Back entry of data: how valuable is historical data in a new system?

[Mali Kambandu]

Back entry of data: as a new registry is designed, one consideration to be made is how valuable is old data in the new system. May participants share their experiences with back-entry of data when transitioning from one system to another? How much historical data should be stored in the new system? What has been most useful? What is most accurate? What is most cost effective? What lessons can be learned?

[Grégoire Lurton]

Hi Mali,

Here is some feedback on the change of the HIV care registries that was made in Guinea in 2012-2013.

We decided to transfer all data from previous registries in the new tools. This transfer was made by people from my group at the time (Solthis) and our partners at the MOH. This was a burdensome task as we had to manually copy a few thousands patients all over the country. Meanwhile, general feeling was it was worthy and the proper way to do it. Here are a few reasons for this decision and things we learned on the way.

• We wanted facility health workers to hit the ground running with this new tool, with no time lost for adaptation or data transfer. Chronicity of HIV thus made it necessary to transfer the backlog of data on patients already in care in the new registry. Data transfer was made during a visit by MOH personal in facilities right after initial training. After this, HW where able to use the registry in routine mode from the start.
• The data transfer was made by people from the MOH along with the facility HW. It turns out this was a great follow-up to the initial training as it was a real-life example, in a familiar context for HW. It was a good way for us to spot weaknesses in the initial training, and to update trainings and SOPs. 
• Also, having MOH people enter a large amount of data was an occasion for them to get a first hand experience in using the registries besides formal exercises. The later expressed this was useful for them in subsequent supervisions and work.
• This transfer was also the occasion for an audit of each facility's HIV - HMIS. Trying to get the most accurate information to transfer in new tools was a good way to spot inconsistencies in the data, problems with data circulation or other issues. In particular in some big hospitals, this was the occasion to solve some larger problems.
• At the beginning of the registries modification process, facility health workers were a bit reticent to what they perceived as a complication forced on them. Spending time in facility helping them to get set up with directly usable tools, and showing MOH workers were willing to put time and effort in implementing the new registries had a very positive role in the relationship between frontline HW and MOH personnal.

In the meantime, this process was long and costly. It was possible for us to make this investment at that time, but it may not always be the case. In retrospect, a rule of thumb in implementing new registries is probably to accompany the update process to a point where it is already working routinely, with no need to go back to previous tools (especially when computing reports). Data that has already been extracted or won't be reused (eg. regarding patients who finished follow up in the facility long ago) are probably not useful to transfer. The limit between what data to transfer or not depends on the type of data collected in the registry (patients follow-up ? drug consumption ? patients admissions ?...) the type of information you want to extract from it (follow up rates at 12 Month ?, monthly counts of cases ?) and how important system memory is for your organization.

Regards,

Grégoire

2016-01-28 0:24 GMT-08:00 Mali Kambandu <malika...@gmail.com>:

Back entry of data: as a new registry is designed, one consideration to be made is how valuable is old data in the new system. May participants share their experiences with back-entry of data when transitioning from one system to another? How much historical data should be stored in the new system? What has been most useful? What is most accurate? What is most cost effective? What lessons can be learned?

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