Ensuring data quality? Let’s walk in the shoes of Community Health Workers in Kenya and Malawi

By Kingsley Chikaphupha, Regeru Njoroge Regeru and Kate Hawkins

Data from community health programmes is essential in understanding their contribution to healthy lives and promotion of well-being of all. Unfortunately, the quality of data reported by Community Health Workers is often poor meaning – like community health programmes themselves – this information remains on the periphery of health systems and is not used by decision- and policy-makers at district and national levels.

Let us put ourselves in the shoes of a Community Health Volunteer (CHV) in urban Kenya:

Why should I worry about the quality of the data that I report to the Community Health Extension Worker (CHEW), a.k.a. my supervisor? Us CHVs are meant to meet with the CHEW monthly but she never calls us. I am still holding on to reports for the past two months because I don’t know where to take them. 

And wait – what does data quality even mean? No one has ever told me. When I was recruited as a CHV two years ago, I was replacing another volunteer from my area who had suddenly dropped out from the programme. He had to go make money to feed his family. I was recruited after one of my friends who is also a CHV introduced me to the CHEW for our community unit. She told me that I was lucky because a non-governmental organisation would be conducting a training on water, sanitation and hygiene (WASH) in a few days and that I could join that training and then start working. The CHEW took me to our Chief and he gave his approval and that was that. I attended training on WASH the next week and the CHEW gave me photocopies of a form she said I should use to collect data when I make household visits. I began visiting households in our community unit with my friend and then eventually by myself. When I first started using that form I noticed there was so much we are meant to write about mother and child health. No one has ever taught me about mother and child health! My friend told me I should record data using ticks and crosses but this confused me so I just use 1s and 0s. Some of the terms also confuse me – what exactly does skilled delivery mean?

Anyway – I’ll just keep doing what I’m doing because whenever we meet the CHEW she just picks up our forms and we never get any feedback.

Now let us put ourselves of the shoes of a Community Health Volunteer in rural Malawi:

My Health Surveillance Assistant (HSA), a.k.a. my supervisor, has just called for me to come and help him with data collection about how many children under five in my catchment area are up to date with immunization. Now what am I going to write on? I just bought a new notebook for school for my child last week – I guess I must tear out some pages so I have data to give to my supervisor. I wish we had a tool from the government – after all we are collecting data that goes into government forms used by our supervisors.

Community health workers have the potential to be the ‘eyes and ears’ of the health system. They are our first point of contact with communities, collecting data that should be an essential underpinning to decisions about health service provision. Yet as these vignettes illustrate, the ways which they are treated run counter to the frequently repeated claim that decision making should be evidence based.

And we can do so much better. It is time that all community health programmes took steps to demonstrate how much they appreciate community-level data, and the people who collect it.

We put forward the following six recommendations for community health programmes:

  1. Inform Community Health Workers why the data they collect and report is important.
  2. Provide Community Health Workers with the tools that they need to do the job and ensure these are designed with their input.
  3. Teach Community Health Workers how to complete their data collection and reporting tools and provide regular feedback and guidance on data management especially when new tools or processes are introduced.
  4. Support supervisors of Community Health Workers in analysis of community-level data for identification of gaps and increased responsiveness to the challenges facing their communities.
  5. Provide written guidelines and procedures for data management in community health information systems.
  6. Inform Community Health Workers how the data they have reported has been used in decision- and policy-making so that they can see the impact of their labour.