Pay for Quality

72 Pay for Quality KCE Reports 118
However, on the various types of intermediate outcomes often also positive effects
were found (S). This contrasts with long term outcome targets for which no significant
effects were detected, whenever included (W).
It is striking that most studies are focused on the correction of underuse of appropriate
care, with varying P4Q results, whereas only two studies also focus on the overuse of
inappropriate care (lab testing prescription, medical imaging prescription, drug
prescription, etc.) 171 , 215 . The first study found positive results, the second reported
mixed effects (some positive, some showed no significant difference and the effect
seemed to decrease with time) (C). For the second study the behavioural independent
nature of the P4Q scheme should be taken into account. GPs agreed beforehand, by
means of a democratic majority decision at a regional meeting, to improve prescribing
according to a one page evidence based formulary and to be more critical and efficient
in their prescribing on antibiotics and gastric medicine in general. However, the bonus
was performance independent, and given to all the GPs.
Most P4Q studies are in compliance with SMART goals (specific, measurable, achievable,
relevant, and timely), although it was often unclear why and by whom specific patient
groups and targets were selected. If we look at P4Q results the reporting of a high
involvement of stakeholders led more often to positive results, as compared to studies
that did not report such an involvement (S). In addition, with regard to targets being
relevant and timely, almost no study indicated that a previously detected quality
problem (high variability or low performance) on a specific target was the reason to
include it in a P4Q programme. Most studies referred to general lack of quality findings
without assessing them in a local context as a first step, and to base indicator selection
on those findings. Studies with a baseline measurement only used those results for
comparison reasons, not for selection purposes. Especially in acute care conditions a
number of baseline reports with already a high performance level are presented (e.g. 80
to 90% achievement on certain included measures). Looking at P4Q results this
presence or absence for room for improvement seems to have been of influence on
finding positive or no effects (S). A related lack in the reporting of studies concerns the
dynamical aspects of quality enhancement. No studies report on a cyclical selection and
refinement of indicators through time as a function of room for improvement. For the
QOF a number of small scale changes to the indicator set have been made and others
are planned, but their effects have not been studied yet.
There is an evolution in the number of targets and indicators which are included in P4Q
programmes. Programs during the nineties included often only one or a few targets.
Later on, this number expanded gradually through the years with the start up of new
programmes. The QOF with almost 150 indicators is one example. In terms of P4Q
results a very limited target selection seems to correspond with lesser P4Q effects,
especially in the domain of preventive care (S).
5.1.2 Quality measurement
Data validity and its acceptance are reported as sufficient in most studies. With the aid
of the Healthcare Effectiveness Data and Information Set (HEDIS), which is standardized
over USA health plans to foster comparability, and based on strict data validity criteria
many studies make use of existing databases originally intended for other purposes
(although mostly also financing related). Differences in data collection method
(automatic extraction, secondary data use, additional registration; sampling versus
continuous) have not led to substantial differences in clinical P4Q results (S). However,
the effect of the choice of the data source on cost effectiveness of the programme and
on provider satisfaction (due to the level of paperwork and workload effects) remains
unclear after reviewing empirical results.
A few studies tested for data coding quality and the level of gaming the system. Their
results show that coding quality was generally good, but that there was also some
gaming present, however to a limited extent (W). How detected gaming is dealt with is
often not described.