Evaluating the economic value of the CDC CRE Toolkit

Continuing the theme of CPE (or CRE if you prefer) Toolkit evaluation, a US research group has performed a modelling study to evaluate the economic impact of the US CDC CRE Toolkit. Curiously, whilst all approaches generated cost savings eventually, hospitals acting independently rather than as a co-ordinated region resulted in faster but ultimately smaller cost savings.

Whilst the study is titled an evaluation of the CDC CRE Toolkit, it only models one aspect of the Toolkit: the screening of inter-facility transfers for CPE carriage. The study compared two strategies: either all hospitals implementing inter-facility screening for CPE when a set threshold of CPE detected locally had been reached (“a co-ordinated approach”) or hospitals implemented inter-facility screening for CPE at different local thresholds of CPE detection (“uncoordinated approach”). The team used a model that has been used previously to examine CPE transmission dynamics in Orange County, California.

A few reflections:

  • As with any and all models, the outcomes stand or fall by the reliability of the data used to parameterise the models. Perhaps most importantly, do we really understand the local and regional transmission dynamics of CPE well enough to parameterise this sort of model accurately enough to be useful?
  • The cost of HCAI depends on your perspective. If you’re a hospital, you may save money by reducing CPE transmission. But if you’re an insurer, you’re unlikely to save.
  • The study focuses heavily on inter-facility transfer, but doesn’t seem to make any reference to the screening of other patient groups (e.g. re-admissions from the same hospital, admissions to high-risk specialities, and contact tracing). These important variables may well influence CPE transmission dynamics greatly.
  • They used a rather high estimate for attributable mortality for the costings from a societal perspective (35% attributable mortality in the main model). This figure may to true of a BSI in the ICU but it’s not going to be true of a wound infection in a general ward. This is important, since mortality following CPE infection was the main cost driver from a societal perspective. (Worth noting though that varying the probability of infection estimate – 5% – seemed to affect the cost outcome more than varying the attributable mortality estimate in the sensitivity analysis.)
  • This study focussed on whether a given approach was cost-saving, although also included an analysis of whether the two approaches at various thresholds of CPE identification locally were cost-effective. All of the scenarios that they presented were cost-effective by year 5, and most by year 2. And the financial win is in the multi-millions of dollars bracket.
  • This sort of study is always going to be frustrating because you will be left saying “what if you tested the model in scenario x”, and the authors can’t possibly report all scenarios. Indeed, the authors comment: ‘Decision makers can use our results to determine investment for the approach that best fits their situation.’ Could we consider reporting modelling studies like this in a more dynamic way, including an interactive module that readers can play with, to really fit the model to their situation? Would work well on a journal website and be quite a draw I suspect if any editors happen to be reading?!

This is more important work from a prolific research group. Overall, the findings are helpful in guiding decision making and certainly strengthen the case that enhanced screening for CPE can be a cost-effective way of reducing CPE transmission.


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