Mobile devices are often described as an opportunity to increase efficiency and reduce costs in healthcare. While those expectations are certainly widespread, the data backing it up isn’t quite there yet.
A recent study published by a team based at the Carter Center in Atlanta shares their experience in utilizing a tablet-based disease surveillance platform and compares it to more traditional methods.
Far beyond a small pilot test, they evaluated this tablet-based system in a project that collected data from 12,000 households in Ethiopia. In comparing the tablet-based approach to the traditionally used methods for collecting data, they found significant gains in efficiency, accuracy, and speed. As far as costs, they found the two methods to be equivalent but noted that the fact they could reuse the tablets later would likely lead to long-term cost savings.
As a leading public health organization, the Carter Center regularly performs large scale surveys to collect data to help guide interventions. Traditionally, the data is collected by trained field workers using paper forms which must be printed and shipped to relatively remote locations. The data must then be securely collected and transported back to a central location for manual entry in a database for analysis. The opportunity here is fairly obvious.
Starting with a comprehensive needs assessment, they developed an Android app for tablet devices for data collection by field workers. The app was then piloted in a smaller group to help the developers understand the real world constraints and improve the design of the app before launch. Teams were trained on the tablet in a small-scale setting before being deployed to the field to collect data from 12,000 households in total. Process data and results were then compared to a similar survey collecting the same information in a neighboring part of Ethiopia 7 months prior. That survey reached just over 9,000 households.
The needs assessment and resulting platform is a particularly interesting read. For this field work in relatively remote and resource poor settings, they selected a 7 inch Android tablet with built-in GPS, camera, and removable SD memory. One particularly interesting component included was the use of a QR code scanner app to link collected specimens to the survey data.
In this experience, the reported total time to collect and process the data was significantly less when tablets were used as opposed to the paper-based method–511 person-days versus 790 person-days. They additionally noted that while it took 1 day to put the survey into an app format and load it on to 20 tablets, it took 18 person-days to print/collate/staple/distribute the 9,000 paper surveys. There were also fewer data entry errors, specifically when it came to identifying data. In the field, they noted that the paper group (21 teams) took 26 days to complete their survey of 9,000 households while in the tablet group (13 teams) it took 38 days to survey 12,000 households – a savings of 52 person-days.
Oddly enough, when they collected more in-depth process data in the pilot study before this large scale deployment, there was no significant difference identified in the time required to collect the data. They also noted some unexpected downsides. There was a slightly higher rate of refusal of households to participate when a tablet was used vs. paper (0.8% vs. 0.3%). They also noted that there were more problems with missing geographic coordinates in the tablet group than the paper group for unclear reasons.
As far as costs, they noted that the tablet platform incurred an additional ~$10,000 in expenses for the devices, battery packs, adapters, and SD cards. In comparison, the cost of printing the paper surveys and then manually entering the information into a database was nearly $14,000. While they call these costs roughly equivalent, they make the important point that the $10,000 in device costs are a fixed expense – they can be used again on the next large-scale survey, thereby conferring significant cost savings.
This real-world, large-scale experience offers some extraordinary insights in the potential benefits of mobile technology in healthcare. It’s particularly interesting to note that while the large-scale deployment indicated significant gains in efficiency and likely cost savings, the pilot data suggests that it is not just because it’s faster to enter data into a tablet.
While a lot of the time saving is in the work that happens before and after the field, the authors reported efficiency gains in the field work alone as well–an observation that is at odds with what they found in the pilot study, where each encounter was timed. Given that the pilot was conducted after 1 day of training, this observation suggests that it takes more time for users to really become adept at using the tablet and realize the associated improvement in efficiency. Overall, this study highlights nicely both a well thought out process for utilization of mobile technology and subsequent evaluation of its effectiveness.
Reference: King, J. D., Buolamwini, J., Cromwell, E. a, Panfel, A., Teferi, T., Zerihun, M., Emerson, P. M. (2013). A novel electronic data collection system for large-scale surveys of neglected tropical diseases. PloS one, 8(9), e74570. doi:10.1371/journal.pone.0074570