Using matching methods to account for selection bias in Norway’s Primary Care Teams (PCT) pilot

Norway is piloting team-based primary care delivery models: Honorarmodellen (HM) and Driftstilskuddsmodellen (DM). In addition to organisational changes, the DM transforms provider payment, which seems to attract specific practices. This, coupled with the small number of DM practices, makes it difficult to produce credible evidence regarding the model and its effects on health system performance. I examine whether matching methods—specifically, coarsened exact matching, propensity score matching, and propensity score weighting—can improve evaluation in this demanding situation. As in previous studies on the small sample performance of matching methods, I find no clear best method. This suggests using propensity score weighting, which does not discard data. In the final section of the article, I offer additional advice to help improve the evaluation in similar situations.