Publications

Abstract

Glioblastoma (GBM) has a median overall survival of 16-21 months. As patients with GBM suffer concurrently from terminal cancer and a disease with progressive neurocognitive decline, advance care planning (ACP) and palliative care (PC) are critical. We conducted a systematic review exploring published literature on the prevalence of ACP, end-of-life (EOL) services utilization (including PC services), and experiences among adults with GBM. We searched from database inception until 20 December 2020. Preferred reporting items for systematic reviews guidelines were followed. Included studies were assessed for quality using the Newcastle-Ottawa Scale. The 16 articles were all nonrandomized studies conducted in six countries with all but two published in 2014 or later. ACP documentation varied from 4-55%, PC referral was pursued in 39-40% of cases, and hospice referrals were made for 66-76% of patients. Hospitalizations frequently occurred at the EOL with 20-56% of patients spending over 25% of their overall survival time hospitalized. Many GBM patients do not pursue ACP or have access to PC. There is a dearth of focused and high-quality studies on ACP, PC, and hospice use among adults with GBM. Prospective studies that address these and additional aspects related to EOL care, such as healthcare costs and inpatient supportive care needs, are needed.

View details for DOI 10.3390/cancers13122867

View details for PubMedCentralID PMC8228109

Abstract

IMPORTANCE: The development of Artificial Intelligence (AI) and other machine diagnostic systems, also known as Software as a Medical Device (SaMD), and its recent introduction into clinical practice, requires a deeply-rooted foundation in bioethics, for consideration by regulatory agencies and other stakeholders around the globe.OBJECTIVES: Initiate a dialogue on the issues to consider when developing a bioethically sound foundation for AI in medicine, based on images of eye structures, for discussion with all stakeholders.EVIDENCE REVIEW: The scope of the issues and summaries of the discussions under consideration by the Foundational Principles of Ophthalmic Imaging and Algorithmic Interpretation Working Group, as first presented during the Collaborative Community on Ophthalmic Imaging inaugural meeting on September 7, 2020, and afterwards in the working group.FINDINGS: AI has the potential to fundamentally improve the access to healthcare and patient outcomes, while decreasing disparities, lowering cost, as well as enhancing the care team. Nevertheless, substantial concerns exist. Ethicists, AI algorithm experts, as well as the Food and Drug Administration (FDA) and other regulatory agencies, industry, patient advocacy groups, clinicians and their professional societies, other provider groups, payors, and other healthcare stakeholders working together in collaborative communities to resolve such issues as non-maleficence, autonomy and equity, is essential to attain this potential, and impacts all levels of the design, validation and implementation of AI in medicine. Design, validation and implementation of AI warrant meticulous attention.CONCLUSIONS AND RELEVANCE: The development of a bioethically sound foundation may be possible if it is based in non-maleficence, autonomy and equity, for considerations for the design, validation and implementation for AI systems. Achieving such a foundation will be helpful for continuing successful introduction into medicine, before consideration by regulatory agencies around the globe.Fundamental improvements in accessibility and quality of healthcare, decrease in health disparities, and lower cost can thereby be achieved. These considerations should be discussed with all stakeholders and expanded upon as a useful initiation of this dialogue.

View details for DOI 10.1016/j.ophtha.2021.08.023

View details for PubMedID 34478784

View details for DOI 10.1097/MAT.0000000000001545

View details for PubMedID 34352820

Abstract

OBJECTIVES: Through improving diagnostics and prognostics genomic sequencing promises to significantly impact clinical decisions for children with critical cardiac disease. Little is known about how families of children with critical cardiac disease perceive the impact of genomic sequencing on clinical care choices.DESIGN: Qualitative interview study.SETTING: A high-volume, tertiary pediatric heart center.SUBJECTS: Families of children with critical cardiac disease.INTERVENTIONS: None.MEASUREMENTS AND MAIN RESULTS: Thematic analysis of interview response content. Thirty-five families were interviewed. Three themes emerged: 1) benefits versus challenges of having genomic sequencing results, and 2) fears of clinical applications of genomic sequencing, and 3) nonclinical fears related to genomic sequencing. Participants struggled with perceived uses of genomic sequencing-derived knowledge. They described comfort in foreknowledge of their child's likely disease course but articulated significant apprehension around participating in care decisions with limited knowledge of genomic sequencing, genomic sequencing uses to inform clinical resource rationing decisions, and genomic sequencing uses by third parties impacting financial pressures families experience caring for a child with critical cardiac disease.CONCLUSIONS: Families' perceptions of genomic sequencing uses in critical cardiac disease appear to strain their overall trust in the health system. Erosion of trust is concerning because the potential of genomic sequencing in critical cardiac disease will be unrealized if families are unwilling to undergo genomic sequencing, let alone to participate in the ongoing research needed to link genomic sequencing variants to clinical outcomes. Our findings may have implications for genomic sequencing use in children with other critical, high-acuity diseases.

View details for DOI 10.1097/PCC.0000000000002669

View details for PubMedID 33591072

Abstract

OBJECTIVE: To better understand diverse experts' views about the ethical implications of ongoing research funded by the National Institutes of Health that uses machine learning to predict HIV/AIDS risk in sub-Saharan Africa (SSA) based on publicly available Demographic and Health Surveys data.DESIGN: Three rounds of semi-structured surveys in an online expert panel using a modified Delphi approach.PARTICIPANTS: Experts in informatics, African public health and HIV/AIDS and bioethics were invited to participate.MEASURES: Perceived importance of or agreement about relevance of ethical issues on 5-point unipolar Likert scales. Qualitative data analysis identified emergent themes related to ethical issues and development of an ethical framework and recommendations for open-ended questions.RESULTS: Of the 35 invited experts, 22 participated in the online expert panel (63%). Emergent themes were the inclusion of African researchers in all aspects of study design, analysis and dissemination to identify and address local contextual issues, as well as engagement of communities. Experts focused on engagement with health and science professionals to address risks, benefits and communication of findings. Respondents prioritised the mitigation of stigma to research participants but recognised trade-offs between privacy and the need to disseminate findings to realise public health benefits. Strategies for responsible communication of results were suggested, including careful word choice in presentation of results and limited dissemination to need-to-know stakeholders such as public health planners.CONCLUSION: Experts identified ethical issues specific to the African context and to research on sensitive, publicly available data and strategies for addressing these issues. These findings can be used to inform an ethical implementation framework with research stage-specific recommendations on how to use publicly available data for machine learning-based predictive analytics to predict HIV/AIDS risk in SSA.

View details for DOI 10.1136/bmjopen-2021-052287

View details for PubMedID 34321310

Abstract

BACKGROUND: Digital phenotyping (also known as personal sensing, intelligent sensing, or body computing) involves the collection of biometric and personal data in situ from digital devices, such as smartphones, wearables, or social media, to measure behavior or other health indicators. The collected data are analyzed to generate moment-by-moment quantification of a person's mental state and potentially predict future mental states. Digital phenotyping projects incorporate data from multiple sources, such as electronic health records, biometric scans, or genetic testing. As digital phenotyping tools can be used to study and predict behavior, they are of increasing interest for a range of consumer, government, and health care applications. In clinical care, digital phenotyping is expected to improve mental health diagnoses and treatment. At the same time, mental health applications of digital phenotyping present significant areas of ethical concern, particularly in terms of privacy and data protection, consent, bias, and accountability.OBJECTIVE: This study aims to develop consensus statements regarding key areas of ethical guidance for mental health applications of digital phenotyping in the United States.METHODS: We used a modified Delphi technique to identify the emerging ethical challenges posed by digital phenotyping for mental health applications and to formulate guidance for addressing these challenges. Experts in digital phenotyping, data science, mental health, law, and ethics participated as panelists in the study. The panel arrived at consensus recommendations through an iterative process involving interviews and surveys. The panelists focused primarily on clinical applications for digital phenotyping for mental health but also included recommendations regarding transparency and data protection to address potential areas of misuse of digital phenotyping data outside of the health care domain.RESULTS: The findings of this study showed strong agreement related to these ethical issues in the development of mental health applications of digital phenotyping: privacy, transparency, consent, accountability, and fairness. Consensus regarding the recommendation statements was strongest when the guidance was stated broadly enough to accommodate a range of potential applications. The privacy and data protection issues that the Delphi participants found particularly critical to address related to the perceived inadequacies of current regulations and frameworks for protecting sensitive personal information and the potential for sale and analysis of personal data outside of health systems.CONCLUSIONS: The Delphi study found agreement on a number of ethical issues to prioritize in the development of digital phenotyping for mental health applications. The Delphi consensus statements identified general recommendations and principles regarding the ethical application of digital phenotyping to mental health. As digital phenotyping for mental health is implemented in clinical care, there remains a need for empirical research and consultation with relevant stakeholders to further understand and address relevant ethical issues.

View details for DOI 10.2196/27343

View details for PubMedID 34319252

Abstract

PURPOSE: Social media may be particularly valuable in research in rare genetic diseases because of the low numbers of patients and the rare disease community's robust online presence. The goal of this systematic review was to understand how social media is currently used in rare disease research and the characteristics of the participants in these studies.METHODS: We conducted a systematic review of six databases to identify studies published in English between January 2004 and November 2020, of which 120 met inclusion criteria.RESULTS: Most studies were observational (n=114, 95.0%) and cross-sectional (n=107, 89.2%), and more than half (n=69, 57.5%) utilized only surveys. Only 101 rare diseases were included across all studies. Participant demographics, when reported, were predominantly female (70.1% ± 22.5%) and white (85.0% ± 11.0%) adult patients and caregivers.CONCLUSION: Despite its potential benefits in rare disease research, the use of social media is still methodologically limited and the participants reached may not be representative of the rare disease population by gender, race, age, or rare disease type. As scholars explore using social media for rare disease research, careful attention should be paid to representativeness when studying this diverse patient community.

View details for DOI 10.1038/s41436-021-01273-z

View details for PubMedID 34282302

Abstract

BACKGROUND: The COVID-19 pandemic has accelerated the adoption of telemedicine, including teledermatology. Monitoring skin lesions using teledermatology may become increasingly important for several skin diseases, including low-risk skin cancers. The purpose of this study was to describe the key factors that could serve as barriers or facilitators to skin disease monitoring using mobile health technology (mHealth) in older adults.METHODS: Older adult dermatology patients 65years or older and their caregivers who have seen a dermatologist in the last 18months were interviewed and surveyed between December 2019 and July 2020. The purpose of these interviews was to better understand attitudes, beliefs and behaviours that could serve as barriers and facilitators to the use of mHealth and active surveillance to monitor low-risk skin cancers.RESULTS: A total of 33 interviews leading to 6022 unique excerpts yielded 8 factors, or themes, that could serve as barriers, facilitators or both to mHealth and active surveillance. We propose an integrated conceptual framework that highlights the interaction of these themes at both the patient and provider level, including care environment, support systems and personal values.DISCUSSION AND CONCLUSIONS: These preliminary findings reveal factors influencing patient acceptance of active surveillance in dermatology, such as changes to the patient-provider interaction and alignment with personal values. These factors were also found to influence adoption of mHealth interventions. Given such overlap, it is essential to address barriers and facilitators from both domains when designing a new dermatology active surveillance approach with novel mHealth technology.PATIENT OR PUBLIC CONTRIBUTION: The patients included in this study were participants during the data collection process. Members of the Stanford Healthcare and Denver Tech Dermatology health-care teams aided in the recruitment phase of the data collection process.

View details for DOI 10.1111/hex.13229

View details for PubMedID 34190397

Abstract

BACKGROUND: Considerable effort has been devoted to the development of artificial intelligence, including machine learning-based predictive analytics (MLPA) for use in health care settings. The growth of MLPA could be fueled by payment reforms that hold health care organizations responsible for providing high-quality, cost-effective care. Policy analysts, ethicists, and computer scientists have identified unique ethical and regulatory challenges from the use of MLPA in health care. However, little is known about the types of MLPA health care products available on the market today or their stated goals.OBJECTIVE: This study aims to better characterize available MLPA health care products, identifying and characterizing claims about products recently or currently in use in US health care settings that are marketed as tools to improve health care efficiency by improving quality of care while reducing costs.METHODS: We conducted systematic database searches of relevant business news and academic research to identify MLPA products for health care efficiency meeting our inclusion and exclusion criteria. We used content analysis to generate MLPA product categories and characterize the organizations marketing the products.RESULTS: We identified 106 products and characterized them based on publicly available information in terms of the types of predictions made and the size, type, and clinical training of the leadership of the companies marketing them. We identified 5 categories of predictions made by MLPA products based on publicly available product marketing materials: disease onset and progression, treatment, cost and utilization, admissions and readmissions, and decompensation and adverse events.CONCLUSIONS: Our findings provide a foundational reference to inform the analysis of specific ethical and regulatory challenges arising from the use of MLPA to improve health care efficiency.

View details for DOI 10.2196/26391

View details for PubMedID 34156338

Abstract

OBJECTIVE: To analyze the impact of factors in healthcare delivery on the net benefit of triggering an Advanced Care Planning (ACP) workflow based on predictions of 12-month mortality.MATERIALS AND METHODS: We built a predictive model of 12-month mortality using electronic health record data and evaluated the impact of healthcare delivery factors on the net benefit of triggering an ACP workflow based on the models' predictions. Factors included nonclinical reasons that make ACP inappropriate: limited capacity for ACP, inability to follow up due to patient discharge, and availability of an outpatient workflow to follow up on missed cases. We also quantified the relative benefits of increasing capacity for inpatient ACP versus outpatient ACP.RESULTS: Work capacity constraints and discharge timing can significantly reduce the net benefit of triggering the ACP workflow based on a model's predictions. However, the reduction can be mitigated by creating an outpatient ACP workflow. Given limited resources to either add capacity for inpatient ACP versus developing outpatient ACP capability, the latter is likely to provide more benefit to patient care.DISCUSSION: The benefit of using a predictive model for identifying patients for interventions is highly dependent on the capacity to execute the workflow triggered by the model. We provide a framework for quantifying the impact of healthcare delivery factors and work capacity constraints on achieved benefit.CONCLUSION: An analysis of the sensitivity of the net benefit realized by a predictive model triggered clinical workflow to various healthcare delivery factors is necessary for making predictive models useful in practice.

View details for DOI 10.1093/jamia/ocaa318

View details for PubMedID 33355350

Abstract

The rise of genomic technologies has catalyzed shifts in the health care landscape through the commercialization of genome sequencing and testing services in the genomics marketplace. The development of consumer genomics into a growing array of information technologies aimed at collecting, curating, and broadly sharing personal data and biological materials reconstitutes the meaning of health and reframes patients into biocitizens. In this context, the good biocitizen is expected to assume personal responsibility for health through consumption of genomic information and acquiescence to public and private efforts at data surveillance and aggregation. These shifts raise fundamental questions about how competing interests of the public, the state, and corporate entities will be reconciled and what trade-offs are demanded for the promise of precision health.

View details for DOI 10.1002/hast.1156

View details for Web of Science ID 000543918300008

View details for PubMedID 32597530

Abstract

This study describes challenges faced while incorporating sometimes conflicting stakeholder feedback into study design and development of patient-facing materials for a translational genomics study aiming to reduce health disparities among diverse populations.We conducted an ethnographic analysis of study documents including summaries of patient advisory committee meetings and interviews, reflective field notes written by study team members, and correspondence with our institutional review board (IRB). Through this analysis, we identified cross-cutting challenges for incorporating stakeholder feedback into development of our recruitment, risk assessment, and informed consent processes and materials.Our analysis revealed three key challenges: (1) balancing precision and simplicity in the design of study materials, (2) providing clinical care within the research context, and (3) emphasizing potential study benefits versus risks and limitations.While involving patient stakeholders in study design and materials development can increase inclusivity and responsiveness to patient needs, patient feedback may conflict with that of content area experts on the research team and IRBs who are tasked with overseeing the research. Our analysis highlights the need for further empirical research about ethical challenges when incorporating patient feedback into study design, and for dialogue with genomic researchers and IRB representatives about these issues.

View details for DOI 10.1038/s41436-020-0763-z

View details for PubMedID 32089547

Abstract

BACKGROUND: Standardized pretransplant psychosocial assessment is critically needed in Thailand to optimize medical and psychosocial outcomes after transplantation. The Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT) is a comprehensive and evidence-based tool that has demonstrated excellent reliability and predictive value in many psychosocial transplant studies. We translated the SIPAT into Thai and explored the validity and reliability of the SIPAT-Thai version among Thai transplant recipients.METHODS: We translated the original SIPAT into Thai following the World Health Organization's standard forward-backward translation procedure and then cross-sectionally assessed its validity and reliability in 110 Thai solid organ transplant candidates. The correlation between background data, total, and sectional scoring results of SIPAT-Thai were also analyzed.RESULTS: The SIPAT-Thai demonstrated moderate to good reliability, which was represented by internal consistency with a Cronbach alpha of .751 and interrater reliability with a kappa value at 0.767. The index of item-objective congruence value was 0.94, indicating good the content validity.CONCLUSIONS: The SIPAT-Thai was systematically translated and shown to have acceptable validity and a moderate to good reliability index. The use of the SIPAT-Thai would provide a standardized, evidence-based, and a more systematic pretransplant psychosocial evaluation process for transplant candidates in Thailand.

View details for DOI 10.1016/j.transproceed.2021.02.013

View details for PubMedID 33741202

Abstract

Background and objectives: There has been a recent increase in older patients admitted to general hospitals. A significant percentage of hospitalized older patients are ≥75 years old, which differ from the patients aged 65 to 74 years old in terms of functional status at patient discharge. This study aims to compare sociodemographic, clinical features, and factors associated with length of hospital stay in youngest-old and oldest-old populations of inpatients referred to the consultation liaison psychiatry unit. Material and methods: This is an observational, cross-sectional, retrospective, and comparative study. We obtained data from a sample of 1017 patients (≥65 years) admitted to a general hospital and referred from different services (medicine, surgery, etc.) to the consultation liaison psychiatry unit. The sample was divided into two groups of patients: youngest-old (65-74 years) and oldest-old (≥75 years). Psychiatric evaluations were performed while the patients were on wards at the hospital. Psychopharmacs were started as needed. A comparative analysis was carried out and predictive factors related to length of hospital stay were calculated. Results: The reference rate to consultation liaison psychiatry unit was 1.45% of the total older patients hospitalized. Our study demonstrates differences between the groups of older people: the oldest-old group were mainly female (p < 0.001), had more previous psychiatric diagnoses (p < 0.001), physical disabilities (p = 0.02), and neurocognitive disorders (p < 0.001), they used more antipsychotics (p < 0.001), and more frequently had a discharge disposition to a nursing home (p = 0.036). The presence of physical disability (beta = 0.07, p < 0.001) and logtime to referral to consultation liaison psychiatry unit (beta = 0.58, p < 0.001) were associated with increased length of hospital stay. Conclusions: Youngest-old and oldest-old people should be considered as two different types of patients when we consider clinical features. The time to referral to consultation liaison psychiatry unit seems to be a relevant factor associated with length of hospital stay.

View details for DOI 10.3390/medicina57030256

View details for PubMedID 33799510

View details for Web of Science ID 000575913300013

View details for DOI 10.1177/1073110520917008

View details for PubMedID 32342787

Abstract

Applications of facial recognition technology (FRT) in health care settings have been developed to identify and monitor patients as well as to diagnose genetic, medical, and behavioral conditions. The use of FRT in health care suggests the importance of informed consent, data input and analysis quality, effective communication about incidental findings, and potential influence on patient-clinician relationships. Privacy and data protection are thought to present challenges for the use of FRT for health applications.

View details for DOI 10.1001/amajethics.2019.180

View details for PubMedID 30794128

View details for DOI 10.1038/s41746-018-0075-8

View details for Web of Science ID 000453910600001

Abstract

Self-referred imaging is one of the latest health care services to be marketed directly to consumers. Most aspects of these services are unregulated, and little is known about the messages in advertising used to attract potential consumers. We conducted a detailed analysis of print advertisements and informational brochures for self-referred imaging with respect to themes, content, accuracy, and emotional valence.Forty print advertisements from US newspapers around the country and 20 informational brochures were analyzed by 2 independent raters according to 7 major themes: health care technology; emotion, empowerment, and assurance; incentives; limited supporting evidence; popular appeal; statistics; and images. The Fisher exact test was used to identify significant differences in information content.Both the advertisements and the brochures emphasized health care and technology information and provided assurances of good health and incentives to self-refer. These materials also encouraged consumers to seek further information from company resources; virtually none referred to noncomplying sources of information or to the risks of having a scan. Images of people commonly portrayed European Americans. We found statistical differences between newspaper advertisements and mailed brochures for references to "prevalence of disease" (P<.001), "death" (P<.003), and "radiation" (P<.001). Statements lacking clear scientific evidence were identified in 38% of the advertisements (n = 15) and 25% of the brochures (n = 5).Direct-to-consumer marketing of self-referred imaging services, in both print advertisements and informational brochures, fails to provide prospective consumers with comprehensive balanced information vital to informed autonomous decision making. Professional guidelines and oversight for advertising and promotion of these services are needed.

View details for Web of Science ID 000225701900003

View details for PubMedID 15596630

Abstract

To examine different protocols for handling incidental findings on brain research MRIs, and provide a platform for establishing formal discussions of related ethical and policy issues.Corresponding authors identified from a database of peer-reviewed publications in 1991-2002 involving functional MRI (fMRI), alone or in combination with other imaging modalities, were invited to participate in this web-based survey. The survey asked questions regarding knowledge and handling of incidental findings, as well as characteristics of the scanning environment, training required, IRB protocol requirements, and neuroradiologist involvement.Seventy-four investigators who conduct MRI studies in the United States and abroad responded. Eighty-two percent (54/66) reported discovering incidental findings in their studies, such as arteriovenous malformations, brain tumors, and developmental abnormalities. Substantial variability was found in the procedures for handling and communicating findings to subjects, neuroradiologist involvement, personnel permitted to operate equipment, and training.Guidelines for minimum and optimum standards for detecting and communicating incidental findings on brain MRI research are needed.

View details for DOI 10.1002/jmri.20180

View details for Web of Science ID 000224762700001

View details for PubMedID 15503329

View details for PubMedCentralID PMC1506385

Abstract

Chylothorax is a potentially serious complication of lung and heart-lung transplantation. This article describes the clinical course of chylothorax in 3 heart-lung allograft recipients. We discuss management options, including dietary modifications, octreotide infusion, thoracic duct ligation and embolization, and surgical pleurodesis. In addition, we describe the novel use of aminocaproic acid to reduce lymph flow. We propose a multidisciplinary approach for the management of chylothorax that includes both medical and surgical options.

View details for Web of Science ID 000221393700018

View details for PubMedID 15135382

View details for DOI 10.1007/s12630-019-01472-y

View details for PubMedID 31485958

View details for DOI 10.1007/s12630-019-01376-x

View details for Web of Science ID 000480745300004

View details for PubMedID 30357277

Abstract

PURPOSE: Genomic sequencing has become an increasingly powerful and relevant tool to be leveraged for the discovery of genetic aberrations underlying rare, Mendelian conditions. Although the computational tools incorporated into diagnostic workflows for this task are continually evolving and improving, we nevertheless sought to investigate commonalities across sequencing processing workflows to reveal consensus and standard practice tools and highlight exploratory analyses where technical and theoretical method improvements would be most impactful.METHODS: We collected details regarding the computational approaches used by a genetic testing laboratory and 11 clinical research sites in the United States participating in the Undiagnosed Diseases Network via meetings with bioinformaticians, online survey forms, and analyses of internal protocols.RESULTS: We found that tools for processing genomic sequencing data can be grouped into four distinct categories. Whereas well-established practices exist for initial variant calling and quality control steps, there is substantial divergence across sites in later stages for variant prioritization and multimodal data integration, demonstrating a diversity of approaches for solving the most mysterious undiagnosed cases.CONCLUSION: The largest differences across diagnostic workflows suggest that advances in structural variant detection, noncoding variant interpretation, and integration of additional biomedical data may be especially promising for solving chronically undiagnosed cases.

View details for DOI 10.1038/s41436-020-01084-8

View details for PubMedID 33580225

Abstract

Patients with rare and undiagnosed diseases (RUDs) face significant health challenges, which may be exacerbated during the COVID-19 pandemic. The goal of this study was to identify specific impacts of the pandemic on RUD patients, and targets for improving support and health-care access.We conducted an online survey of RUD patients and their family members from 21 April to 8 June 2020, recruited from 76 Facebook groups for RUDs. Questions assessed patient characteristics and impacts of the pandemic on RUD diagnosis and management.Respondents (n = 413), including 274 RUD patients and 139 family members, were predominantly female and white, though income varied. Impacts of the pandemic included (1) barriers to accessing essential health care, (2) specific impacts of restrictive COVID-19 visitation policies on ability to advocate in health-care settings, (3) uncertainty and fear regarding COVID-19 risk, (4) exacerbated physical and mental health challenges, (5) magnified impacts of reduced educational and therapeutic services, and (6) unexpected positive changes due to the pandemic.There are specific, serious challenges affecting RUD patients and families during the COVID-19 pandemic. There is an urgent need to develop approaches to mitigate these challenges both during and beyond the pandemic.

View details for DOI 10.1038/s41436-020-01069-7

View details for PubMedID 33420343

Abstract

PURPOSE: Advances in gene therapy and precision medicine have led to a growing number of novel treatments for rare genetic diseases. Patients/families may lack access to up-to-date, accurate, and relevant information about these treatments. Social media offers one potentially important resource for these communities. Our goal was to understand how patients/families with spinal muscular atrophy (SMA)-a rare genetic condition-used social media to share, consume, and evaluate information about the novel treatment nusinersen (Spinraza) following the drug's approval.METHODS: We conducted qualitative, semistructured interviews with 20 SMA patients or parents of patients, deriving themes and subthemes through content and thematic network analysis. Participants also completed a demographic survey.RESULTS: Participants described leveraging social media to learn about nusinersen treatment, make informed treatment decisions, and advocate for/access treatment. They also described critically evaluating the trustworthiness of nusinersen-related information on social media and the privacy risks of social media use.CONCLUSION: Patients/families used social media to navigate the new and dynamic landscape of nusinersen treatment for SMA, while attempting to mitigate misinformation and privacy risks. As new treatments become available, providers and patients/families may benefit from proactively discussing social media use, so as to maximize important benefits while minimizing risks.

View details for DOI 10.1038/s41436-020-0890-6

View details for PubMedID 32601388

Abstract

PURPOSE: Social media may be particularly valuable in research in rare genetic diseases because of the low numbers of patients and the rare disease community's robust online presence. The goal of this systematic review was to understand how social media is currently used in rare disease research and the characteristics of the participants in these studies.METHODS: We conducted a systematic review of six databases to identify studies published in English between January 2004 and November 2020, of which 120 met inclusion criteria.RESULTS: Most studies were observational (n=114, 95.0%) and cross-sectional (n=107, 89.2%), and more than half (n=69, 57.5%) utilized only surveys. Only 101 rare diseases were included across all studies. Participant demographics, when reported, were predominantly female (70.1% ± 22.5%) and white (85.0% ± 11.0%) adult patients and caregivers.CONCLUSION: Despite its potential benefits in rare disease research, the use of social media is still methodologically limited and the participants reached may not be representative of the rare disease population by gender, race, age, or rare disease type. As scholars explore using social media for rare disease research, careful attention should be paid to representativeness when studying this diverse patient community.

View details for DOI 10.1038/s41436-021-01273-z

View details for PubMedID 34282302

Abstract

Parents of children with undiagnosed conditions struggle to obtain information about how to treat and support their children. It can be particularly challenging to find communities and other parents who share their experiences and can provide emotional and informational support. This study sought to characterize how parents use social media, both throughout the diagnostic odyssey and post-diagnosis, to meet their informational, social, and emotional support needs. We conducted qualitative semi-structured interviews with 14 parents from the Stanford site of the Undiagnosed Diseases Network (UDN), including five whose children had received a diagnosis through study participation. Interview recordings were analyzed using inductive, team-based coding and thematic analysis based in grounded theory using Dedoose qualitative analysis software. Through this process, we identified four key themes related to social media use. First, parents struggled to find the "right" community, often seeking out groups of similar patients based on symptoms or similar conditions. Second, though they found much valuable information through social media about caring for their child, they also struggled to interpret the relevance of the information to their own child's condition. Third, the social support and access to other patients' and families' lived experiences were described as both highly valued and emotionally challenging, particularly in the case of poor outcomes for similar families. Finally, parents expressed the need to balance concerns about their child's privacy with the value of transparency and data sharing for diagnosis. Our results suggest that the needs and experiences of undiagnosed patients and families differ from those with diagnosed diseases and highlight the need for support in best utilizing social media resources at different stages of the diagnostic odyssey.

View details for DOI 10.1002/jgc4.1438

View details for PubMedID 34096130