There are significant delays in the funded access to medicines. Studies indicate that in many countries it takes more than a year for patients to have funded access to medicines after market authorization. This study aimed to understand the disparities in timelines for funded access to medicines across different countries and to identify underlying reasons for this access gap.

We conducted a scoping review to examine the nature of health technology assessment (HTA) processes, current methods, and policies for medicines in ten jurisdictions. The jurisdictions included in this study are Australia, Canada, France, Germany, South Korea, the Netherlands, United Kingdom (divided into England, Scotland and Wales), and United States of America. The information was extracted from the websites of International Network of Agencies for Health Technology Assessment (INAHTA) member agencies in the selected jurisdictions, grey literature from governments’ websites, and peer-reviewed literature.

Overall median time from submission of the evidence dossier to HTA recommendations for most jurisdictions is 22 weeks. Although there are similarities in the time taken to reach a funding decision, there are considerable variations in the time taken for patients to have funded access to medicines after HTA recommendations. Only a few countries mentioned a specific timeline within which medicines approved for funding should be listed. Time taken for price negotiations and other arrangements (i.e., risk-sharing agreements) may contribute to varying timelines for listing medicines for funding. Mostly, such negotiations are confidential and may not be time limited.

There was surprising consistency, globally, in the time it takes for funding decisions after medicines registration. The causes of delays in the medicines’ listing decisions are multifactorial and mostly occur after HTA recommendations. The parallel regulatory-assessment process and prioritization tend to reduce the time to a funding decision. However, transparency is needed in the listing process to improve overall timeliness.

Computerized clinical decision support software (CDSS) are digital health technologies that have been traditionally categorized as medical devices. However, the evaluation frameworks for traditional medical devices are not well adapted to assess the value and safety of CDSS. In this study, we identified a range of challenges associated with CDSS evaluation as a medical device and investigated whether and how CDSS are evaluated in Australia.

Using a qualitative approach, we interviewed 11 professionals involved in the implementation and evaluation of digital health technologies at national and regional levels. Data were thematically analyzed using both data-driven (inductive) and theory-based (deductive) approaches.

Our results suggest that current CDSS evaluations have an overly narrow perspective on the risks and benefits of CDSS due to an inability to capture the impact of the technology on the sociotechnical environment. By adopting a static view of the CDSS, these evaluation frameworks are unable to discern how rapidly evolving technologies and a dynamic clinical environment can impact CDSS performance. After software upgrades, CDSS can transition from providing information to specifying diagnoses and treatments. Therefore, it is not clear how CDSS can be monitored continuously when changes in the software can directly affect patient safety.

Our findings emphasize the importance of taking a living health technology assessment approach to the evaluation of digital health technologies that evolve rapidly. There is a role for observational (real-world) evidence to understand the impact of changes to the technology and the sociotechnical environment on CDSS performance.

Clinical Decision Support Software (CDSS) can improve the quality and safety of care by providing patient-specific diagnostic and treatment recommendations. However, robust evaluation is required to ensure that the recommendations provided are clinically valid, up-to-date, and relevant to a specific clinical context. Most evaluation studies assess CDSS performance from the perspective of end-user requirements. But only occasionally is CDSS subject to stringent pre- and post-market evaluation, making it difficult to determine the safety and quality in practice. This study aimed to assess CDSS evaluation in Australia to identify gaps in evaluation approaches.

We conducted 11 semi-structured interviews with different policymakers from committees involved in digital health activities in Australia. Data were thematically analyzed using both theory-based (deductive) and data-driven (inductive) approaches.

Our findings indicated that evaluating CDSS as a purely technical intervention has overly narrowed the assessment of benefits and risks by inadequately capturing the sociotechnical environment. Existing evaluation methods, adopting a static view of the implemented system, cannot discern the impact of the dynamic clinical environment and rapidly evolving technology on CDSS performance. The timeframe of evaluation studies are also incongruent with fast software upgrade cycles, with clinical practices and software potentially changing by the time evaluation is complete. The regulation of software as a medical device depends on the intended use. CDSS are exempt from regulation because they only ‘produce advice’; however, this ignores the fact that they can transition to specifying a diagnosis and treatment after a software update. There is no framework for continuous post-market monitoring, and this is especially important when a CDSS algorithm can change and impact on patient management.

The sociotechnical environment is a significant factor influencing the impact of CDSS on clinical practice, therefore evaluation approaches must acknowledge the dynamic nature of clinical and organizational contexts. Pragmatic and data-driven methodologies are required for CDSS evaluation that acknowledge the evolving landscape of clinical practice and its relationship to technology.

The clinical data is increasing at a considerably higher rate than the capacity of the healthcare system and clinicians to manage this data. Digital tools such as clinical decision support systems (CDSS) provide opportunities for evidence-based patient care by intelligently filtering and presenting the information required for clinical decision making at the point of care. Despite the success of pilot projects, CDSS have had limited implementation in broader health systems. We aimed to identify challenges faced by policymakers for CDSS implementation and to provide policy recommendations.

We conducted eleven semi-structured interviews with Australian policymakers from state and national committees involved in digital health activities. The data were analyzed using reflexive thematic analysis to identify policy priorities.

Our findings indicate that fragmentation of care processes and structures in the digital health ecosystem is one of the main impediments to delivering coordinated care using CDSS. Five themes for policy action were identified: (i) establishing a shared conceptual framework for user-centered design of CDSS that is aligned with stakeholders’ priorities, (ii) maintaining the right balance between the customization and standardization of systems, (iii) developing mutually agreed semantic interoperability standards at the local, state and national level, allowing generation and exchange of information across the health system without changing its context and meaning, (iv) reorienting organizational structures to build capacity to foster change, and (v) developing collaborative care models to avoid conflicting interests between stakeholders.

Findings highlight the importance of developing system-wide guidance to establish a clear vision for CDSS implementation and alignment of organizational processes across all levels of health care. There is a need to build a shared policy framework for modelling the innovative activities such as CDSS implementation across the digital health landscape which minimizes the operational and strategic fragmentation of different organizations.

Clinical decision support systems (CDSS) are being developed to support evidence-based antibiotic prescribing and reduce the risk of inappropriate or over-prescribing; however, adoption of CDSS into the health system is rarely sustained. We aimed to understand the implementation challenges at a macro (policymakers), meso (organizational) and micro-level (individual practices) to identify the drivers of CDSS non-adoption.

We have adopted a mixed-method study design which comprised of: (i) systematic review and meta-analysis to assess the impact of CDSS on appropriate antibiotic prescribing, (ii) Online survey of clinicians in Australia from hospitals and primary care to identify drivers of CDSS adoption and (iii) in-depth interviews with policymakers to evaluate policy-level challenges and opportunities to CDSS implementation.

CDSS implementation can improve compliance with antibiotic prescribing guidelines, with a relative decrease in mortality, volume of antibiotic use and length of hospital stay. However, CDSS provision alone is not enough to achieve these benefits. Important predictors of clinicians’ perception regarding CDSS adoption include the seniority of clinical end-users (years), use of CDSS, and the care setting. Clinicians in primary care and those with significant clinical experience are less likely to use CDSS due to a lack of trust in the system, fear of comprising professional autonomy, and patients’ expectations. Lack of important policy considerations for CDSS integration into a multi-stakeholder healthcare system has limited the organizational capacity to foster change and align processes to support the innovation.

These results using multiple lines of evidence highlight the importance of a holistic approach when undertaking health technology management. There needs to be system-wide guidance that integrates individual, organizational and system-level factors when implementing CDSS so that effective antibiotic stewardship can be facilitated.

Worldwide, governments employ health technology assessment (HTA) in healthcare funding decision making. Requests to include public perspectives in this are increasing, with the idea being that the public can identify social values to guide policy development, increasing the transparency and accountability of government decision making.

To understand the perspectives of the Canadian public on the rationale and design of public involvement in HTA.

A demographically representative sample of residents of a Canadian province was selected to take part in two sets of two focus groups (sixteen people for the first set and twenty for the second set).

Participants were suspicious of the interests driving various stakeholders involved in HTA. They saw the public as uniquely impartial though also lacking knowledge about health technologies. Participants were also suspicious of personal biases and commended mechanisms to reduce their impact. Participants suggested various involvement methods, such as focus groups, citizens' juries and surveys, noting advantages and disadvantages belonging to each and commending a combination.

We identified a lack of public understanding of how decisions are made and distrust concerning whose interests and values are being considered. Public involvement was seen as a way of providing information to the public and ascertaining their views and values. Participants suggested that public involvement should employ a mixed-methods strategy to support informed debate and participation of a large number of people.

Cystic fibrosis (CF) is the most common autosomal recessive disorder in Caucasians, occurring in one out of every 2,500–2,800 births worldwide, and is associated with a high burden of disease. In Australia, prenatal testing for CF is indicated for pregnant couples identified as carriers or when a fetus is found to have an ‘echogenic bowel’ (FEB). We aimed to determine the effectiveness of prenatal CF testing and to assess ethical dimensions. A key challenge in assessing a prenatal test is selecting appropriate endpoints to indicate clinical effectiveness.

A systematic review was conducted and a linked evidence approach was used to answer the effectiveness question. The literature on ethical considerations relating to prenatal testing was also reviewed.

No studies were identified on the direct effectiveness of prenatal CF testing or downstream consequences. Linked evidence showed good diagnostic performance with a test failure rate of 4.5 percent. Termination of pregnancy occurred in the majority of cases where two mutations were identified in a fetus of carrier parents (155/163; 95 percent), indicating testing impacts clinical management. In FEB cases with CF, termination occurred in around sixty-five percent of pregnancies. Both terminating a pregnancy and having a child with CF were associated with poor short term parental psychological outcomes. Evidence indicates prenatal testing leads to a decreased number of CF-affected births. However, ethical analyses indicated that ‘informed decisions’ should have been the primary outcome of interest.

Proper counselling prior to testing ensures that the aim of prenatal testing is informing reproductive choices in a non-directive way, rather than decreasing the number of CF-affected births (which is ethically problematic). These results suggest that for health technology assessments undertaken on contentious topics, ethical analysis should be undertaken first so appropriate endpoints are selected for the subsequent systematic review of clinical evidence and for the economic model.