06 May 2014

Winfried Meissner – When big data helps cope with post-operative pain

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Handling and analysing large volumes of data related patient-reported pain is a challenging task, which could help patient experience less pain after surgery.

Modern information technologies allow medical researchers to draw on a huge pool of patient data. These are routinely assessed in hospital settings or through health care systems. Scientists may use these so-called big data to investigate specific research questions. The data also serve as a tool for improving patient care and management. The EU-funded project, PAIN OUT, completed in 2012, aimed at improving patient pain management after surgery.

The project’s database contains more than 40,000 data sets obtained from hospitals throughout Europe. Winfried Meissner, head of the Department of Pain Management at Jena University Hospital, Germany, coordinates the project and also its German counterpart, called QUIPS, which has been running for more than ten years. He talks to youris.com about the advantages and challenges of dealing with large volumes of patient data.

What is your approach to data collection in such a large scale endeavour?
Our aim is to establish a registry of data on pain after surgery. A special feature is that we do not only rely on what is in the medical files, but also ask the patients themselves. We collect data on structures and processes in hospitals, such as a patient’s medication after surgery. But we also collect so-called patient-reported outcomes, asking patients to assess pain intensity, pain interference or side effects. Patient feedback is an integral part of the project. At the core of the project is a highly standardised patient questionnaire, which we translated into 20 languages. This allows us to compare the patients’ reports across national borders.

How does this approach lead to better post-operative pain management?
The participating hospitals can compare their results to the results of other hospitals. Thus, they receive an immediate, web-based feedback on the quality of their pain therapy, which helps them identify deficits. There are tools that allow the hospitals to get in touch with other hospitals. This way, hospitals performing worse can learn from the ones performing better. We can also explore the data to answer various research questions. For example, we can evaluate certain therapies. Or analyse whether certain forms of surgery are more painful than others.

What are the advantages of approaches that use large data sets?
In our view, these data complement the traditional approach of evidence-based medicine. Usually, randomised controlled studies based on blinded interventions are the gold standard. These studies have strict inclusion and exclusion criteria and the group of patients is coherent. But often, this approach does not mirror reality. We can test whether the results of controlled trials actually work. And thanks to the high number of cases, we can analyse rare situations and patient groups such as very old patients, which will never be studied in controlled trials.

What are the challenges of gathering and working with large data sets?
One challenge is to standardise data acquisition. For example, the questionnaires had to be translated carefully. We had to put a lot of effort into testing whether people from different countries understood the questions in the same way. Another problem is that these data are obtained in addition to clinical routine work. It is challenging to control many of the factors that come into play. We have to apply advanced statistical methods, so-called multivariate approaches, to account for these factors. It is therefore essential to have experienced experts in the team. For example, we cooperate with biostatisticians from the European Center of Pharmaceutical Medicine in Basel, who give support in analysing the data sets.

How do you ensure patient privacy?
We work together with data protection agencies and ethics committees in all countries involved. Moreover, the IT Department of Leipzig University, Germany, that hosts the database is very experienced in overseeing clinical research and large registries. They ensure that all legal requirements, such as data security and measures against data loss, are guaranteed. In addition, the data set is completely anonymous. We neither save names nor dates of birth. We apply cryptographic techniques to ensure data security and protect the patients’ personal rights.

How will you ensure the future availability of the data?
Right from the beginning, the project was intended to continue even after the EU-funding ended in 2012. We have therefore linked it to medical societies, such as the International Association for the Study of Pain. The participating hospitals pay a fee, which ensures continuous funding. An important aspect is also that we enable the international research community to analyse the data under the supervision of the medical societies.

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