Developing robust composite measures of healthcare quality – Ranking intervals and dominance relations for Scottish Health Boards

Multidimensional performance assessment of public sector organisations using dominance criteria

“…Dominance criteria have been adopted previously to assess ranking uncertainty related to the weights used in the construction of a composite indicator of performance (Schang et al ), but our MVMLM offers two advantages over that study. First, Schang et al do not account for uncertainty associated with the performance estimates themselves, whereas we are able to construct confidence statements for each performance dimension.…”

“…Perhaps the primary reason that observed achievements differ across hospitals is because they treat different types of patients. Accounting for these differences may not be necessary in contexts where funds have been allocated to achieve a standard level of outcome using some form of risk‐adjusted reimbursement formulae (Jacobs, Smith, & Street, ; Schang et al, ; Smith, ). However, in many healthcare systems, hospitals are subject to a prospective payment system that uses fairly crude payment categories to reimburse hospitals for differences in patients (Kobel, Thuilliez, Bellanger, & Pfeiffer, ).…”

“…We seek to overcome this limitation by using dominance criteria to judge performance. Dominance criteria have been employed previously to assess ranking uncertainty associated with the weights used to construct a composite indicator of healthcare performance (Schang, Hynninen, Morton, & Salo, ), but, to the best of our knowledge, such criteria have not been applied when evaluating performance simultaneously across multiple dimensions. The concept of dominance is attractive in that it allows comparison of multidimensional performance profiles under relatively weak assumptions about stakeholders' utility functions.…”

Composite measures of healthcare quality: sensible in theory, problematic in practice

“…For example, patients place a great value on receiving care that is delivered compassionately and in a timely manner,16 while clinicians might sometimes place greater emphasis on the delivery of effective treatments. A key challenge in the use of composite measures is therefore the weighing of selected single outcome measures to reflect individual preferences,17 with different weighing methods being used such as equal, numerator and opportunity-based weighting, or weighting on expert judgement 18. Importantly, to ensure the usability of composite measures, their construction and selection of outcome measures has to be guided by the overall purpose of their use and tailored towards the end user.…”

Eliciting, Applying And Exploring Multidimensional Welfare Weights: Evidence From The Field

“…(), Massey et al . (), Hick (), Alkire et al (), Donohue and Biggs (), Feeny and McDonald () and Schang et al (). The array of aspects of human life being taken into examination is extremely wide; for example, the interdisciplinary review by Linton et al (), which focuses on the concept of well‐being and does not cover age‐specific or condition‐specific measures, identifies as many as 196 dimensions being used in the literature.…”