title: Developing robust composite measures of healthcare quality - Ranking intervals and dominance relations for Scottish Health Boards.
abstract: Although composite indicators are widely used to inform health system performance comparisons, such measures typically embed contentious assumptions, for instance about the weights assigned to constituent indicators. Moreover, although many comparative measures are constructed as ratios, the choice of denominator is not always straightforward. The conventional approach is to determine a single set of weights and to choose a single denominator, even though this involves considerable methodological difficulties. This study proposes an alternative approach to handle incomplete information about an appropriate set of weights and about a defensible denominator in composite indicators which considers all feasible weights and can incorporate multiple denominators. We illustrate this approach for comparative quality assessments of Scottish Health Boards. The results (displayed as ranking intervals and dominance relations) help identify Boards which cannot be ranked, say, worse than 4th or better than 7th. Such rankings give policy-makers a sense of the uncertainty around ranks, indicating the extent to which action is warranted. By identifying the full range of rankings that the organizations under comparison may attain, the approach proposed here acknowledges imperfect information about the "correct" set of weights and the appropriate denominator and may thus help to increase transparency of and confidence in health system performance comparisons.
authors.affiliation: Department of Management, London School of Economics and Political Science, London, United Kingdom; Department of Health Services Management, Ludwig-Maximilians-Universität München, Schackstraße 4, 80539 Munich, Germany. Electronic address: schang@bwl.lmu.de.
authors.forename: Laura
authors.initials: L
authors.lastname: Schang
authors.affiliation: Department of Mathematics and Systems Analysis, Systems Analysis Laboratory, Aalto University School of Science, Aalto, Finland.
authors.forename: Yrjänä
authors.initials: Y
authors.lastname: Hynninen
authors.affiliation: Department of Management Science, Strathclyde Business School, University of Strathclyde, Glasgow, United Kingdom.
authors.forename: Alec
authors.initials: A
authors.lastname: Morton
authors.affiliation: Department of Mathematics and Systems Analysis, Systems Analysis Laboratory, Aalto University School of Science, Aalto, Finland.
authors.forename: Ahti
authors.initials: A
authors.lastname: Salo
mesh_terms: D003015:Clostridium Infections / Q000453:epidemiology; D006801:Humans; D016017:Odds Ratio; D010343:Patient Admission / Q000706:statistics & numerical data; D019984:Quality Indicators, Health Care / Q000145:classification*; D011787:Quality of Health Care / Q000592:standards*; D012017:Referral and Consultation / Q000706:statistics & numerical data; D012606:Scotland; D012930:Social Dominance; D013203:Staphylococcal Infections / Q000453:epidemiology
keywords: Composite indicator; Denominator; Dominance relation; Performance comparison; Ranking interval; Weight