Measuring Quality of Care

Measuring quality of care is not a straightforward business:

  1. Routinely collected outcome data tend to be misleading because of very poor ratios of signal to noise.[1]
  2. Clinical process (criterion based) measures require case note review and miss important errors of omission, such as diagnostic errors.
  3. Adverse events also require case note review and are prone to measurement error.[2]

Adverse event review is widely practiced, usually involving a two-stage process:

  1. A screening process (sometimes to look for warning features [triggers]).
  2. A definitive phase to drill down in more detail and refute or confirm (and classify) the event.

A recent HS&DR report [3] is important for two particular reasons:

  1. It shows that a one-stage process is as sensitive as the two-stage process. So triggers are not needed; just as many adverse events can be identified if notes are sampled at random.
  2. In contrast to (other) triggers, deaths really are associated with a high rate of adverse events (apart, of course, from the death itself). In fact not only are adverse events more common among patients who have died than among patients sampled at random (nearly 30% vs. 10%), but the preventability rates (probability that a detected adverse event was preventable) also appeared slightly higher (about 60% vs. 50%).

This paper has clear implications for policy and practice, because if we want a population ‘enriched’ for high adverse event rates (on the ‘canary in the mineshaft’ principle), then deaths provide that enrichment. The widely used trigger tool, however, serves no useful purpose – it does not identify a higher than average risk population, and it is more resource intensive. It should be consigned to history.

Lastly, England and Wales have mandated a process of death review, and the adverse event rate among such cases is clearly of interest. A word of caution is in order here. The reliability (inter-observer agreement) in this study was quite high (Kappa 0.5), but not high enough for comparisons across institutions to be valid. If cross-institutional comparisons are required, then:

  1. A set of reviewers must review case notes across hospitals.
  2. At least three reviewers should examine each case note.
  3. Adjustment must be made for reviewer effects, as well as prognostic factors.

The statistical basis for these requirements are laid out in detail elsewhere.[4] It is clear that reviewers should not review notes from their own hospitals, if any kind of comparison across institutions is required – the results will reflect the reviewers rather than the hospitals.

Richard Lilford, CLAHRC WM Director

References:

  1. Girling AJ, Hofer TP, Wu J, et al. Case-mix adjusted hospital mortality is a poor proxy for preventable mortality: a modelling studyBMJ Qual Saf. 2012; 21(12): 1052-6.
  2. Lilford R, Mohammed M, Braunholtz D, Hofer T. The measurement of active errors: methodological issues. Qual Saf Health Care. 2003; 12(s2): ii8-12.
  3. Mayor S, Baines E, Vincent C, et al. Measuring harm and informing quality improvement in the Welsh NHS: the longitudinal Welsh national adverse events study. Health Serv Deliv Res. 2017; 5(9).
  4. Manaseki-Holland S, Lilford RJ, Bishop JR, Girling AJ, Chen YF, Chilton PJ, Hofer TP; UK Case Note Review Group. Reviewing deaths in British and US hospitals: a study of two scales for assessing preventability. BMJ Qual Saf. 2016. [ePub].
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