What is Health Technology Assessment or HTA?
HTA has evolved considerably since the first proposals set out in 1976 from the US Office of Technology Assessment.
The current definition of HTA outlines that “HTA is a multidisciplinary process that uses explicit methods to determine the value of a health technology at different points in its lifecycle. The purpose is to inform decision making to promote an equitable, efficient, and high-quality health system.”
There are a number of things alongside this definition that provide additional detail, these are:
A health technology is an intervention with a broad definition, for example, it can be something that prevents, diagnoses, or treats a medical condition, amongst other things.
- The process is formal, systematic, and transparent which considers the best available evidence.
- The dimensions of value for a health technology may examine the intended and unintended consequences of using a health technology compared with existing alternatives.
- The dimensions often include clinical effectiveness; safety, costs, economic implications and ethical issues, to name just a handful.
- The overall value may vary depending on the perspective taken, the stakeholders involved, and the decision context.
- HTA can be applied at different points in the lifecycle of a health technology.
So what does this mean?
So practically this means, when decisions are made in healthcare they are the result of HTA (a formal and systematic process) and central to that process is the best available evidence. As a patient and recipient of healthcare, that sounds entirely reasonable and what you would hope – your care is Evidence Based and conducted in a thorough manner.
As originators of new and innovative health technologies – we therefore see that HTA is a critical process in the use of our innovations and central to any success is the evidence we generate to support them.
Taking a step back – decision makers want the best available evidence and as innovators we want to fully demonstrate the value our innovation brings – so how do we do this?
Here comes the tricky part, as this is where practicalities enter the frame.
Look around the world, Health systems are all different, as people we are not identical and our contexts are not the same, therefore evidence requirements can and do vary. We therefore must think about what data are required to support these different contextual decisions but one must also consider whether it is practical to generate evidence for every single eventuality?
One also has to be mindful that it also takes time to generate data. As an example, if you think about your average phase 3 study, this could take 3 years to readout but you need to know what endpoints you are studying at the start of that study – that’s just one example and there’s a whole load more complexity here but that is for another day. You can appreciate however that you need to think and plan ahead, early is good or you might miss your opportunity.
From a practical perspective there will be options about how evidence is collected, therefore as a generator of evidence, one has to decide what is appropriate, feasible and desirable, given the context for the decision that will be made. For example a study that will take so long that any evidence arrives too late for decision making might not be the best approach. Equally by generating evidence that provides only part of the answer will leave further questions – therefore as a generator of evidence you must make a choice knowing that there are likely trade-offs.
The core message here is HTA and Evidence are central to decision making about how health technology is used – whether that is at a local, national, regional or global level. Evidence is therefore central to any success you want to have. Due to the complexities associated with evidence generation, how evidence is generated needs to be carefully planned and planning early is always good.
United States Congress: Office of Technology Assessment. Development of Medical Technology: Opportunities for Assessment August 1976
O’Rourke, B et al. Value Health. 2020; 23(6):824–825