Using Separate Single-Outcome Risk Presentations Instead of Integrated Multioutcome Formats Improves Comprehension in Discrete Choice Experiments.

INTRODUCTION: Despite decades of research on risk-communication approaches, questions remain about the optimal methods for conveying risks for different outcomes across multiple time points, which can be necessary in applications such as discrete choice experiments (DCEs). We sought to compare the effects of 3 design factors: 1) separated versus integrated presentations of the risks for different outcomes, 2) use or omission of icon arrays, and 3) vertical versus horizontal orientation of the time dimension. METHODS: We conducted a randomized study among a demographically diverse sample of 2,242 US adults recruited from an online panel (mean age 59.8 y, s = 10.4 y; 21.9% African American) that compared risk-communication approaches that varied in the 3 factors noted above. The primary outcome was the number of correct responses to 12 multiple-choice questions asking survey respondents to identify specific numbers, contrast options to recognize dominance (larger v. smaller risks), and compute differences. We used linear regression to test the effects of the 3 design factors, controlling for health literacy, graph literacy, and numeracy. We also measured choice consistency in a subsequent DCE choice module. RESULTS: Mean comprehension varied significantly across versions (P < 0.001), with higher comprehension in the 3 versions that provided separated risk information for each risk. In the multivariable regression, separated risk presentation was associated with 0.58 more correct responses (P < 0.001; 95% confidence interval: 0.39, 0.77) compared with integrated risk information. Neither providing icon arrays nor using vertical versus horizontal time formats affected comprehension rates, although participant understanding did correlate with DCE choice consistency. CONCLUSIONS: In presentations of multiple risks over multiple time points, presenting risk information separately for each health outcome appears to increase understanding. HIGHLIGHTS: When conveying information about risks of different outcomes at multiple time points, separate presentations of single-outcome risks resulted in higher comprehension than presentations that combined risk information for different outcomes.We also observed benefits of presenting single-outcome risks separately among respondents with lower numeracy and graph literacy.Study participants who scored higher on risk understanding were more internally consistent in their responses to a discrete choice experiment.

VER-Net: a hybrid transfer learning model for lung cancer detection using CT scan images.

BACKGROUND: Lung cancer is the second most common cancer worldwide, with over two million new cases per year. Early identification would allow healthcare practitioners to handle it more effectively. The advancement of computer-aided detection systems significantly impacted clinical analysis and decision-making on human disease. Towards this, machine learning and deep learning techniques are successfully being applied. Due to several advantages, transfer learning has become popular for disease detection based on image data. METHODS: In this work, we build a novel transfer learning model (VER-Net) by stacking three different transfer learning models to detect lung cancer using lung CT scan images. The model is trained to map the CT scan images with four lung cancer classes. Various measures, such as image preprocessing, data augmentation, and hyperparameter tuning, are taken to improve the efficacy of VER-Net. All the models are trained and evaluated using multiclass classifications chest CT images. RESULTS: The experimental results confirm that VER-Net outperformed the other eight transfer learning models compared with. VER-Net scored 91%, 92%, 91%, and 91.3% when tested for accuracy, precision, recall, and F1-score, respectively. Compared to the state-of-the-art, VER-Net has better accuracy. CONCLUSION: VER-Net is not only effectively used for lung cancer detection but may also be useful for other diseases for which CT scan images are available.

Defining the Dimensions of Diversity to Promote Inclusion in the Digital Era of Health Care: A Lexicon.

The pandemic provided a stark reminder of the inequities faced by populations historically marginalized by the health care system and accelerated the adoption of digital health technologies to drive innovation. Digital health technologies' purported promises to reduce inefficiencies and costs, improve access and health outcomes, and empower patients add a new level of urgency to health equity. As conventional medicine shifts toward digital medicine, we have the opportunity to intentionally develop and deploy digital health technologies with an inclusion focus. The first step is ensuring that the multiple dimensions of diversity are captured. We propose a lexicon that encompasses elements critical for implementing an inclusive approach to advancing health care quality and health services research in the digital era.

Usability and acceptability of virtual reality for chronic pain management among diverse patients in a safety-net setting: a qualitative analysis.

Objective: The aim of this study was to understand the usability and acceptability of virtual reality (VR) among a racially and ethnically diverse group of patients who experience chronic pain. Materials and Methods: Using the Technology Acceptance Model theory, we conducted semistructured interviews and direct observation of VR use with English-speaking patients who experience chronic pain treated in a public healthcare system (n = 15), using a commercially available VR technology platform. Interviews included questions about current pain management strategies, technology use, experiences and opinions with VR, and motivators for future use. Results: Before the study, none of the 15 participants had heard about or used VR for pain management. Common motivators for VR use included a previous history of substance use and having exhausted many other options to manage their pain and curiosity. Most participants had a positive experience with VR and 47% found that the VR modules distracted them from their pain. When attempting the navigation-based usability tasks, most participants (73%-92%) were able to complete them independently. Discussion: VR is a usable tool for diverse patients with chronic pain. Our findings suggest that the usability of VR is not a barrier and perhaps a focus on improving the accessibility of VR in safety-net settings is needed to reduce disparities in health technology use. Conclusions: The usability and acceptability of VR are rarely studied in diverse patient populations. We found that participants had a positive experience using VR, showed interest in future use, and would recommend VR to family and friends.

Virtual Reality for Chronic Pain Management Among Historically Marginalized Populations: Systematic Review of Usability Studies.

BACKGROUND: Virtual reality (VR) has potential to improve chronic pain management outcomes. However, the majority of studies assessing VR are conducted in predominantly White populations in well-resourced settings, thus leaving a gap in knowledge of VR use among diverse populations who experience a significant chronic pain burden. OBJECTIVE: This review aims to examine the extent to which usability of VR for chronic pain management has been studied within historically marginalized patient groups. METHODS: We conducted a systematic search to identify studies with usability outcomes located in high-income countries that included a historically marginalized population, defined by a mean age greater than or equal to 65 years, lower educational attainment (greater than or equal to 60% having attained high school education or less), and being a racial or ethnic minority (less than or equal to 50% non-Hispanic White people for studies based in the United States). RESULTS: Our analysis included 5 papers, which we used to conduct a narrative analysis. Three studies examined VR usability as a primary outcome. All studies assessed VR usability using different measures, of which 4 found VR to be usable by their respective study population. Only 1 study found a significant improvement in pain levels post-VR intervention. CONCLUSIONS: The use of VR shows promise for chronic pain management, but few studies include populations that are older, have limited educational attainment, or have racial or ethnic diversity. Additional studies with these populations are needed to further develop VR systems that work best for diverse patients with chronic pain.

Integrating Patient-Generated Health Data Throughout the Total Product Life Cycle of Medical Devices.

Nearly ubiquitous use of personal electronics, wearable sensors, and other types of digital health technologies, along with wireless connectivity, makes the capture of health data directly from an individual easier, enabling the use of patient-generated health data (PGHD) as a potential bridge between a patient's home and the healthcare system. This type of real-world data may be a completely new type of information, or it may be a more frequent collection of traditional information over longer time periods to form a longitudinal view of a patient's health status that can inform decision-making in clinical, medical product regulatory, and coverage and reimbursement settings. The U.S. Food and Drug Administration's Center for Devices and Radiological Health (CDRH) has been exploring and advancing the collection and use of PGHD since 2016, hosting a public meeting on the topic in May 2021. This manuscript presents highlights from various discussions at this meeting including those on the importance of stakeholder engagement, characteristics of high data quality, and PGHD in practice in patient-driven registries, as well as a look forward to some of the opportunities in the field.

Exploring Chronic Pain and Pain Management Perspectives: Qualitative Pilot Analysis of Web-Based Health Community Posts.

BACKGROUND: Patient perspectives are central to the US Food and Drug Administration's benefit-risk decision-making process in the evaluation of medical products. Traditional channels of communication may not be feasible for all patients and consumers. Social media websites have increasingly been recognized by researchers as a means to gain insights into patients' views about treatment and diagnostic options, the health care system, and their experiences living with their conditions. Consideration of multiple patient perspective data sources offers the Food and Drug Administration the opportunity to capture diverse patient voices and experiences with chronic pain. OBJECTIVE: This pilot study explores posts from a web-based patient platform to gain insights into the key challenges and barriers to treatment faced by patients with chronic pain and their caregivers. METHODS: This research compiles and analyzes unstructured patient data to draw out the key themes. To extract relevant posts for this study, predefined keywords were identified. Harvested posts were published between January 1, 2017, and October 22, 2019, and had to include #ChronicPain and at least one other relevant disease tag, a relevant chronic pain management tag, or a chronic pain management tag for a treatment or activity specific to chronic pain. RESULTS: The most common topics discussed among persons living with chronic pain were related to disease burden, the need for support, advocacy, and proper diagnosis. Patients' discussions focused on the negative impact chronic pain had on their emotions, playing sports, or exercising, work and school, sleep, social life, and other activities of daily life. The 2 most frequently discussed treatments were opioids or narcotics and devices such as transcutaneous electrical nerve stimulation machines and spinal cord stimulators. CONCLUSIONS: Social listening data may provide valuable insights into patients' and caregivers' perspectives, preferences, and unmet needs, especially when conditions may be highly stigmatized.

Digital technologies: Innovations that transform the face of drug development.

Recently, digital health technologies (DHTs) and digital biomarkers have gained a lot of traction in clinical investigations, motivating sponsors, investigators, and regulators to discuss and implement integrated approaches for deploying DHTs. These new tools present new and unique challenges for optimal technology integration in clinical trial processes, including operational, ethical, and regulatory issues. In this paper, we gathered different perspectives to discuss challenges and perspectives from three different stakeholders: industry, US regulators, and a public-private partnership consortium. The complexities of DHT implementation, which include regulatory definitions, defining the scope of validation experiments, and the need for partnerships between BioPharma and the technology sectors, are highlighted. Most of these challenges are related to translation of DHT-derived measures into endpoints that are meaningful to clinicians and patients, participant safety, training, and retention and privacy of data. The example of the Wearable Assessments in the Clinic and Home in PD (WATCH-PD) study is discussed as an example that demonstrated the advantages of pre-competitive collaborations, which include early regulatory feedback, data sharing, and multistakeholder alignment. Future advances in DHTs are expected to spur device-agnostic measured development and incorporate patient reported outcomes in drug development. More efforts are needed to define validation experiments for a defined context of use, incentivize data sharing and development of data standards. Multistakeholder collaborations via precompetitive consortia will help facilitate broad acceptance of DHT-enabled measures in drug development.

Patient-Centered Clinical Trial Design for Heart Failure Devices via Bayesian Decision Analysis.

BACKGROUND: The statistical significance of clinical trial outcomes is generally interpreted quantitatively according to the same threshold of 2.5% (in one-sided tests) to control the false-positive rate or type I error, regardless of the burden of disease or patient preferences. The clinical significance of trial outcomes-including patient preferences-are also considered, but through qualitative means that may be challenging to reconcile with the statistical evidence. OBJECTIVE: We aimed to apply Bayesian decision analysis to heart failure device studies to choose an optimal significance threshold that maximizes the expected utility to patients across both the null and alternative hypotheses, thereby allowing clinical significance to be incorporated into statistical decisions either in the trial design stage or in the post-trial interpretation stage. In this context, utility is a measure of how much well-being the approval decision for the treatment provides to the patient. METHODS: We use the results from a discrete-choice experiment study focusing on heart failure patients' preferences, questioning respondents about their willingness to accept therapeutic risks in exchange for quantifiable benefits with alternative hypothetical medical device performance characteristics. These benefit-risk trade-off data allow us to estimate the loss in utility-from the patient perspective-of a false-positive or false-negative pivotal trial result. We compute the Bayesian decision analysis-optimal statistical significance threshold that maximizes the expected utility to heart failure patients for a hypothetical two-arm, fixed-sample, randomized controlled trial. An interactive Excel-based tool is provided that illustrates how the optimal statistical significance threshold changes as a function of patients' preferences for varying rates of false positives and false negatives, and as a function of assumed key parameters. RESULTS: In our baseline analysis, the Bayesian decision analysis-optimal significance threshold for a hypothetical two-arm randomized controlled trial with a fixed sample size of 600 patients per arm was 3.2%, with a statistical power of 83.2%. This result reflects the willingness of heart failure patients to bear additional risks of the investigational device in exchange for its probable benefits. However, for increased device-associated risks and for risk-averse subclasses of heart failure patients, Bayesian decision analysis-optimal significance thresholds may be smaller than 2.5%. CONCLUSIONS: A Bayesian decision analysis is a systematic, transparent, and repeatable process for combining clinical and statistical significance, explicitly incorporating burden of disease and patient preferences into the regulatory decision-making process.

Use of Bayesian decision analysis to maximize value in patient-centered randomized clinical trials in Parkinson's disease.

A fixed one-sided significance level of 5% is commonly used to interpret the statistical significance of randomized clinical trial (RCT) outcomes. While it is necessary to reduce the false positive rate, the threshold used could be chosen quantitatively and transparently to specifically reflect patient preferences regarding benefit-risk tradeoffs as well as other considerations. How can patient preferences be explicitly incorporated into RCTs in Parkinson's disease (PD), and what is the impact on statistical thresholds for device approval? In this analysis, we apply Bayesian decision analysis (BDA) to PD patient preference scores elicited from survey data. BDA allows us to choose a sample size (n) and significance level (α) that maximizes the overall expected value to patients of a balanced two-arm fixed-sample RCT, where the expected value is computed under both null and alternative hypotheses. For PD patients who had previously received deep brain stimulation (DBS) treatment, the BDA-optimal significance levels fell between 4.0% and 10.0%, similar to or greater than the traditional value of 5%. Conversely, for patients who had never received DBS, the optimal significance level ranged from 0.2% to 4.4%. In both of these populations, the optimal significance level increased with the severity of the patients' cognitive and motor function symptoms. By explicitly incorporating patient preferences into clinical trial designs and the regulatory decision-making process, BDA provides a quantitative and transparent approach to combine clinical and statistical significance. For PD patients who have never received DBS treatment, a 5% significance threshold may not be conservative enough to reflect their risk-aversion level. However, this study shows that patients who previously received DBS treatment present a higher tolerance to accept therapeutic risks in exchange for improved efficacy which is reflected in a higher statistical threshold.

Do PRO Measures Function the Same Way for all Individuals With Heart Failure?

Women diagnosed with heart failure report worse quality of life than men on patient-reported outcome (PRO) measures. An inherent assumption of PRO measures in heart failure is that women and men interpret questions about quality of life the same way. If this is not the case, the risk then becomes that the PRO scores cannot be used for valid comparison or to combine outcomes by subgroups of the population. Inability to compare subgroups validly is a broad issue and has implications for clinical trials, and it also has specific and important implications for identifying and beginning to address health inequities. We describe this threat to validity (the psychometric term is differential item functioning), why it is so important in heart-failure outcomes, the research that has been conducted thus far in this area, the gaps that remain, and what we can do to avoid this threat to validity. PROs bring unique information to clinical decision making, and the validity of PRO measures is key to interpreting differences in heart failure outcomes.

Investigating gender-based differential item functioning on the Kansas City Cardiomyopathy Questionnaire (KCCQ) using qualitative content analysis.

PURPOSE: The purpose of this study is to evaluate potential gender-based differences in interpreting the Kansas City Cardiomyopathy Questionnaire (KCCQ-23) and to explore if there are aspects of health-related quality of life (HRQOL) not captured by the KCCQ-23 that are important to assess in men and/or women with heart failure (HF). METHODS: Patients ≥ 22 years of age with clinician-diagnosed HF and left ventricular ejection fraction ≤ 40% were recruited from two academic medical centers to participate in semi-structured concept elicitation and cognitive debriefing interviews. Enrollment was stratified by patient-identified gender (half women/half men). All interviews were conducted over the phone/web and audio recorded. Interviews were transcribed and descriptive qualitative content analysis was used to summarize findings overall and by gender. RESULTS: Twenty-five adults (56% women) diagnosed with HF participated. The average age was 67 years (range: 25-88). Women attributed a wider variety of symptoms to HF than men. Some participants had difficulty differentiating whether their experiences were due to HF, side effects of their medications, or age. We found very little evidence that participants interpreted KCCQ-23 items differently based on gender. CONCLUSIONS: Overall, our findings indicate that interpretation of the KCCQ-23 items were similar in men and women. However, some modifications to items may improve clarity of interpretation for a wide range of patients.

Development of a Patient Preference Survey for Wearable Kidney Replacement Therapy Devices.

Background: Recent innovations have the potential to disrupt the current paradigm for kidney failure treatment. The US Food and Drug Administration is committed to incorporating valid scientific evidence about how patients weigh the benefits and risks of new devices into their decision making, but to date, premarket submission of patient preference information (PPI) has been limited for kidney devices. With input from stakeholders, we developed a survey intended to yield valid PPI, capturing how patients trade off the potential benefits and risks of wearable dialysis devices and in-center hemodialysis. Methods: We conducted concept elicitation interviews with individuals receiving dialysis to inform instrument content. After instrument drafting, we conducted two rounds of pretest interviews to evaluate survey face validity, comprehensibility, and perceived relevance. We pilot tested the survey with in-center hemodialysis patients to assess comprehensibility and usability further. Throughout, we used participant input to guide survey refinements. Results: Thirty-six individuals receiving in-center or home dialysis participated in concept elicitation (N=20) and pretest (N=16) interviews. Participants identified reduced fatigue, lower treatment burden, and enhanced freedom as important benefits of a wearable device, and many expressed concerns about risks related to device disconnection-specifically bleeding and infection. We drafted a survey that included descriptions of the risks of serious bleeding and serious infection and an assessment of respondent willingness to wait for a safer device. Input from pretest interviewees led to various instrument modifications, including treatment descriptions, item wording, and risk-level explanations. Pilot testing of the updated survey among 24 in-center hemodialysis patients demonstrated acceptable survey comprehensibility and usability, although 50% of patients required some assistance. Conclusions: The final survey is a 54-item web-based instrument that will yield estimates of the maximal acceptable risk for the described wearable device and willingness to wait for wearable devices with lower risk.

Patient-reported outcomes and medical device evaluation: from conception to implementation.

BACKGROUND: The insights gleaned from patient-reported outcomes (PROs) have implications across the healthcare ecosystem, from clinical investigations to evaluate the safety and effectiveness of medical devices to clinical care and reimbursement decisions. The U.S. Food and Drug Administration's (FDA) Center for Devices and Radiological Health (CDRH) hosted a public meeting in September 2020 discussing how PROs can be used in medical device evaluation throughout the total product life cycle, as well as methods for developing and modifying PRO instruments to ensure they are fit-for-purpose. This commentary presents key points of discussion from the meeting, providing insight into the increased interest in PRO data to support medical product development while also exploring future opportunities of incorporating PRO data throughout healthcare. MAIN BODY: Thoughtful use of fit-for-purpose PRO instruments to integrate the patient's voice into clinical care paradigms, medical device development, regulatory decisions, and reimbursement and coverage decisions were emphasized throughout the meeting. Existing PRO instruments may be used if the context of use is appropriate. Modifications to an existing PRO instrument may also be explored to ensure the instrument is fit-for-purpose in a new context of use. Development of a novel PRO instrument may be necessary to capture attributes in a new patient population or application. Multi-stakeholder collaborations, of which patients are a key component, create efficiencies in the development and modification of PRO instruments. CONCLUSION: Continued multi-stakeholder collaborations bringing together researchers, clinicians, patients, regulators, and payers are critical to further advance the inclusion of the patient voice incorporating PRO instruments throughout the healthcare ecosystem in an efficient manner that is least burdensome to patients.

Do patient-reported outcome measures measure up? A qualitative study to examine perceptions and experiences with heart failure proms among diverse, low-income patients.

BACKGROUND: The Kansas City Cardiomyopathy Questionnaire (KCCQ) is a Patient-Reported Outcome Measure (PROM) used to evaluate the health status of patients with heart failure (HF) but has predominantly been tested in settings serving predominately white, male, and economically well-resourced populations. We sought to examine the acceptability of the shorter version of the KCCQ (KCCQ-12) among racially and ethnically diverse patients receiving care in an urban, safety-net setting. METHODS: We conducted cognitive interviews with a diverse population of patients with heart failure in a safety net system to assess their perceptions of the KCCQ-12. We conducted a thematic analysis of the qualitative data then mapped themes to the Capability, Opportunity, Motivation Model of Behavior framework. RESULTS: We interviewed 18 patients with heart failure and found that patients broadly endorsed the concepts of the KCCQ-12 with minor suggestions to improve the instrument's content and appearance. Although patients accepted the KCCQ-12, we found that the instrument did not adequately measure aspects of health care and quality of life that patients identified as being important components of managing their heart failure. Patient-important factors of heart failure management coalesced into three main themes: social support, health care environment, and mental health. CONCLUSIONS: Patients from this diverse, low-income, majority non-white population experience unique challenges and circumstances that impact their ability to manage disease. In this study, patients were receptive to the KCCQ-12 as a tool but perceived that it did not adequately capture key health components such as mental health and social relationships that deeply impact their ability to manage HF. Further study on the incorporation of social determinants of health into PROMs could make them more useful tools in evaluating and managing HF in diverse, underserved populations.

Quantifying Benefit-Risk Preferences for Heart Failure Devices: A Stated-Preference Study.

BACKGROUND: Regulatory and clinical decisions involving health technologies require judgements about relative importance of their expected benefits and risks. We sought to quantify heart-failure patients' acceptance of therapeutic risks in exchange for improved effectiveness with implantable devices. METHODS: Individuals with heart failure recruited from a national web panel or academic medical center completed a web-based discrete-choice experiment survey in which they were randomized to one of 40 blocks of 8 experimentally controlled choice questions comprised of 2 device scenarios and a no-device scenario. Device scenarios offered an additional year of physical functioning equivalent to New York Heart Association class III or a year with improved (ie, class II) symptoms, or both, with 30-day mortality risks ranging from 0% to 15%, in-hospital complication risks ranging from 0% to 40%, and a remote adjustment device feature. Logit-based regression models fit participants' choices as a function of health outcomes, risks and remote adjustment. RESULTS: Latent-class analysis of 613 participants (mean age, 65; 49% female) revealed that two-thirds were best represented by a pro-device, more risk-tolerant class, accepting up to 9% (95% CI, 7%-11%) absolute risk of device-associated mortality for a one-year gain in improved functioning (New York Heart Association class II). Approximately 20% were best represented by a less risk-tolerant class, accepting a maximum device-associated mortality risk of 3% (95% CI, 1%-4%) for the same benefit. The remaining class had strong antidevice preferences, thus maximum-acceptable risk was not calculated. CONCLUSIONS: Quantitative evidence on benefit-risk tradeoffs for implantable heart-failure device profiles may facilitate incorporating patients' views during product development, regulatory decision-making, and clinical practice.

Psychometric Evaluation of the Kansas City Cardiomyopathy Questionnaire in Men and Women With Heart Failure.

BACKGROUND: The Kansas City Cardiomyopathy Questionnaire (KCCQ) has been psychometrically evaluated in multiple heart failure (HF) populations, but the comparability of its psychometric properties between men and women is unknown. METHODS: Data from 3 clinical trials (1 in stable HF with preserved ejection fraction, 1 each in stable and acute HF with reduced ejection fraction) and 1 prospective cohort study (stable HF with reduced ejection fraction), incorporating 6773 men and 3612 women with HF, were used to compare the construct validity, internal and test-retest reliability, ability to detect change, predict mortality and hospitalizations and minimally important differences between the 2 sexes. Interactions of the KCCQ overall summary and subdomain scores by sex were independently examined. RESULTS: The KCCQ-Overall Summary score correlated well with New York Heart Association functional class in both sexes across patients with stable (correlation coefficient: -0.40 in men versus -0.49 in women) and acute (-0.37 in men versus -0.34 in women) HF. All KCCQ subdomains demonstrated concordant relationships with relevant comparison standards with no significant interactions by sex in 19 of 21 of these construct validity analyses. All KCCQ scores were equally predictive and other psychometric evaluations showed similar results by sex: test-retest reliability (intraclass correlation coefficient 0.94 in men versus 0.92 in women), responsive to change (standardized response mean 1.01 in both sexes), as were the minimally important differences and internal reliability. CONCLUSIONS: The psychometric properties of the KCCQ, in terms of validity, prognosis, reliability, and sensitivity to change, are comparable in men and women with HF with preserved ejection fraction and HF with reduced ejection fraction.