Challenges in Cost-Effectiveness Analysis of genomic tests

From: Cost-effectiveness analyses of genetic and genomic diagnostic tests (Must read)

Type of challenge	Example of challenge	Description of challenge
Methodological	Selecting the appropriate evaluative framework	Is the standard extra-welfarist view and use of CEA appropriate, or should the distinct theoretical approach reflecting the welfarist view and use of CBA be adopted to allow consequences other than health gain, such as the value of diagnostic information from the genomic-targeted diagnostic test, to be valued?
	Relevant study perspective	Is the standard recommendation to focus on the use of health-care services appropriate when the genomic-targeted diagnostic test may provide information that affects the use of other services, such as education or employment?
	Relevant time horizon	Is a lifetime sufficient when the impact of a genomic-targeted diagnostic test may extend to infinite time horizons that are not limited by the lifespan of one individual?
	Defining the relevant study population	Is the standard definition of a patient (the person receiving the technology) appropriate when there could be spillover effects to family members (currently alive or to be born) as a result of information from a genomic-targeted diagnostic test?
	Valuing consequences	Is identifying and measuring the impact on health status alone sufficient to capture the (good and bad) consequences of a genomic-targeted diagnostic test?
Technical	Variation in the individual characteristics of the relevant study population	The use of cohort state transition Markov models, sometimes combined with decision trees, cannot easily capture the impact of individual patient variation within a population with different genotypes and phenotypes
	Number of diagnostic and, if appropriate, subsequent treatment pathways	The use of cohort state transition Markov models, sometimes combined with decision trees, cannot easily account for multiple comparators often needed when evaluating a new genomic-targeted diagnostic test
	Capturing impact of reduced time to diagnosis	The use of cohort state transition Markov models, sometimes combined with decision trees, cannot account for the impact of reduced time to achieve a diagnosis, which is often a proposed benefit of a genomic-targeted diagnostic test
	Capturing impact of capacity constraints	Decision analytic model-based CEA currently assumes limitless capacity within health-care systems, which is often not a reasonable assumption when introducing a genomic-targeted diagnostic test to populations for whom a diagnosis was not previously available
Practical	Availability of data	There is often a lack of data available to populate decision analytic model-based CEA
	National tariff of test cost	No national tariff for genomic-targeted tests exist
Organizational	Complex health-care systems	Decision analytic model-based CEA assumes that money saved and benefits accrued are transferable, but this is often challenging in complex health-care systems that comprise an overarching funding mechanism (public, private, insurance), a service and staffing model for providing care for different sectors (community, general practice, hospital, specialist) and a means of allocating funding to these different sectors
	Generalizability of results	Decision analytic model-based CEA is relevant only to the defined decision problem, and decision-makers who want to use the results must decide whether the focus of the analysis is relevant to their own jurisdiction
	Expensive nature of health technology assessment	Decision analytic model-based CEA conducted within national health technology assessment processes requires considerable funding and expertise that are not available to all, which may contribute to the inequity in access to new genomic-targeted diagnostic tests across the world

1. CBA, cost-benefits analysis; CEA, cost-effectiveness analysis.

 

Payment systems vs. prices in health care

Payment Methods: How They Work

The problem in health care is not that prices play a role—that is unavoidable. The problem is that prices are distorted in ways that result in inefficient allocation of health care resources. Patients and physicians use too much of health care services that are of low value and not enough of services that are of high value.

This statement refers to US private health care. It may refer to any private health system. The JAMA article reflects an interesting and forgotten issue: The Importance of Relative Prices in Health Care Spending. Data is usually unavailable, and few studies are able to show the implications of relative prices on outcomes.
My impression is that we should review the role of prices in health care and understand better that we do need payment systems, that beyond the standard Hayek signal for producers and consumers, there is a signal of appropriate acces that sends the regulator. This is what some health systems try to apply in public settings, and what we did in Catalonia long ago.
Therefore, the key issue is not to define the method as this report does, though it is necessary. The most important focus should be devoted to the environment and the process that finally will guarantee access and quality of outcomes.

PS. By the way, does anybody know where current payment system in Catalonia stands? Glups!

Paying for high intensity inpatient activities

How should hospital reimbursement be refined to support concentration of complex care services?

Concentration of certain inpatient activities is absolutely necessary to guarantee the right efficiency and outcomes that can only be achieved under a large scale. However, how to pay for this is a different and difficult issue. Usually these activities result from a blending of costs of care, teaching costs, and sometimes with research costs. Therefore, the first step is to try to split them as far as possible.
A new paper tries to disentangle in part the issue of how to pay for complex services, and says:

There is no universally agreed definition of what constitutes complex care hospital care, but in England attempts have been made to define complex care according to the  presence of specific diagnoses and procedures in each patient’s medical record. We have applied these complex care definitions to determine whether the receipt of complex care is associated with higher costs relative to patients allocated to the same HRG who did not receive complex care. To do this, we estimate random effects models using patient-level activity and cost data for all patients admitted to English hospitals during the 2013/14 financial year. Compared to otherwise equivalent patients allocated to the same HRG, costs were more than 10% higher for patients receiving 26 (out of 69) types of complex care delivered in hospitals.

And the reason behind these higher costs, maybe severity within the classification or ...

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