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Pannunzio V, Morales Ornelas HC, Gurung P, van Kooten R, Snelders D, van Os H, Wouters M, Tollenaar R, Atsma D, Kleinsmann M. Patient and Staff Experience of Remote Patient Monitoring-What to Measure and How: Systematic Review. J Med Internet Res 2024; 26:e48463. [PMID: 38648090 DOI: 10.2196/48463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 08/25/2023] [Accepted: 02/20/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience-measuring methods and tools exists. OBJECTIVE This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain. METHODS Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By "RPM interventions," we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique. RESULTS In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation. CONCLUSIONS At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain.
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Affiliation(s)
- Valeria Pannunzio
- Department of Design, Organisation and Strategy, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands
| | - Hosana Cristina Morales Ornelas
- Department of Sustainable Design Engineering, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands
| | - Pema Gurung
- Walaeus Library, Leiden University Medical Center, Leiden, Netherlands
| | - Robert van Kooten
- Department of Surgery, Leiden University Medical Center, Leiden, Netherlands
| | - Dirk Snelders
- Department of Design, Organisation and Strategy, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands
| | - Hendrikus van Os
- National eHealth Living Lab, Department of Public Health & Primary Care, Leiden University Medical Center, Leiden, Netherlands
| | - Michel Wouters
- Department of Surgery, Netherlands Cancer Institute - Antoni van Leeuwenhoek, Amsterdam, Netherlands
| | - Rob Tollenaar
- Department of Surgery, Leiden University Medical Center, Leiden, Netherlands
| | - Douwe Atsma
- Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands
| | - Maaike Kleinsmann
- Department of Design, Organisation and Strategy, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands
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Nazi KM, Newton T, Armstrong CM. Unleashing the Potential for Patient-Generated Health Data (PGHD). J Gen Intern Med 2024; 39:9-13. [PMID: 38252246 PMCID: PMC10937868 DOI: 10.1007/s11606-023-08461-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 10/06/2023] [Indexed: 01/23/2024]
Abstract
Patient-generated health data (PGHD) is data created, captured, or recorded by patients in between healthcare appointments, and is an important supplement to data generated during periodic clinical encounters. PGHD has potential to improve diagnosis and management of chronic conditions, improve health outcomes, and facilitate more "connected health" between patients and their care teams. Electronic PGHD is rapidly accelerating due to the proliferation of consumer health technologies, remote patient monitoring systems, and personal health platforms. Despite this tremendous growth in PGHD and anticipated benefits, broadscale use of PGHD has been challenging to implement with significant gaps in current knowledge about how PGHD can best be employed in the service of high-quality, patient-centered care. While the role of PGHD in patient self-management continues to grow organically, we need a deeper understanding of how data collection and sharing translate into actionable information that supports shared decision-making and informs clinical care in real-world settings. This, in turn, will foster both clinical adoption and patient engagement with PGHD. We propose an agenda for PGHD-related research in the Veterans Health Administration that emphasizes this clinical value to enhance our understanding of its potential and limitations in supporting shared decision-making and informing clinical care.
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Affiliation(s)
- Kim M Nazi
- Trilogy Federal, LLC, Arlington, VA, USA.
- KMN Consulting Services, LTD, Coxsackie, NY, USA.
- Trilogy Federal, LLC, 44 Mountain View Drive, Coxsackie, NY, 12051, USA.
| | - Terry Newton
- Office of Connected Care, US Department of Veterans Affairs, Washington, DC, USA
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Jan M, Coppin-Renz A, West R, Gallo CL, Cochran JM, Heumen EV, Fahmy M, Reuteman-Fowler JC. Safety Evaluation in Iterative Development of Wearable Patches for Aripiprazole Tablets With Sensor: Pooled Analysis of Clinical Trials. JMIR Form Res 2023; 7:e44768. [PMID: 38085556 PMCID: PMC10751624 DOI: 10.2196/44768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 06/16/2023] [Accepted: 09/23/2023] [Indexed: 12/29/2023] Open
Abstract
BACKGROUND Wearable sensors in digital health may pose a risk for skin irritation through the use of wearable patches. Little is known about how patient- and product-related factors impact the risk of skin irritation. Aripiprazole tablets with sensor (AS, Abilify MyCite; Otsuka America Pharmaceutical, Inc) is a digital medicine system indicated for the treatment of patients with schizophrenia, bipolar I disorder, and major depressive disorder. AS includes aripiprazole tablets with an embedded ingestible event marker, a wearable sensor attached to the skin through a wearable patch, a smartphone app, and a web-based portal. To continuously improve the final product, successive iterations of wearable patches were developed, including raisin patch version 4 (RP4), followed by disposable wearable sensor version 5 (DW5), and then reusable wearable sensor version 2 (RW2). OBJECTIVE This analysis pooled safety data from clinical studies in adult participants using the RP4, DW5, and RW2 wearable patches of AS and evaluated adverse events related to the use of wearable patches. METHODS Safety data from 12 studies in adults aged 18-65 years from May 2010 to August 2020 were analyzed. All studies evaluated safety, with studies less than 2 weeks also specifically examining human factors associated with the use of the components of AS. Healthy volunteers or patients with schizophrenia, bipolar I disorder, or major depressive disorder were enrolled; those who were exposed to at least 1 wearable patch were included in the safety analysis. Adverse events related to the use of a wearable patch were evaluated. Abrasions, blisters, dermatitis, discoloration, erythema, irritation, pain, pruritus, rash, and skin reactions were grouped as skin irritation events (SIEs). All statistical analyses were descriptive. RESULTS The analysis included 763 participants (mean [SD] age 42.6 [12.9] years; White: n=359, 47.1%; and male: n=420, 55%). Participants were healthy volunteers (n=269, 35.3%) or patients with schizophrenia (n=402, 52.7%), bipolar I disorder (n=57, 7.5%), or major depressive disorder (n=35, 4.6%). Overall, 13.6% (104/763) of the participants reported at least 1 SIE, all of which were localized to the wearable patch site. Incidence of ≥1 patch-related SIEs was seen in 18.1% (28/155), 14.2% (55/387), and 9.2% (28/306) of participants who used RP4, DW5, and RW2, respectively. Incidence of SIE-related treatment discontinuation was low, which is reported by 1.9% (3/155), 3.1% (12/387), and 1.3% (4/306) of participants who used RP4, DW5, and RW2, respectively. CONCLUSIONS The incidence rates of SIEs reported as the wearable patch versions evolved from RP4 through RW2 suggest that information derived from reported adverse events may have informed product design and development, which could have improved both tolerability and wearability of successive products. TRIAL REGISTRATION Clinicaltrials.gov NCT02091882, https://clinicaltrials.gov/study/NCT02091882; Clinicaltrials.gov NCT02404532, https://clinicaltrials.gov/study/NCT02404532; Clinicaltrials.gov NCT02722967, https://clinicaltrials.gov/study/NCT02722967; Clinicaltrials.gov NCT02219009, https://clinicaltrials.gov/study/NCT02219009; Clinicaltrials.gov NCT03568500, https://clinicaltrials.gov/study/NCT03568500; Clinicaltrials.gov NCT03892889, https://clinicaltrials.gov/study/NCT03892889.
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Affiliation(s)
- Michael Jan
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | | | - Robin West
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | - Christophe Le Gallo
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
- Genmab US, Inc, Plainsboro, NJ, United States
| | - Jeffrey M Cochran
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
| | | | - Michael Fahmy
- Otsuka Pharmaceutical Development & Commercialization, Inc, Princeton, NJ, United States
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Chang P, Wang C, Chen Y, Wang G, Lu A. Identification of runner fatigue stages based on inertial sensors and deep learning. Front Bioeng Biotechnol 2023; 11:1302911. [PMID: 38047289 PMCID: PMC10691589 DOI: 10.3389/fbioe.2023.1302911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 11/06/2023] [Indexed: 12/05/2023] Open
Abstract
Introduction: Running is one of the most popular sports in the world, but it also increases the risk of injury. The purpose of this study was to establish a modeling approach for IMU-based subdivided action pattern evaluation and to investigate the classification performance of different deep models for predicting running fatigue. Methods: Nineteen healthy male runners were recruited for this study, and the raw time series data were recorded during the pre-fatigue, mid-fatigue, and post-fatigue states during running to construct a running fatigue dataset based on multiple IMUs. In addition to the IMU time series data, each participant's training level was monitored as an indicator of their level of physical fatigue. Results: The dataset was examined using single-layer LSTM (S_LSTM), CNN, dual-layer LSTM (D_LSTM), single-layer LSTM plus attention model (LSTM + Attention), CNN, and LSTM hybrid model (LSTM + CNN) to classify running fatigue and fatigue levels. Discussion: Based on this dataset, this study proposes a deep learning model with constant length interception of the raw IMU data as input. The use of deep learning models can achieve good classification results for runner fatigue recognition. Both CNN and LSTM can effectively complete the classification of fatigue IMU data, the attention mechanism can effectively improve the processing efficiency of LSTM on the raw IMU data, and the hybrid model of CNN and LSTM is superior to the independent model, which can better extract the features of raw IMU data for fatigue classification. This study will provide some reference for many future action pattern studies based on deep learning.
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Affiliation(s)
- Pengfei Chang
- School of Physical Education and Sports Science, Soochow University, Suzhou, China
| | - Cenyi Wang
- School of Physical Education and Sports Science, Soochow University, Suzhou, China
| | - Yiyan Chen
- School of Physical Education and Sports Science, Soochow University, Suzhou, China
- Department of Physical Education, Suzhou Vocational University, Suzhou, China
| | - Guodong Wang
- School of Physical Education and Sports Science, Soochow University, Suzhou, China
| | - Aming Lu
- School of Physical Education and Sports Science, Soochow University, Suzhou, China
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Hilty DM, Stubbe D, McKean AJ, Hoffman PE, Zalpuri I, Myint MT, Joshi SV, Pakyurek M, Li STT. A scoping review of social media in child, adolescents and young adults: research findings in depression, anxiety and other clinical challenges. BJPsych Open 2023; 9:e152. [PMID: 37563766 PMCID: PMC10594088 DOI: 10.1192/bjo.2023.523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 06/08/2023] [Accepted: 06/09/2023] [Indexed: 08/12/2023] Open
Abstract
BACKGROUND Social media and other technologies are reshaping communication and health. AIMS This review addresses the relationship between social media use, behavioural health conditions and psychological well-being for youth aged <25 years. METHOD A scoping review of 11 literature databases from 2000 to 2020 explored research studies in youth in five areas: clinical depression and anxiety, quantitative use, social media mode, engagement and qualitative dimensions and health and well-being. RESULTS Out of 2820 potential literature references, 140 met the inclusion criteria. The foci were clinical depression and anxiety disorders (n = 78), clinical challenges (e.g. suicidal ideation, cyberbullying) (n = 34) and psychological well-being (n = 28). Most studies focused on Facebook, Twitter, Instagram and YouTube. Few studies are longitudinal in design (n = 26), had comparison groups (n = 27), were randomised controlled trials (n = 3) or used structured assessments (n = 4). Few focused on different youth and sociodemographic populations, particularly for low-income, equity-seeking and deserving populations. Studies examined association (n = 120; 85.7%), mediating (n = 16; 11.4%) and causal (n = 4; 2.9%) relationships. Prospective, longitudinal studies of depression and anxiety appear to indicate that shorter use (≤3 h/day) and purposeful engagement is associated with better mood and psychological well-being. Depression may predict social media use and reduce perception of support. Findings provide families, teachers and providers ways to engage youth. CONCLUSIONS Research opportunities include clinical outcomes from functional perspective on a health continuum, diverse youth and sociodemographic populations, methodology, intervention and privacy issues. More longitudinal studies, comparison designs and effectiveness approaches are also needed. Health systems face clinical, training and professional development challenges.
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Affiliation(s)
- Donald M. Hilty
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, California, USA; and Mental Health, Veterans Affairs Northern California Health Care System, California, USA
| | - Dorothy Stubbe
- Child Study Center, Yale School of Medicine, Connecticut, USA
| | | | - Pamela E. Hoffman
- Department of Psychiatry & Behavioral Science, Yale School of Medicine, Connecticut, USA
| | - Isheeta Zalpuri
- Department of Psychiatry & Behavioral Science, Stanford University Medical Center, California, USA
| | - Myo T. Myint
- Department of Psychiatry & Behavioral Science, Tulane University School of Medicine, Louisiana, USA
| | - Shashank V. Joshi
- Department of Psychiatry & Behavioral Science, Stanford University Medical Center, California, USA
| | - Murat Pakyurek
- Division of Child and Adolescent Psychiatry, University of California, Davis School of Medicine, California, USA
| | - Su-Ting T. Li
- Department of Pediatrics, University of California, Davis School of Medicine, California, USA
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Miranda R, Oliveira MD, Baptista FM, Albuquerque I. Telemonitoring in Portugal: where do we stand and which way forward? Health Policy 2023; 131:104761. [PMID: 36905784 DOI: 10.1016/j.healthpol.2023.104761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 02/25/2023] [Accepted: 03/04/2023] [Indexed: 03/07/2023]
Abstract
Following the pandemic, there is growing pressure in Portugal to adopt new practices that promote more efficient, sustainable, and equitable healthcare. Telemonitoring (TM) has been identified as a valuable solution, particularly for chronically ill, long-term or socially isolated patients. Several initiatives have since emerged. Thus, Portuguese stakeholders recognise the need to reflect upon TM's current state and prospects. This study aims to provide a comprehensive analysis of the TM landscape in Portugal. We begin by analysing the underlying conditions for telehealth development. Then, we describe the governmental strategy and priorities towards TM - the National Strategic Plan for Telehealth development and NHS reimbursement opportunities for TM. To understand TM implementation, adoption, and dissemination in Portugal, we analyse 46 reported initiatives and adoption studies focusing on providers' perspectives. Finally, a structured reflection on current challenges and the way forward is provided, according to the seven domains of the Nonadoption, Abandonment, and challenges to the Scale-up, Spread, and Sustainability (NASSS) framework. The adoption of TM by Portuguese institutions has been growing, leveraged by the telehealth governance model and public reimbursement mechanisms, proving particularly relevant during the pandemic. However, monitored patients are still few. Low digital literacy among patients and providers, lack of care integration and resource scarcity represent barriers hampering pilot TM initiatives' scale-up.
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Cerdan de las Heras J, Andersen SL, Matthies S, Sandreva TV, Johannesen CK, Nielsen TL, Fuglebjerg N, Catalan-Matamoros D, Hansen DG, Fischer TK. Hospitalisation at Home of Patients with COVID-19: A Qualitative Study of User Experiences. Int J Environ Res Public Health 2023; 20:1287. [PMID: 36674043 PMCID: PMC9858642 DOI: 10.3390/ijerph20021287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 01/05/2023] [Accepted: 01/06/2023] [Indexed: 06/17/2023]
Abstract
Hospitalisation at Home (HaH) is a new model providing hospital-level care at home as a substitute for traditional care. Biometric monitoring and digital communication are crucial, but little is known about user perspectives. We aim to explore how in-patients with severe COVID-19 infection and clinicians engage with and experience communication and self-monitoring activities following the HaH model. A qualitative study based on semi-structured interviews of patients and clinicians participating in the early development phase of HaH were conducted. We interviewed eight clinicians and six patients. Five themes emerged from clinicians: (1) staff fear and concerns, (2) workflow, (3) virtual closeness, (4) patient relatives, and (5) future HaH models; four themes emerged from patients: (1) transition to home, (2) joint responsibility, (3) acceptability of technologies, and (4) relatives. Despite technical problems, both patients and clinicians were enthusiastic about the conceptual HaH idea. If appropriately introduced, treatment based on self-monitoring and remote communication was perceived acceptable for the patients; however, obtaining vitals at night was an overwhelming challenge. HaH is generally acceptable, perceived patient-centred, influencing routine clinical workflow, role and job satisfaction. Therefore, it calls for educational programs including more perspective than issues related to technical devices.
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Affiliation(s)
- Jose Cerdan de las Heras
- Department of Clinical Research, Copenhagen University Hospital—North Zealand, 3400 Hillerød, Denmark
| | - Signe Lindgård Andersen
- Department of Clinical Research, Copenhagen University Hospital—North Zealand, 3400 Hillerød, Denmark
| | - Sophie Matthies
- Department of Clinical Research, Copenhagen University Hospital—North Zealand, 3400 Hillerød, Denmark
- Department of Respiratory Medicine and Infectious Diseases, Copenhagen University Hospital—North Zealand, 3400 Hillerød, Denmark
| | | | - Caroline Klint Johannesen
- Department of Clinical Research, Copenhagen University Hospital—North Zealand, 3400 Hillerød, Denmark
- Department of Virology and Microbiological Special Diagnostics, Statens Serum Institut, 2300 Copenhagen, Denmark
| | - Thyge Lynghøj Nielsen
- Department of Respiratory Medicine and Infectious Diseases, Copenhagen University Hospital—North Zealand, 3400 Hillerød, Denmark
| | - Natascha Fuglebjerg
- Department of Clinical Research, Copenhagen University Hospital—North Zealand, 3400 Hillerød, Denmark
| | | | - Dorte Gilså Hansen
- Institute of Public Health, Research Unit of General Practice, University of Southern Denmark, 5230 Odense, Denmark
| | - Thea K. Fischer
- Department of Clinical Research, Copenhagen University Hospital—North Zealand, 3400 Hillerød, Denmark
- Department of Public Health, University of Copenhagen, 1353 Copenhagen, Denmark
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Ratitch B, Rodriguez-Chavez IR, Dabral A, Fontanari A, Vega J, Onorati F, Vandendriessche B, Morton S, Damestani Y. Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials. Digit Biomark 2022; 6:83-97. [PMID: 36466953 PMCID: PMC9716191 DOI: 10.1159/000525897] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 05/31/2022] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND The proliferation and increasing maturity of biometric monitoring technologies allow clinical investigators to measure the health status of trial participants in a more holistic manner, especially outside of traditional clinical settings. This includes capturing meaningful aspects of health in daily living and a more granular and objective manner compared to traditional tools in clinical settings. SUMMARY Within multidisciplinary teams, statisticians and data scientists are increasingly involved in clinical trials that incorporate digital clinical measures. They are called upon to provide input into trial planning, generation of evidence on the clinical validity of novel clinical measures, and evaluation of the adequacy of existing evidence. Analysis objectives related to demonstrating clinical validity of novel clinical measures differ from typical objectives related to demonstrating safety and efficacy of therapeutic interventions using established measures which statisticians are most familiar with. KEY MESSAGES This paper discusses key considerations for generating evidence for clinical validity through the lens of the type and intended use of a clinical measure. This paper also briefly discusses the regulatory pathways through which clinical validity evidence may be reviewed and highlights challenges that investigators may encounter while dealing with data from biometric monitoring technologies.
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Affiliation(s)
- Bohdana Ratitch
- Statistics and Data Insights, Bayer, Westmount, Québec, Canada
| | - Isaac R. Rodriguez-Chavez
- Strategy Center for Decentralized Clinical Trials and Digital Medicine, Drug Development Solutions, ICON plc, Blue Bell, Pennsylvania, USA
| | - Abhishek Dabral
- Global Development Operations, Amgen Inc., Thousand Oaks, California, USA
| | | | - Julio Vega
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Francesco Onorati
- Applied Data Science, Current Health, A Best Buy Health Company, Boston, Massachusetts, USA
| | - Benjamin Vandendriessche
- Byteflies, Antwerp, Belgium & Department of Electrical, Computer and Systems Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Stuart Morton
- Emerging Digital Medicines, Eli Lilly & Co., Indianapolis, Indiana, USA
| | - Yasaman Damestani
- Digital Medicine, Karyopharm Therapeutics, Newton, Massachusetts, USA
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Saleem JJ, Wilck NR, Murphy JJ, Herout J. Veteran and Staff Experience from a Pilot Program of Health Care System-Distributed Wearable Devices and Data Sharing. Appl Clin Inform 2022; 13:532-540. [PMID: 35613912 DOI: 10.1055/s-0042-1748857] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
Abstract
OBJECTIVE The growing trend to use wearable devices to track activity and health data has the potential to positively impact the patient experience with their health care at home and with their care team. As part of a pilot program, the U.S. Department of Veterans Affairs (VA) distributed Fitbits to Veterans through four VA medical centers. Our objective was to assess the program from both Veterans' and clinicians' viewpoints. Specifically, we aimed to understand barriers to Fitbit setup and use for Veterans, including syncing devices with a VA mobile application (app) to share data, and assess the perceived value of the device functions and ability to share information from the Fitbit with their care team. In addition, we explored the clinicians' perspective, including how they expected to use the patient-generated health data (PGHD). METHODS We performed semi-structured interviews with 26 Veterans and 16 VA clinicians to assess the program. Responses to each question were summarized in order of frequency of occurrence across participants and audited by an independent analyst for accuracy. RESULTS Our findings reveal that despite setup challenges, there is support for the use of Fitbits to engage Veterans and help manage their health. Clinicians believed there were benefits for having Veterans use the Fitbits and expected to use the PGHD in a variety of ways as part of the Veterans' care plans, including monitoring progress toward health behavior goals. Veterans were overwhelmingly enthusiastic about using the Fitbits; this enthusiasm seems to extend beyond the 3 month "novelty period." CONCLUSION The pilot program for distributing Fitbits to Veterans appears to be successful from both Veterans' and clinicians' perspectives and suggests that expanded use of wearable devices should be considered. Future studies will need to carefully consider how to incorporate the PGHD into the electronic health record and clinical workflow.
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Affiliation(s)
- Jason J Saleem
- Department of Industrial Engineering, J.B. Speed School of Engineering, University of Louisville, Louisville, Kentucky, United States.,Center for Human Systems Engineering, University of Louisville, Louisville, Kentucky, United States
| | - Nancy R Wilck
- Department of Veterans Affairs (VA), Office of Connected Care, Patient Care Services, Veterans Health Administration, Washington, District of Columbia, United States
| | - John J Murphy
- Department of Veterans Affairs (VA), Office of Connected Care, Patient Care Services, Veterans Health Administration, Washington, District of Columbia, United States
| | - Jennifer Herout
- Department of Veterans Affairs (VA), Office of Connected Care, Patient Care Services, Veterans Health Administration, Washington, District of Columbia, United States
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Andrews JA, Craven MP, Lang AR, Guo B, Morriss R, Hollis C. Making remote measurement technology work in multiple sclerosis, epilepsy and depression: survey of healthcare professionals. BMC Med Inform Decis Mak 2022; 22:125. [PMID: 35525933 PMCID: PMC9077644 DOI: 10.1186/s12911-022-01856-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 04/15/2022] [Indexed: 11/21/2022] Open
Abstract
Background Epilepsy, multiple sclerosis (MS) and depression are long term, central nervous system disorders which have a significant impact on everyday life. Evaluating symptoms of these conditions is problematic and typically involves repeated visits to a clinic. Remote measurement technology (RMT), consisting of smartphone apps and wearables, may offer a way to improve upon existing methods of managing these conditions. The present study aimed to establish the practical requirements that would enable clinical integration of data from patients’ RMT, according to healthcare professionals. Methods This paper reports findings from an online survey of 1006 healthcare professionals currently working in the care of people with epilepsy, MS or depression. The survey included questions on types of data considered useful, how often data should be collected, the value of RMT data, preferred methods of accessing the data, benefits and challenges to RMT implementation, impact of RMT data on clinical practice, and requirement for technical support. The survey was presented on the JISC online surveys platform. Results Among this sample of 1006 healthcare professionals, respondents were positive about the benefits of RMT, with 73.2% indicating their service would be likely or highly likely to benefit from the implementation of RMT in patient care plans. The data from patients’ RMT devices should be made available to all nursing and medical team members and could be reviewed between consultations where flagged by the system. However, results suggest it is also likely that RMT data would be reviewed in preparation for and during a consultation with a patient. Time to review information is likely to be one of the greatest barriers to successful implementation of RMT in clinical practice. Conclusions While further work would be required to quantify the benefits of RMT in clinical practice, the findings from this survey suggest that a wide array of clinical team members treating epilepsy, MS and depression would find benefit from RMT data in the care of their patients. Findings presented could inform the implementation of RMT and other digital interventions in the clinical management of a range of neurological and mental health conditions. Supplementary Information The online version contains supplementary material available at 10.1186/s12911-022-01856-z.
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Affiliation(s)
- J A Andrews
- NIHR MindTech MedTech Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, UK. .,Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK.
| | - M P Craven
- NIHR MindTech MedTech Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, UK.,Human Factors Research Group, Faculty of Engineering, University of Nottingham, Nottingham, UK.,NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - A R Lang
- Human Factors Research Group, Faculty of Engineering, University of Nottingham, Nottingham, UK
| | - B Guo
- ARC-EM, School of Medicine, University of Nottingham, Nottingham, UK
| | - R Morriss
- NIHR MindTech MedTech Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, UK.,Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK.,NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK.,ARC-EM, School of Medicine, University of Nottingham, Nottingham, UK
| | - C Hollis
- NIHR MindTech MedTech Co-operative, Institute of Mental Health, University of Nottingham, Nottingham, UK.,Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK.,NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
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11
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Bilden R, Torous J. Global Collaboration Around Digital Mental Health: The LAMP Consortium. J Technol Behav Sci 2022; 7:227-33. [PMID: 35071742 DOI: 10.1007/s41347-022-00240-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 12/02/2021] [Accepted: 01/03/2022] [Indexed: 11/29/2022]
Abstract
Despite the great potential, there has been a lack of progress in the development of sharable and scalable tools for digital mental health due to difficulty in reproducibility and clinical application. The LAMP Platform was developed to address this gap by creating a single platform that works for a variety of clinical and research use cases. The study aims to understand how a consortium of clinical and research sites can help onboard, execute, and expand digital health research, software, and use cases. The Division of Digital Psychiatry implemented a formal consortium with goal of expanding the reach of mindLAMP as a digital mental health platform, enabling diverse studies and expanded use cases, and supportint growth of mindLAMP and consortium members’ research. The LAMP Consortium has brought together 54 sites from across the world, encouraging collaboration and idea sharing. These sites’ locations range from the USA to the Czech Republic to Australia, and apply the many features of LAMP to research, clinical, research and clinical, and industry use. The most popular features were surveys, sharing/viewing data, and GPS passive data collection. A user support network is necessary to encourage research and clinical use of the LAMP Platform. Resources like documentation, an online forum, and newsletters are essential to promote cooperation between many types of sites that is essential to advancing the field of digital mental health.
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12
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Mucic D, Shore JH, Hilty DM, Krysta K, Krzystanek M. Lessons Learned or Forgotten? Impacts of COVID-19 on the Future Direction of Global (e-)Mental Health Care. Curr Psychiatry Rep 2021; 23:86. [PMID: 34842979 PMCID: PMC8628486 DOI: 10.1007/s11920-021-01300-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/01/2021] [Indexed: 11/28/2022]
Abstract
PURPOSE OF REVIEW The COVID-19 pandemic has impacted lives globally, posing unique challenges to mental health services exposing vulnerability and limitations within these systems. During the course of the pandemic, telecommunications technologies (e-mental health care) have served a critical role in psychiatric care. It is important to understand current lessons learned in e-mental health care and implications for global mental health systems for both emerging from the pandemic and after the pandemic has ended. RECENT FINDINGS There are significant regulatory, policy, and evaluation challenges for global e-mental health impacting patients, clinicians, health systems, and decision-makers. These include complex regulatory issues, difficulties of providing care across boundaries, and keeping pace with the implementation of new technologies in behavioral health. The collaborative development of global standards along with policies, appropriate regulations, and developing new models of research and development opens the possibility of improved access to care across national boundaries.
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Affiliation(s)
- D Mucic
- Little Prince Treatment Centre, Havneholmen 82, 5th, 1561, Copenhagen V, Denmark.
| | - J H Shore
- Office of Telehealth and Technology Implementation for Behavioral Health Practice and Science (TIPS), Department of Psychiatry, Aurora, USA
- Department of Psychiatry and Family Medicine, School of Medicine And Centers for American Indian and Alaska Native Health, School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - D M Hilty
- VA Northern California Health Care, System & UC Davis School of Medicine, 2230 Stockton Boulevard, Sacramento, CA, 95817, USA
| | - K Krysta
- Department of Psychiatry and Psychotherapy, Faculty of Medical Sciences in Katowice, Clinic of Psychiatric Rehabilitation, Medical University of Silesia, Ziołowa 45/47, 40-635, Katowice, Poland
| | - M Krzystanek
- Department of Psychiatry and Psychotherapy, Faculty of Medical Sciences in Katowice, Clinic of Psychiatric Rehabilitation, Medical University of Silesia, Ziołowa 45/47, 40-635, Katowice, Poland
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13
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Blom JMC, Colliva C, Benatti C, Tascedda F, Pani L. Digital Phenotyping and Dynamic Monitoring of Adolescents Treated for Cancer to Guide Intervention: Embracing a New Era. Front Oncol 2021; 11:673581. [PMID: 34262863 PMCID: PMC8273734 DOI: 10.3389/fonc.2021.673581] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 06/07/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Johanna M. C. Blom
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Chiara Colliva
- Azienda Unità Sanitaria Locale di Modena, Distretto di Carpi, Carpi, Italy
| | - Cristina Benatti
- Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Fabio Tascedda
- Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Luca Pani
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Department of Psychiatry and Behavioral Sciences, University of Miami, Miami, FL, United States
- VeraSci., Durham, NC, United States
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14
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Polsky M, Moraveji N. Early Identification of COVID-19 Infection Using Remote Cardiorespiratory Monitoring: Three Case Reports. Interact J Med Res 2021; 10:e27823. [PMID: 34086588 PMCID: PMC8211097 DOI: 10.2196/27823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 05/17/2021] [Accepted: 05/31/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND The adoption of remote patient monitoring (RPM) in routine medical care requires increased understanding of the physiologic changes accompanying disease development and the proactive interventions that will improve outcomes. OBJECTIVE The aim of this study is to present three case reports that highlight the capability of RPM to enable early identification of viral infection with COVID-19 in patients with chronic respiratory disease. METHODS Patients at a large pulmonary practice who were enrolled in a respiratory RPM program and who had contracted COVID-19 were identified. The RPM system (Spire Health) contains three components: (1) Health Tags (Spire Health), undergarment waistband-adhered physiologic monitors that include a respiratory rate sensor; (2) an app on a smartphone; and (3) a web dashboard for use by respiratory therapists. The physiologic data of 9 patients with COVID out of 1000 patients who were enrolled for monitoring were retrospectively reviewed, and 3 instances were identified where the RPM system had notified clinicians of physiologic deviation due to the viral infection. RESULTS Physiologic deviations from respective patient baselines occurred during infection onset and, although the infection manifested differently in each case, were identified by the RPM system. In the first case, the patient was symptomatic; in the second case, the patient was presymptomatic; and in the third case, the patient varied from asymptomatic to mildly symptomatic. CONCLUSIONS RPM systems intended for long-term use and that use patient-specific baselines can highlight physiologic changes early in the course of acute disease, such as COVID-19 infection. These cases demonstrate opportunities for earlier diagnosis, treatment, and isolation. This study supports the need for further research into how RPM can be effectively integrated into clinical practice.
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Affiliation(s)
- Michael Polsky
- Pulmonary Associates of Richmond, North Chesterfield, VA, United States
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Al-marsy A, Chaudhary P, Rodger JA. A Model for Examining Challenges and Opportunities in Use of Cloud Computing for Health Information Systems. ASI 2021; 4:15. [DOI: 10.3390/asi4010015] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Health Information Systems (HIS) are becoming crucial for health providers, not only for keeping Electronic Health Records (EHR) but also because of the features they provide that can be lifesaving, thanks to the advances in Information Technology (IT). These advancements have led to increasing demands for additional features to these systems to improve their intelligence, reliability, and availability. All these features may be provisioned through the use of cloud computing in HIS. This study arrives at three dimensions pertinent to adoption of cloud computing in HIS through extensive interviews with experts, professional expertise and knowledge of one of the authors working in this area, and review of academic and practitioner literature. These dimensions are financial performance and cost; IT operational excellence and DevOps; and security, governance, and compliance. Challenges and drivers in each of these dimensions are detailed and operationalized to arrive at a model for HIS adoption. This proposed model detailed in this study can be employed by executive management of health organizations, especially senior clinical management positions like Chief Technology Officers (CTOs), Chief Information Officers (CIOs), and IT managers to make an informed decision on adoption of cloud computing for HIS. Use of cloud computing to support operational and financial excellence of healthcare organizations has already made some headway in the industry, and its use in HIS would be a natural next step. However, due to the mission′s critical nature and sensitivity of information stored in HIS, the move may need to be evaluated in a holistic fashion that can be aided by the proposed dimensions and the model. The study also identifies some issues and directions for future research for cloud computing adoption in the context of HIS.
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