What does it mean to be patient centered in health economics?

By  Jacquelyn W. Chou, MPP, MPL, Vice President, PRECISIONheor

Drug pricing has become a hot-button issue in recent years in the US. Reducing health care spending, and pharmaceutical spending in particular, is one of the few areas of bipartisan agreement in a time of increasingly divisive bipartisanship. A popular argument is the notion of aligning prices with value, and so “cost-effectiveness models,” a fairly wonky concept, has entered the mainstream lexicon.

Suggestions for a health technology assessment type agency like NICE in the UK, and setting prices based on these types of evaluations have been growing in popularity. This is juxtaposed against a backdrop of a growing movement towards more patient-centered health care. Health economics can sit at this intersection between cost-effective care and patient-centered care. But the approach towards cost-effectiveness needs to change to a provide a better voice for patients in the science, rather than serving as a cost-containment tool.

What is a cost-effectiveness model?

Put simply, a cost-effectiveness model is meant to weigh the benefits of an intervention against the costs of that intervention. Doing so, the clinical benefits of an intervention are monetized. There is much controversy around the method for monetizing the benefits. However, even beyond that, the scope of what is included in a cost-effectiveness model is very narrow. The traditional construct aims to translate the clinical benefits as captured in the clinical trial, but it misses other aspects of potential benefit that are still of critical importance to patients. There is general agreement that these elements are an important source of the value provided by health innovations. However, these are values that are missed in cost-effectiveness discussions and health technology assessments.

How can we better represent patients?

As cost-effectiveness models move from a wonky area of science, used by technical specialists to serve a specific and narrow purpose, to potentially a primary player in decisions that can profoundly affect the ability of patients to access treatments, the field of health economics and outcomes research needs to do better in service of the patients being affected. The elements of value currently included in cost-effectiveness models are too narrow to adequately capture the meaningful and significant changes to a patient’s day-to-day life and lifetime trajectory that can be created by health innovations.

First, evidence on these critical elements of patient value, such as gains to productivity, reductions in caregiver burden, or the value of knowing you may have a future, needs to be generated. Primary data collection and preference elicitation techniques can be used to determine what aspects of value are relevant for a given patient population, and to quantify and monetize those aspects of value. Other benefits can be estimated using real world datasets. Developing these estimates eliminates the argument that it is technically not possible to include these elements of patient value.

Second, once that evidence is generated, incorporating these elements of patient value should become a standardized part of a cost-effectiveness framework. Health economics researchers are well aware that the conventional cost-effectiveness model does not include these patient-centered aspects of value. Already there are a growing number of different models and approaches that seek to broaden the cost-effectiveness model to be more representative of patient values. However, these efforts are viewed as the alternative rather than the standard. A shift in the science needs to occur so this broader view on cost-effectiveness becomes the standard view.

Providing better representation of patients warrants adding into a cost-effectiveness model aspects of disease management that are of material and practical importance to patients. This is a critical step to ensuring that we as a society are appropriately valuing care and making the right resource allocation decisions.