What is Health Technology Assessment?

Health Technology Assessment (HTA) is a process in which health technologies (including pharmaceuticals, procedures, medical devices and digital health technologies [DHTs]) are systematically evaluated so healthcare providers, payers and policymakers can understand the true value of the technology.

The primary aim of HTA is to support informed decision-making in healthcare by assessing the costs and benefits associated with a technology and concluding if the technology represents value for money.

For the payers of healthcare services provided to patients, whether that be Government/Public (NHS in the UK, Medicare in the US) or commercial insurers (private medical insurance) it’s important that all health technologies provide some benefit for their cost. Different payers will have different thresholds for the amount of benefit a medicine can provide for a certain amount of cost. For example, in the UK, NICE will only recommend that the NHS provide technologies that cost less than £20,000 per 1 quality adjusted life year (QALY) (one year of life at 100% quality of life).

In Figure 1 below, Intervention B would be considered cost-effective compared to Intervention A at the £30,000/QALY level but not the £20,000/QALY level.

So, if you are developing a patient facing DHT, and you want healthcare providers to provide the technology to patients, read on for a brief introduction to HTA for digital health.

What Does Health Technology Assessment Involve?

HTA encompasses a broad range of assessments to provide comprehensive data for decision-making, primarily focusing on clinical effectiveness, cost-effectiveness, and budget impact.

Clinical Effectiveness

The clinical effectiveness section measures how well a technology works in the clinical setting. Clinical effectiveness is typically evaluated through various stages of randomised clinical trials (RCTs), including Phase I (safety), Phase II (efficacy), and Phase III (comparative effectiveness). For the HTA submission, data from Phase III trials are often required to provide robust evidence of the technology’s benefits over existing treatments.

Key questions addressed include:

• Is the technology safe?
• Does the technology work?
• Which patients benefit from the technology the most?
• Is there a meaningful improvement in quality of life while using the technology?

However, in the case of DHTs, a variety of study designs are used. In a systematic review published in the Journal of Medical Internet Research, various study designs used to evaluate DHTs were highlighted, each with their own strengths and weaknesses:

Randomised Controlled Trials (RCTs):

• Description: Participants are randomly assigned to intervention or control groups.
• Benefits: High level of evidence due to randomisation, which minimises bias.
• Limitations: Can be expensive and time-consuming.

Quasi-experimental Designs:

• Description: Non-randomised controlled trials where participants are assigned to groups without randomisation.
• Benefits: Easier to implement than RCTs, useful in real-world settings.
• Limitations: Higher risk of bias as groups may differ in ways other than the intervention.

Pre-post Studies:

• Description: Measure outcomes before and after an intervention without a control group.
• Benefits: Simple and cost-effective, good for preliminary assessments.
• Limitations: Weak evidence as changes might not be solely due to the intervention.

Observational Studies:

• Description: Include prospective cohort studies, retrospective studies, cross-sectional studies, and surveys.
• Benefits: Can observe real-world outcomes and collect large amounts of data.
• Limitations: Cannot establish causation due to lack of controlled intervention.

Qualitative Studies or Mixed Methods:

• Description: Use interviews, focus groups, and mixed methods to gather detailed insights.
• Benefits: Provides in-depth understanding of user experiences and implementation processes.
• Limitations: Subjective data that may not be generalisable.

Other Research Methods:

• Description: Include pilot studies, simulation, or usability testing.
• Benefits: Useful for initial testing and development phases.
• Limitations: Generates preliminary findings that require further validation.

The same review extracted the effects (outcomes) that were commonly measured and reported in studies that investigated DHTs, in the figure below you can see a list of these outcomes and the percent of studies that reported them with a higher percentage indicating a more commonly measured outcome and a lower percentage indicating a less used outcome.

The evaluation categorised health effects into five main areas:

Health and Clinical Outcomes:

• Description: General indicators (e.g., health status, quality of life, medication management) and disease-specific indicators (e.g., diabetes or hypertension).
• Importance: These outcomes measure the direct impact on patients’ health and are crucial for assessing whether an intervention improves clinical conditions.
• Situations to Use: When evaluating the effectiveness of interventions aimed at improving specific health conditions or general well-being.

Psychological and Behavioural Outcomes:

• Description: Indicators such as patient-provider communication, satisfaction, self-efficacy, self-management, adherence to therapy, and perceived social support.
• Importance: Reflect how digital health interventions influence patients’ behaviour and psychological state, which are essential for long-term health management.
• Situations to Use: When assessing interventions designed to change patient behaviour or improve mental health and communication with healthcare providers.

Health Care Utilisation:

• Description: Impact on resources like time used by patients/providers and use of the healthcare system (e.g., hospitalisations, outpatient care).
• Importance: These indicators assess the economic and resource implications for both patients and the healthcare system, helping to understand cost-effectiveness.
• Situations to Use: When evaluating the economic impact of digital health interventions on healthcare systems.

System Adoption and Use:

• Description: Patient adoption/utilisation and professional practice changes.
• Importance: Measures how well digital health interventions are accepted and used by patients and healthcare providers, critical for the success and sustainability of these interventions.
• Situations to Use: When studying the acceptance, practical use, and impact on professional practices of new digital health technologies.

System Attributes:

• Description: Usability for patients and providers.
• Importance: Evaluates the ease of use and functionality of digital health systems, which can affect user satisfaction and continued use.
• Situations to Use: When developing or refining digital health tools to ensure they meet user needs effectively.

Cost-Effectiveness

The cost effectiveness section evaluates the economic value of the technology by comparing its costs to its health benefits. Cost-effectiveness is often measured using metrics such as the Incremental Cost-Effectiveness Ratio (ICER), which assesses the additional cost per unit of health benefit gained, usually measured in Quality-Adjusted Life Years (QALYs) gained. Results for this evaluation are typically derived through economic modelling of the clinical trial data (mentioned above).

Key questions addressed:

• What are the costs associated with the technology?
• Does the technology provide good value for money?

To evaluate cost effectiveness in a methodologically robust way, a cost effectiveness analysis (CEA) or preferably a cost utility analysis (CUA) must be performed.

To help you decide which type of economic evaluation to perform for your product, see our post on the 5 types of early economic evaluation for DHTs.

Key characteristics of a robust analysis

In a systematic review of cost-effectiveness analyses of DHTs, published in Frontiers in Public Health, key characteristics for evaluations of digital health products were reported, these would be considered essential for a HTA submission, however these are largely the same as for pharmaceuticals and medical devices (payers want to be able to compare all health technologies in the same way, and the ICER is the best way of doing so).

Inclusion of Cost-Utility Analysis (CUA):

• Description: CUA was performed in addition to the primary CEA 23% of the time.
• Importance: Incorporating CUA helps in measuring the value of health outcomes in terms of quality-adjusted life years (QALYs), providing a more comprehensive evaluation of the intervention’s benefits.

Costing Perspective:

• Description: the payer/healthcare provider perspective was adopted 69% of the time, while the societal perspective was used 54% of the time (sometimes in addition to payer/provider).
• Importance: The perspective determines which costs are included in the analysis. The payer perspective focuses on direct medical costs to patients and healthcare providers, while the societal perspective includes broader economic impacts, such as direct non-medical costs and indirect costs, making it a useful viewpoint for understanding the wider economic implications of a technology.

If you need help deciding which costing perspective is right for your technology, then check out our ultimate guide to measuring the costs of digital health technologies.

Measurement of QALYs:

• Description: Various instruments were used to derive QALYs from trials, including ShortForm-6 Dimensions, European Quality of Life 5-Dimensions, Health Related Quality of Life, and others.
• Importance: Using reliable and validated instruments to measure QALYs ensures that the health outcomes are accurately captured and comparable across different studies.

To find out more about CEA and CUA, please find a link to our post on the 5 types of Economic Evaluation For Digital Health Technologies (DHTs)

Budget Impact Analysis

Budget Impact Analysis (BIA) assesses the financial implications of adopting the technology within a healthcare budget. Integrating a technology into existing healthcare systems is associated with short- and long-term costs, these include direct costs such as purchase, implementation, and maintenance, as well as indirect costs like training and changes in workflow.

Questions to consider are:

• Can we afford to pay for all people who might need the technology?
• Does the technology provide good value in the long run?

When conducting a BIA:

Specify the Target Population:

• Begin by identifying the population likely to be impacted by the new product.
• Estimate the prevalence and incidence of individuals with the relevant disease or condition who would benefit from the product.
• Account for previously untreated individuals who might seek treatment once your product becomes available.
• Segment the population by disease severity or stage, allowing for a detailed budget impact analysis for different subgroups.
• Recognise that as your product gains adoption, the proportion of individuals at various stages can shift over time.

Set the Boundaries of the Analysis:

• Determine the timescale for measuring changes in health expenditure and cost savings, aligning with the budget holder’s planning horizon rather than the disease duration.
• Carefully consider whether expected changes in expenditure and cost savings will materialise within your chosen timeframe, as this is pivotal for accurate analysis.

Determine Treatment Mix:

• Assess any changes in treatment mix resulting from your product’s availability.
• Evaluate the product’s uptake and whether it will replace or supplement existing treatment options.
• If your product displaces an existing one, estimate the cost savings from replacing the current option.

Estimate Product and Disease-related Costs:

• Follow general guidelines for measuring costs in health economic evaluations, but note that BIA often adopts a more restrictive budget holder perspective, typically excluding development costs or patient-incurred costs.
• Consider how your product might alter disease-related costs; for example, if it prevents heart conditions, factor in the avoided treatment costs. This is particularly pertinent when immediate impacts on disease-related expenditure are anticipated, such as with acute conditions.

Report the Results:

• Present budget impact results in a disaggregated manner, detailing each main cost component individually. This breakdown enables budget holders to grasp the relative weight of each component within the total cost impact.
• Report these impacts separately for each year considered in your analysis.
• Include sensitivity analysis scenarios to understand how varying key assumptions—such as population size, treatment mix, and cost measurements—affect the budget impact assessment.

To find out more about Budget Impact Analysis, please find a link to our post on Economic Evaluation For Digital Health Technologies (DHTs)

Key Principles of HTA for Digital Health

Several key principles guide the HTA process for digital health technologies and promote equitable, efficient, and high-quality health systems. These principles ensure the delivery of quality health services and the development of health technology assessment (HTA) concepts and agencies in different regions.

Multidisciplinary Approach

HTA requires input from various disciplines:

• Clinical Experts: Provide insights into clinical effectiveness and the unmet need in the patient pathway.
• Health Economists: Evaluate the robustness of the modelling assumptions and methodology
• Patient Representatives: Offer perspectives on usability and impact.

This multidisciplinary approach ensures comprehensive evaluations that consider all relevant factors.

Transparency and Objectivity

The HTA process must be transparent and objective:

• Methodologies Access: Stakeholders should have access to the methodologies used. This builds trust in the results and recommendations.
• Evidence Consideration: Transparency in evidence consideration ensures objectivity. The NICE evidence standards framework provides a robust methodology for companies to follow when seeking reimbursement in the UK.

Continuous Evaluation

Digital health technologies evolve rapidly:

• Regular Updates: Continuous evaluation is necessary to keep up with technological advancements and emerging evidence. Regular updates ensure decisions remain relevant over time.
• Emerging Evidence: Incorporating new evidence helps maintain the relevance of assessments.

Patient-Centered Focus

Incorporating patient perspectives is crucial in HTA for digital health:

• Patient Needs Assessment: Understanding patient needs helps tailor assessments.
• Preferences and Experiences: Reflecting real-world usage enhances assessment relevance.

In research conducted on patients’ perspectives of DHTs, published in PEC innovation journal, 6 key facilitatory factors and barriers to digital health adoption were discussed. These factors are shown in the figure below.

Companies should seek to highlight aspects of their products that facilitate enhanced patient experience, while minimising the barriers to adoption:

Patient empowerment, self-management, and personalisation drive adoption of digital health tools:

• Engaged patients benefit most from managing their health conditions using digital tools.
• Empowerment and personalisation can shift healthcare models from paternalistic to patient-centred, fostering collaborative relationships between clinicians and patients.
• Personalised digital platforms enhance patient experience but must balance the need for human contact in traditional consultations.
• Successful digital health tools should cater to both patient and clinician needs to avoid increasing clinician workload.

Patient acceptance and active involvement are pivotal for technology success:

• Patients’ active role in designing digital health tools ensures that these solutions meet their needs and abilities, leading to higher uptake and sustained use.
• Participatory design, involving patients alongside clinicians and technicians, addresses barriers to adoption and enhances user satisfaction.
• Continuous use of digital health tools depends on understanding and empathising with both patients’ and providers’ experiences.
• A paradigm shift towards human-centred design in healthcare is necessary to improve the efficiency and experience of healthcare delivery.

Challenges and Limitations

Despite its benefits, HTA in the context of digital health technologies faces several challenges and limitations:

• Rapid Technological Changes: The fast pace of innovation in digital health can outstrip the ability of HTA processes to keep up. Technologies may become outdated by the time an assessment is completed, reducing the relevance of the findings.

• Data Privacy and Security: Evaluating digital health technologies often involves handling sensitive patient data. Ensuring data privacy and security while conducting comprehensive assessments is a significant challenge.

• Interoperability Issues: Digital health technologies often need to integrate with existing healthcare systems. Assessing the interoperability of these technologies can be complex and may limit the generalisability of HTA findings.

• Limited Long-Term Evidence: Many digital health technologies are relatively new, and there may be a lack of long-term evidence on their effectiveness and safety. This can make it difficult to draw definitive conclusions from HTA.

• Resource Intensity: Conducting thorough HTA requires significant resources, including time, expertise, and funding. This can be a barrier, especially in low-resource settings.

• Regulatory Variability: Different regions may have varying regulatory requirements for digital health technologies, complicating the HTA process and limiting the applicability of findings across different healthcare systems.

Addressing these challenges requires ongoing adaptation and innovation in HTA methodologies to ensure they remain robust and relevant in the rapidly evolving field of digital health.

Conclusion

Health Technology Assessment is a vital tool in evaluating digital health technologies. Through a robust understanding of HTA, its importance within the context of healthcare decision-making, and the key principles guiding its practice, stakeholders can make informed choices that enhance patient care and optimise resource allocation.

How Healthonomix can help?

If you are currently evidence planning for your product and would like to chat to an expert, please feel free to contact us to speak to an expert within the team.