex Development Challenges

The world that we live in today is far from ideal; but does not stop motivated individuals from working towards mitigating societal, economic and environmental challenges. Across the world, various stakeholders such as government organizations, humanitarian organizations, corporates and investors are working towards designing and implementing interventions in the social sector to bring about positive impact. However, riddled with strategic and operational challenges, these stakeholders often require the assistance of adept development consultancies. A trusted ally for the development sector is Sambodhi Research a global development consulting organization.

Founded in 2005, the firm holds expertise in monitoring, evaluation & learning (MLE), data analytics, capacity building, technical assistance, “Through our services, we produce high quality, statistically significant and robust evidence to enable informed decision making in the policy and implementation realm for interventions,” explains Sudhanshu Malhotra, Vice President Business Development, Sambodhi Research. Headquartered in Noida, the firm’s services have so far aided interventions in sectors such as energy access, environment and climate change, agriculture, livelihood, public health & nutrition, wash, skill development, education, financial inclusion and governance.

Countering Operational ChallengesThe social development sector often treats measurement and learning as after thoughts. This causes various operational challenges such as inadequate budgeting for measurement and monitoring, unrealistic expectations from the programme outcome/impact and unrealistic expectations from research activities. Sambodhi counters  these challenges by engaging early on with stakeholders at the programme design stage and thus creating visibility and awareness on potential MLE and research. Working in the niche area, Sambodhi’s MLE support services include impact evaluations, process evaluations, concurrent monitoring, process monitoring and embedded long term MLE .

Using statistically sound experimental and quasi experimental methods, innovative techniques in data analytics and collecting data itself to ensure quality, the company also carries out large scale multi surveys in both urban and rural settings. To cater to need of handling composite data that is rapidly transitioning from numerical to complex-textual and audio-visual. Sambodhi is also heavily invested in mastering and applying evaluative methods based on qualitative inquiry The company also holds expertise in research and data analysis which includes data analytics support by applying big data as well as lean data principles to the development context. With its data services extending from descriptive to predictive and prescriptive analytics, Sambodhi has built strong proficiency in rendering research support for cross sectional studies and assessments. Formative research and other activities falling under the gamut of social research. “We see ourselves as research service provider bridging the gap between traditional and main stream consulting, and this positions us very uniquely in the development consulting space,” adds Sudhanshu.

Building Capacities in Social SectorThe social development sector is constantly evolving. Equipped with the right expertise, Sambodhi also works towards supporting and updating the capacities of its developmental partners through its capacity building and training services. The company’s trainings focus on areas such as research design, data analytics. MLE techniques, results based frameworks, statistical software and proposal writing, amongst others. The firm undertakes class room and customized training in the field of MLE and has so far trained over 8000 senior mid career professionals.

Over the years, Sambodhi has succeeded in harbouring trust in the social development sector and has worked with prestigious clients such as the Government of India, various State Governments, the World Bank Group, various UN Organizations, Academia such as Duke University and LSHTM, and foundations such as the the Bill and Melinda Gates Foundation and Rockefeller Foundation, amongst others. Although headquartered in India, the company has offices in Cambodia and Tanzania. “Apart from South Asia, we are actively pursuing international growth in the Sub-Saharan Africa and South East Asia regions,” adds Sudhanshu. Engaged in work which has an impact on the lives of the poor and the marginalized, Sambodhi certainly has its heart in the right place.

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Gender and Global Health

Former President of USA George HW Bush once remarked,” Let me tell you, this gender thing is history.” At that time, this caused instantaneous outrage not just in political but non political circles as well. However, it soon died down. I believe Bush was excused (or at least wasn’t taken to the cleaners, literally) because he is a Republican. But when Larry Summers, then as President of Harvard University, and an advisor to many Democrat presidents mentioned the unmentionables regarding gender, this caused serious angst amongst people, leading to his resignation. It is a different debate altogether whether to consider a Democrat a more rational person than a Republican. But when Summers’s faux pas led to that uproar, it surely didn’t come as a surprise that Harvard chose a woman, Drew Faust to replace him. The point I wish to make here is times have changed—just being politically correct is no longer acceptable. How are things like gender juxtaposed in the true sense of the word in modern discourse is what really matters, especially when it comes to discussing global health issues.

According to the WHO, definition of gender is: “socially constructed roles, behaviors, activities, and attributes that a given society considers appropriate for men and women”. However, while gender mainstreaming is well documented in programmatic interventions on health universally, the picture on the ground reveals a different story. During my stay so far in India, I have observed that often there a blurred vision when it comes to discussing gender which is often confused with only women’s health issues. For instance, I have observed in field visits that most men perceive MNCH issues solely the prerogative of women. One such program Sambodhi recently evaluated for BBC Media Action tackled this problem head on. Called the Chaar Gaanth program, the program initiated rural men to take active role in preparing for child birth. This is a novel program and its reach is limited. I believe in order to meet the MDGs, and to actually reduce gender inequities a lot needs to change, not just people’s perception on gender.

Sambodhi helps evaluate many maternal, newborn and child health (MNCH) programs for many bilateral and multilateral agencies. In most cases, however I have noticed the programs have been designed such that the health of women is complementary to, but not synonymous with, the promotion of gender equity in health. Further, I have noticed that global health policies and programs focused on prevention of and care for the health needs of men are notably few in number. To overcome entrenched ideas within global health is imperative and even more important to convince donors and governments to ensure that programs address the health needs of both women and men. Galvanizing gender into global health necessitates these thoughts and actions are more political to influence interactions among the prevailing ideas, relevant interests, and institutions which determine health policies.

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Using Analytics Advantage For Data Mining

What data could do without analytics? Nothing, it would have just been a data collection with no meaning. Analytics defined data using data mining.Google defines data mining as an analytic process designed to explore data (usually large amounts of data – typically business or market related – also known as “big data“) in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns. Analytics can be used in data mining process to the extreme content.

Here are the Data mining classes of tasks:

1. The identification of unusual data records or data errors that require further investigation.
2. Searching for relationships between variables.
3. Discovering groups and structures in the data that are in some way or another “similar”
4. Generalizing known structure to apply to new data.
5. Regression – to find a function this models the data with the least error.
6. Compact representation of the data set.

Now let’s look into each step and understand how analytics play a vital role in data mining.

The first two steps are the most crucial ones. Depending upon the data, you have options of straightforward predictors for a regression model, to elaborate exploratory analysis. This is the basic yet most important step in data mining. If this goes wrong, the complete analysis would have an incorrect basis.

The next two stages incorporates the technique of applying the correct on once choice. It involves various models and predicting the best one. The variables you choose are independent and predictive analysis comes in play for these steps. You may have to apply different techniques on same data set and get the most desired output.

Now let’s talk about the final two stages of data mining which produces results. The model which you have selected in the previous two stages would be applied to the new data and produce predictions. What future could react to our stimulus is predicted in this step.Errors are eradicated to the maximum and if the desired results are not generated, re-evaluation is done.

Almost every field in business requires data mining. Custom relationship management is one such area wherein customer related data is scanned and explored to get into the minds of customer. The return on investment is high and this is profitable as you get to know what your business would be most likely to behave to changes. Science, engineering, social business, everything encompasses this beautiful tool.

The area is wide, put on your thinking caps and start exploring.

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Whither Impact Evaluation

Public programmes are designed to achieve certain objectives. Different governments, international organizations and multilateral aid agencies fund and implement interventions that intend to reduce poverty, improve public health and improve quality of education, among other things. However, these interventions work in a complex ecosystem involving myriad players and it is not straightforward to determine whether the interventions have worked or not. It requires rigorous impact evaluation methodologies to find out whether there were any changes due to the intervention.

The main aim of an evaluation exercise is to find out whether there were any changes after an intervention, and if there were changes, how much of it can be attributed to the intervention. In other words, it is the science and art of finding out what works and what does not work in the public policy sphere. Over the years, impact evaluation has become almost mandatory requirement to any large intervention. Many organizations have developed state-of-the-art expertise in providing impact evaluation services to governments, international organizations and aid agencies.

As the discipline expands, two basic questions can be asked about the nature of the role that impact evaluation plays in development sector programmes. The first question is whether impact evaluation makes the actual objectives of a development intervention redundant. The first thing should be kept in mind that the prerequisite of any impact evaluation exercise is a carefully planned intervention. So, the primary focus of the agencies should on implementing the intervention.

The second question raised is whether impact evaluation does really make a difference. When we ask this, we would like to know how many policy decisions were actually taken based on the results from an evaluation exercise. Are the learnings from evaluation able to change the way policy making is approached by different governments, international organizations and multilateral aid organizations, which forms the main consumers of impact evaluation reports? If it is not happening, there is something wrong, and valuable learnings from years of experience in the field are being lost into voluminous reports that hardly anyone reads to any effect. These questions are better asked to the evaluators themselves.

There is an urgent need for the evaluators around the globe to ponder on these issues and find ways to rediscover the discipline. Impact evaluation must not be reduced to a routine exercise which is carried out for the sake of it. It is imperative that every researcher asks one simple question, “How can I make my work count?” The good news is that there are ways to make it happen. The best way to do it is to make sure that the learnings from evaluation reach a wider audience.

The broader goal is to create a voice in favour of evidence based policy making. Making the learnings of research accessible to the public is the first step towards achieving it. Evaluators can make more use of their research by owning the research outcomes and making them available through diverse forms of media. Bringing together everybody in the profession through seminars, workshops etc. and creating a strong and vibrant community of evaluators for knowledge sharing will be very helpful in this regard. The power of information & communication technology (ICT), internet and social media can be leveraged to this effect.

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5-points researchers may consider while conducting large scale surveys in slums

Metro cities are cosmopolitan in nature. The population in the cosmopolitan cities are generally heterogeneous which constitutes migrated people from different parts of the country. Especially in developing countries, the migration of labor is an important phenomenon of the urbanization process. These cities have changing trends in terms of demography and development. Sizable proportion of the population in most Indian cities lives in slum areas, especially in Mumbai and Delhi in India. According to Census 2011 figures, approximately 37% and 11% of the total population dwell in slums in the cities of Mumbai and Delhi respectively. The increasing slum population have witnessed an indication of worsening living conditions and increasing poverty in cities in India. Disparities in health condition of the population between cities and among different groups of the population in the same city are increasing. This has led to increased need of attention for specific interventions to urban slum areas. And with these enhanced attention by the government, foundations, donors, NGOs and corporate, several studies are also being carried out in the slum populations.

The article seeks to describe challenges faced while conducting research in metro cities, with special mention of my Mumbai experience. This article aims to help researchers who are contemplating of conducting large scale research among slum dwellers. This article is a reflection of our research experience on community based survey for a communicable disease in Mumbai. The study was conducted in slums of 15 wards of Mumbai covering the slum areas. Broadly the article focuses on the issues of identifying the location and boundary and seasonal habitation pattern, seasonal challenges in collecting data, instability in the habitat, problems faced in conducting research on communicable disease, getting correct information from the respondents, non-response rate, expectation of community from the survey, survey fatigue due to large number of surveys happening in the slums.

1. Locating Maps

Location identification as well as identifying their boundary is paramount before conducting a large scale study among slum dwellers. Usually for surveys of these nature, maps are procured from NSSO (UFS maps or the Urban Frame Survey maps), Census (CEB maps or the Census Enumeration Block maps), and other government offices. Sampling frame for our study was slums in 15 wards for Mumbai. Almost all the maps we procured from an agency were poorly drafted with recurring issues like – incorrect directions, untraceable landmarks and improper use of designated symbols for classifying the buildings/structures. Most of times, instructions etc are hand written and the hand writing on the maps were illegible. Many areas were redeveloped. Ideally one Primary Sampling Unit (PSU) / cluster map should consist of around 160-200 households, but there were many that had around 1000 HHs.

Now in order to identify the slums within those maps, list of slums was procured from the office of another government agency, which were matched with the cluster maps. We experienced, although aome areas were marked as slums as per the list but when actually visited, some of those areas were very well developed and clean. On the other hand some slums which are newly developed did not feature in the list. Since the list is not updated on a regular basis, these lists may not represent the entire slum dwellers of a city. As researchers, we have no control over this and we will have to live with it perhaps.

2. Seasonal habitations

Availability or non-availability of the target respondents are very much dependent on the season when the data collection is planned in India. This is more concerning when we plan a study in Mumbai, considering a huge migrated population. So, if the survey is planned for the month of April/May/June, we need to be careful. Owing to the summer vacations in the schools, most of families originally from northern part of the country, would go to their native places. The families left, may not be a complete representation of the population. The rainy season that follows summer, poses it’s own challenges in Mumbai due to frequent cancellation of local trains and water logging here and there. Therefore, if possible one should plan for data collection between October and March.

Since, most of the times, all the members of the household go out for work, we often find a substantial number of locked houses. Moreover, as most of these people work in informal settings, to meet with these people the survey team needs to be very flexible for timing, ie. Plan for late evening, as in the early morning too, the respondents are extremely busy in their daily household chores like washing utensils, fetching and storing water, preparing breakfast and lunch for the members etc. In order to take time and elicit good response provision of small gift in our budget can be made if it is possible.

3. Attrition of Research Investigators

Researchers need to be cognizant of high attrition of the field team workers. It is not at all easy conducting a study on communicable disease where we run the risk getting infected. I have personally experienced half of the team members dropping out in just 3 days of field work. The biggest reason being the difficulty in reaching, locating, moving in slums areas. Mumbai also known as the city of dreams, has several opportunities. Also, knowing the nature of project, which are generally short term, the team members do not did not have the motivation to perform. Therefore, it may be a good idea to train 50% more people than planned.

4. Survey Fatigue

Due to the increased development focus on the urban slums, the studies conducted amongst the slum dwellers have also increased. And with these surveys, they do not get any direct tangible benefits. As a result, they have started getting cynical about these studies. We have also seen, sometimes, some of our field team members, make some false commitments in order to seek their time, which goes unfulfilled. These false promises may be catastrophic for that study and for future studies as well.

5. Perceived Health Hazard in case of communicable diseases

If field people are engaged in the field work for any communicable disease, there are high chances that they will be very reluctant in participating in the study. This is quite natural, especially if the study area is a slum. A possible solution to this could be by engaging a senior medical doctor, practicing in that field, who takes several sessions with the field workers on the actual and perceived risks.

Conclusion

Careful planning can help researchers execute the field work within the planned time line and budgets. Though, some of the solutions suggested above like training additional people, offering gifts, engaging senior medical consultants etc, apparently seems be cost enhancing, but in actual terms, all of these gets compensated if the field work completes on time without major hassles. To conclude, as the scenario is significantly changing in cities, many new issues can arise, which can be resolved then, but some of the issues as indicated above can be thought upon before conducting a survey.

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14 to 40 in 20 years – Status of Rural toilets in India and SBM

Swachch Bharat Mission aims at Open Defecation Free (ODF) India by 2019. The erstwhile NBA, rechristened as Swachch Bharat Mission, is being carried out in a mission mode and a results based approach is being followed. It is evident from a recent tender from the Department of Panchayati Raj & Rural development, from a state Govt. Perhaps many other states are following the suit. Significant attention was being paid to coverage (ie. construction of toilets) followed by it’s usage to ensure ODF. Heartening to note that sustainability of ODF status is also given due importance in these requests.

But, achieving 100% ODF within 3-4 year time sounds like a humongous target. India lacks both in terms of hardware and software in sanitation. If we look at the current status of toilets in India, more than half of us defecate in open currently.

If we just look at the trends – it took us about 20 years to reach forty percent (NSSO 69th round 2012-13 and MDWS Baseline survey 2012-13) coverage from fourteen percent in 1993 as per NSSO (49th round) estimates. [Please see chart: % HH having latrine (Rural)]

Okay, one can think that the toilets can still be constructed with the honest effort of the executing agencies and the desired political commitment, which perhaps exists. But the real challenge will be in implementing the software bit of it. Making people use toilets by changing their age old practice of open defecation may be a big challenge. Concerted efforts may have to be made in order to change their current behaviour.

Effective Behaviour Change Communication (BCC) models may have to be developed, piloted and implemented with good amount of perseverance. They have to be tailored and targeted to the specific audience and need not be based on “one size fit all” theory.

And then, ensuring sustainability of the practices will be very critical, as we can easily slip back to our original practice. It may be a good idea to do some scientific studies to using using a combination of methodologies like RCT, Quasi-Experimental and observational cohort study (OCS) to accept / reject the hypothesis.

Having said these, if we see things at a macro level, our country, especially in rural India, we still struggle for basic food, shelter and water needs. Therefore for most of us, sanitation is not our top priority. I remember, while conducting a study in Bihar, when I was discussing the importance of desired sanitation behaviors with one of my respondents in Gaya district, he very candidly said “pehle khana kahyege tab na pakhana ke bare mein sochenge” (I would first like to think about how to fill my stomach before thinking of defecating). Very valid!

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Innovations in thematic Monitoring – Need for composite scores in the field of Water Sanitation and Hygiene

Indian subcontinent’s attempt towards providing its population with clean drinking water and hygienic living conditions witnessed its inception prior to independence. In the post-independence period, the attempts were given statutory mandate through Directive Principles of State Policy (DPSP) and First Five Year Plans (1951-1956). The attempts received further push during the First International Decade for Clean Drinking Water also known as the First International Water and Sanitation Decade, 1981-1990, setup by the United Nations. It was during this period of time when India’s first nationwide sanitation programme, Central Rural Sanitation Programme (CRSP), was launched in 1986 by Ministry of Rural Development. Since then several notable programs such as; The Accelerated Rural Water Supply Programme, Rajiv Gandhi National Drinking Water Mission, Total Sanitation Campaign (1999) and the ongoing Swachh Bharat Mission have been implemented stressing on provision of clean drinking water and sanitation facilities.

Following the government’s commitment towards water and sanitation, much human and financial resources have been allocated towards the national programmes. As per the reports, (http://sanitation.indiawaterportal.org/english/node/3234), the financial allocation under rural sanitation programme for the financial year 2015-2016 witnessed a hike of 27 per cent (Rs. 3,625 crore) from the last year. Interestingly the centre’s overall contribution towards Ministry of Drinking Water and Sanitation (MoDWS) has been almost halved, from INR 12,107 crores to INR 6,224 crores. The decrease in overall government funding has been synergized with the tax exemptions for corporations willing to spend their CSR funds over the Swacch Bharat and Clean Ganga missions (http://www.firstpost.com/business/budget-2015-100-tax-exemption-for-cont…).

While the move might be considered as restructuring government’s share in social spending through pooling in corporate resources, one also needs to analyse the present mechanisms in place to effectively evaluate the impact planned interventions have caused. With a 27 per cent hike in spending, one should expect a proportional hike in accountability and cost-effectiveness of the programmes. While there has been much ado on the implementation efficacy of an intervention, one hardly witnesses a debate on the monitoring and evaluation methodology involved in the operational cycle. An absence of such debates disturbs the delicate praxis between policy and implementation.

Currently the most large-scale and extensive surveys conducted in India, capturing data on water, sanitation and hygiene, is based upon stand-alone indicators. However, the indicators, though exhaustive as stand-alone concepts, have not been visualized as a composite whole. In simpler terms one can find the data for key sanitation indicators such as; availability of toilet within household premises as the sole representative indicator. In continuation, one would also find indicators on drinking water facilities and hygiene practices for the same household. But a univariate analysis, as in case of most studies, do not provide the researchers/implementers with a composite understanding of the situation. The resulting report is thus lengthy, exhaustive and would requires additional efforts to be simplified and made representable to the larger audience.

The above mentioned methodological limitation can be regarded a classical case faced by several constructs. In the world of programme planning and intervention there are no individual/decisive indicators, but a plethora of so. Hence, one needs to create composite score-cards, indexes and clubbed scores in order to effectively monitor its progress. Based on the same principle the world witnessed the rise of Human Development Index as one of the most quoted composite scores. Local examples such as the National Air Quality Index can be viewed as manifestations of this principle.

The field of water, sanitation and hygiene requires a similar intervention by tailoring an index for itself. The results of such an index would go a long way in defining the course of programme implementation. Inter-state results can be developed and ranked, as well as disaggregated across smaller geographical units. In the event of a state getting a lower score, one can identify the exact construct in which the state has performed poorly, as thus would require additional support. To add a window of accountability, the report card (hardly a page or two) can be presented to the beneficiaries for larger dissemination of information. The emerging result would be easy to comprehend yet powerful.

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Scams and development

Yesterday’s article (dated 2nd July 2015) titled “Mother of all scams: For dole, pregnant five times in 10 months” in the Times of India ( one of the leading English daily in India), reports a disturbing fact related to one of the most important schemes – “Janani Suraksha Yojna “, under the National Health Mission (NHM). (Please Janani Suraksha Yojana (JSY) is an intervention, with the objective of reducing maternal mortality and neo-natal mortality by promoting institutional delivery.

The scheme is implemented in all states and Union Territories (UTs) of India, with a special focus on eight EAG states (ie. Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttar Pradesh and Uttarakhand) and Assam, which are the low performing states (LPS). The classification of low performing and high performing states were based on the institutional delivery rate of the states. States with equal to or less than 25% institutional delivery were classified as Low Performing States (LPS) and those above 25% were grouped under the High Performing States (HPS).

The Time of India report underscores some startling “facts”, which reports massive corruption in JSY money. As per the report in Bareilly district of Uttar Pradesh (one of the Low Performing States) “A woman, was declared pregnant three times in four months to avail benefits under the scheme.Another woman who had not conceived in 12 years was paid Rs 1,400 as honorarium by the health department. Yet another woman in Bahraich, a 60-year’s old-, pregnant’s got “a five times in 10 months”.

This is not an aberration. There have been several other instances and been reported in the past.Similar misuse and corruption around the JSY from Rajasthan was also reported titled “Janani Suraksha Yojana under scanner” in the Times of India newspaper approximately four years ago on the 26th July 2011. (Please Apparently, Rajasthan is also one of the Low Performing States.

Reading for These Upon, one’s Would like to Understand how of states For for These have fared on the key health indicators directory Specially Maternal Mortality Ration (the MMR) and Neo reports-Natal Mortality Rate (NNMR). MMR is the defined as ratio of maternal deaths per 1,00,000 live births and NNMR is defined as number of neonates dying before reaching 28 days of age, per 1,000 live births in a given year.

As per the AHS data shown in the figure, all the states barring Uttrakhand has very high MMR, which is more than 200. Madhya Pradesh reports the highest proportion of the JSY beneficiaries (73%) followed by Odisha (70%), but it’s NNMR is higher than most of the other states. Not sure, if the JSY benefits have translated into improved MMR and NNMR. Assam reports highest MMR (301) among the LPS, although more than 55% have availed the JSY benefits. However, this data needs to be seen with abundant caution. I had an access to the raw data, I could run some tests to understand the association between JSY uptake and mortality indicators, but in absence of the raw data, we can at least see some trends, which are definitely not too encouraging.

As per the Word bank data estimates Israel has the lowest MMR of 2 per 1,00,000 live births. India’s neighbouring countries like Pakistan (170), Sri Lanka (29th), Malaysia (29th), China (32), Bhutan (120) Bangladesh (170), Nepal (190), too reports relatively better MMR status than these states. (The Source: http://data.worldbank.org/indicator/SH.STA.MMRT/countries/all?display=default ).

These trends sufficiently suggests that it’s high time the implementers start showing more seriousness in effective implementation and motoring of the national schemes in order to achieve better results. We can just hope that with the improved financial inclusion and the idea of ​​making Direct Benefit Transfers (DBT), helps in eliminating these widespread scams and the benefits reaches to the real beneficiaries.Nothing can be worse than seeing mothers dying while delivering a child.

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Nutrition in India – Debates and Controversies

In the year 2005-06, the Third Round of National Family Health Survey (NFHS 2005-06) released state and national level estimates on the nutritional status of children under five years of age in India. The report noted that 40.4 per cent of the children in India were reported as underweight. Subsequently in the HUNGaMA Report presented in the year 2011, the indicator for malnutrition remained as high as the previous reports, with 40 per cent of the children underweight and 60 per cent stunted.

In the financial year of 2010-11, the approved budget outlay for expenditure under public health stood at INR 5560 crores while the subsequent budget raised the outlay to INR 5720 crores. The nutritional estimates raised a fundamental question on the efficacy of health interventions at a point of time when India spent nearly 4 per cent of its GDP over public health. It lead the then Prime Minister Manmohan Singh observe that the issue of malnutrition among children was a “national shame”.

However, the reports were far from being universally accepted and were also widely criticized on methodological grounds. In his working paper titled “The Myth of Child Malnutrition in India”, released by IIPS (International Institute of Population Sciences), Arvind Panagariya questioned the use of reference standards for classifying children (under five years of age) as malnourished. Seconding the argument, Panagariya also questioned whether a certain individual suffering from malnutrition can be “pushed” into the safe (adequately nourished zone) within their life time as it takes generations for a population to reach its full nutritional potential.

While the second argument can be more prudently discussed by students and scholars of medical fraternity, much can be said about the first; reference standards. My understanding over the methodological protocol involved while calculating malnutrition majorly stems from the nutritional analysis conducted on the data gathered by Annual Health Survey – Clinical Anthropometric and Biochemical survey (AHS-CAB, 2013-2014). After its release, AHS-CAB shall provide the most recent estimates on malnutrition and non-communicable, life-style oriented diseases for the 9 EAG states in India.

There are presently popular reference standards for calculating malnutrition namely; NCHS (National Centre Health Statistics, U.S.) Standards and the MGRS (Multicenter Growth Study Group, WHO) standards. While the NFHS 2 (National Family Health Survey, Second Round) made use of NCHS standards, subsequently the NFHS 3 made use of MGRS standards. AHS-CAB makes use of the MGRS reference standards 2007, updated by WHO. Both the studies provide a normal growth curve for children under 5 years of age and can be most popularly seen in the growth charts available at Sub-Centres or hospitals in India. While these be the tools, how does one calculate “malnutrition” per se?

The reference standards calculates three constructs namely:

1. Weight for Height (Wasting) – Whether the child has adequate weight for his/her present height. The construct may depict rapid loss in weight owing to high incidence of diseases.
2. Height for Age (Stunting) – Whether the child has adequate height/length for his/her age.
3. Weight for Age (Underweight) – Whether the child has adequate weight for his/her age.

While Wasting represents a rapid loss in weight vis-à-vis the child’s height, stunting represents a long-term undernourishment. Finally, underweight is used as a composite score for both wasting and stunting and is most popularly reported (given the relative stability). The Growth Charts available with the frontline workers also aims to track the indicator of underweight (Weight for Age). Children lying below -2 SD are considered as moderately malnourished, children lying below -3 SD are considered as severely malnourished.

Though the process follows a robust model, the questions arise after calculation of Z-scores for the three constructs. The current MGRS reference standard is based on the data collected across Brazil, Ghana, India, Norway, Oman and U.S) vis-à-vis the NCHS. However, the growth chart follows a logic, as pointed out by Panagariya that, “all differences between the height and weight of population occur due the differences in nutrition”. Therefore, the scores observe that the differences between the sample of a child taken from a well-to-do neighborhood in New Delhi and one residing at a remote village in the state of Chhattisgarh is solely because of the nutritional differences. While this might make statistical sense, in all actuality populations differ based upon their race, ethnicity, cultural practices and genetic make-up. Effectively, one is therefore not comparing apple with an apple by following the standards.

While this can be regarded as one of the several issues plaguing the methodology, a deeper concern arises with the hiatus caused by unquestioned reporting and linear interpretation of the reports. If unexplained and unchecked, the public outcry over malnutrition might cause health practitioners to push infants recording low birth weight above the malnutrition levels through administration of external supplements, a trend not unknown to us currently. If this be a way forward, what happens to the previous argument of longitudinal “catching-up” process? What is the upper limit for the supplement beyond which one risks building obesity? Given the limitations, whether one should make use of reference standards at all?

Such questions need to be addressed while one interprets the survey results. While reference standards are the most convenient and popularly used methods, they should also be interpreted with more care and prudence. India is well placed to develop its own reference standards based upon a more diverse sample that can be regularly updated. While such considerations lie mostly with the policy makers, it is recommended that the underlying concepts of nutrition should be disseminated within the larger populace using simple language. In the words of an anonymous author, “An educated citizenry is a vital requisite for our survival as a free people”.

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Quality of Care in Public Facilities: Still a Big Question Mark!

It is a well-known fact that delivering in hospitals are much safer than delivering at home. Hospitals have experts who can help provide the best care possible for the mother and the baby. There are nurses who looks after the mother, provide her with emotional support and counsels her throughout the painful progression of childbirth. It is assuring to know that in case of any complications, you will have immediate access to specialist care.

To extend the benefits to the rural section of the society, Janani Suraksha Yojna was launched by the government of India in 2005 to promote institutional deliveries in public facilities by providing conductional cash transfer to women. With the launch of this flagship program, the institutional deliveries have increase many folds throughout the country.

NFHS shows the increase in institutional deliveries from 40% in 2006 to 78% in 2010-11 across India. With the advent of JSY, it is considered that increase in institutional deliveries will be accompanied by improved quality of care, but that is not the case. With the increase of case load in the facilities, a lot is left to be said about the quality of services in public facilities. Many women coming to public facilities for maternity care face disagreeable circumstances on a daily basis.

Few such instances were highlighted while exploring the quality of services in few public healthcare facilities in Uttar Pradesh.

A 22 year old Pushpa Devi came into the facility during wee hours of one morning with labor pains. She was accompanied with her mother-in-law and husband. The attending nurse checked her once on admitting her in the facility and then completely disregarded her for the next couple of hours stating that there was sufficient time for delivery. Throughout her ordeal, Pushpa laid on her bed, crying with pain, while her mother-in-law tried to get the attention of the nurse to examine her daughter-in-law.

When the nurse came to check up on Pushpa, she criticized her on lack of care of her genitals. The woman’s vaginal discharge had an awful smell which she couldn’t tolerate. She left her again, stating that she will return only when the head of the baby was visible. On constant pleading with the staff, the nurse came back, poured Sarson ka Tel (mustard oil) over her genitals, performed episiotomy (an incision made in the perineum during childbirth to facilitate easy delivery of the baby) which is a common malpractice in first childbirth and delivered the baby within 15 minutes. All this while, she scolded Pushpa, and called her ‘dirty’.

This is just one incidence wherein the pregnant women was not given attention, she was ignored, disrespected and mistreated.

Corruption

It is a common practice to extract money from the family of the woman coming to the facility for delivery. This is worst in maternity wards. From the free ambulance service who transports the woman to the hospital, to the staff in the facility, demand money at every step to do their job. Relatives are asked to pay token amount before handing the newborn to the family, double the amount if the baby is a boy. Anews report highlighting this form of endemic corruption describes the vicious cycle of poverty trap that a poor family fall into while availing delivery care services from a public facility. A report on Maternal Mortality in India by Centre for Reproductive Rights, describes that the case is worse for a poor woman who have to pay a huge amount for lower quality of care which serves as a deterrent against seeking institutional care and leads to higher pregnancy related complications. A sub-standard quality of care compiled with under the table payment, creates a ‘poverty trap’ for the family, which turns this happy occasion into a sour experience.

Harmful practices

With an increase in case load of women coming to public hospitals for delivery, the overburdened staff employs unnecessary and many a times harmful procedures to speed up the process of delivery. An article (Sharma JB, 2009) discusses such childbirth practices in public facility, which are being employed unnecessarily such as induction of labor, applying pressure on abdomen, episiotomy, manual exploration of uterus for removing placenta, etc., which are still being widely practiced in spite of evidence of their harmful effects. On the other hand, useful practices like use of partograph for monitoring labor, delayed cord cutting, practicing active management of third stage of labor, or sterile cord cutting are not been regularly followed. Episiotomy is a routine procedure employed in primigravida women or those delivering for the first time. An article in The Journal of The American Medical Association found that routine episiotomy has no direct benefit. In fact many studies have indicated that use of episiotomy leads to many complications such as incontinence of urine, incontinence of stool, painful coition etc. Despite this fact, the incidence of episiotomy was very high which was highlighted in a population based study conducted in Chennai (Sathiyasekaran et al, 2007) where it was seen that in 67% of the cases, episiotomy was employed. In another study highlighting the benefit of JSY on institutional deliveries, it was found that in 79% cases oxytocin was used, while in 57% cases pressure was applied on abdomen to hasten the process of labor.

Behavioral aspects

Cases like Pushpa are very commonly faced in public facilities, especially by poor section of the society. An article described many incidents where women in public facilities are slapped, shouted at, threatened and neglected during their delivery. In a common scenario, public hospitals are so packed with patients that they have to settle in dirty corridors, whereas the hospital staffs are plagued with long duty hours handling many patients at a time. But does this give them an excuse to disrespect, ignore and misbehave with patients?

Sensitizing health care professionals towards patient needs, especially during delicate experiences such as childbirth will help in improving the quality of care. At the same time, it is imperative to think ‘how far can one expect an overburdened physician to provide emotional comfort to his patients’.

With the advent of JSY, institutional deliveries have clearly increased in facilities in the past few years, but the question remains: Are the facilities able to cope up with the increase in caseloads? There still remains a dearth of healthcare professionals in proportion to increase in patient ratio. It is not fair to healthcare professionals, expecting them to handle 20-25 cases of deliveries in a day following all the prescribed protocols. There is a need of interventions such as NIPI-UNDP initiative- Yashoda, a mother aid, who not only provides emotional support to women during their delivery but also counsel her on important aspects such as breastfeeding, immunization, skin-to-skin care etc. We also need a strategy at the policy level which addresses the gap between available resources and increase demand of delivery care services to ensure good quality of care.

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Towards a Data-driven Public Health System

Changing Paradigm of Public Health

Over the last few decades, the public health system has undergone many changes. With the use of technology, huge volumes of data get generated at the health facilities every day. There has been an increased acceptance among the global health community that data can play a big role in influencing health policy.

In a country like India, where myriad problems plague the public health system, the availability of quality data can really make a difference. It can direct the scare resources towards the right problem at the right time. Based on the evidence, the public health programmes can be made more target-oriented.

HMIS and MCTS

In India, the Health Management Information System (HMIS) and the Mother and Child Tracking System (MCTS) are two primary sources of public health data. HMIS was launched in 2008 by the Ministry of Health & Family Welfare (MoHFW) to meet the growing demand of micro-level data on population and health for use in monitoring, planning and programme implementation. Currently, around 1.79 lakh health facilities are reporting monthly data to HMIS. HMIS provides capability of data reporting and analysis in the form of dashboards and serves as a key input to health policy formulation and interventions.

Mother and Child Tracking System (MCTS), launched in 2009 by MoHFW, is a name based application which facilitates monitoring of universal access to maternal and child health services by all pregnant women and children. Its aim is to help reduce maternal, infant and child mortality by ensuring that all the pregnant women and children receive a full set of medical services. MCTS tracks all pregnant women right from conception up to 42 days post partum and all new born up to five years of age.

Data Quality Issues

However, data quality issues have reduced the usefulness of HMIS data . The low quality of the HMIS is evident from three factors: high percentage of missing data, high occurrence of invalid entries and the presence of outliers. Moreover, HMIS has failed to ensure reporting from all private health facilities. Also, instances of repeat entries are common at the lower levels of reporting. Over the past few years, the quality of data has improved. Yet, it still falls short of the requirements of evidence based health policy planning. Data quality has to increase substantially before it can be used for monitoring and planning in the health sector.

Encouraging Data Use at the Micro-level

Having stated the problem of data quality, one question remains, “What could be done to make the health information systems more reliable?” One way to achieve this is to encourage the use of HMIS data at the micro level. This will improve the understanding about HMIS among the field level workers. HMIS reporting starts with the auxiliary nurse and midwives (ANM). As they become aware of the usefulness of HMIS data, the quality of reporting is going to improve. Another way is to encourage discussions on HMIS data in regular community meetings. If these small steps are taken, the quality of HMIS reports can be improved substantially.

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Training: Facilitating Evidence Based Policy?

Framing a strong policy is the keystone to the foundation of effective governance. A healthy policy environment stimulates a virtuous cascade of events and actions, propelling a country to prosperity. Yet it is astonishing and sometimes painful to see the frequency and extent of policy failure in India. A simple google search on failed policies in India will provide one with ample evidence in support of the preceding statement.

To the author’s understanding, grave policy blunders are prima facie the outcomes of erroneous/ biased/ incomplete/ absence of policy analysis followed by faulty authorization. There is also the problem of fixing relevant policy agenda so as to work towards formulating policies in priority areas, but that is another matter! Coming back to policy formulation; it is chiefly guided by agenda, evidence and deliberation. The agenda decides the kind of evidence generated or collected and then the deliberations and negotiations begin towards deciding the fate of the policy matter.

Agendas are formed under various pressures: those of demand, individual proclivities or the zeitgeist. The job of those in the business of gathering evidence is to ensure that representative and unbiased evidence that plays to no particular side, is generated. However, the real-world seldom allows for that especially if the evidence generation calls for heavy spending.

Studies, quoted in the parliament with vehement flailing of the arms and passionate speeches, suggesting that one side or the other is better, should be questioned. And in order for them to be questioned, those who play decision-makers must understand those studies. This involves education. It is essential to educate both the bureaucracy and the polity in ‘understanding evidence’.

What is evidence? How was it collected? Is it scientifically robust? Who collected it? Why was it collected? What does it mean for me? How is it being packaged and communicated to me? These are questions that decision makers must feel comfortable to ask. Numbers, figures and technical terms often make many skirt them, diminishing the value that these bring towards ensuring richness of policy debate. The author recommends that mandatory training should be administered to all those at the helm of policy decision making. This should not be highly technical, rather should be built upon a practitioner’s viewpoint that would equip the decision maker with the understanding to ask the right questions when it comes to evidence invariably drawn out of research studies.

The training would serve the dual purpose of improving understanding of evidence as well as sensitization of decision makers towards why evidence led policy decisions make sense. This may also have a spill-over effect in the form of increased focus on research activities.

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Impact evaluation has become an important part of public-policymaking. Thousands of impact evaluation studies are conducted across the world every year, and most of them ask a straightforward question, “What really works?”. However, usually the question is followed by another one that “Is it meaningful to ask such a question? Is it answerable at all?” The realist evaluation approach tries to make the evaluation question comprehensive, and in that effort makes it answerable.

The Realist Approach

In 1997, Ray Pawson and Nick Tilley proposed the realist approach, urging the evaluators to ask a more comprehensive question. Pawson and Tilley argued that in order to be more useful for decision makers, evaluators need to ask, “What works, for whom does it work, in what respects, to what extent, in what contexts, and how?”. They drew ideas from the works of Karl Popper and Donald Campbell, two of the most celebrated thinkers of the modern age. Karl Popper’s ideas on ‘Piecemeal Social Engineering’ and his promotion of trial and error, learning to refine policymaking has significant influence on realist view. Similarly, they also drew upon Donald Campbell’s work on ‘Reforms as Experiments’. The basic premise is that reforms should be small and incremental, if they have to be effective as large scale interventions lead to disasters. After Pawson and Tilley, many interpretations of the realist approach has surfaced, however, the basic realist question remains the same.

The Realist Understanding of How the Programmes Work

The realist approach has a distinctive take on the way programmes bring about change. There are four basic assumptions about the nature of the programmes that realist evaluation is based upon.Firstly, programmes are theories that incarnate, multiple theories of change are at work for every programme and the effectiveness of the programme depends upon combined efficacy of these theories. The second assumption is that programmes are embedded into different layers of social and cultural reality, influencing and influenced by any changes in behaviours, events and social conditions. Thirdly, programmes require active engagement of those who are touched by them to effect changes. Finally, programmes are open systems and they cannot be isolated from its surroundings. Realists accept that externalities always impact on the delivery of a programme and this entails that they are never quite implemented in the same way.

For any programme, realists try to identify the generative mechanisms that bring about change. The next stage is to identify the contextsrelevant to the operation the programme mechanisms. Outcome-patterns comprise the intended and unintended consequences of programmes, resulting from the activation of different mechanisms in different contexts. The next step is to identify the appropriate Context mechanism outcome pattern configuration (CMOCs), indicating how programmes activate mechanisms amongst whom and in what conditions, to bring about change. The context-mechanism-outcome configuration (CMOC) is used as the main structure for realist analysis. It uses an iterative research cycle which tries to identify all the relevant CMOCs that are at work for the programme. The evaluation output are in terms of CMOCs, i.e. statements like “This has worked under these circumstances for these target beneficiaries in this way”.

The scope of realist enquiry is broad, and it is applicable to any social science discipline. It has an added advantage of flexibility. It may be used prospectively (in formative evaluations), concurrently (in summative evaluations) or retrospectively (in research synthesis). Moreover, it has no particular preference for either quantitative or qualitative methods. Usually, both quantitative and qualitative data are collected in a realist evaluation, often with quantitative data being focused on context and outcomes and qualitative data on generative mechanisms.

Realist Response to policy questions

Having outlined the basic principles of realist evaluation, one might ask what would be the response of a realist evaluator when posed with a tough policy question. If asked whether an intervention worked, the realist is going to say, “It depends”. It might sound useless as a response, but the realist will detail out everything it depends on, i.e. “What worked and for whom, in what respects, to what extent, in what contexts, and how? He is also going to provide the detail of what did not work, why it did not work and for whom it did not work. After the success of a pilot, the realist is not likely to recommend that the programme should go all out. The table below gives frequently occurring policy questions and typical realist responses to them.

The Policy Question

The Realist Response

Did that intervention work?

It depends (in what respects?)

Does that intervention work?

It depends on the conditions.

Does that programme work?

Parts only, in some places and at some times

Should we fund X rather than Y?

Check first to see if they are commensurable

The pilot was great, should we go large?

Unlikely, but you’d have to wait and see

Will it have a lasting effect?

No, play only to its strengths

Can you let us known before the next

spending round?

Sorry, not in all hone

Realist Approach: Pragmatism or Pessimism

Its reluctance to offer universal policy prescription on most of the issues may be termed as a defeatist approach by the host of experts. But before dismissing the realist approach, it should be kept in mind that there exists a very thin line between pessimism and pragmatism. To understand the realist’s refusal to scale up any intervention, we must trace back to its ideological roots, which may be found in the works of Karl Popper. Popper always favoured ‘Piecemeal Social Engineering’ in the form of small-scale interventions. It is no wonder that realists refuse to generalize their findings.

In a world where billions remain in abject poverty, there is a tendency among policymakers and evaluators to generalize the findings, especially when the findings are positive. Therefore, it is not hard to find instances of interventions which worked well in Asia but failed miserably when introduced in Africa. The realists advise caution before such mistakes, and promote a better understanding on how the programmes bring changes.

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