Assessing the functionality of the routine health information system in health facilities of Yaoundé, Cameroon: a cross-sectional study

Imagine a city where every shop, school, and hospital keeps a daily diary of what happens inside its walls. Now, imagine that the mayor needs to read all these diaries to decide where to send more teachers, which roads to fix, or how to stop a flu outbreak. If the diaries are messy, missing pages, or written in a secret code no one understands, the mayor is flying blind. This is the world of Routine Health Information Systems (RHIS). It's not just about fancy computers or digital apps; it's the backbone of how a country knows if its people are getting sick, if doctors are available, and if the health system is actually working. Think of it as the nervous system of a nation's health: if the signals (data) don't get from the fingertips (hospitals) to the brain (government), the body can't react to pain or danger. When this system works well, leaders can make smart choices to save lives. When it fails, resources go to the wrong places, and diseases can spread unnoticed.

In the bustling capital city of Yaoundé, Cameroon, a team of researchers decided to check the pulse of this nervous system. They didn't just look at the computers; they looked at the whole machine: the people who write the reports, the rules that guide them, and the way the data is actually used to make decisions. They treated the health system like a complex engine, checking if the fuel (data) was flowing smoothly from the pistons (hospitals) to the steering wheel (decision-makers). Their goal was to see if the engine was running hot and fast, or if it was sputtering and stuck in neutral.

The Great Health System Check-Up

The researchers visited 88 different health facilities across six districts in Yaoundé between November 2024 and July 2025. They used a special "report card" tool called the MEASURE Evaluation RHIS rapid assessment tool. Think of this tool as a giant checklist with 97 questions, ranging from "Do you have a plan for data?" to "Is your computer working?" and "Do you actually read the reports you send?"

They scored each facility on a scale of 0 to 100%. If a facility scored 60% or higher, it was considered to have "good functionality." If it was below 60%, it was "poor."

The Big Picture: A Mixed Bag
The results were a bit like a classroom where some students are acing the test while others are struggling to pass. Overall, 65.9% of the health facilities (58 out of 88) had "good" functionality. That's a majority, but the researchers warned that this isn't a reason to pop the champagne yet. It's more like a student who passed the math test but failed the history and science sections. The system is working, but it's fragile.

The Engine vs. The Driver
Here is where the story gets interesting. The researchers broke the health system down into four main parts, like checking different parts of a car:

1. Data Collection and Processing (The Mechanics): This is the part where data is gathered and written down. This was the strongest part, scoring 46%. It's like the car's engine is actually running; the pistons are firing, and the wheels are turning. The facilities are good at collecting numbers and sending them up the chain.
2. Data Analysis and Use (The Navigation): This is about looking at the numbers to make decisions. This scored 44%. It's okay, but not great.
3. Data and Decision Support Needs (The Map): This checks if the system knows what information it actually needs. This scored 39%.
4. Management and Governance (The Driver and the Rules): This is the most critical part—the rules, the leadership, and the people in charge. This scored the lowest at 29%.

The researchers found a huge gap here. The "mechanics" (collecting data) are working better than the "driver" (governance and management). It's as if a car has a powerful engine but no steering wheel, no driver's license, and no one to tell the driver where to go. The system is good at making the data, but bad at managing the people who make it.

The Human Factor
The weakest link of all was Human Resources, which scored a dismal 11%. Imagine a factory where the machines are brand new, but the workers haven't been hired, trained, or given a paycheck. That's what the data showed. There is a severe lack of dedicated staff to manage health information. The researchers noted that while some facilities have people doing the work, there isn't a strong, organized structure to support them. It's a bit like trying to build a house with a great blueprint but no masons.

The Neighborhood Effect
The study also found that where a hospital is located matters a lot. It's like a city where some neighborhoods have great streetlights and others are pitch black.

• The Winners: The Efoulan district was perfect, with 100% of its facilities scoring well. Nkolndongo (91.3%) and Biyem-Assi (84.2%) were also doing great.
• The Strugglers: On the other side, Cité Verte only had 20% of its facilities doing well, and Djoungolo was at 22.7%. Nkolbisson was right in the middle at 50%.

This suggests that the local "coach" (the district health team) makes a huge difference. In the winning districts, the coaches are probably giving better feedback and support. In the struggling ones, the facilities are left to figure it out on their own. Interestingly, whether a hospital was public or private didn't seem to matter much; both types had similar success rates.

The Feedback Loop
One of the biggest problems found was the "feedback loop." Imagine a student handing in a test and never getting it back with a grade or comments. That's what many health facilities are experiencing. Only 27.1% of facilities said they got regular feedback from the district level about the data they sent. Without feedback, the people at the bottom don't know if they are doing a good job or if their data is being used. The data use in Yaoundé seems to rely on the personal motivation of individual staff members rather than a system that forces everyone to use the data.

What This Means for the Future

The paper concludes that while Yaoundé's health information system is improving, it's standing on shaky ground. The researchers suggest that if the government keeps buying new computers or software (the "tools") without fixing the "driver" (governance) and hiring/trainings the "masons" (human resources), the system won't get much better.

They argue that the next step isn't just more technology. It's about building a strong foundation: hiring dedicated data managers, creating clear rules for leadership, and making sure the district teams actually talk back to the hospitals. If they do this, the "engine" they've already built can finally drive the car forward. Without these changes, the system might keep running, but it won't be going anywhere fast.