Pay for Quality
Pay for Quality
Pay for Quality
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KCE Reports 118 <strong>Pay</strong> <strong>for</strong> <strong>Quality</strong> 11<br />
2.1.2 Selection of and data-extraction from articles related to equity<br />
To describe the equity dimension of P4Q models a selection of publications from the<br />
main database was selected from the above evidence table. Afterwards two reviewers<br />
(SW and PB) per<strong>for</strong>med an independent full text analysis. Publications labelled as<br />
“doubtful relevance concerning the impact on equity” by one of the two reviewers,<br />
were discussed between the reviewers until consensus was reached. In addition, all<br />
references of relevant equity articles were once again screened <strong>for</strong> additional material<br />
and one publication was added.<br />
In a second phase the researchers (SW and PB) assessed how equity is conceptualized<br />
in the studies (to what extent did the selected papers address different domains of<br />
equity and did they conceptualize equity as vertical or horizontal or both?). To do this<br />
systematically, the researchers developed a grid which includes all equity-related<br />
concepts identified as essential (see appendix 10).<br />
2.1.3 Revision of the conceptual framework into an evidence based state of the<br />
art framework<br />
After the results were available from the conceptual framework construction and from<br />
the systematic review of the P4Q evidence base (equity dimension as well as all other<br />
quality dimension), both were integrated by relating the evidence base to the theoretical<br />
assumptions. The initial framework was assumed to be a set of hypotheses to be<br />
confirmed or disconfirmed by empirical findings.<br />
When confronting theory with evidence, it is important to consider both the internal<br />
validity as the external validity of the findings. The internal validity is guarded by the<br />
previous ‘hard’ approach using a systematic review process. However, as suggested by<br />
Leontien et al (2008), this is combined with a Realist Evaluation Approach (see<br />
publications by Pawson & Tilley) to address external validity 33 . This approach addresses<br />
the question of what works <strong>for</strong> whom in what circumstances? Measures are expected<br />
to vary in their impact depending on the conditions in which they are introduced.<br />
Realistic evaluation assumes that mechanisms supporting an intervention are activated<br />
by conditions and can explain observed patterns in outcomes. These configurations are<br />
also known as context mechanism regularities which can be explored to uncover the<br />
‘black box’ behind an intervention as P4Q.<br />
Both underlying mechanisms (more practically than fundamentally behaviourally<br />
approached) and contextual factors are identified in the conceptual framework. During<br />
the revision process these were specifically related to evidence on outcomes. Missing<br />
links are also identified. The results can be consulted in Chapter 5.<br />
2.1.4 Consultation of international experts as P4Q involved country<br />
representatives<br />
For the international comparison study (chapter 6) four countries are taken into<br />
account, namely the USA, the UK, the Netherlands and Australia. 6 experts were<br />
chosen, based on their expertise with P4Q. For the USA and the UK, 2 key experts per<br />
country were invited to participate. For the Netherlands and Australia, two countries<br />
which are still in a starting phase of implementing P4Q, with only a few P4Q schemes<br />
operational, only 1 key expert per country was invited to participate.<br />
Prof. Rosenthal and Prof. Damberg acted as US experts. The last 10 years Prof.<br />
Rosenthal has been working as a health care economist at the Harvard school of public<br />
health. Most of her work is related to provider-payer incentives. Her research focuses<br />
primarily on <strong>Pay</strong> For <strong>Quality</strong> and other payment mechanisms like capitation and FFS.<br />
Dr. Damberg is a health services researcher, who works at a non profit US think-thank,<br />
named RAND. In the past she has worked <strong>for</strong> both the federal government doing health<br />
policy work, as well as <strong>for</strong> the private industry. Her main areas of interest are<br />
measuring quality and per<strong>for</strong>mance of the health system, patient safety, consumerdirected<br />
health plans, and assessing the impact of health care re<strong>for</strong>m initiatives on<br />
quality and costs. Since 1992 most of her research has focused on <strong>Pay</strong> For <strong>Quality</strong>.