How Might We Overcome the Health Data Utilization Challenge?

Vx Data Insights
7 min readDec 17, 2021


7 Priority Areas for Intervention

This is the last story in the VxData Insights blog series and contains excerpts from the final Cross-Country Report. To read the full report and learn more about this work, please visit our project website.

During the VxData Insights study, the team conducted roughly 200 contextual interviews and observations with healthcare workers and managers from Community all the way up to National levels in Kenya, the DRC and Mozambique. Pictured above is a nurse in the DRC, reporting immunization data at a health facility.

Despite significant headway, routine immunization and new vaccine introductions still face strong challenges related to collecting and using quality data for planning, management, and performance improvement. Prioritizing and adequately addressing these challenges is difficult without understanding the full context in which they occur.

This story contains excerpts from the VxData Insights Cross-Country Report, which aims to provide a deeper understanding of the root causes of underutilization of data in immunization programs and highlight priority areas for intervention. This report is also available in French and Portuguese. For more about this work, visit

To address this need, the VxData Insights study took a Human-Centered Design approach to gather the perspectives and data-specific challenges of actors at all levels in the expanded immunization programs (EPI) in three countries — Kenya, the DRC and Mozambique.

Through roughly 200 conversations with healthcare workers and managers from Community all the way up to National levels, we gained a deeper understanding of the factors that lower participants’ ABILITY and MOTIVATION to utilize data for decision-making. These factors have been synthesized into the 8 Root Causes Framework (pictured below).

8 ROOT CAUSES for underutilization of data for decision-making: This framework was generated based on contextual interviews with healthcare workers and managers at all levels of the system in Kenya, Mozambique, and the DRC. 8 Root Causes — Access, Time, Tools & Protocols, Know-how, Working Conditions, Trust in Data, Agency, and Influence. These can be further organized around two factors — Low Ability and Low Motivation for use. — were identified. For additional details and information on how this framework was generated, please refer to the Cross-Country Brief.

The 8 Root Causes framework was shared with stakeholders in each country during a series of co-creation workshops. Based on input during these workshops, the team identified 7 Priority Areas for intervention that cut across all three geographies.

In compiling these Priority Areas, we did not focus on what’s new, rather we set out to identify what is most impactful for change. This means we evaluated all of the Root Causes and Sub-causes to identify the ones that were both high priority to the system actors and relatively less difficult to fix. As such, while some of the Priority Areas may not be new, we believe they are crucial to highlight.

7 PRIORITY AREAS for intervention — Based on our research in Kenya, Mozambique, and the DRC as well as input during co-creation workshops, the team identified 7 Priority Areas for intervention that cut across all three geographies. For each of the Priority Areas, we have indicated the relative priority level for the three geographies, indicated by black dots. One dot indicates medium priority in a particular geography and three dots indicate highest priority.

Increase the number and competencies of data-proficient personnel, especially at lower levels of the system

While there is a growing emphasis on improving data quality and utilization, few data-specific roles exist within the system, especially at the lower levels. Most data collection, reporting, and review work is done by personnel who don’t consider it to be a core part of their job, meaning the work is often rushed, deprioritized, or outsourced to unofficial workers.

Adding or developing additional data-proficient personnel throughout the lower levels of the system, as well as carving out dedicated time for completing specific tasks will help to establish data as a priority and create opportunities for more meaningful utilization of data by all actors.

Ensure steady availability of basic resources needed for recording, managing, and accessing data

STORIES FROM THE FIELD -SHORTAGES OF DATA COLLECTION TOOLS DEMOTIVATE AND LOWER DATA QUALITY: Shortages of paper tools needed to collect and report data are very common. When facilities run out of official tools, staff have to make photocopies or use plain lined notebooks to capture the data. They may reproduce the original tool or exclude and add new data fields that feel more relevant to their decision-making (such as next vaccination date and contact numbers). This makes the Sub County data m
STORIES FROM THE FIELD — SHORTAGES OF DATA COLLECTION TOOLS DEMOTIVATE AND LOWER DATA QUALITY: Shortages of paper tools needed to collect and report data are very common. When facilities run out of official tools, staff have to make photocopies or use plain lined notebooks to capture the data. They may reproduce the original tool or exclude and add new data fields that feel more relevant to their decision-making (such as next vaccination date and contact numbers). This makes the Sub County data manager’s job a lot more difficult, creating inconsistencies between the reports and the digital system. The additional work and possible cost of photocopying and supplies also gives facilities an excuse to not submit reports, leading to long delays and data gaps. (Kenya)

Some managers and healthcare workers have data skills and appreciate the value of good data, yet are unable to perform their basic data-related duties due to a lack of funds for airtime, internet, and transport or reporting tools.

Ensuring that the basic resource needs are consistently met is a cost-effective way to increase the productivity of healthcare workers and managers, meaning skills and resources already on the ground will be utilized more effectively.

Redesign Facility level tools to reduce workload & better support decision-making

Facility level tools are siloed according to how the data needs to be used at higher levels and not designed with facility workflows or the data-needs of frontline healthcare workers in mind. This makes data collection duplicative and unnecessarily time-consuming and forces facility staff to create additional tools to utilize the data for their needs.

Redesigning tools around the facility workflows and information needs will reduce the amount of time needed to collect the data and lower the threshold for data utilization at the facility level.

Speed up data-input and improve data accessibility in DHIS-2

The current DHIS-2 user system experience is poor, often the result of bugs or system lags that hinder the ability to input, manage or retrieve data. Inconsistencies between the data fields in paper reports and DHIS-2 significantly slow down data input and, at times, can introduce errors.

Modernizing and debugging DHIS-2 could mean significantly less time spent on data entry and more time for data verification and analysis. Leveraging existing DHIS-2 apps to provide access to data on mobile devices (with more efficient offline capability and, clear guidance on interoperability when computers and internet are available) could also make data more accessible to busy managers and Facility level staff.

Foster more frequent, two-way interactions around data and decision-making between actors at all levels

STORIES FROM THE FIELD — WHATSAPP GROUPS CAN PROMOTE INTERACTIONS OUTSIDE OF REGULAR REPORTING STRUCTURES: The Mashako Plan, a nation-wide routine immunization revitalization initiative, has encouraged the use of smartphones, specifically through WhatsApp groups. Henri, a Zonal Medical Health Officer in a semi-rural health zone near Kinshasa, noted that to transfer data faster, send reminders in case of delays, communicate new guidelines or share knowledge it was very useful; however, since not all of his heads of facility had received the promised money to cover their internet plans, some of his data was still untimely and lacked the necessary back and forth for quality control. (DRC)

Interactions between system levels tend to be sparse and one-way, with data primarily moving up from the Community and Facility levels. Insights from the collected data rarely make their way back to the facilities and feedback is given only when data is missing or inaccurate, leaving lower level actors feeling disconnected from the decision-making process.

With the integration of more streamlined, flexible and individualized interactions between levels, we can increase and promote involvement and ownership, accountability, sharing, appreciation and use of data. This can also promote better data understanding and awareness across levels and transform currently passive interactions into more engaged, trusted and useful ones.

Improve supervision effectiveness, shifting away from one-off checklist visits and towards providing continuous, constructive feedback over time

With limited resources and time, current Supportive Supervision activities are mainly geared towards enforcing protocol and catching major issues. Because the visits are infrequent and rarely EPI-specific, the emphasis is put on going down the checklist to take the “facility vitals” over building skills and having meaningful interactions with staff. Feedback is also not well documented or shared with staff. Not surprisingly, healthcare workers tend to see themselves as protocol-followers, not decision-makers.

With more emphasis placed on skill-building and better documentation and continuity between visits, Supportive Supervision activities and opportunities
for mentoring and coaching (such as via well-facilitated and interactive review meetings or facility monthly exchanges that include community representatives) have the potential to improve healthcare worker motivation and agency.

Improve the budgeting process by engaging political and administrative decision-makers and providing timely data on actual funds available

STORIES FROM THE FIELD — PARTNER FUNDING CAN COME AND GO, YET PROGRAMS RELY ON IT FOR CORE ACTIVITIES: Nestor is a Zonal Head Nurse in a rural geography of the DRC. He laments the lack of transportation available for him to access his facilities to verify data or give feedback. When their area was a “red zone,” because of the Ebola outbreak, they received motorcycles and funding for gas, which he thinks improved the data quality greatly. Now that the epidemic has been resolved and their area was declassified, partner aid has stopped rolling in and he is unable to accomplish his required two monthly “retro-information” (feedback sessions). This feels like a punishment and leaves Nestor nervous that all the efforts put into improving data quality will go to waste. (DRC)

A lot of time and resources, especially at the Subnational level, are dedicated towards official, data-based planning procedures such as generating work plans and annual budgets, intended to help utilize immunization program resources more strategically. Unfortunately, these activities frequently fail to reflect the reality on the ground, as the data used in the planning is not always accurate. Furthermore, those ultimately responsible for allocating money towards the immunization program don’t always have the necessary context to set appropriate priorities.

Plans are made based on optimistic anticipated government allocations and/or partner funding that may not materialize. When funding does arrive, it is usually less than projected and frequently delayed (particularly for at least the first three months of the fiscal year and sometimes longer). Local managers therefore run out of resources and/or are forced to abandon their long-term plans to address more immediate needs such as paying overdue bills and taking care of emergencies.

Political and administrative decision-makers (such as the Executive Committee and Assembly members) need to be more proactively engaged to ensure that funding priorities are guided by data and that more accurate funding information is available and clearly communicated for planning purposes. Partner funding mechanisms also need to be more predictable and timely, so they can be incorporated into the official planning work.

This story contains excerpts from the VxData Insights Cross-Country Report. Written by Emilia Klimiuk.

The VxData Insights study is a joint research effort between Sonder Collective and John Snow Inc. (JSI) to apply the Human-Centered Design approach in order to uncover and prioritize data specific challenges that healthcare workers and managers at all levels within a country encounter in delivering immunization services in Kenya, the Democratic Republic of the Congo, and Mozambique.
Sonder Collective specializes in the application of Human-Centered Design to social and health challenges, particularly in low resource settings. The Sonder team has intensive experience conducting design research in maternal and newborn child health, sexual and reproductive health and rights, community health, health supply chains and HIV in Sub-Saharan Africa. John Snow Inc. (JSI) is a public health management consulting and research organization that works to improve health outcomes through strengthening health systems in partnership with country Governments. JSI works across immunization, maternal newborn and child health, nutrition, supply chain system design, paper based and digital information systems globally. JSI has led on immunization on USAID flagship projects like the Maternal and Child Survival Program, TSHIP and has been a key partner on MEASURE Evaluation for the past 20 years.



Vx Data Insights

A Human-Centered Design study in Kenya, DRC, and Mozambique to understand how data is used for decision-making in delivering immunization services.