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BackgroundDespite a doubling of osteoarthritis-targeted mobile health (mHealth) apps and high user interest and demand for health apps, their impact on patients, patient outcomes, and providers has not met expectations. Most health and medical apps fail to retain users longer than 90 days, and their potential for facilitating disease management, data sharing, and patient-provider communication is untapped. An important, recurrent criticism of app technology development is low user integration design. User integration ensures user needs, desires, functional requirements, and app aesthetics are responsive and reflect target user preferences. ObjectiveThis study aims to describe the co-design process for developing a knee osteoarthritis minimum viable product (MVP) mHealth app with patients, family physicians, and researchers that facilitates guided, evidence-based self-management and patient-physician communication. MethodsOur qualitative co-design approach involved focus groups, prioritization activities, and a pre-post quality and satisfaction Kano survey. Study participants included family physicians, patient researchers and patients with knee osteoarthritis (including previous participants of related collaborative research), researchers, key stakeholders, and industry partners. The study setting was an academic health center in Southern Alberta. ResultsDistinct differences exist between what patients, physicians, and researchers perceive are the most important, convenient, desirable, and actionable app functional requirements. Despite differences, study participants agreed that the MVP should be electronic, should track patient symptoms and activities, and include features customized for patient- and physician-identified factors and international guideline-based self-management strategies. Through the research process, participants negotiated consensus on their respective priority functional requirements. The highest priorities were a visual symptom graph, setting goals, exercise planning and daily tracking, and self-management strategies. The structured co-design with patients, physicians, and researchers established multiple collaborative processes, grounded in shared concepts, language, power, rationale, mutual learning, and respect for diversity and differing opinions. These shared team principles fostered an open and inclusive environment that allowed for effective conceptualization, negotiation, and group reflection, aided by the provision of tangible and ongoing support throughout the research process, which encouraged team members to question conventional thinking. Group-, subgroup-, and individual-level data helped the team reveal how and for whom perspectives about individual functional requirements changed or remained stable over the course of the study. This provided valuable insight into how and why consensus emerged, despite the presence of multiple and differing underlying rationales for functional requirement prioritization. ConclusionsIt is feasible to preserve the diversity of perspectives while negotiating a consensus on the core functional requirements of an mHealth prototype app for knee osteoarthritis management. Our study sample was purposely constructed to facilitate high co-design interactivity. This study revealed important differences between the patient, physician, and researcher preferences for functional requirements of an mHealth app that did not preclude the development of consensus.

Despite the emerging evidence in recent years, successful implementation of clinical genomic sequencing (CGS) remains limited and is challenged by a range of barriers. These include a lack of standardized practices, limited economic assessments for specific indications, limited meaningful patient engagement in health policy decision-making, and the associated costs and resource demand for implementation. Although CGS is gradually becoming more available and accessible worldwide, large variations and disparities remain, and reflections on the lessons learned for successful implementation are sparse. In this commentary, members of the Global Economics and Evaluation of Clinical Genomics Sequencing Working Group (GEECS) describe the global landscape of CGS in the context of health economics and policy and propose evidence-based solutions to address existing and future barriers to CGS implementation. The topics discussed are reflected as two overarching themes: (1) system readiness for CGS and (2) evidence, assessments, and approval processes. These themes highlight the need for health economics, public health, and infrastructure and operational considerations; a robust patient- and family-centered evidence base on CGS outcomes; and a comprehensive, collaborative, interdisciplinary approach.

Health policies and associated research initiatives are constantly evolving and changing. In recent years, there has been a dizzying increase in research on emerging topics such as the implications of changing public and private health payment models, the global impact of pandemics, novel initiatives to tackle the persistence of health inequities, broad efforts to reduce the impact of climate change, the emergence of novel technologies such as whole-genome sequencing and artificial intelligence, and the increase in consumer-directed care. This evolution demands future-thinking research to meet the needs of policymakers in translating science into policy. In this paper, the Health Affairs Scholar editorial team describes ten health policy challenges for the next 10 years. Each of the ten assertions describes the challenges and steps that can be taken to address those challenges. We focus on issues that are traditionally studied by health services researchers such as cost, access, and quality, but then examine emerging and intersectional topics: equity, income, and justice; technology, pharmaceuticals, markets, and innovation; population health; and global health.

BACKGROUND: Prognostic disclosure is essential to informed decision making in oncology, yet many oncologists are unsure how to successfully facilitate this discussion. This scoping review determines what prognostic communication models exist, compares and contrasts these models, and explores the supporting evidence. METHOD: A protocol was created for this study using the Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols extension for Scoping Reviews. Comprehensive literature searches of electronic databases MEDLINE, EMBASE, PsycINFO and Cochrane CENTRAL were executed to identify relevant publications between 1971 and 2020. RESULTS: In total, 1532 articles were identified, of which 78 met inclusion criteria and contained 5 communication models. Three of these have been validated in randomised controlled trials (the Serious Illness Conversation Guide, the Four Habits Model and the ADAPT acronym) and have demonstrated improved objective communication measures and patient reported outcomes. All three models emphasise the importance of exploring patients illness understanding and treatment preferences, communicating prognosis and responding to emotion. CONCLUSION: Communicating prognostic estimates is a core competency skill in advanced cancer care. This scoping review highlights available communication models and identifies areas in need of further assessment. Such areas include how to maintain learnt communication skills for lifelong practice, how to assess patient and caregiver understanding during and after these conversations, and how to best scale these protocols at the institutional and national levels.

The emergence of next-generation genomic sequencing (NGS) tests for use in clinical care has generated widespread interest around the globe, but little is known about the availability and funding of these tests worldwide. We examined NGS availability across world regions and countries, with a particular focus on availability of three key NGS tests-Whole-Exome Sequencing or Whole-Genome Sequencing for diagnosis of suspected genetic diseases such as intellectual disability disorders or rare diseases, non-invasive prenatal testing for common genetic abnormalities in fetuses and tumor sequencing for therapy selection and monitoring of cancer treatment. We found that these NGS tests are available or becoming available in every major region of the world. This includes both high-income countries with robust genomic programmes such as the USA and the UK, and growing availability in countries with upper-middle-income economies. We used exploratory case studies across three diverse health care systems (publicly funded/national (UK), publicly funded/provincial (Canada) and mixed private/public system (USA)) to illustrate the funding challenges and approaches used to address those challenges that might be adopted by other countries. We conclude by assessing what type of data and initiatives will be needed to better track and understand the use of NGS around the world as such testing continues to expand.

PurposeThe Open Payments transparency program publishes data on industry-physician payments, in part to discourage relationships considered inappropriate including gifts, meals, and speaker's bureau fees. We evaluated trends in physician-level payments to test whether implementation of Open Payments resulted in fewer industry-radiation oncologist (RO) interactions or shifted interactions toward those considered more appropriate compared with medical oncologists (MOs) and other hospital-based physicians (HBPs).Methods and materialsWe performed a retrospective, population-based cohort study of practicing US ROs versus MOs and HBPs in 2014 matched to general (nonresearch) payments between 2014 and 2018. Trends in payments were analyzed and reported by nature of payment. Values of payments to ROs from the top 10 companies were identified.ResultsFrom 2014 to 2018, 3379 (90.3%) ROs accepted 106,930 payments totaling $40.8 million. The per-physician number and value of payments was lower in radiation oncology than in medical oncology and higher than HBPs. The proportion of ROs accepting payments increased from 61.8% in 2014 to 64.2% in 2018; the proportion of MOs accepting payments decreased from 78.7% to 77.7%; and the proportion of HBPs decreased from 40.8% to 37.5%, respectively. The annual per-physician value and number of payments accepted by ROs and MOs increased. Payments in entertainment, meals, travel and lodging, and gifts increased among ROs and remained stable or decreased among MOs and HBPs. Consulting payments increased across all groups. Top RO payors produced novel cancer therapeutics, hydrogel spacers, radiation treatment machines, and opioids.ConclusionsIndustry payments to ROs have become more common since OP's inception, while becoming less common for MOs and HBPs. Payments to ROs and MOs have become more frequent and of modestly increasing value compared with other HBPs, for whom the value is decreasing. No large changes in the nature of relationships were seen in ROs. Increased engagement with financial conflicts of interest is needed in radiation oncology.

ObjectivesThe objective of this article is to describe the unique challenges and present potential solutions and approaches for economic evaluations of precision medicine (PM) interventions using simulation modeling methods.MethodsGiven the large and growing number of PM interventions and applications, methods are needed for economic evaluation of PM that can handle the complexity of cascading decisions and patient-specific heterogeneity reflected in the myriad testing and treatment pathways. Traditional approaches (eg, Markov models) have limitations, and other modeling techniques may be required to overcome these challenges. Dynamic simulation models, such as discrete event simulation and agent-based models, are used to design and develop mathematical representations of complex systems and intervention scenarios to evaluate the consequence of interventions over time from a systems perspective.ResultsSome of the methodological challenges of modeling PM can be addressed using dynamic simulation models. For example, issues regarding companion diagnostics, combining and sequencing of tests, and diagnostic performance of tests can be addressed by capturing patient-specific pathways in the context of care delivery. Issues regarding patient heterogeneity can be addressed by using patient-level simulation models.ConclusionThe economic evaluation of PM interventions poses unique methodological challenges that might require new solutions. Simulation models are well suited for economic evaluation in PM because they enable patient-level analyses and can capture the dynamics of interventions in complex systems specific to the context of healthcare service delivery.