Including Quality of Care in Efficiency Measures: Creating Incentives Consistent with Maximising Net Benefit in Practice


Research and reimbursement processes for choosing whether to invest in existing or new health technologies, approaches or programs have focused on net benefit maximisation in evaluating alternative interventions, strategies and programs. However, for net benefit maximising incentives to arise in support of the choice and actual way programs or technologies are used in practice, requires appropriate regulation and incentives for net benefit maximisation in monitoring provider efficiency in practice. That is, efficiency measures of health care providers and institutions such as hospitals allowing for health-care providers and institutions such as hospitals, quality of care and downstream health system impacts consistent with maximising net benefit (Donaldson and Gerard 1993; Eckermann 2004; Eckermann and Coelli 2013). For efficiency measures to create appropriate incentives for health system quality of care in practice:

  • (i) Quality of care impacts need to be valued in efficiency measures across providers consistent with the appropriate underlying economic objective - maximising net benefit.
  • (ii) Differences in actual populations cared for across providers (i.e. risk factors of patients at admission) need to be adjusted for to maintain comparability.
  • (iii) Downstream as well as within-service effects of care (e.g. within admission and post separation effects of quality of care measures) and their associated cost need to be appropriately allowed for in monitoring to maintain appropriate coverage of net benefit impacts.

We show in this chapter that each of these factors is key to appropriate incentives in practice given that perverse incentives are otherwise typically created for cost per service minimising quality of care (e.g. hospital minimum cost per admission quality of care), cream skimming and costs and effect shifting, respectively.

We initially focus on needing to appropriately specify quality of care variables (e.g. waiting times, mortality, morbidity, iatrogenic events, readmission, etc.) in efficiency measures consistent with the appropriate underlying objective of

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S. Eckermann, Health Economics from Theory to Practice,

DOI 10.1007/978-3-319-50613-5_9

maximising health system net benefit as the cornerstone for creating appropriate incentives for quality of care. The net benefit correspondence theorem (NBCT) is identified and illustrated to be the only method for specifying quality variables in efficiency measures which creates incentives for net benefit maximising quality of care (Eckermann 2004; Eckermann and Coelli 2013).

Importantly the NBCT also uniquely provides a robust framework with coverage and comparability conditions to prevent perverse incentives for cost and effect shifting and cream skimming and appropriately qualify analysis where these conditions are not adequately met.

To satisfy coverage conditions and prevent perverse cost and effect shifting incentives, robust quality of care variables in hospitals need to be at a clinical activity (DRG) level with data linkage or modelling to an adequate common time point allowing for post separation health system impacts of care. To satisfy comparability conditions in preventing cream skimming incentives requires standardising cost and effects to control for exogenous within DRG differences between hospital patient population risk factors at admission.

The chapter concludes discussing the NBCT as a generalizable method and its extension to other health care and wider settings, as well as multiple effect domains (Chap. 10) and funding mechanisms (Sect. 12.6). Key Links that the NBCT provides between HTA and practice in jointly addressing optimal research, reimbursement and regulatory decisions are also highlighted.

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