Transforming the nutrition information system

Discussion of Ethiopia Nutrition Information System in early 2011

In Ethiopia, the role of the national Nutrition Information System (NIS) has been clearly stated in the Ethiopian National Nutrition Programme (NNP). There are three constituent parts to this role. These provide a ‘comprehensive’ and holistic structure to NIS design: to support timely warning and adequate interventions at woreda and higher levels, to develop, manage and evaluate the NNP at all levels, and to inform other sectors like agriculture, water/sanitation and economic development. This comprehensive vision for the NIS is to inform understanding of the nutritional situation with respect to chronic and newly occurring problems, as well as the causes of these problems, and how these change over time in order to help in decision-making at all levels. However, while the NIS can effectively accommodate and be ‘open’ to an unlimited amount of data, the ability to trigger an effective and appropriate response requires that the information is timely, reliable and consistent. These conditions ultimately determine the basic parameters upon which the initial choice of information for the NIS is made. Put simply, all data should be trusted and continuously available,
data should be triangulated to generate ‘contextspecific’ and evidence-based information and there should be a clear process, agreed by all actors, to feed information into decision-making.

Unique data situation in Ethiopia

Ethiopia is in quite a unique position because, over the last thirty years, large amounts of data have been collected by the Early Warning System (EWS), including health and nutrition information. However, the nutrition information collected by the EWS provides only scattered data – mostly alert signals based upon ‘observable’ degeneration. Data is collected directly from health workers at ‘critical times’ and without systematic comparison with what would be ‘normal’ for a given time of year. Nutritional assessments are required during these critical times to confirm ‘emergencies’ but the seasonality of these critical times creates a widespread, simultaneous demand for assessments, which rarely can be adequately met. In recent years, targeting of surveys has been improved through increased use of routine data sources, at least to indicate where an assessment is most urgently needed. Nutrition data are now available and accessible on a monthly and quarterly basis at the lowest levels due in large measure to three programmes: The Community Based Nutrition programme (CBN), the Therapeutic Feeding Programme (TFP) and Community Health Days (CHD). These routine systems are the monitoring backbone of the NNP, which – at least theoretically – can be combined to inform timely warning and be shared with other sectors. Similarly, a number of diseases are also currently being tracked on a weekly basis through the Public Health Emergency Management (PHEM) system. Thus, there is a very real potential for the EWS to systematically tap into specific data from existing health information sources and vice-versa. This will be most effective if a consensus is reached on key indicators, in particular for timely warning. The key question, ultimately, is whether decision-makers from all sectors are willing to exchange and use available routine data to inform their decisions and response.

Nutrition data management

While there are ‘trust’ issues on data quality and credibility, the administrative decentralisation and existence of a widespread health network, creates the rare opportunity to build capacities, accountability and transparency at lower levels like the woreda and the kebele. Initial data collectors are volunteers and frontline health practitioners. Many report that data collection is an additional burden to their already crowded agenda. After the initial collection, data flows up through various levels via supervisors and health officials. However, little feedback is given through the system so that people directly involved have a limited sense of what is actually done with the information provided. The sheer volume of reports stored testifies to the regularity of data collection undertaken and the immediate priority that should be given to improve the ‘efficiency’ of the process. Currently, asking for nutrition information from a woreda official leads to a paper-chase given the amount of report forms collated. Where officials have been provided with a computer, data appears to have been regularly updated. Given the increased requirements for information
management, it seems inevitable that woreda Health Offices will move from a paper-based system to a computerised one, allowing them to perform data quality checks that otherwise are time consuming and prone to mistakes if done manually. The implication here is that woreda level officials are mostly young, often computer-literate, professionals with degrees. Provision of adequate tools/software to practically manage information can help build their capacity to implement the system. If information is not properly valued at
woreda level, where most data are collated and ‘checked’, then the task of quality assurance at higher levels is nigh-on impossible.

Added value of NIS: triangulation of data

What is ‘new’ in the NIS paradigm is the requirement for ‘triangulation’ to provide evidence-based information for decision making. This implies that collected data are not interpreted in isolation but are brought together from different sources. The strength of triangulation is the ‘contextualisation’ of the data, meaning numbers and/or standardised observations are grounded in ‘local knowledge’. Frontline practitioners in health-posts have access to nutrition and health information through regular contact with patients. With nutrition, for example, they are in the best position to judge if the deteriorating weight of a child during monthly growth monitoring or his/ her admission in the Outpatient Therapeutic Programme (OTP) is linked to lack of food in the family or to other causes like illness, inappropriate feeding practices, etc. It is this ‘proximity’ that allows for the triangulation to be most helpful at community level whereby root causes of malnutrition can be identified. An example where this could be used is in chronically food
insecure areas supported by the Productive Safety Net Programme (PSNP) where risk financing mechanisms exist to address new chronic or temporary food insecurity. By monitoring increases in underweight (as an early indicator) and OTP admissions (as a late indicator), frontline health practitioners, who are members of the Food Security Task Forces (FSTF), can play a crucial role in providing information for appeal processes.
However, the credibility of their information will depend on their full understanding that risk financing mechanisms are only accessible when malnutrition is linked to food insecurity. Thus, triangulation of data at source is a kind of check by key people before information is fed into the decision-making processes or reported to higher levels.

Trust, accountability and transparency

In Ethiopia, in line with governmental decentralisation, woreda and kebele level administrations have been given increased power to analyse, assess and act on their own changing situation. They are therefore more responsible and accountable for both development and emergency response. Addressing the challenges of how information can feed into decision-making will ensure the credibility and sustainability of the NIS. At the moment, available data from routine sources are not adequately linked to information use. The main challenge for data utilisation at higher levels is that sources are not fully trusted while at lower levels there are
limitations over capacities and mandate. While data quality assurance can be built into the system,
especially by improving lower-level capacity, more emphasis needs to be given to the human aspect. ‘Trust’ cannot be built without attention to the role played by each stakeholder, starting with frontline practitioners. ‘Accountability’ cannot be acquired if there is no hand over of responsibility. ‘Transparency’ cannot be promoted without making response and feedback more visible. The NIS in Ethiopia can be built upon coupling available data sources with adequate technical support provided throughout the health system.
However, technical inputs are not enough to ensure its sustainability. A sense of ‘value’ is what motivates people and without it, the simple transmission of data to higher levels will not provide incentive to stakeholders for their input. ‘Triangulation’ is most effective at community level where individual data sets can be compared at source and understood within a given context. Frontline practitioners play a crucial role in building the credibility of the NIS but this can only come about with increased recognition of the role they play in informing decision-making. As the process of decentralisation continues within Ethiopia, important decisions to be taken at the lowest levels, risk financing mechanisms being an example, will require bringing together available data from different sources. This, in turn, will rely increasingly on key people accountable for informing this process at the frontline. Before trusting the Nutrition Information ‘System’, a vote of confidence should be given to empowering the information ‘Source’. Credibility, after all, should always start with the people.