Health Information Management: Integrating Information Technology ...

STRATEGY, IMPLEMENTATION AND EVALUATION 201
organizational, professional, economic, ethical/legal issues) that come to play in
such decisions and generate a balanced judgement.
Combinations of qualitative and quantitative methods in information systems
evaluation have been made—albeit infrequently—since the end of the 1980s. In
such studies, qualitative results were usually seen as the exploratory ‘first steps’
that could at best inform the ‘real’ research of generating hypotheses to be tested
using experimental or statistical techniques. During the last decade, more
symmetrical integrations have been proposed under the label of the
‘multimethod’ approach, where the different methods each produce their own
data, without an implicit proposed hierarchy between them. One of the reasons
for the importance of ‘multimethod’ research is that the use of different methods
is needed to capture the diverse and diffuse nature of information systems’
effects. Another reason is to strengthen the robustness of research results by
looking at the way in which research results coming from different methods
support each other (or not), which is called triangulation.
Though we agree with these insights, we would like to argue that this is still a
very loose ‘integration’ of qualitative and quantitative methods. At best,
qualitative and quantitative researchers cooperate, and jointly decide on issues
best amenable for qualitative or quantitative evaluation. Having thus ‘divided the
turf’, studies are usually done rather independently and, more often than not, the
results discussed follow these borders drawn. In addition, the results from the
different studies are often phrased in such different idioms that ‘integration’
becomes completely (practically and theoretically) impossible.
True integration requires joint design and execution of the study, where data
from one method are used as input for the other. Hereby we mean to take results
from one method as a starting point for research of the other method. In this way
it is possible to capitalize on the strong points of each method in order to
gain more understanding in the ‘that’ and the ‘how’ or’ why’. After all, it is
obvious that having established that something is the case is a rather useful input
to investigating why that is so. And, vice versa, the insight ‘how’ a specific effect
is achieved can be greatly strengthened by the knowledge how often this is so.
Explained like this, the interrelation of the two methods becomes almost all too
obvious. Yet truly integrated designs are still rare.
Using results from one method as input for the other makes it possible to
capitalize on the strong points of each method and increases the understanding
and strength of the overall results. Applying methods in this way supposes a
careful sequencing of the design. Qualitative research often is a prerequisite for
quantitative research, because qualitative methods are best in identifying and
selecting research topics for investigation. Quantitative research can, after that,
be used to quantify these topics. Interpreting the results from quantitative
research, subsequently, requires qualitative methods. For example, to conclude
whether the results can be regarded as ‘bad’ or ‘good’, or to understand
fluctuations or apparent contradiction in measured scores, qualitative
interpretation is required to make sense of the numbers obtained. For formative