Everyone Loves a Story
“Tell me a fact and I’ll learn. Tell me a truth and I’ll believe. Tell me a story and I’ll remember it forever” – Native American Proverb
The mobile health field is at its core an incredibly personal field. There are few industries where your successes and failures are tied so tangibly to improvements in an individual person’s life. Whether it’s a nutrition intervention in Africa or a mother and child health program in India, there are almost always great individual improvements to be seen.
So why the do we talk about this stuff like we’re reporting on the stock market?
In my first months in this field I was surprised to see how much vocabulary and acronyms (so many acronyms) it was necessary to learn. It isn’t uncommon to hear a phrase like “Our mobile delivery and tracking intervention is driving towards meeting MDG5 and our M&E department has a promising study with a significant p-value in the works.” I understand the need for short-hand to aid communication – all industries joke about their acronyms – but I think it is important to remember our audience and make sure we can still communicate our ideas and our successes to the uninitiated.
I gave a presentation recently to an audience of mixed familiarity with mHealth and needed to make sure it would be accessible to a broad audience and the main points would be remembered so I tried to introduce each topic with a story as well. It’s easy to say “We need to work with users to design the best solution.” But our point will resonate even better if it is delivered in an engaging manner. Besides, everyone loves a story!
Here’s a few I presented earlier, but I’m sure everyone has better ones:
The importance of user-centered design
A few months ago I was visiting a village in Zambia where we planned to give phones to each of the community health care workers. They would use the phones to synchronize data once a day with the district office. We had been told by the district officers that mobile connectivity wouldn’t be an issue in the villages and we designed our program with that in mind. However, when we arrived at the village we realized we had no service on any of the carriers.
This was a major problem as the village was remote and travelling to get a connection would be very difficult. Our program hinged on the data being synchronized every day. We started brainstorming ideas – could a more expensive phone get a signal; perhaps we could convince the mobile operators to expand coverage (not likely); should we buy the workers bikes to ride to where reception was? We didn’t have any real viable ideas when one of the local village workers overheard and stopped us. “No, no, no,” she said. “Do you see that ant hill in the distance? That is where we get our reception. Every day, at five o’clock, I will go stand on that ant hill and hold my phone up in the air to synchronize. It will be fine.” This was apparently a well-known solution in that village and one that everyone was used to doing.
In the mobile health field it is important to work closely with the program participants. Often times the best solutions will come directly from the community members and users themselves. The perspective and local knowledge they bring is vital to the success of any program and often results in simple solutions to seemingly intractable problems.
The importance of tracking individual stories
My mother used to teach a class of 7 year olds at our local school. When it was time to return from the cafeteria to the classroom she would count the students to make sure she didn’t leave anyone behind. One day, though, when she got back to her classroom, she had two boys that she didn’t recognize in her class, and two of her students were missing. Some of the kids had gotten mixed up, but my mother had counted the correct number so she didn’t notice the mistake. After some considerable panic, she located her students in the classroom next door and avoided a crisis. After that day, though, she always confirmed each student individually.*
Aggregation is a necessary short-hand when we are dealing with large groups of people and data. This is especially true in health interventions where the data sets are large and communication channels are often lacking. However, just like happened to my mom, there are dangers in relying too heavily on aggregations. It is important that we do not lose the individual story of a beneficiary. This is one area where mobile technology can make a big difference. If data collected on the ground can be transmitted back to management without losing the details we can start getting better insights and making more informed decisions.
In one example, I visited a clinic that tracked admissions and discharges of malnourished children. Each month they reported to headquarters the total number of children admitted and the total number that were discharged as healthy. The numbers were generally pretty good for this clinic. But what these aggregate numbers disguised was the re-admittance rate of the discharged patients. Anecdotally, the local clinicians knew that they were seeing many of the same children returning weeks later with the same condition, but the aggregate numbers they reported had no way of showing this. The administrative burden would have been too great to track, report, and interpret individual patient data in their paper-based system, so they were only able to track the aggregate numbers. With mobile data collection and reporting they would have been able to report much more detailed patient data with less effort.
*The movie “Home Alone” is the best example of this type of counting mix-up going terribly and hilariously awry.
The importance of providing value to all users
I used to work for a private company that required all employees to submit time cards detailing every task they did down to the minute level. Trivial events like a three minute phone call or a ten minute coffee break had to be diligently recorded and submitted. One week, while in a rush I filled my time card out incorrectly, but to my surprise, no one said anything. A tremendous amount of data entry was being asked of me, I was receiving no value from it, and I couldn’t see the value derived up the chain either. After a few weeks you can probably guess what happened … nobody was filling out their time cards any more.
Every time we implement a process, we are making a chain of people who must act together to achieve success. If that chain is broken anywhere along the way the process will fail. The timecard system at my old company failed because the people it relied on to fill them out received no value from it. In health interventions, we rely a tremendous amount on the diligence of community health workers (many unpaid) to achieve success. It is crucial that those workers also see the value in the data they are collecting and the effort they are putting forth.
With mobile tools there is a temptation to collect massive amounts of data simply because you can. But for every data collected you should ask the questions “Will I make any specific decisions based on this information?” and “Is the burden to collect this data worth the value I will derive from it?” If the answer to both of those questions isn’t ‘yes’ you may need to rethink the value of the data you are collecting and the burden it is putting on the workforce.
The importance of measuring progress
I grew up near a lake and would often try to swim to a dock on the other side. I would put my head down and swim as hard as I could, but it is hard to swim a straight line and I would inevitably drift off course. The longer I swam without looking up, the more off-course I would find myself when I finally did check. Even if I was pointed just slightly off-course, it would eventually add up to being way off the mark if I didn’t check my progress frequently enough. (A few times I had actually turned all the way around and was swimming back to where I started). The key to making it to the other side was not just swimming hard but also constantly checking and adjusting my direction.
Health interventions have a similar problem. We need to be able to swim for a bit and then pop our heads up and make minor course corrections. Perhaps we realize we should be delivering inputs slightly differently, or maybe adherence to follow up schedules is below expectations and training is required. But what these decisions require is getting the right information into the right people’s hands in a timely manner. This often proves difficult due to the burdens of data collection. In many interventions, a thorough baseline is taken at the start of the program to help understand the problem and direct our actions. However, it may be a few years before the next baseline is taken to evaluate progress. By that time, minor issues that could have been caught and remedied early on may have quite a large cumulative effect. It was a 15 minute swim to the other side of that lake, but if I had simply swam for 15 minutes without ever looking up, I never would have hit my target.
Through the use of mobile technologies we can lower the barriers gathering this evaluation information so quicker decisions can be made from it. Often, taking a full baseline requires hiring a temporary workforce, distributing thousands of surveys, manually entering the data into a computer, and finally analyzing the results. Mobile technology can both speed this process and also enable programs to quickly collect data points that may not be associated with a full baselining effort. In this manner, a constant data stream flows into the organization to enable data-based course corrections to happen as early as possible.
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