Quality Management in Data Driven Medical Research

Abstract

• Introduction

Medical Research faces measurements growing in numbers, in resolution, and in complexity under nationally different legal and ethical regulations. The internet is pushing this development. Well-known and new publication platforms become more and more divers. Publishing companies have been bought by money investors and changed their value systems. All this leads to unmanageable data oceans with billions of not easy to validate published “results”.

• Background

The development over the last two decades is reflected in some publications. The National Library of Medicine in Washington is analyzing this historical change in collaboration with other national libraries, e.g. NLM, Washington and ZBmed, Cologne. International organizations are trying to find solutions for these problems, e.g. addressing “open science”, “FAIR data” or other concepts. An important irritating aspect is, that the costs for reading publications may be very different – motivating persons with little resources to utilize primarily “free” publications.  All these changes make it very difficult to understand, how literature and knowledge management will be in the future, how modern libraries have to work, how young scientists and health professionals have to be trained regarding updating their skills etc. etc.

• Goal

To derive some general recommendations for national strategies for the digital transformation of medical research and health care based on lessons learnt in different countries.

• Material and Methods

Strategy papers from Germany, the EU, and other countries are evaluated by the German Council for Information Infrastructures (RFII). These results are reflected based on personal activities in relation with NLM and ZBmed. In addition it is reflected how long the learning process took in Germany and how difficult it is in Germany to update the existing scientific and clinical systems to deal with such changes.

• Results

The key success factor of science management has become the way how data is handled, its origin documented, and its use checkable by third parties. The uncontrollable amount of low-level publications has to be massively changed to get to transparent and handable new forms of scientific exchange. Validation of results became more important than ever.

The Göttingen University and its integrated Medical School and teaching hospital (UMG) have been addressing these issues over many years already – with very different success. The paper reports on many findings out of this process to describe how complex the change from the traditional clinical research and clinical care to the highly dynamic knowledge management of the future will be. As one consequence, the University, the UMG, and a Polytec have established the Göttingen Medical Campus to address these new developments together. Since 2000 about new Professorships were started dealing with these issues in various faculties and working together in the Campus Institute of Data Science (CIDAS).

Another learning process has been the building up of national collaboration platforms in science since 1999 – starting with the Telematics Platform for Medical Research Networks (TMF) – and mostly funded by the national ministry of Research (BMBF) in Berlin. The latest new structure in this context are the national Medical Informatics Initiative (MII) and the National Research Data Infrastructure (NFDI).

The presentation tries to address important experience from these processes in the last two decade. These “learnt results” are clearly convincing how much impact the new data rich science world will have on research organizations, funding programs, and training procedures for scientists. It cannot formulate conclusions but prove that we are in a historical change process taking several decades.

• Conclusion

Institutions and countries who want to play an important role in the scientific world have to strategically work to move away from two outdated realities:

(1)   From non validatable publications in great numbers to serious modern forms of publications based on published and checkable data and data provenance information.

(2)   From small and often instable analog (specimen) and digital data collections in isolated small research labs to professionally handled data management sites of financially stabile organizations on the levels of medical schools or universities.

(3)   From interested computer fans to professionally trained data curators and to physicians enabled to update constantly their clinical work methods based on support systems for them and for their patients. The support systems reflecting and allowing a special individualized clinical decision at the state of art of clinical research.