The need for accurate epidemiology data to drive a higher success rate with Health Technology Assessments

picture1Most drug or device launches today require a health economic valuation often in the form of a Health Technology Assessment (HTA) to satisfy payers that the new ‘technology’ is advantageous for the health system.

Most HTAs include epidemiology data in some form. This is often included in order to understand the impact of the technology on the entire health care system within a country, assessments of disease prevalence and severity will be used to estimate budget impact on a system, alternatively hospital or other data that can indicate number of patients that could benefit from the technology is used.

And despite the multi-disciplinary approach of most teams preparing dossiers and models, a recent analysis of HTA submissions[1] which included an ICER calculation rejection found rejection rates of between 24%-58%, depending on reviewing agency.

One of the main reasons sited for rejection of an HTA dossier, particularly those including ICER calculations was a discrepancy between the resulting ICER calculated by the evidence review group versus the submitting manufacturer.

A key reason given for this was related to issues with the study population. Criticisms run from inappropriate methodology in the main clinical study to application of data not relevant to the country or population under consideration. Some supporting comments from reviewers include, “indicated population not specific enough”, and “study populations did not reflect intended population in clinical practice”.

In similar research completed by PAREXEL in 2014, they were able to list in descending order of frequency the reasons why drugs fail to gain market access with their HTA submission.

Primary reason for HTAs being rejected by Reviewing Body [2]
 1. Non-robust economics
 2. Uncertain clinical benefit
 3. Inappropriate trial design, comparator, or patient population
 4. Increased drug costs
 5. Safety concerns

This highlights clearly the benefit of collecting the relevant data, specific to the unmet patient needs and the patient populations to build the economic case.

In general, health economists and those involved in preparing HTA-type assessments on behalf of manufacturers, both in-house and agency side, have typically come from non-medical disciplines. The majority would not be familiar with diseases, from an epidemiological or pathological standpoint. This makes the job of sifting through the thousands of published papers to find the appropriate information difficult to impossible for a non-medical professional.

However, this deficit is not apparent on the side of the evidence review group – these tend to be academic groups that are truly multi-disciplinary with application of rigour to the selection of data that are used for comparative analyses.

The cost-implications of the HTA outcome are clear: should full access not be awarded, a recommendation can be given for use in a restricted population, thus restricting use and therefore revenue to the manufacturer, or the HTA can be rejected entirely, leading to further delays and costs for the manufacturer as the HTA must be re-done and/or appealed.

Of course, success can not be guaranteed solely through use of more rigorous epidemiology data, but it can help to significantly limit the likelihood that the reviewing group finds and applies different data to that in the original HTA submission and puts the brakes on a potentially successful product launch.


[1] Elizabeth A Griffiths, Janek K Hendrich, Samuel DR Stoddart, Sean CM Walsh, Acceptance of health technology assessments submissions with incremental cost-effectiveness ratios above the cost-effectiveness threshold, ClinicoEconomics and Outcome Research 2015:7 463-476.

[2] “Exploring the Variability Between Disease Type and the Proportion of Submissions with ICERS Lower Than the Threshold That Are Rejected by HTA Agencies,” PAREXEL, 2014.