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Claggett J, Petter S, Joshi A, Ponzio T, Kirkendall E. An Infrastructure Framework for Remote Patient Monitoring Interventions and Research. J Med Internet Res 2024; 26:e51234. [PMID: 38815263 PMCID: PMC11176884 DOI: 10.2196/51234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 10/12/2023] [Accepted: 04/09/2024] [Indexed: 06/01/2024] Open
Abstract
Remote patient monitoring (RPM) enables clinicians to maintain and adjust their patients' plan of care by using remotely gathered data, such as vital signs, to proactively make medical decisions about a patient's care. RPM interventions have been touted as a means to improve patient care and well-being while reducing costs and resource needs within the health care ecosystem. However, multiple interworking components must be successfully implemented for an RPM intervention to yield the desired outcomes, and the design and key driver of each component can vary depending on the medical context. This viewpoint and perspective paper presents a 4-component RPM infrastructure framework based on a synthesis of existing literature and practice related to RPM. Specifically, these components are identified and considered: (1) data collection, (2) data transmission and storage, (3) data analysis, and (4) information presentation. Interaction points to consider between components include transmission, interoperability, accessibility, workflow integration, and transparency. Within each of the 4 components, questions affecting research and practice emerge that can affect the outcomes of RPM interventions. This framework provides a holistic perspective of the technologies involved in RPM interventions and how these core elements interact to provide an appropriate infrastructure for deploying RPM in health systems. Further, it provides a common vocabulary to compare and contrast RPM solutions across health contexts and may stimulate new research and intervention opportunities.
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Affiliation(s)
- Jennifer Claggett
- School of Business, Wake Forest University, Winston-Salem, NC, United States
- Center for Healthcare Innovation, School of Medicine, Wake Forest University, Winston-Salem, NC, United States
| | - Stacie Petter
- School of Business, Wake Forest University, Winston-Salem, NC, United States
| | - Amol Joshi
- School of Business, Wake Forest University, Winston-Salem, NC, United States
- Center for Healthcare Innovation, School of Medicine, Wake Forest University, Winston-Salem, NC, United States
| | - Todd Ponzio
- Health Science Center, University of Tennessee, Memphis, TN, United States
| | - Eric Kirkendall
- Center for Healthcare Innovation, School of Medicine, Wake Forest University, Winston-Salem, NC, United States
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Rodríguez I, Cajamarca G, Herskovic V. When does self-report of pain occur?: A study of older adults. PeerJ 2022; 10:e13716. [PMID: 35873914 PMCID: PMC9306549 DOI: 10.7717/peerj.13716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 06/21/2022] [Indexed: 01/17/2023] Open
Abstract
Technologies for self-care can drive participatory health and promote independence of older adults. One self-care activity is regularly measuring and registering personal health indicators (self-reporting). Older adults may benefit from this practice, as they are more likely to have chronic health issues and have specific self-monitoring needs. However, self-reporting technologies are usually not designed specifically for them. Pain is usually measured using patient reports compiled during medical appointments, although this process may be affected by memory bias and under reporting of fluctuating pain. To address these issues, we introduced a simple tangible interface to self-report pain levels and conducted a three-hour evaluation with 24 older adults. The goal of this study was to identify whether specific activities, activity levels or pain levels trigger older adults to self-report their pain level, besides to understand how older adults would use such a device. Within the limited time frame of the experiment, the majority of our participants chose to report pain when they felt it most, not reporting lower levels of pain. No evidence was found to suggest a relationship between the reporting of pain and the activity (or activity level). Several design insights intended to improve the design of technologies are provided.
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Affiliation(s)
- Iyubanit Rodríguez
- Department of Engineering, Universidad de Costa Rica, Alajuela, Alajuela, Costa Rica
| | - Gabriela Cajamarca
- Department of Computer Science, Pontificia Universidad Católica de Chile, Santiago, Región Metropolitana, Chile
| | - Valeria Herskovic
- Department of Computer Science, Pontificia Universidad Católica de Chile, Santiago, Región Metropolitana, Chile
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Corman BHP, Rajupet S, Ye F, Schoenfeld ER. The Role of Unobtrusive Home-Based Continuous Sensing in the Management of Postacute Sequelae of SARS CoV-2. J Med Internet Res 2022; 24:e32713. [PMID: 34932496 PMCID: PMC8989385 DOI: 10.2196/32713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 11/15/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
Amid the COVID-19 pandemic, it has been reported that greater than 35% of patients with confirmed or suspected COVID-19 develop postacute sequelae of SARS CoV-2 (PASC). PASC is still a disease for which preliminary medical data are being collected-mostly measurements collected during hospital or clinical visits-and pathophysiological understanding is yet in its infancy. The disease is notable for its prevalence and its variable symptom presentation, and as such, management plans could be more holistically made if health care providers had access to unobtrusive home-based wearable and contactless continuous physiologic and physical sensor data. Such between-hospital or between-clinic data can quantitatively elucidate a majority of the temporal evolution of PASC symptoms. Although not universally of comparable accuracy to gold standard medical devices, home-deployed sensors offer great insights into the development and progression of PASC. Suitable sensors include those providing vital signs and activity measurements that correlate directly or by proxy to documented PASC symptoms. Such continuous, home-based data can give care providers contextualized information from which symptom exacerbation or relieving factors may be classified. Such data can also improve the collective academic understanding of PASC by providing temporally and activity-associated symptom cataloging. In this viewpoint, we make a case for the utilization of home-based continuous sensing that can serve as a foundation from which medical professionals and engineers may develop and pursue long-term mitigation strategies for PASC.
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Affiliation(s)
- Benjamin Harris Peterson Corman
- Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, United States
- Program in Public Health, Stony Brook University, Stony Brook, NY, United States
| | - Sritha Rajupet
- Department of Family, Population & Preventive Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, United States
- Department of Biomedical Informatics, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, United States
| | - Fan Ye
- Department of Electrical and Computer Engineering, College of Engineering and Applied Science, Stony Brook University, Stony Brook, NY, United States
| | - Elinor Randi Schoenfeld
- Department of Family, Population & Preventive Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, United States
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Tauben DJ, Langford DJ, Sturgeon JA, Rundell SD, Towle C, Bockman C, Nicholas M. Optimizing telehealth pain care after COVID-19. Pain 2020; 161:2437-2445. [PMID: 32826752 PMCID: PMC7566302 DOI: 10.1097/j.pain.0000000000002048] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 08/03/2020] [Accepted: 08/06/2020] [Indexed: 12/23/2022]
Affiliation(s)
- David J. Tauben
- Departments of Anesthesiology & Pain Medicine
- Medicine, University of Washington, Seattle, WA, United States
| | | | | | - Sean D. Rundell
- Departments of Rehabilitation Medicine
- Health Services, University of Washington, Seattle, WA, United States
| | - Cara Towle
- Department of Psychiatry & Behavioral Sciences, University of Washington, Seattle, WA, United States
| | - Christina Bockman
- Department of Pharmacy, University of Washington, Harborview Medical Center, Seattle, WA, United States
| | - Michael Nicholas
- Pain Management Research Institute, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
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LeBaron V, Bennett R, Alam R, Blackhall L, Gordon K, Hayes J, Homdee N, Jones R, Martinez Y, Ogunjirin E, Thomas T, Lach J. Understanding the Experience of Cancer Pain From the Perspective of Patients and Family Caregivers to Inform Design of an In-Home Smart Health System: Multimethod Approach. JMIR Form Res 2020; 4:e20836. [PMID: 32712581 PMCID: PMC7481872 DOI: 10.2196/20836] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 07/11/2020] [Accepted: 07/25/2020] [Indexed: 01/20/2023] Open
Abstract
Background Inadequately managed pain is a serious problem for patients with cancer and those who care for them. Smart health systems can help with remote symptom monitoring and management, but they must be designed with meaningful end-user input. Objective This study aims to understand the experience of managing cancer pain at home from the perspective of both patients and family caregivers to inform design of the Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C) smart health system. Methods This was a descriptive pilot study using a multimethod approach. Dyads of patients with cancer and difficult pain and their primary family caregivers were recruited from an outpatient oncology clinic. The participant interviews consisted of (1) open-ended questions to explore the overall experience of cancer pain at home, (2) ranking of variables on a Likert-type scale (0, no impact; 5, most impact) that may influence cancer pain at home, and (3) feedback regarding BESI-C system prototypes. Qualitative data were analyzed using a descriptive approach to identity patterns and key themes. Quantitative data were analyzed using SPSS; basic descriptive statistics and independent sample t tests were run. Results Our sample (n=22; 10 patient-caregiver dyads and 2 patients) uniformly described the experience of managing cancer pain at home as stressful and difficult. Key themes included (1) unpredictability of pain episodes; (2) impact of pain on daily life, especially the negative impact on sleep, activity, and social interactions; and (3) concerns regarding medications. Overall, taking pain medication was rated as the category with the highest impact on a patient’s pain (=4.79), followed by the categories of wellness (=3.60; sleep quality and quantity, physical activity, mood and oral intake) and interaction (=2.69; busyness of home, social or interpersonal interactions, physical closeness or proximity to others, and emotional closeness and connection to others). The category related to environmental factors (temperature, humidity, noise, and light) was rated with the lowest overall impact (=2.51). Patients and family caregivers expressed receptivity to the concept of BESI-C and reported a preference for using a wearable sensor (smart watch) to capture data related to the abrupt onset of difficult cancer pain. Conclusions Smart health systems to support cancer pain management should (1) account for the experience of both the patient and the caregiver, (2) prioritize passive monitoring of physiological and environmental variables to reduce burden, and (3) include functionality that can monitor and track medication intake and efficacy; wellness variables, such as sleep quality and quantity, physical activity, mood, and oral intake; and levels of social interaction and engagement. Systems must consider privacy and data sharing concerns and incorporate feasible strategies to capture and characterize rapid-onset symptoms.
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Affiliation(s)
- Virginia LeBaron
- University of Virginia School of Nursing, Charlottesville, VA, United States
| | - Rachel Bennett
- University of Virginia School of Nursing, Charlottesville, VA, United States
| | - Ridwan Alam
- University of Virginia School of Engineering & Applied Science, Charlottesville, VA, United States
| | - Leslie Blackhall
- University of Virginia School of Medicine, Charlottesville, VA, United States
| | - Kate Gordon
- Virginia Commonwealth University Health, Richmond, VA, United States
| | - James Hayes
- University of Virginia School of Engineering & Applied Science, Charlottesville, VA, United States
| | - Nutta Homdee
- University of Virginia School of Engineering & Applied Science, Charlottesville, VA, United States
| | - Randy Jones
- University of Virginia School of Nursing, Charlottesville, VA, United States
| | - Yudel Martinez
- University of Virginia School of Engineering & Applied Science, Charlottesville, VA, United States
| | - Emmanuel Ogunjirin
- University of Virginia School of Engineering & Applied Science, Charlottesville, VA, United States
| | - Tanya Thomas
- University of Virginia School of Nursing, Charlottesville, VA, United States
| | - John Lach
- The George Washington University School of Engineering & Applied Science, Washington, DC, United States
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Adams AT, Adams P, Murnane EL, Elfenbein M, Sannon S, Gay G, Choudhury T, Chang PF. Keppi: A Tangible User Interface for Self-Reporting Pain. ACM TRANSACTIONS ON APPLIED PERCEPTION 2018; 2018:502. [PMID: 30542253 PMCID: PMC6287633 DOI: 10.1145/3173574.3174076] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Motivated by the need to support those self-managing chronic pain, we report on the development and evaluation of a novel pressure-based tangible user interface (TUI) for the self-report of scalar values representing pain intensity. Our TUI consists of a conductive foam-based, force-sensitive resistor (FSR) covered in a soft rubber with embedded signal conditioning, an ARM Cortex-M0 microprocessor, and Bluetooth Low Energy (BLE). In-lab usability and feasibility studies with 28 participants found that individuals were able to use the device to make reliable reports with four degrees of freedom as well map squeeze pressure to pain level and visual feedback. Building on insights from these studies, we further redesigned the FSR into a wearable device with multiple form factors, including a necklace, bracelet, and keychain. A usability study with an additional 7 participants from our target population, elderly individuals with chronic pain, found high receptivity to the wearable design, which offered a number of participant-valued characteristics (e.g., discreetness) along with other design implications that serve to inform the continued refinement of tangible devices that support pain self-assessment.
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