Many of the challenges in clinical research stem from the experience gap between researchers and their patients. The research teams who conduct clinical trials do so with years of specialized education and training under their belt, while most participants journey through the patient experience as laypeople. This disparity creates a mandate for the development of strategies and tools that can reconcile researchers’ technical language and medical expertise with the common language to which most patients are restricted. One of these tools is dictionary coding, a solution that streamlines the process for translating patient-reported symptoms into official terminology. Dictionary coding has appeared among the software offerings of the electronic data capture (EDC) industry, and has simplified the process of coding and recording patient-reported adverse events for Sponsors and CROs that use it.
How does it work?
Medical coding is essential for ensuring that the adverse events reported by clinical trial patients are recorded and analyzed accurately. One way to do this is to submit a case report form (CRF) populated with adverse event data to a professional medical coder, who works to link the patient’s description to the corresponding medical terminology for that adverse event. When done manually, however – especially in larger, multi-site trials in which a coder at one site processes data collected at another – this can take time and even risk compromising data accuracy.
Dictionary coding catalyzes this process. Here’s how it works:
- An EDC software integrates with one or more of the numerous electronic medical dictionaries available to the research industry
- An investigator enters a patient’s description of an adverse event into the EDC system verbatim – the patient may report that they “have a short headache every few hours” or that they “keep getting a pins-and-needles feeling in the same spot on my back”
- Key words from that patient’s description are processed by the medical dictionary, which matches them to an appropriate ailment category
- Medical coders are able to code the adverse event more quickly thanks to the more organized and specific data provided by this process
Dictionary Coding and Phase I
For the purposes of keeping things organized and efficient, dictionary coding may be more beneficial to mid- to late-phase clinical trials, in which patient populations extend well into the triple digits and thereby necessitate the use of multiple trial sites. But in terms of the overall purpose of a clinical trial, the feature can be a particularly useful resource to Phase I trials. As the primary endpoints of a Phase I trial are not the efficacy of a drug but rather its safety and dosage profile, the analysis of adverse events plays a front-and-center role, and any tool that streamlines the recording and analysis of adverse events thus enhances researchers’ most fundamental work. And the ability to quickly and accurately document the ways a drug affects patients at various dosage levels not only allows researchers to more quickly create a safety profile of that drug, but to respond to the timeline pressures from Sponsors that can be particularly intense in Phase I.
On a more interpersonal level, dictionary coding can allow for better communication between patients and researchers. The same aspect of the nature of Phase I that makes adverse event analysis so important – that is, the as-yet-undetermined safety profile of a treatment – is what causes the “guinea pig” fear among potential patients that all too often complicates recruitment and retention efforts in Phase I. If patients feel empowered to report their reactions in their own words, and that this is sufficient for researchers to take appropriate action in a timely fashion, it can humanize patients’ perspective on clinical research, make them feel valued and listened to, and quell the sense that they’re subject to an esoteric process they don’t feel connected with.
Dictionary Coding with Medrio
Today, a number of EDC companies have incorporated dictionary coding technology into their software. Among those companies is Medrio, which has integrated with various coding dictionaries including MedDRA, VedDRA, WHODrug, and others. Medrio takes great care to consistently use the most up-to-date versions of them, with a trained support staff to guide customers through their implementation.
Perhaps there is no other venue in clinical research in which communication between researchers and patients is more important than it is in Phase I. The industry is fortunate to have resources like dictionary coding to allow all involved parties to speak their own languages, to bridge the experience gap that often makes comfort and satisfaction among patients elusive.