“Reducing inequalities, ensuring financial viability”, par William Weeks


William Weeks, IMéRA Fellow 215-2016, est professeur de psychiatrie et de médecine communautaire et familiale à l’Institut Dartmouth.

Article paru dans Fellows#24 (Réformer les systèmes de santé publique), publication du RFIEA.

 

Public healthcare systems have a dual obligation. Foremost, they must strive to improve the health of the people they serve. Second, they have a duty to taxpayers to use scarce resources efficiently and effectively in their primary pursuit.
The tension between those obligations suggests that public healthcare systems should be strategic in how they address and resolve health inequities. Budget limitations preclude public healthcare systems from doing everything that they might like to do, so they must prioritize their efforts. Here, I propose a five-step process for prioritizing efforts.

First, it is critical for a public healthcare system to understand the state of health, health care access, and healthcare use in its population. Small area variation analysis techniques, conducted over time, can help identify inequalities in those measures, determine whether there are persistent regional patterns in any observed inequities, and also determine what is possible. This last part is critical, because what can be demonstrated to be tangibly and practically feasible can motivate performance improvement in healthcare settings that demonstrate room for improvement. Further, those who deliver or organize care services in higher performance regions can share their best practices with those in lower performance regions; however, they must be identified first.

Second, public health system leaders need to understand the drivers of any observed health inequities and identify which of those drivers might be modifiable. It is possible that with similar levels of performance, drivers might differ in different regions. This would suggest that tailored and targeted approaches to interventions would be most effective: what might work in one region might not in another if the drivers of the same level of disparities are different.

Third, public health system leaders must determine the costs of the means through which changes can be effected. These costs should include anticipated startup and maintenance costs and use standard financial discounting methods to allow for comparison of costs in present value terms. Importantly, sensitivity analyses that include both optimistic and pessimistic estimates of costs should be conducted so that a range and probabilistic distribution of present value cost estimates can be generated.

Fourth, estimates of the impact of interventions on health measures and the disparities that the interventions were designed to ameliorate must be calculated. Here, too, sensitivity analyses that examine ranges of anticipated impacts – and the timing of those impacts – should be conducted. Importantly, externalities should be estimated in this step (and may modify results in the former step). For instance, if reduction in mortality rates in one region would stimulate economic activity in that region, the indirect impact of improved economic activity on further reducing mortality rates should be considered. And, should that process uncover the potential for additional tax revenues generated by the improved economic activity, the impact of those tax receipts should be incorporated into the former step, as well.

Finally, once these preliminary analyses have been completed, public health system leaders must prioritize the list of potential interventions. Given their obligation to taxpayers, they should prioritize efforts that maximize health outcomes (or generate the greatest reduction in health disparities) at the lowest possible cost. There is a strategic aspect to this step, as well. Anticipated timing of the interventions and their impacts on health and externalities can impact the order in which interventions should be implemented. For instance, an intervention that has less of a direct health impact might be prioritized before one that has a greater direct health impact if the former were anticipated to generate economic growth that could fund – and extend – the latter.

Critical to any analysis of health states and health disparities – including disparities in healthcare access – is an information system that collects relevant. Such a system need to routinely and consistently collect data so that data definitions are constant over time and are uniformly interpreted across geographic settings. Only by maintaining a data repository that preserves data over time can one assess whether progress in meeting the objectives of an intervention have been made.

But once such systems are in place, public health system leaders have the obligation to use those data to transparently identify health disparities that warrant intervention, anticipate and strategically prioritize the impact of interventions on those disparities, and implement chosen interventions in a systematized and cost-responsible manner. The proposed framework detailed above provides one method of doing so.


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