In (mobile) data we trust
Henrik Nakskov from NNIT discusses the importance of data integrity when you make clinical trials data mobile.
Gaining increased mobility has long been a goal of medical professionals and trial sponsors alike. Mobility holds promises of enhanced efficiency and may drive growth, but it also brings its own set of challenges that must be addressed. If we look at clinical trials, information is highly sensitive and subject to strict processes of validation.
When you mobilise clinical trials data, medical professionals need to be able to have unconditional faith in the figures. The consequences of making a decision on a non-validated data foundation can be fatal - in terms of patient safety, and in terms of operational and financial jeopardy for companies developing drugs. Hence, the same strict regimen needs to be persevered in mobility in order to maintain the data credibility.
Standardise first, then mobilise
According to Henrik Nakskov, life science industry expert at NNIT, there are four areas the life science business must deal with in the process of going mobile:
- standardisation: induce unity and structure via processes
- data management: employ metadata and master data governance
- mobility strategy: align mobility with the overall business strategy
- knowledge management: how do people collaborate and what do they require from IT?
Understand the relation between variables
In an area as unpredictable as clinical trials, one can never guess how a single change can affect an entire system. As the trial process gets more complex and the number of variables increases, understanding causality, designing adequate processes and finding a way of mobilising theimportant pieces of data, at any time and through any mode, becomes vital.
Mobilise the vital safety data
For sponsors, who are held responsible if something goes wrong, data integrity is very much a matter of urgency. Also, they are not in a position to continuously monitor all the data associated with a trial. They want to be able to extract the most important information from a vast pool of dynamic data.
"Safety considerations mean that data monitoring is a very big part of clinical trials today," Nakskov explains. "Sponsors travel a lot and are increasingly eager to get the conclusive data on the fly - especially the deviant data, which is why signal detection and alerts when data deviate from the expected must be prioritised."
Metadata and master data governance
Being able to trust in data is also contingent on proper data management and the employment of metadata and master data governance. This method is widely adopted and allows you to track a data element all the way from the origin through to the receiver.
"We view metadata and master data as tools, not just theory," says Nakskov. "Each time a data element goes from one part of the chain to another, we attach metadata. This tells you where the data has come from and which processes it has been through.
"It may seem ironic that in order to control the amount of sensitive data, more data is added. But it is the only way to ensure the integrity of data and allow increased mobility," says Nakskov. "However, the problem with metadata and master data is that many companies don?t have a unified DM governance for all systems, so you may enrich with metadata and master data, but differently within each system. As a consequence, data integrity is at stake. This once again takes us back to the issue of standardisation - quite simply, there is no short cut if you want to be able to trust mobile data".
Apart from employing metadata and master data governance, companies as a minimum must consider:
- which data needs to be mobilised
- which core systems need to be mobilised
- which processes will ensure validated data.