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Table 1 Summary of characteristic differences and challenges of HTA of medical devices

From: Health technology assessment of medical devices: current landscape, challenges, and a way forward

Characteristic differences and challenges

Description

References

Available clinical evidence

The characteristic differences between pharmaceuticals and medical devices may lead to a large gap in terms of the availability of evidence, especially clinical evidence

• Considerable challenges exist in performing an RCT for medical devices. For example, a double-blind procedure was usually hard to implement due to differences in the appearance of medical devices

• Another reason was that implantable medical devices require informed consent from a patient before implantation as they involve an invasive procedure

• There was a lack of infrastructure, e.g., qualified clinical centers and trained professionals to conduct RCTs for medical devices

[3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]

Device-user interaction

Unlike drugs, the performance of medical devices sometimes depends on their users’ experience as well

• The so-called “learning curve”: the launch of a medical device is followed by a training or initiation period during which healthcare professionals learn how to handle the technology. As healthcare professionals gain more experience over time, they were able to grasp the subtle differences that affected the overall clinical benefits, thus making the best use of the technology

• The learning curve had inevitably interfered with the HTA of medical devices because the comparative effectiveness between newly-launched and traditional products was a function of the product itself and operators’ proficiency, which was hard to quantify

• The clinical adoption of medical devices may also associate with wider impact of organizational change, for instance, there may be a need for additional training of physicians or other health professionals, or the introduction of a given device may require a hospital to reorganize services to accommodate the new technology or procedure

[3,4,5,6,7,8,9, 11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27]

Short product life cycle and quick upgrade

Unlike drugs, the product life cycle of medical devices is usually as short as one to 3 years

• The key contributing factor was that medical devices undergo continuous improvement and incremental innovation, which might result in the existence of various models and specifications within a single product class

• Recognizing the iterative nature of medical devices, regulatory agencies exempted such variants from rigorous clinical trials as long as the safety of the new variant was the same as the original. As a result, manufacturers had neither enough time to collect data for economic evaluations nor an incentive to invest in clinical research and HTA

• From researchers’ perspective, the short life cycle required the HTA of medical devices to be done in a timely manner, otherwise the results could become outdated

• Pricing was typically more dynamic than that of pharmaceuticals, which increased the complexity of calculating costs

• Rapid product iteration also made it difficult to conduct HTA since the definition of standard of care was unclear or constantly changing among medical devices with multiple specifications and models

[4,5,6,7,8,9, 11,12,13,14,15,16,17,18,19,20, 22, 25,26,27,28]

Inexplicit target population and lack of direct clinical outcomes

The economic evaluation of medical devices used in screening or diagnostics was ever more challenging as most did not have an explicit target population, nor do they produce clinical outcomes directly

• These devices were used in multiple disease areas or as part of the care pathway with a group of other devices. For example, the positron emission tomography-computed tomography (PET/CT) was used in the diagnosis and follow-up of a number of malignant tumors (e.g., cervical cancer, colorectal cancer, non-small cell lung cancer, melanoma, and ovarian cancer)

• Since these devices or diagnostics are integrated as a specific part of the clinical pathway. As a result, it is hard to quantitatively observe the direct impact of these medical devices on patients’ ultimate medical outcomes

[3, 20, 23, 24, 27]