The Need to Include Quality in Efficiency Measures Consistent with Maximising Net Benefit

Health economics in processes of health technology assessment (HTA) have stressed the importance of jointly comparing the incremental cost (ДС) and health effects (ДЕ) of strategies relative to an appropriate comparator. At a threshold value for effects of care (Д), this comparison is equivalent to a decision-making objective of maximising incremental net benefit (INB):

This has been the explicit or implicit economic objective underlying analysis throughout Chaps. 1 to 7, while shown to be equivalent to minimising net loss with multiple stratgey comparisons in Chap. 8.

However, conventional measures of economic efficiency across health-care providers or health systems such as hospitals in practice reflect a cost minimising objective with cost per service based measures. For example, with cost per admission efficiency measures in hospitals (with or without case mix adjustment, Australian Government 2000). Hence, in contrast to HTA, efficiency measures of performance of hospital providers in practice, while including the per admission cost of quality of care, ignore the effects of quality of care. To illustrate such differences, consider comparing 45 NSW hospitals in treating patients at a clinical activity diagnostic-related group (DRG) level for respiratory infection DRG E62a in Table 9.1, given cost per admission and mortality rate for this DRG.

Presenting this evidence in Fig. 9.1 jointly for costs and mortality rates per admission, what incentives does comparing costs alone create?

Table 9.1 Cost per admission ($/Ad) and mortality rate per admission (Mort %) for 45 NSW hospitals (Hosp) treating respiratory infection DRG E62a

Fig. 9.1 Cost per admission and mortality rate for DRG E62a in 45 NSW hospitals (Source: Eckermann 2004, “Hospital performance including quality: creating incentives consistent with evidence-based medicine” PhD Dissertation, UNSW, Sydney. http://www.library.unsw.edu. au/~thesis/adt-NUN/public/adt-NUN20051018.135506/)

It is clear that if we only consider cost per admission (the vertical axis in Fig. 9.1) and ignore quality of care (horizontal axis), we make hospitals accountable for the expected average cost of their mix of clinical activities, but not patient quality of care effects such as mortality. Case-mix proponents describe such lack of accountability for patient outcomes as ‘clinical neutrality’ of case-mix efficiency measures and funding mechanisms (Brook 2002).

However, such partial efficiency measures based on cost per admission alone while creating incentives to minimize cost per admission also create incentives (Eckermann 1994) for:

• (i) Minimum cost per admission quality of care;
• (ii) Cost-shifting (e.g. high readmission rates); and
• (iii) Cream skimming (i.e. choosing less complex patients), to the extent predictive differences are observable between patients within activities compared (e.g. within DRG E62a in Table 9.1 and Fig. 9.1).

In relation to cost shifting (ii), given characteristic incomplete vertical integration of hospitals in health systems (Evans 1981), minimum cost per admission quality of care can more generally be expected to have impacts post separation on higher treatment in other institutional health-care settings, general practice, specialist and aged care services and informal care in non-institutional settings as well as higher hospital readmission rates. The key implication is that minimising cost per admission does not equate to minimum health system costs in considering downstream impacts, let alone maximising health system net benefit in considering the health system cost and value of hospital quality of care (Eckermann 2004).