title: Measuring patients' priorities using the Analytic Hierarchy Process in comparison with Best-Worst-Scaling and rating cards: methodological aspects and ranking tasks.
abstract: BACKGROUND
  Identifying patient priorities and preference measurements have gained importance as patients claim a more active role in health care decision making. Due to the variety of existing methods, it is challenging to define an appropriate method for each decision problem. This study demonstrates the impact of the non-standardized Analytic Hierarchy Process (AHP) method on priorities, and compares it with Best-Worst-Scaling (BWS) and ranking card methods.
  
  
  METHODS
  We investigated AHP results for different Consistency Ratio (CR) thresholds, aggregation methods, and sensitivity analyses. We also compared criteria rankings of AHP with BWS and ranking cards results by Kendall's tau b.
  
  
  RESULTS
  The sample for our decision analysis consisted of 39 patients with rare diseases and mean age of 53.82 years. The mean weights of the two groups of CR ≤ 0.1 and CR ≤ 0.2 did not differ significantly. For the aggregation by individual priority (AIP) method, the CR was higher than for aggregation by individual judgment (AIJ). In contrast, the weights of AIJ were similar compared to AIP, but some criteria's rankings differed. Weights aggregated by geometric mean, median, and mean showed deviating results and rank reversals. Sensitivity analyses showed instable rankings. Moderate to high correlations between the rankings resulting from AHP and BWS.
  
  
  CONCLUSIONS
  Limitations were the small sample size and the heterogeneity of the patients with different rare diseases.
  
  
  CONCLUSIONS
  In the AHP method, the number of included patients is associated with the threshold of the CR and choice of the aggregation method, whereas both directions of influence could be demonstrated. Therefore, it is important to implement standards for the AHP method. The choice of method should depend on the trade-off between the burden for participants and possibilities for analyses.
authors.affiliation: Center for Health Economics Research Hannover (CHERH), Leibniz University of Hannover, Otto-Brenner-Str. 1, D-30159, Hanover, Germany. ks@cherh.de.
authors.forename: Katharina
authors.initials: K
authors.lastname: Schmidt
authors.affiliation: Center for Health Economics Research Hannover (CHERH), Leibniz University of Hannover, Otto-Brenner-Str. 1, D-30159, Hanover, Germany.
authors.forename: Ana
authors.initials: A
authors.lastname: Babac
authors.affiliation: Center for Health Economics Research Hannover (CHERH), Leibniz University of Hannover, Otto-Brenner-Str. 1, D-30159, Hanover, Germany.
authors.forename: Frédéric
authors.initials: F
authors.lastname: Pauer
authors.affiliation: Center for Health Economics Research Hannover (CHERH), Leibniz University of Hannover, Otto-Brenner-Str. 1, D-30159, Hanover, Germany.
authors.forename: Kathrin
authors.initials: K
authors.lastname: Damm
authors.affiliation: Center for Health Economics Research Hannover (CHERH), Leibniz University of Hannover, Otto-Brenner-Str. 1, D-30159, Hanover, Germany.|Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), Member of the German Center for Lung Research (DZL), Hanover, Germany.
authors.forename: J-Matthias
authors.initials: JM
authors.lastname: von der Schulenburg
keywords: Analytic Hierarchy Process; Best-worst-scaling; Decision making; Method comparison; Patient preferences