Assessment of the Barriers and Enablers of the Use of mHealth Systems in Sub-Saharan Africa According to the Perceptions of Patients, Physicians, and Health Care Executives in Ethiopia: Qualitative Study.

BACKGROUND: Digital technologies are increasingly being used to deliver health care services and promote public health. Mobile wireless technologies or mobile health (mHealth) technologies are particularly relevant owing to their ease of use, broad reach, and wide acceptance. Unlike developed countries, Sub-Saharan Africa experiences more challenges and obstacles when it comes to deploying, using, and expanding mHealth systems. In addition to barriers, there are enabling factors that could be exploited for the design, implementation, and scaling up of mHealth systems. Sub-Saharan Africa may require tailored solutions that address the specific challenges facing the region. OBJECTIVE: The overall aim of this study was to identify the barriers and enablers for using mHealth systems in Sub-Saharan Africa from the perspectives of patients, physicians, and health care executives. METHODS: Multi-level and multi-actor in-depth semistructured interviews were employed to qualitatively explore the barriers and enablers of the use of mHealth systems. Data were collected from patients, physicians, and health care executives. The interviews were audio recorded, transcribed verbatim, translated, and coded. Thematic analysis methodology was adopted, and NVivo software was used for the data analysis. RESULTS: Through this rigorous study, a total of 137 determinants were identified. Of these determinants, 68 were identified as barriers and 69 were identified as enablers. Perceived barriers in patients included lack of awareness about mHealth systems and language barriers. Perceived enablers in patients included need for automated tools for health monitoring and an increasing literacy level of the society. According to physicians, barriers included lack of available digital health systems in the local context and concern about patients' mHealth capabilities, while enablers included the perceived usefulness in reducing workload and improving health care service quality, as well as the availability of mobile devices and the internet. As perceived by health care executives, barriers included competing priorities alongside digitalization in the health sector and lack of interoperability and complete digitalization of implemented digital health systems, while enablers included the perceived usefulness of digitalization for the survival of the highly overloaded health care system and the abundance of educated manpower specializing in technology. CONCLUSIONS: mHealth systems in Sub-Saharan Africa are hindered and facilitated by various factors. Common barriers and enablers were identified by patients, physicians, and health care executives. To promote uptake, all relevant stakeholders must actively mitigate the barriers. This study identified a promising outlook for mHealth in Sub-Saharan Africa, despite the present barriers. Opportunities exist for successful integration into health care systems, and a user-centered design is crucial for maximum uptake.

Mitigating Health-Related Uncertainties During Pregnancy: The Role of Smart Health Monitoring Technologies.

Pregnancy is a time filled with uncertainties, which can be challenging and lead to fear or anxiety for expectant parents. Health monitoring technologies that allow monitoring of the vital signs of both the mother and fetus offer a way to address health-related uncertainties. But are smart health monitoring technologies (SHMTs) actually an effective means to reduce uncertainties during pregnancy, or do they have the opposite effect? Using conceptual reasoning and phenomenological approaches grounded in existing literature, this Viewpoint explores the effects of SHMTs on health-related uncertainties during pregnancy. The argument posits that while SHMTs can alleviate some health-related uncertainties, they may also create new ones. This is particularly the case when the abundance of vital data overwhelms pregnant persons, leads to false-positive diagnoses, or raises concerns about the accuracy and analysis of data. Consequently, it is concluded that the use of SHMTs is not a cure-all for overcoming health-related uncertainties during pregnancy. Since the use of such monitoring technologies can introduce new uncertainties, it is important to carefully consider where and for what purpose they are used, use them sparingly, and promote a pragmatic approach to uncertainties.Using conceptual reasoning and phenomenological approaches grounded in existing literature, the effects of SHMTs on health-related uncertainties during pregnancy are explored. The argument posits that while SHMTs can alleviate some health-related uncertainties, they may also create new ones. This is particularly the case when the abundance of vital data overwhelms pregnant persons, leads to false-positive diagnoses, or raises concerns about the accuracy and analysis of data. Consequently, it is concluded that the use of SHMTs is not a cure-all for overcoming health-related uncertainties during pregnancy. Since the use of such monitoring technologies can introduce new uncertainties, it is important to carefully consider where and for what purpose they are used, use them sparingly, and promote a pragmatic approach to uncertainties.

Codesign of health technology interventions to support best-practice perioperative care and surgical waitlist management.

OBJECTIVES: This project aimed to determine where health technology can support best-practice perioperative care for patients waiting for surgery. METHODS: An exploratory codesign process used personas and journey mapping in three interprofessional workshops to identify key challenges in perioperative care across four health districts in Sydney, Australia. Through participatory methodology, the research inquiry directly involved perioperative clinicians. In three facilitated workshops, clinician and patient participants codesigned potential digital interventions to support perioperative pathways. Workshop output was coded and thematically analysed, using design principles. RESULTS: Codesign workshops, involving 51 participants, were conducted October to November 2022. Participants designed seven patient personas, with consumer representatives confirming acceptability and diversity. Interprofessional team members and consumers mapped key clinical moments, feelings and barriers for each persona during a hypothetical perioperative journey. Six key themes were identified: 'preventative care', 'personalised care', 'integrated communication', 'shared decision-making', 'care transitions' and 'partnership'. Twenty potential solutions were proposed, with top priorities a digital dashboard and virtual care coordination. DISCUSSION: Our findings emphasise the importance of interprofessional collaboration, patient and family engagement and supporting health technology infrastructure. Through user-based codesign, participants identified potential opportunities where health technology could improve system efficiencies and enhance care quality for patients waiting for surgical procedures. The codesign approach embedded users in the development of locally-driven, contextually oriented policies to address current perioperative service challenges, such as prolonged waiting times and care fragmentation. CONCLUSION: Health technology innovation provides opportunities to improve perioperative care and integrate clinical information. Future research will prototype priority solutions for further implementation and evaluation.

SurvInt: a simple tool to obtain precise parametric survival extrapolations.

BACKGROUND: Economic evaluation of emerging health technologies is mandated by agencies such as the National Institute for Health and Care Excellence (NICE) to ensure their cost is proportional to their benefit. To avoid bias, NICE stipulate that the benefit of a treatment is assessed across the lifetime of the patient population, which can be many decades. Unfortunately, follow-up from a clinical trial will not usually cover the required period and the observed follow-up will require extrapolation. For survival data this is often done by selecting a preferred model from a set of candidate parametric models. This approach is limited in that the choice of model is restricted to those originally fitted. What if none of the models are consistent with clinical prediction or external data? METHOD/RESULTS: This paper introduces SurvInt, a tool that estimates the parameters of common parametric survival models which interpolate key survival time co-ordinates specified by the user, which could come from external trials, real world data or expert clinical opinion. This is achieved by solving simultaneous equations based on the survival functions of the parametric models. The application of SurvInt is shown through two examples where traditional parametric modelling did not produce models that were consistent with external data or clinical opinion. Additional features include model averaging, mixture cure models, background mortality, piecewise modelling, restricted mean survival time estimation and probabilistic sensitivity analysis. CONCLUSIONS: SurvInt allows precise parametric survival models to be estimated and carried forward into economic models. It provides access to extrapolations that are consistent with multiple data sources such as observed data and clinical predictions, opening the door to precise exploration of regions of uncertainty/disagreement. SurvInt could avoid the need for post-hoc adjustments for complications such as treatment switching, which are often applied to obtain a plausible survival model but at the cost of introducing additional uncertainty. Phase III clinical trials are not designed with extrapolation in mind, and so it is sensible to consider alternative approaches to predict future survival that incorporate external information.

Combining user-centered design and behavioral theory to enhance health technologies: A personas-based approach for a primary-care based multifactorial falls risk assessment tool.

INTRODUCTION: Multifactorial falls risk assessment tools (FRATs) can be an effective falls prevention method for older adults, but are often underutilized by health care professionals (HCPs). This study aims to enhance the use and implementation of multifactorial FRATs by combining behavioral theory with the user-centered design (UCD) method of personas construction. Specifically, the study aimed to (1) construct personas that are based on external (i.e., needs, preferences) and intrinsic user characteristics (i.e., behavioral determinants); and (2) use these insights to inform requirements for optimizing an existing Dutch multifactorial FRAT (i.e., the 'Valanalyse'). METHODS: Survey data from HCPs (n = 31) was used to construct personas of the 'Valanalyse.' To examine differences between clusters on 68 clustering variables, a multivariate cluster analysis technique with non-parametric analyses and computational methods was used. The aggregated external and intrinsic user characteristics of personas were used to inform key design and implementation requirements for the 'Valanalyse,' respectively, whereby intrinsic user characteristics were matched with appropriate behavior change techniques to guide implementation. RESULTS: Significant differences between clusters were observed in 20 clustering variables (e.g., behavioral beliefs, situations for use). These variables were used to construct six personas representing users of each cluster. Together, the six personas helped operationalize four key design requirements (e.g., guide treatment-related decision making) and 14 implementation strategies (e.g., planning coping responses) for optimizing the 'Valanalyse' in Dutch geriatric, primary care settings. CONCLUSION: The findings suggest that theory- and evidence-based personas that encompass both external and intrinsic user characteristics are a useful method for understanding how the use and implementation of multifactorial FRATs can be optimized with and for HCPs, providing important implications for developers and eHealth interventions with regards to encouraging technology adoption.

Access in all areas? A round up of developments in market access and health technology assessment: part 3.

In this latest update, we explore some of the key updates in market access over recent months including the UK's voluntary scheme for branded medicines pricing, access and growth (VPAG), the first drugs funded by the Innovative Medicines Fund in the UK and the Direct Access Scheme in France, and, finally, the new Institute for Clinical and Economic Review (ICER) value assessment framework in the USA.

mHealth Apps for the Self-Management of Low Back Pain: Systematic Search in App Stores and Content Analysis.

BACKGROUND: With the rapid development of mobile health (mHealth) technology, many health apps have been introduced to the commercial market for people with back pain conditions. However, little is known about their content, quality, approaches to care for low back pain (LBP), and associated risks of use. OBJECTIVE: The aims of this research were to (1) identify apps for the self-management of LBP currently on the market and (2) assess their quality, intervention content, theoretical approaches, and risk-related approaches. METHODS: The UK iTunes and Google Play stores were initially searched for apps related to the self-management of LBP in May 2022. A repeat search in June 2023 was conducted to ensure that any relevant new apps developed in the last year were incorporated into the review. A total of 3 keywords recommended by the Cochrane Back and Neck Group were used to search apps "low back pain," "back pain," and "lumbago." The quality of the apps was assessed by using the 5-point Mobile App Rating Scale (MARS). RESULTS: A total of 69 apps (25 iOS and 44 Android) met the inclusion criteria. These LBP self-management apps mainly provide recommendations on muscle stretching (n=51, 73.9%), muscle strengthening (n=42, 60.9%), core stability exercises (n=32, 46.4%), yoga (n=19, 27.5%), and information about LBP mechanisms (n=17, 24.6%). Most interventions (n=14, 78%) are consistent with the recommendations in the National Institute for Health and Care Excellence (NICE) guidelines. The mean (SD) MARS overall score of included apps was 2.4 (0.44) out of a possible 5 points. The functionality dimension was associated with the highest score (3.0), whereas the engagement and information dimension resulted in the lowest score (2.1). Regarding theoretical and risk-related approaches, 18 (26.1%) of the 69 apps reported the rate of intervention progression, 11 (15.9%) reported safety checks, only 1 (1.4%) reported personalization of care, and none reported the theoretical care model or the age group targeted. CONCLUSIONS: mHealth apps are potentially promising alternatives to help people manage their LBP; however, most of the LBP self-management apps were of poor quality and did not report the theoretical approaches to care and their associated risks. Although nearly all apps reviewed included a component of care listed in the NICE guidelines, the model of care delivery or embracement of care principles such as the application of a biopsychosocial model was unclear.

Justifying the source of external comparators in single-arm oncology health technology submissions: a review of NICE and PBAC assessments.

Background: The drive to expedite patient access for diseases with high unmet treatment needs has come with an increasing use of single-arm trials (SATs), especially in oncology. However, the lack of control arms in such trials creates challenges to assess and demonstrate comparative efficacy. External control (EC) arms can be used to bridge this gap, with various types of sources available to obtain relevant data. Objective: To examine the source of ECs in single-arm oncology health technology assessment (HTA) submissions to the National Institute for Health and Care Excellence (NICE) and the Pharmaceutical Benefits Advisory Committee (PBAC) and how this selection was justified by manufacturers and assessed by the respective HTA body. Methods: Single-arm oncology HTA submission reports published by NICE (England) and PBAC (Australia) from January 2011 to August 2021 were reviewed, with data qualitatively synthesized to identify themes. Results: Forty-eight oncology submissions using EC arms between 2011 and 2021 were identified, with most submissions encompassing blood and bone marrow cancers (52%). In HTA submissions to NICE and PBAC, the EC arm was typically constructed from a combination of data sources, with the company's justification in data source selection infrequently provided (PBAC [2 out of 19]; NICE [6 out of 29]), although this lack of justification was not heavily criticized by either HTA body. Conclusion: Although HTA bodies such as NICE and PBAC encourage that EC source justification should be provided in submissions, this review found that this is not typically implemented in practice. Guidance is needed to establish best practices as to how EC selection should be documented in HTA submissions.

R WE ready for reimbursement? A round up of developments in real-world evidence relating to health technology assessment: part 14.

In this latest update we highlight: a publication from the US FDA regarding the definitions of real-world data (RWD) and real-world evidence (RWE); a publication from academic researchers on a demonstration project for target trial emulation; a publication from the National Institute of Health and Care Excellence (NICE) on the 1 year anniversary of their RWE framework; and a publication from NICE and Flatiron Health on the utility of US RWD for initial UK health technology assessment decision making.

Implementation of health technologies in Brazil: analysis of federal guidelines for the public health system. / Implementação de tecnologias em saúde no Brasil: análise de orientações federais para o sistema público de saúde.

This study aimed to identify the regulatory framework and federal guidelines that support the process of implementing health technologies in the Unified Health System (SUS) through analysis of documents and legislation related to the National Health Technology Management Policy, published between 2009 and 2021. The search and selection of documents and subsequent data extraction were carried out. The documents were grouped into three categories: structural regulatory documents, recommendations on evaluation of technologies, and recommendations on clinical guidelines. In 38.8% of the regulatory documents, citations to implementation related mainly to SUS clinical guidelines were identified; however, no document dedicated to guiding implementation actions was identified. Recommendations related to implementations were identified in 27.1% of the reports and 66.1% of the guidelines, although without standardization and, in general, in little detail, focusing on resources and actions needed for making technology available rather than on methods and interventions for its implementation. The results evidence a gap in formal guidelines to guide the implementation process in Brazil, representing an opportunity for the development of models aligned with the reality of the SUS.

O objetivo foi identificar o arcabouço regulatório e as orientações federais que sustentam o processo de implementação de tecnologias em saúde no Sistema Único de Saúde (SUS), por meio da análise de documentos e legislações relacionados à Política Nacional de Gestão de Tecnologias de Saúde, publicados entre 2009 e 2021. Foi realizada busca e seleção dos documentos e posterior extração de dados, agrupados por três categorias: normativas estruturantes, recomendações na avaliação de tecnologias e recomendações nas diretrizes clínicas. Em 38,8% das normativas, foram identificadas citações à implementação relacionadas principalmente às diretrizes clínicas do SUS, mas nenhum documento dedicado a orientar as ações de implementação. As recomendações relacionadas às implementações foram identificadas em 27,1% dos relatórios e em 66,1% das diretrizes, mas sem padronização e, de modo geral, pouco detalhadas, com foco em recursos e ações necessárias para a disponibilização da tecnologia, ao invés de métodos e intervenções para implementação. Os resultados confirmam a existência de uma lacuna de diretrizes formais para guiar o processo de implementação no Brasil, o que se constitui em oportunidade para o desenvolvimento de modelos alinhados à realidade do SUS.

Understanding the Integrated Health Management System Policy in China From Multiple Perspectives: Systematic Review and Content Analysis.

BACKGROUND: The integrated health management system (IHMS), which unites all health care-related institutions under a health-centered organizational framework, is of great significance to China in promoting the hierarchical treatment system and improving the new health care reform. China's IHMS policy consists of multiple policies at different levels and at different times; however, there is a lack of comprehensive interpretation and analysis of these policies, which is not conducive to the further development of the IHMS in China. OBJECTIVE: This study aims to comprehensively analyze and understand the characteristics, development, and evolution of China's IHMS policy to inform the design and improvement of the system. METHODS: We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to collect 152 policy documents. With the perspective of policy tools and policy orientation as the core, a comprehensive 6D framework including policy level, policy nature, release time, policy tools, stakeholders, and policy orientation was established by combining the content of policy texts. These dimensions were then analyzed using content analysis. RESULTS: First, we found that, regarding the coordination of policy tools and stakeholders, China's IHMS policy was more inclined to use environment-based policy tools (1089/1929, 56.45%), which suggests a need for further balance in the internal structure of policy tools. Attention to different actors varied, and the participation of physicians and residents needs further improvement (65/2019, 3.22% and 11/2019, 0.54%, respectively). Second, in terms of level differences, Shanghai's IHMS policy used fewer demand-based policy tools (43/483, 8.9%), whereas the national IHMS policy and those of other provinces and cities used fewer supply-based tools (61/357, 17.1% and 248/357, 69.5%, respectively). The national IHMS strategy placed more emphasis on the construction of smart health care (including digital health; 10/275, 3.6%), whereas Shanghai was a leader in the development of healthy community and healthy China (9/158, 5.7% and 4/158, 2.5%, respectively). Third, in terms of time evolution, the various policy tools showed an increasing and then decreasing trend from 2014 to 2021, with relatively more use of environment-based policy tools and less use of demand-based policy tools in the last 3 years. The growth of China's IHMS policy can be divided into 3 stages: the disease-centered period (2014-2017), the e-health technology development period (2017-2019), and the health-centered period (2018-2021). CONCLUSIONS: Policy makers should make several adjustments, such as coordinating policy tools and the uneven relationships among stakeholders; grasping key policy priorities in the context of local characteristics; and focusing on horizontal, multidimensional integration of health resources starting from the community. This study expands the objects of policy research and improves the framework for policy analysis. The findings provide some possible lessons for future policy formulation and optimization.

Patient Engagement and Patient Experience Data in Regulatory Review and Health Technology Assessment: A Global Landscape Review.

BACKGROUND: Working with patients through meaningful patient engagement (PE) and incorporating patient experience data (PXD) is increasingly important in medicines and medical device development. However, PE in the planning, organization, generation, and interpretation of PXD within regulatory and health technology assessment (HTA) decision-making processes remains challenging. We conducted a global review of the PE and PXD landscape to identify evolving resources by geography to support and highlight the potential of integration of PE and PXD in regulatory assessment and HTA. METHODS: A review of literature/public information was conducted (August 2021-January 2023), led by a multistakeholder group comprising those with lived or professional experience of PE and PXD, to identify relevant regulatory and HTA initiatives and resources reviewed and categorized by geography and focus area. RESULTS: Overall, 53 relevant initiatives/resources were identified (global, 14; North America, 11; Europe, 11; Asia, nine; UK, six; Latin America, one; Africa, one). Most focused either on PE (49%) or PXD (28%); few (11%) mentioned both PE and PXD (as largely separate activities) or demonstrated an integration of PE and PXD (11%). CONCLUSIONS: Our analysis demonstrates increasing interest in PE, PXD, and guidance on their use individually in decision-making. However, more work is needed to offer guidance on maximizing the value of patient input into decisions by combining both PE and PXD into regulatory and HTA processes; the necessity of integrating PE in the design and interpretation of PXD programs should be highlighted. A co-created framework to achieve this integration is part of a future project.

Mobile Technology-Based Interventions for Stroke Self-Management Support: Scoping Review.

BACKGROUND: There is growing interest in enhancing stroke self-management support using mobile health (mHealth) technology (eg, smartphones and apps). Despite this growing interest, "self-management support" is inconsistently defined and applied in the poststroke mHealth intervention literature, which limits efforts to synthesize and compare evidence. To address this gap in conceptual clarity, a scoping review was conducted. OBJECTIVE: The objectives were to (1) identify and describe the types of poststroke mHealth interventions evaluated using a randomized controlled trial design, (2) determine whether (and how) such interventions align with well-accepted conceptualizations of self-management support (the theory by Lorig and Holman and the Practical Reviews in Self-Management Support [PRISMS] taxonomy by Pearce and colleagues), and (3) identify the mHealth functions that facilitate self-management. METHODS: A scoping review was conducted according to the methodology by Arksey and O'Malley and Levac et al. In total, 7 databases were searched. Article screening and data extraction were performed by 2 reviewers. The data were analyzed using descriptive statistics and content analysis. RESULTS: A total of 29 studies (26 interventions) were included. The interventions addressed 7 focal areas (physical exercise, risk factor management, linguistic exercise, activities of daily living training, medication adherence, stroke education, and weight management), 5 types of mobile devices (mobile phones or smartphones, tablets, wearable sensors, wireless monitoring devices, and laptops), and 7 mHealth functions (educating, communicating, goal setting, monitoring, providing feedback, reminding, and motivating). Collectively, the interventions aligned well with the concept of self-management support. However, on an individual basis (per intervention), the alignment was less strong. CONCLUSIONS: On the basis of the results, it is recommended that future research on poststroke mHealth interventions be more theoretically driven, more multidisciplinary, and larger in scale.

The value and impact of health technology assessment: discussions and recommendations from the 2023 Health Technology Assessment International Global Policy Forum.

Health technology assessment (HTA) programs inform decision making about the value and reimbursement of new and existing health technologies; however, they are under increasing pressure to demonstrate that they are a cost-effective use of finite healthcare resources themselves. The 2023 HTAi Global Policy Forum (GPF) discussed the value and impact of HTA, including how it is assessed and communicated, and how it could be enhanced in the future. This article summarizes the discussions held at the 2023 HTAi GPF, where the challenges and opportunities related to the value and impact of HTA were debated. Core themes and recommendations identified that defining the purpose of value and impact assessment is an essential first step prior to undertaking it, and that it can be done through the use and expansion of existing tools. Further work around aligning HTA programs with underlying societal values is needed to ensure the long-term value and impact of HTA. HTA could also have a role in assessing the efficiency of the wider health system by applying HTA methods or concepts to broader budgetary allocations and organizational aspects of health care. Stakeholders (particularly patients, industry, and clinicians but also payers, wider society, and the media) should ideally be actively engaged when undertaking the value and impact assessment of HTA. More concerted efforts in communicating the role and remit of HTA bodies would also help stakeholders to better understand the value and impact of HTA, which in turn could improve the implementation of HTA recommendations and application to future actions in the lifecycle of technologies.

[Application of photoplethysmography for atrial fibrillation in early warning, diagnosis and integrated management].

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. Early diagnosis and effective management are important to reduce atrial fibrillation-related adverse events. Photoplethysmography (PPG) is often used to assist wearables for continuous electrocardiograph monitoring, which shows its unique value. The development of PPG has provided an innovative solution to AF management. Serial studies of mobile health technology for improving screening and optimized integrated care in atrial fibrillation have explored the application of PPG in screening, diagnosing, early warning, and integrated management in patients with AF. This review summarizes the latest progress of PPG analysis based on artificial intelligence technology and mobile health in AF field in recent years, as well as the limitations of current research and the focus of future research.

The extent and quality of qualitative evidence included in health technology assessments: a review of submissions to NICE and CADTH.

OBJECTIVES: Qualitative methods allow in-depth exploration of patient experiences and can provide context for healthcare decision making. Frameworks for patient-based evidence in health technology assessment (HTA) are expanding; yet, how extensively qualitative methods are currently used is unclear. This review characterized the extent and quality of qualitative data submitted to National Institute for Health and Care Excellence (NICE) and Canadian Agency for Drugs and Technologies in Health (CADTH) for HTA. METHODS: NICE and CADTH submissions from September 2019 to August 2021 were reviewed. Submission characteristics and features of patient-based evidence included within submissions were extracted. The quality of qualitative reporting was assessed using the CASP checklist. RESULTS: Patient-based evidence was included in 83/107 NICE and 119/124 CADTH submissions. A small proportion described qualitative data collection (NICE=14; CADTH=24) and analysis (NICE=6; CADTH=9) methods. One-to-one interviews were the most common data collection method, and thematic analysis was exclusively used. Thirty-three percent of NICE submissions scored >7 yes responses on CASP, versus 78 percent of CADTH submissions. CONCLUSIONS: Although patient-based evidence was common in the submissions reviewed, only 14/107 NICE and 24/124 CADTH submissions involved formal qualitative data collection. Use of formal analysis methods was even rarer and reporting tended to be brief. At present, there is little guidance about qualitative evidence most likely to be informative and therefore to potentially impact decision making. Ensuring, however, that qualitative data are collected and analyzed in a systematic, rigorous way will maximize their usefulness and ensure that patient voices are clearly heard.

Institute for Clinical and Economic Review - Peterson Health Technology Institute value assessment framework for digital health technologies.

Digital health technologies (DHTs) are a broad and rapidly innovating class of interventions with distinctive pathways for development, regulatory approval, uptake and reimbursement. Given the unique nature of DHTs, existing value assessment frameworks and evidence standards for health technologies such as drugs and devices are not directly applicable. The value assessment framework presented here describes a conceptual model and associated methods to guide assessments of DHTs. The framework seeks to accomplish two goals: to set evidence standards that guide technology developers to generate robust evidence on their products; and to provide reviews that help organizations adopt high-impact DHTs with the strongest evidence for delivering improved clinical outcomes and cost savings. This assessment framework will serve as the roadmap for future evaluations of DHTs by the Institute for Clinical and Economic Review (ICER) and the Peterson Health Technology Institute (PHTI). We believe that all stakeholders will benefit from comprehensive and explicit standards of evidence on the different dimensions necessary to understand the value of DHTs.

The role of quantitative bias analysis for nonrandomized comparisons in health technology assessment: recommendations from an expert workshop.

The use of treatment effects derived from nonrandomized studies (NRS) in health technology assessment (HTA) is growing. NRS carry an inherently greater risk of bias than randomized controlled trials (RCTs). Although bias can be mitigated to some extent through appropriate approaches to study design and analysis, concerns around data availability and quality and the absence of randomization mean residual biases typically render the interpretation of NRS challenging. Quantitative bias analysis (QBA) methods are a range of methods that use additional, typically external, data to understand the potential impact that unmeasured confounding and other biases including selection bias and time biases can have on the results (i.e., treatment effects) from an NRS. QBA has the potential to support HTA bodies in using NRS to support decision-making by quantifying the magnitude, direction, and uncertainty of biases. However, there are a number of key aspects of the use of QBA in HTA which have received limited discussion. This paper presents recommendations for the use of QBA in HTA developed using a multi-stakeholder workshop of experts in HTA with a focus on QBA for unmeasured confounding.