Innovative Health Technologies Research Articles

Sintilimab plus anlotinib as second or further-line therapy for extensive disease small cell lung cancer: a phase 2 investigator-initiated non-randomized controlled trial

Treatment options remain rather limited for extensive disease small cell lung cancer (ED-SCLC) patients in second or further-line setting. The phase 2 investigator-initiated non-randomized study enrolled patients who had disease progression on at least one line of platinum-based chemotherapy. Participants received intravenous sintilimab 200mg on day one and oral daily anlotinib 12mg on days 1-14 once every three weeks per cycle. The primary endpoint was progression-free survival (PFS). The secondary endpoints included overall survival (OS), objective response rate (ORR), disease control rate (DCR) and safety. This study is registered with ClinicalTrials.gov (NCT04055792). Forty-two patients were enrolled between August 29, 2019 and December 26, 2021at Henan Cancer Hospital in China. 37 patients were evaluable for efficacy. The median follow-up was 24.8 months (IQR: 16.9-28.2). The median PFS was 6.1 months (95% CI: 5.0-7.3). The OS was 12.7 months (95% CI: 7.1-18.2). The ORR was 56.8% (21/37, 95% CI: 40.0-73.5) and the DCR was 89.2% (33/37, 95% CI: 78.7-99.7). Forty patients (40/42, 95%) had at least one treatment-related adverse event (TRAE). Immune-related adverse events (irAEs) were reported in 39 patients (39/42, 93%), while grade 3 or higher irAEs occurred in 11 patients (11/42, 26%). The most frequent irAEs were hypothyroidism (16/42, 38%), elevated gamma-glutamyl transpeptidase (15/42, 36%) and elevated creatine kinase MB (15/42, 36%). The most frequent grade 3 or higher irAEs were elevated gamma-glutamyl transpeptidase (5/42, 12%) and increased aspartate aminotransferase (3/42, 7%). Sintilimab plus anlotinib demonstrated promising antitumor activities as second or further-line therapy for ED-SCLC and had manageable toxicities. The findings support further randomized controlled trials of this combination regimen for ED-SCLC. Henan Province Health and Youth Subject Leader Training Project, Henan Health Science and Technology Innovation Talents, ZHONGYUAN QIANREN JIHUA, Henan International Joint Laboratory of drug resistance and reversal of targeted therapy for lung cancer, Tumor Research Fund of Anti-Angiogenesis Targeted Therapy of China Anti-Cancer Association.

Dose the increasing burden of social endowment affect sustainable development of economy?

The rapid increase in the number of older people under the background of population aging has gradually changed the disease spectrum of society, making aging diseases more prevalent, and increasing the demand for health care services, medical and health services, and health insurance among older people, ultimately leading to increasing household and social spending on old age. This study is conducted to assess the impact of those spending burden on the sustainable development of economy and find out some practical and effective solutions. This paper constructs a theoretical model to illustrate the relationship between the old-age dependency ratio and the marginal product of capital (MPK), and then establishes a two-way fixed effect model based on transnational panel data of 81 countries from 1981 to 2017 to verify this relationship empirically. This paper finds that, after controlling a series of variables, an increased burden of old-age dependency leads to a decline in the MPK, a key macroeconomic variable and also a sustainable development criteria, but in which health care, health security systems, and technological innovation play a key and moderating role. The conclusion is also valid after tackling the problem of endogeneity with different methods, like two-stage least squares (TSLS) and the generalized methods of moments (GMM). Overall, before population aging, countries that are old-but-not-rich should encourage more supply-side investments in public health system or technological innovation, and adjust retirement system, or gradually encourage childbearing to strive for time and space for later sustainable development of public health system and economy.

Facilitating family communication of familial hypercholesterolemia genetic risk: Assessing engagement with innovative chatbot technology from the IMPACT-FH study.

To assess use of two web-based conversational agents, the Family Sharing Chatbot (FSC) and One Month Chatbot (OMC), by individuals with familial hypercholesterolemia (FH). FSC and OMC were sent using an opt-out methodology to a cohort of individuals receiving a FH genetic result. Data from 7/1/2021 through 5/12/2022 was obtained from the electronic health record and the chatbots' HIPAA-secure web portal. Of 175 subjects, 21 (12%) opted out of the chatbots. Older individuals were more likely to opt out. Most (91/154, 59%) preferred receiving chatbots via the patient EHR portal. Seventy-five individuals (49%) clicked the FSC link, 62 (40%) interacted, and 36 (23%) shared a chatbot about their FH result with at least one relative. Ninety-two of the subjects received OMC, 22 (23%) clicked the link and 20 (21%) interacted. Individuals who shared were majority female and younger on average than the overall cohort. Reminders tended to increase engagement. Results demonstrate characteristics relevant to chatbot engagement. Individuals may be more inclined to receive chatbots if integrated within the patient EHR portal. Frequent reminders can potentially improve chatbot utilization. FSC and OMC employ innovative digital health technology that can facilitate family communication about hereditary conditions.

OP115 Scoping Meta-Review On Methods Used To Assess Artificial Intelligence-Based Medical Devices For Heart Failure

IntroductionThe International Federation of Medical and Biological Engineering created a multidisciplinary working group to discuss assessments of artificial intelligence and machine learning (AI/ML) applications in health care. Engineers, clinicians, and economists identified evidence generation as a critical topic. Heart failure (HF) was selected to investigate the available evidence on the clinical effectiveness and safety of AI/ML applications. Attention was paid to transparency of AI/ML methods and their data sources.MethodsA scoping review was conducted on AI/ML algorithms developed for the management of HF. A search for systematic reviews, scoping reviews, and meta-analyses published from 1976 to October 2022 was conducted in Embase, MEDLINE, and Scopus.ResultsOf 456 relevant publications, 21 papers were included in the final analysis. Most papers (10 systematic reviews, five meta-analyses, and six non-systematic or scoping reviews) included studies conducted in North America. No study was conducted in Africa. The healthcare setting was not clearly stated in approximately half of the studies. A lack of agreement was noticed regarding the quality assessment tools used among the reviews. The most common data source for AI/ML algorithms was electronic health records, but in some cases data sources were not reported. While deep learning emerged as the most common adopted methodology, covariates were not always included in the algorithm development. The review demonstrated that comparative assessment of algorithms requires further investigation, given the high variability in the comparator used (e.g., clinical gold standard, other AI/ML algorithms, or other statistical methods). The main investigated endpoints were the incidence of HF and the number of hospital admissions.ConclusionsWhen assessing innovative health technologies such as AI/ML applications in health care, evidence is among the main challenges. Our scoping review, focusing on algorithms developed to manage HF, showed that the biggest challenges relate to the quality of the studies, the adoption of a comparative approach, and transparency of methods.

HPR212 The Use of Managed Entry Agreements (MEAs) for Accessing Innovative Health Technologies

HPR212 The Use of Managed Entry Agreements (MEAs) for Accessing Innovative Health Technologies

PP14 The Role Of Health Technology Assessment In The Public Hospitals Of The National Health Service Of Catalonia

IntroductionHospitals play an essential role to facilitate the appropriate introduction of health technologies into the National Health System. We aimed to analyze if the decision-making at the hospital level is based on health technology assessment (HTA).MethodsWe developed a seventeen-question survey to assess the decision-making mechanisms for the introduction of health innovation into the public hospitals of the National Health Service (NHS) of Catalonia. All questions were related to the field of HTA and health innovation. We asked about the process of new health technology acquisition, the existence of HTA units, and the impact those units might have within the center. We invited the three main public healthcare providers (n= 68 centers). We performed a quantitative analysis grouping the results by type of healthcare provider.ResultsThirty-five different health providers (51.5%) remitted forty-two responses. We identified two differential mechanisms for the introduction of health innovation in those centers: 51.4 percent used a directive committee for decision-making, whereas 37.1 percent employed a technical commission. Some centers (8.6%) used both options. Both the directive committees and technical commissions predominantly considered the professional experience or scientific evidence provided by the healthcare professionals of the center (80%) or external HTA reports or clinical practice guidelines (65.7%) to guide their decision-making. Using HTA products developed within the center was less frequent (34.3%). Only 57.1 percent of the healthcare providers had an HTA unit, but 75 percent of them declared that HTA products had a direct and quantifiable impact on their decision-making regarding the introduction of innovation. Healthcare providers without HTA units manifested their willingness to adopt HTA practices into their decision-making processes.ConclusionsHTA at the hospital level is not a common practice when deciding to introduce innovative health technologies in the NHS of Catalonia. However, the main healthcare providers agreed that the introduction of HTA is necessary for improving their decision-making and that the HTA agency, Agency for Health Quality and Assessment of Catalonia (AQuAS) will play a key role (training, promoting, and assessing).

OP74 Analysis Of Literature And Research Foci In Overdiagnosis Based On Citespace

IntroductionWith the rapid development of innovative health technologies, evidence increasingly shows that overdiagnosis is harmful to a person’s health and that it is a global public health issue. This study aimed to analyze the current research status and corresponding foci in the field of overdiagnosis in Chinese and English databases using bibliometric methods.MethodsA search was conducted in the English Web of Science Core Collection database and the Chinese China National Knowledge Infrastructure database for literature published from inception to 31 December 2021. CiteSpace (version 5.8 R1) software was used to perform bibliometric analysis on the countries, institutions, and keyword clusters of the included literature on overdiagnosis and to draw a corresponding visual knowledge map.ResultsA total of 2,841 English and 43 Chinese publications were included. There was an increasing trend in the annual publication volume of both Chinese and English literature, with the publication volume of English research increasing significantly since 2010. In terms of countries and institutions, the top ten in English research on overdiagnosis were all from high income countries. The cooperation among these countries and institutions was close, unlike in China where the cooperation was relatively limited. Analysis of keyword clustering showed that the potential research foci for English literature on overdiagnosis included breast cancer, thyroid cancer, prostate cancer, lung cancer, and other tumor types, whereas the clustering in Chinese records was relatively scattered and mainly focused on overdiagnosis of thyroid cancer.ConclusionsThe research topics in the Chinese literature on overdiagnosis lag significantly behind English research. It is suggested that more research on overdiagnosis and related fields should be actively promoted and conducted in China in the future.

Best Practices for Developing a Diabetes mHealth App.

The widespread use of smartphones in the United States has led to a surge in mHealth apps designed to support people with various health issues. Yet the effectiveness and long-term impacts of these apps still need to be determined. This article presents a case study of the development of MyT1DHero, an mHealth app for people with type 1 diabetes, to identify best practices for app development. We propose four essential best practices based on the insights gained from this case study: incorporating theoretical frameworks, prioritizing user feedback, engaging key stakeholders, and establishing a robust data-collection foundation. These findings have practical implications for researchers and developers seeking to create effective mHealth interventions. Furthermore, we suggest future research directions to advance the development and implementation of innovative health technologies.

Precision medicine in neurodegeneration: the IHI-PROMINENT project.

Neurodegenerative diseases are one of the most important contributors to morbidity and mortality in the elderly. In Europe, over 14 million people are currently living with dementia, at a cost of over 400 billion EUR annually. Recent advances in diagnostics and approval for new pharmaceutical treatments for Alzheimer's disease (AD), the most common etiology of dementia, heralds the beginning of precision medicine in this field. However, their implementation will challenge an already over-burdened healthcare systems. There is a need for innovative digital solutions that can drive the related clinical pathways and optimize and personalize care delivery. Public-private partnerships are ideal vehicles to tackle these challenges. Here we describe the Innovative Health Initiative (IHI) public-private partnership project PROMINENT that has been initiated by connecting leading dementia researchers, medical professionals, dementia patients and their care partners with the latest innovative health technologies using a precision medicine based digital platform. The project builds upon the knowledge and already implemented digital tools from several collaborative initiatives that address new models for early detection, diagnosis, and monitoring of AD and other neurodegenerative disorders. The project aims to provide support to improvement efforts to each aspect of the care pathway including diagnosis, prognosis, treatment, and data collection for real world evidence and cost effectiveness studies. Ultimately the PROMINENT project is expected to lead to cost-effective care and improved health outcomes.

The Impact of the Digital Economy on the Health Industry from the Perspective of Threshold and Intermediary Effects: Evidence from China

This study explores the effect of the digital economy driving the development of the health industry and the mechanism behind it. Based on the panel data of 27 Chinese provinces from 2014–2021, this paper uses the entropy weight method to construct a comprehensive indicator evaluation system for the health industry, digital economy, and technological innovation. The two-way fixed effects model and panel threshold model are used to explore the impact of the digital economy on the health industry, and the intermediary effects model is used to analyze the mechanism role of technological innovation in the impact of the digital economy on the health industry. The results show that the digital economy can drive the development of the health industry. The driving effect shows obvious regional heterogeneity, with the strongest in the west, the second strongest in the central part, and the weakest in the east. This driving effect also has non-linear characteristics. Improving technological innovation is an important mechanism for the development of the health industry driven by the digital economy. This study promotes the exploration of the construction path of “Healthy China”, and reflects the importance of implementing dynamic and differentiated digital economy strategies and increasing the R&D of core technologies to drive the development of the health industry.

Evaluation of Chinese healthcare organizations' innovative performance in the digital health era.

Healthcare workers' relationship with industry is not merely an agent mediating between consumer and vendor, but they are also inventors of the interventions they exist to deliver. Driven by the background of the digital health era, scientific research and technological (Sci-tech) innovation in the medical field are becoming more and more closely integrated. However, scholars shed little light on Sci-tech relevance to evaluate the innovation performance of healthcare organizations, a distinctive feature of healthcare organizations' innovation in the digital health era. Academic publications and patents are the manifestations of scientific research outputs and technological innovation outcomes, respectively. The study extracted data from publications and patents of 159 hospitals in China to evaluate their innovation performance. A total of 18 indicators were constructed, four of which were based on text similarity match and represented the Sci-tech relevance. We then applied factor analyses, analytical hierarchy process, and logistic regression to construct an evaluation model. We also examined the relationship between hospitals' innovation performance and their geographical locations. Finally, we implemented a mediation analysis to show the influence of digital health on hospital innovation performance. A total of 16 indicators were involved, four of which represented the Sci-tech including the number of articles matched per patent (NAMP), the number of patents matched per article (NPMA), the proportion of highly matched patents (HMP), and the proportion of highly matched articles (HMA). Indicators of HMP (r = 0.52, P = 2.40 × 10-12), NAMP (r = 0.52, P = 2.54 × 10-12), and NPMA (r = 0.51, P = 5.53 × 10-12) showed a strong positive correlation with hospital innovation performance score. The evaluation model in this study was different from other Chinese existing hospital ranking systems. The regional innovation performance index (RIP) of healthcare organizations is highly correlated with per capita disposable income (r = 0.58) and regional GDP (r = 0.60). There was a positive correlation between digital health innovation performance scores and overall hospital innovation performance scores (r = 0.20). In addition, the hospitals' digital health innovation performance affected the hospital's overall innovation score with the mediation of Sci-tech relevance indicators (NPMA and HMA). The hospitals' digital health innovation performance score showed a significant correlation with the number of healthcare workers (r = 0.44). This study constructed an assessment model with four invented indicators focusing on Sci-tech relevance to provide a novel tool for researchers to evaluate the innovation performance of healthcare organizations in the digital health era. The regions with high RIP were concentrated on the eastern coastal areas with a higher level of economic development. Therefore, the promotion of scientific and technological innovation policies could be carried out in advance in areas with better economic development. The innovations in the digital health field by healthcare workers enhance the Sci-tech relevance in hospitals and boost their innovation performance. The development of digital health in hospitals depends on the input of medical personnel.

Thinking Beyond the Device: An Overview of Human- and Equity-Centered Approaches for Improved Health Technology Design.

A shift in the traditional technocentric view of medical device design to a human-centered one is needed to bridge existing translational gaps and improve health equity. To ensure the successful and equitable adoption of health technology innovations, engineers must think beyond the device and the direct end user and must seek a more holistic understanding of broader stakeholder needs and the intended context of use early in a design process. The objectives of this review article are (a) to provide rationale for the need to incorporate meaningful stakeholder analysis and contextual investigation in health technology development and biomedical engineering pedagogy, (b) to review existing frameworks and human- and equity-centered approaches to stakeholder engagement and contextual investigation for improved adoption of innovative technologies, and (c) to present case study examples of medical device design that apply these approaches to bridge the gap between biomedical engineers and the contexts for which they are designing. Expected final online publication date for the Annual Review of Biomedical Engineering, Volume 25 is June 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

HTA96 Applying Early Health Technology Assessments to Inform Novel Health Technology Innovation

To examine how early health economic models and technology assessments can be used to inform and influence the development of novel health technologies.

Three-dimensional convolutional neural network model to identify clinically significant prostate cancer in transrectal ultrasound videos: a prospective, multi-institutional, diagnostic study.

Identifying patients with clinically significant prostate cancer (csPCa) before biopsy helps reduce unnecessary biopsies and improve patient prognosis. The diagnostic performance of traditional transrectal ultrasound (TRUS) for csPCa is relatively limited. This study was aimed to develop a high-performance convolutional neural network (CNN) model (P-Net) based on a TRUS video of the entire prostate and investigate its efficacy in identifying csPCa. Between January 2021 and December 2022, this study prospectively evaluated 832 patients from four centres who underwent prostate biopsy and/or radical prostatectomy. All patients had a standardised TRUS video of the whole prostate. A two-dimensional CNN (2D P-Net) and three-dimensional CNN (3D P-Net) were constructed using the training cohort (559 patients) and tested on the internal validation cohort (140 patients) as well as on the external validation cohort (133 patients). The performance of 2D P-Net and 3D P-Net in predicting csPCa was assessed in terms of the area under the receiver operating characteristic curve (AUC), biopsy rate, and unnecessary biopsy rate, and compared with the TRUS 5-point Likert score system as well as multiparametric magnetic resonance imaging (mp-MRI) prostate imaging reporting and data system (PI-RADS) v2.1. Decision curve analyses (DCAs) were used to determine the net benefits associated with their use. The study is registered at https://www.chictr.org.cn with the unique identifier ChiCTR2200064545. The diagnostic performance of 3D P-Net (AUC: 0.85-0.89) was superior to TRUS 5-point Likert score system (AUC: 0.71-0.78, P=0.003-0.040), and similar to mp-MRI PI-RADS v2.1 score system interpreted by experienced radiologists (AUC: 0.83-0.86, P=0.460-0.732) and 2D P-Net (AUC: 0.79-0.86, P=0.066-0.678) in the internal and external validation cohorts. The biopsy rate decreased from 40.3% (TRUS 5-point Likert score system) and 47.6% (mp-MRI PI-RADS v2.1 score system) to 35.5% (2D P-Net) and 34.0% (3D P-Net). The unnecessary biopsy rate decreased from 38.1% (TRUS 5-point Likert score system) and 35.2% (mp-MRI PI-RADS v2.1 score system) to 32.0% (2D P-Net) and 25.8% (3D P-Net). 3D P-Net yielded the highest net benefit according to the DCAs. 3D P-Net based on a prostate grayscale TRUS video achieved satisfactory performance in identifying csPCa and potentially reducing unnecessary biopsies. More studies to determine how AI models better integrate into routine practice and randomized controlled trials to show the values of these models in real clinical applications are warranted. The National Natural Science Foundation of China (Grants 82202174 and 82202153), the Science and Technology Commission of Shanghai Municipality (Grants 18441905500 and 19DZ2251100), Shanghai Municipal Health Commission (Grants 2019LJ21 and SHSLCZDZK03502), Shanghai Science and Technology Innovation Action Plan (21Y11911200), and Fundamental Research Funds for the Central Universities (ZD-11-202151), Scientific Research and Development Fund of Zhongshan Hospital of Fudan University (Grant 2022ZSQD07).

Conceptual Framework for the Adoption of Innovative Health Technologies In Response to Health Emergencies

Introduction:Rapid developments in healthcare technology can significantly improve the quality, availability, and immediacy of care in health emergency events; however, without a cohesive framework to conceptualize the interplay between emerging technologies, we risk creating silos, ignoring applications, and reducing interoperability between innovations.Method:This framework was developed after reviewing the current literature regarding new technologies in healthcare assessment and delivery, discussing relevant innovations with experts, and analyzing global market trends in emerging health technology capabilities.Results:Innovative health technologies deployed in disaster settings can be grouped by their relevance to (1) Disease and Injury Surveillance and Detection, (2) Population Protection, (3) Responder Protection, and (4) Disease and Injury Management. The first category encompasses technologies that help characterize the severity and scope of an event at its onset, utilizing a network of wearable devices, sensors, remote infectious disease sampling, and other tools. Once an incident occurs, technologies aimed at Population Protection are necessary to preserve the well-being of unaffected citizens. Scaled-up on-demand manufacturing for prophylactic medical countermeasures and needle-free delivery mechanisms for pre-treatments against CBRN threats will be paramount. Healthcare and emergency responders require additional support before and during incident response, especially just-in-time training through virtual and augmented reality, biometric monitoring, next-generation personal protective equipment, and enhanced communications capabilities. Finally, delivering care to patients in healthcare emergencies will require optimized allocation of scarce resources based upon acuity and survivability. Effective healthcare service delivery can be bolstered using Telehealth, autonomous patient transport, drone delivery, robotic and haptically guided care delivery, and decision support tools.Conclusion:To effectively manage the successful adoption and implementation of innovative tools applicable to health emergencies, areas of impact and utility should be comprehensively categorized. This framework guides emergency managers, policymakers, and innovators alike to understand how individual developments coalesce in the larger context of disaster prevention, response, and recovery.

Lessons from Developing Multimedia Learning Materials for the Digital Generation

Recognizing that traditional textbooks on need-driven health technology innovation were increasingly misaligned with the needs of today’s undergraduate biomedical engineering students and the faculty who teach them, we initiated an effort to develop new learning materials for this audience. To guide our efforts, we conducted literature searches on best practices in the development of online content and engaging digital learners (primarily Gen-Z). We further held a series of discussions with biomedical engineering students and instructors at universities across the United States. This input led us to the development of a set of modular, online, multimedia learning materials specifically designed for the new generation of undergraduate learners. In this article, we present the key decisions that helped shape the project. We also share the results of feedback surveys and focus groups that shed light on how the materials have been preliminarily received. Finally, we reflect on challenges, opportunities, and lessons from this project that may be helpful to other initiatives focused on the creation of multimedia content for the digital generation.

A Model-Based Estimate of the Cost-Effectiveness Threshold in Germany.

Value-based pricing of new, innovative health technologies defined as pricing through economic evaluation requires the use of a basic cost-effectiveness threshold. This study presents a cost-effectiveness model that determines the cost-effectiveness threshold for life-extending new, innovative technologies based on health system opportunity costs. To estimate health system opportunity costs, the study used German data and examined the period between 1896 and 2014. To this end, it determined intertemporal differences in the remaining lifetime spending and life expectancy by age and gender. To account for the age composition of the population, it weighted age-specific intertemporal changes in the remaining lifetime spending and life expectancy by the age-specific population size. To estimate life expectancy gains solely attributable to the health care system, it used aggregated data on amenable mortality. It calculated the cost-effectiveness ratio of health care spending in the German health care system on average and at the margin. Based on the cost-effectiveness ratio of health care spending at the margin, the threshold value for life-prolonging new, innovative technologies was at least €42,634 per life-year gained, with a point estimate of €88,107 per life-year gained. Based on the average ratio, the threshold value dropped below €34,000 per life-year gained. This study provides new evidence on the cost-effectiveness threshold for value-based pricing of new, innovative technologies. Data from Germany suggest that a threshold value based on health care spending at the margin is considerably higher than that based on the average ratio.

Using an Accelerated Undergraduate Needs Finding Course to Build Skills, Inspire Confidence, and Promote Interest in Health Technology Innovation.

Many undergraduate educational experiences in biomedical design lack clinical immersion-based needs finding training for students. Convinced of the merits of this type of training for undergraduates, but unable to offer a quarter-long course due to faculty and administrative constraints, we developed an accelerated block-plan course, during which students were dedicated solely to our class for 3 weeks. The course focused on the earliest stages of the health technology innovation process-conducting effective clinical observations and performing comprehensive need research and screening. We grounded the course in experiential learning theory (with hands-on, collaborative, and immersive experiences) and constructivist learning theory (where students integrated prior knowledge with new material on need-driven innovation). This paper describes the design of this intensive block-plan course and the teaching methods intended to support the achievement of five learning objectives. We used pre- and post-course surveys to gather self-reported data about the effect of the course on student learning. Despite the accelerated format, we saw statistically significant gains for all but one sub-measure across the learning objectives. Our experience supports key benefits of the block-plan model, and the results indicate that specific course design choices were effective in achieving positive learning outcomes. These design decisions include (1) opportunities for students to practice observations before entering the clinical setting; (2) a framework for the curriculum that reinforced important concepts iteratively throughout the program; (3) balanced coverage of preparation, clinical immersion, and need research; (4) extensive faculty and peer coaching; and (5) providing hands-on prototyping opportunities while staying focused on need characterization rather than solution development. Based on our experience, we expect that this model is replicable across institutions with limited bandwidth to support clinical immersion opportunities.

Efficacy of faecal microbiota transplantation in patients with progressive supranuclear palsy-Richardson's syndrome: a phase 2, single centre, randomised clinical trial

Faecal microbiota transplantation (FMT) has demonstrated efficacy in treating gastrointestinal (GI) diseases, such as Clostridium difficile infection (CDI) and inflammatory bowel disease (IBD). GI dysfunction is a frequent and occasionally dominating symptom of progressive supranuclear palsy-Richardson's syndrome (PSP-RS). However, it is not known whether FMT has clinical efficacy for PSP-RS. This 36-week, randomised, placebo-controlled, parallel-group, phase 2 clinical trial was performed at a university tertiary referral hospital in China. From August 15 2021 to December 31 2021, a total of 68 newly diagnosed patients with PSP-RS (male 40 [59%], female 28 [41%]) who had never received any antiparkinsonian medications were enrolled and randomly assigned to receive either healthy donor FMT (n=34, FMT group) or a mixture of 0.9% saline and food colouring (E150c) as sham transplantation (n=34, placebo group) through transendoscopic enteral tubing (TET). Two days after oral antibiotics, participants received 1 week of transplantation. After an interval of 4 weeks, retransplantation was performed. Then, the last transplantation was given after another interval of 4 weeks, and the participants were followed up for 24 weeks (week 36). Clinicaltrials.gov identifier: ChiCTR-2100045397. Among 68 patients who were randomised (mean age, 67.2 (SD 5.1); 40 [59%] were male, 28 [41%] were female), 63 participants completed the trial. Efficacy analyses were performed on the intention-to-treat (ITT) analysis set. At week 16, the mean PSP Rating Scale (PSPRS) scores (the primary outcome) improved from 40.1 (SD 7.6) to 36.9 (SD 5.9) in the FMT group, whereas the scores changed from 40.1 (SD 6.9) to 41.7 (SD 6.2) in the placebo group, for a treatment benefit of 4.3 (95% CI, 3.2-5.4) (P<0.0001). After 3-cycle intervention, symptoms of constipation, depression, and anxiety (the secondary outcome) improved significantly at week 16 in the FMT group compared with the placebo group, the majority of which were maintained at the 24-week follow-up (week 36). Our findings suggest that, compared with placebo, FMT treatment significantly improved motor and nonmotor symptoms in patients with PSP-RS, as well as reduced intestinal inflammation and enhanced the intestinal barrier by regulating the intestinal microbiota composition. The National Natural Science Foundation of China (No. 82122022, 82171248, 81873791, and 82230084), Natural Science Foundation of Henan Province for Excellent Young Scholars (no. 202300410357), and Henan Province Young and Middle-Aged Health Science and Technology Innovation Talent Project (YXKC2020033).

A comparative analysis of non-invasive prenatal testing in Ontario and Quebec: the role of governing style in health technology innovation & adoption

BackgroundWhile processes of adoption and the impacts of various health technologies have been extensively studied by health services and policy researchers, the influence of policy makers’ governing styles on these processes have been largely neglected. Through a comparative analysis of non-invasive prenatal testing (NIPT) in the Canadian provinces of Ontario and Quebec, this article examines how decisions about this technology were shaped by contrasting political ideologies, resulting in vastly different innovation and adoption strategies and outcomes.MethodsA comparative qualitative investigation comprising of a document analysis followed by semi-structured interviews with key informants. Interview participants were researchers, clinicians, and private sector medical laboratory employees based in Ontario and Quebec, Canada. Interviews were conducted both in person and virtually– owing partly to the COVID-19 pandemic – to garner perspectives regarding the adoption and innovation processes surrounding non-invasive prenatal testing in both provinces. All interviews were recorded and transcribed verbatim and data were analyzed using thematic analysis.ResultsThrough an analysis of 21 in-depth interview transcripts and key documents, the research team identified three central themes: 1) health officials in each province demonstrated a unique approach to using the existing scholarly literature on NIPT; 2) each provincial government demonstrated its own preference for service delivery, with Ontario preferring private and Quebec preferring public; and finally, 3) both Ontario and Quebec’s strategies to NIPT adoption and innovation was contextualized within each province’s unique financial positioning and concerns. These findings illustrate how both Quebec’s nationalist focus and use of industrial policy and Ontario’s ‘New Public Management’ style had implications for how this emerging healthcare technology was made available within each province’s publicly-financed health system.ConclusionsOur study reveals how these governments’ differing approaches to using data and research, public versus private service delivery, and financial goals and concerns resulted in distinct testing technologies, access, and timelines for NIPT adoption. Our analysis demonstrates the need for health policy researchers, policy makers, and others to move beyond analyses solely considering clinical and health economic evidence to understand the impact of political ideologies and governing styles.