La discusión de la ley de bases

The majority of participants considered information, evidence, and research to be

significantly lacking in Cambodia. Four themes emerged to explain this perception: 1) uncertain if the investment is worthwhile, 2) quantity and frequency, 3) system gaps, and 4) capacity gaps.

1) Uncertain if the investment is worthwhile: As highlighted previously in this chapter, according to a number of participants, wise investment decisions cannot be made because there is insufficient information to know if efforts have had an impact and/or if course corrections are needed. One government official expressed this gap this way: “…if we want to know about our

intervention, where it is and if what we have done is successful, we don't have the information.”

packets produced, could be tracked, but not the outcome of their use, such as a reduction in malnutrition.

A number of participants commented that for some aspects of nutrition there was information, while for other areas, such as anemia, little was known. This gap was said to limit the community’s understanding of the underlying causes of malnutrition and its ability to create a responsive program. Furthermore, a few participants highlighted that although some data were collected, they were not used. Growth monitoring data was given as an example. Another was that health care workers complete a child’s chart, but do not use the data to track a child’s growth and take action if the child falters.

The lack of evidence, both research and M&E, in Cambodia was also said to mean that individual actors could rationalize their efforts without being challenged or without questioning their value.

Maybe an organization says: ‘This is what we do and we think it's effective.’ It's really hard because there isn't great M&E to say ‘This is working.’

—Funder

2) Quantity and frequency: According to the majority of participants, nutrition data is insufficient, and the data available have not been collected with the frequency needed to be useful. The CDHS conducted every five years was cited as an example.

There is 40% of stunting, but the year of measurement is 2010. In 2015, the story could be different.

—Civil Society

Data we get from the CDHS is not available regularly. Right now we wait every five years. Between those five years we don't know how our

implementation goes.

3) System gaps: The majority of participants said there was no functioning M&E system or reporting mechanism. One participant highlighted the lack of coordination in M&E.

People having different M&E frameworks, so everything is in people's own silo. Even NGOs are not able to combine their M&E in any way, shape or form. Government also has different M&E in different ministries.

—Civil Society

One reason data were unavailable and hence not used in Cambodia was because the current Health Management Information System (HMIS) has few nutrition data, though reportedly NNP has its own system. By contrast, a government official explained that service providers forget or do not pay attention to entering data into the system, or that when a donor’s funding ends, the system no longer functions. This again points to the lack of sustainability of the nutrition response in Cambodia.

Although not all data desired have been routinely collected, some data were available. The reason more were included in the HMIS and therefore collected was because certain activities were considered too new. According to a government official, there was a desire to await the outcome of a program review to know if a program was effective and thus worth including in a national data system. Further, some activities, such as the baby-friendly

community initiative (BFCI), were seen as having too many indicators to include in the HMIS. Indicators of impact, without a survey to measure them, also could not be included. According to a government official from the health sector, for some indicators, the system should work:

So now we have a database for SAM [severe acute malnutrition].

Hopefully now everybody will know very well how to enter data. Then, if you want to know which hospital, which child, just click. It's easy. It looks like an HIS. So we can for some, but not for all indicators in nutrition.

4) Capacity gaps: According to a number of participants, data were not used because of a lack of capacity. This gap ranged from a lack of understanding of M&E to the inability to

analyze and use data. Not understanding M&E and the data collected was said to limit one’s ability to translate learning into practice, particularly interventions that prevent stunting.

As an example, one government official expressed uncertainty about which indicators should be used to track outcomes. Another example offered by a funder who had worked with a government partner highlighted this person’s lack of understanding of the difference between M&E:

She didn't really understand the concept of what we were trying to do. So, when we say monitoring and evaluation, she thinks: ‘How many people attend the trainings?’ Just the idea of what evaluation is. She didn’t understand that we wanted to understand if we had an impact.

—Funder

This capacity gap was also said to influence which data were collected and emphasized as important. For example, during a training one participant observed that the focus was on

completing the forms—“tick here. It needs to look good”—and not on what you do with the data. According to this participant:

I don't think you can deal with this [lack of data use] before you deal with the lack of technical know-how because it means nothing to you. If you don't understand the importance, then you can collect as much data as you want.

—Funder 4.7.1 Summary

Effectively addressing young child chronic malnutrition requires that sufficient data be available and used for decision making. According to the majority of participants, this is not the current situation in Cambodia. Rather, participants believe appropriate investments cannot be made because the nutrition community does not know what works in Cambodia and how the

global evidence-base can be applied. They also reported that collected data are not routinely used, and outcome data, such as feeding behaviors and nutritional status, are not routinely collected. Data that are available, however, were said to be collected too infrequently to inform decision making. Further, according to participants, Cambodia does not currently have a fully functioning HMIS system, nor the M&E capacity required.