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Connolly SL, Sherman SE, Dardashti N, Duran E, Bosworth HB, Charness ME, Newton TJ, Reddy A, Wong ES, Zullig LL, Gutierrez J. Defining and Improving Outcomes Measurement for Virtual Care: Report from the VHA State-of-the-Art Conference on Virtual Care. J Gen Intern Med 2024; 39:29-35. [PMID: 38252238 PMCID: PMC10937867 DOI: 10.1007/s11606-023-08464-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 10/06/2023] [Indexed: 01/23/2024]
Abstract
Virtual care, including synchronous and asynchronous telehealth, remote patient monitoring, and the collection and interpretation of patient-generated health data (PGHD), has the potential to transform healthcare delivery and increase access to care. The Veterans Health Administration (VHA) Office of Health Services Research and Development (HSR&D) convened a State-of-the-Art (SOTA) Conference on Virtual Care to identify future virtual care research priorities. Participants were divided into three workgroups focused on virtual care access, engagement, and outcomes. In this article, we report the findings of the Outcomes Workgroup. The group identified virtual care outcome areas with sufficient evidence, areas in need of additional research, and areas that are particularly well-suited to be studied within VHA. Following a rigorous process of literature review and consensus, the group focused on four questions: (1) What outcomes of virtual care should we be measuring and how should we measure them?; (2) how do we choose the "right" care modality for the "right" patient?; (3) what are potential consequences of virtual care on patient safety?; and (4) how can PGHD be used to benefit provider decision-making and patient self-management?. The current article outlines key conclusions that emerged following discussion of these questions, including recommendations for future research.
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Affiliation(s)
- Samantha L Connolly
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Scott E Sherman
- Virtual Care Consortium of Research (VC CORE), VA New York Harbor Healthcare System, New York, NY, USA
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Navid Dardashti
- Virtual Care Consortium of Research (VC CORE), VA New York Harbor Healthcare System, New York, NY, USA
| | - Elizabeth Duran
- Virtual Care Consortium of Research (VC CORE), VA New York Harbor Healthcare System, New York, NY, USA
| | - Hayden B Bosworth
- Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT) Durham Veterans Affairs Medical Center, Durham, NC, USA
- Department of Population Health Sciences, Duke University Medical Center, Durham, NC, USA
| | - Michael E Charness
- Chief of Staff of the VA Boston Healthcare System, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Terry J Newton
- Director of Clinical Analytics, VA Office of Connected Care, Washington, DC, USA
| | - Ashok Reddy
- General Medicine Service, VA Puget Sound Health Care System, Seattle, WA, USA
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Edwin S Wong
- Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, USA
| | - Leah L Zullig
- Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT) Durham Veterans Affairs Medical Center, Durham, NC, USA
- Department of Population Health Sciences, Duke University Medical Center, Durham, NC, USA
| | - Jeydith Gutierrez
- Center for Access and Delivery Research, Iowa City VA Healthcare System, Iowa City, IA, USA
- Department of Internal Medicine, University of Iowa, Iowa City, IA, USA
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Liu P, Li X, Zhang XM. Healthcare professionals' and patients' assessments of listed mobile health apps in China: a qualitative study. Front Public Health 2023; 11:1220160. [PMID: 37780445 PMCID: PMC10538635 DOI: 10.3389/fpubh.2023.1220160] [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: 05/10/2023] [Accepted: 08/30/2023] [Indexed: 10/03/2023] Open
Abstract
Background In recent years, mobile health (mHealth) has gradually developed in China, and intelligent medicine has become an important research topic. However, there are still significant problems in mHealth applications (apps). Although healthcare professionals and patients are the main users, few studies have focused on their perceptions of the quality of mHealth apps. Objective This study aimed to (1) understand the respective perceptions of healthcare professionals and patients regarding mHealth apps, (2) assess what barriers exist that influence the user experience, and (3) explore how to improve the quality of mHealth apps and the development of the mHealth market in China. The study aims to promote the standardization of mHealth apps and provide effective information for the improvement and development of mHealth apps in the future. Methods Semistructured interviews with 9 patients and 14 healthcare professionals were conducted from January 2022 to April 2022 in the Affiliated Hospital of Xuzhou Medical University. The participants used mHealth apps for more than 3 months, including the "Good Mood" and "Peace and Safe Doctors" apps and apps developed by the hospital that were popular in China. Interview transcripts were analysed using thematic analysis. Results The following five themes were extracted: different concerns, hidden medical dangers, distance and insecurity, barriers for older people, and having positive perceptions of mHealth apps. Healthcare professionals prioritized simplicity in regard to mHealth apps, whereas patients rated effectiveness as the most crucial factor. The study also revealed several problems with mHealth apps, including insufficient information about physician qualifications, inaccurate medical content, nonstandard treatment processes, and unclear accountability, which led to a sense of distance and insecurity among participants. Older individuals faced additional obstacles when using mHealth apps. Despite these issues, the participants remained optimistic about the future of mHealth app development. Conclusion The utilization, advantages, and obstacles of mHealth applications for healthcare professionals and patients were explored through semistructured interviews. Despite the promising prospects for mHealth apps in China, numerous issues still need to be addressed. Enhancing the safety monitoring system and developing user-friendly mHealth apps for older adult patients are essential steps to bridge the gap between healthcare providers and patients.
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Affiliation(s)
- PeiYu Liu
- Department of Anesthesia and Operation Room, Nanjing Drum Tower Hospital, Nanjing, China
| | - XueYun Li
- Department of Anesthesia and Operation Room, Nanjing Drum Tower Hospital, Nanjing, China
| | - Xiao Man Zhang
- Department of Nursing, Xuzhou Medical University, Xuzhou, China
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Khedraki R, Srivastava AV, Bhavnani SP. Framework for Digital Health Phenotypes in Heart Failure. Heart Fail Clin 2022; 18:223-244. [DOI: 10.1016/j.hfc.2021.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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Hospodková P, Berežná J, Barták M, Rogalewicz V, Severová L, Svoboda R. Change Management and Digital Innovations in Hospitals of Five European Countries. Healthcare (Basel) 2021; 9:1508. [PMID: 34828554 PMCID: PMC8625074 DOI: 10.3390/healthcare9111508] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Revised: 10/26/2021] [Accepted: 11/03/2021] [Indexed: 12/13/2022] Open
Abstract
The objective of the paper is to evaluate the quality of systemic change management (CHM) and readiness for change in five Central European countries. The secondary goal is to identify trends and upcoming changes in the field of digital innovations in healthcare. The results show that all compared countries (regardless of their historical context) deal with similar CHM challenges with a rather similar degree of success. A questionnaire distributed to hospitals clearly showed that there is still considerable room for improvement in terms of the use of specific CHM tools. A review focused on digital innovations based on the PRISMA statement showed that there are five main directions, namely, data collection and integration, telemedicine, artificial intelligence, electronic medical records, and M-Health. In the hospital environment, there are considerable reservations in applying change management principles, as well as the absence of a systemic approach. The main factors that must be monitored for a successful and sustainable CHM include a clearly defined and widely communicated vision, early engagement of all stakeholders, precisely set rules, adaptation to the local context and culture, provision of a technical base, and a step-by-step implementation with strong feedback.
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Affiliation(s)
- Petra Hospodková
- Department of Economic Theories, Faculty of Economics and Management, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague, Czech Republic; (P.H.); (L.S.)
- Department of Biomedical Technology, Czech Technical University in Prague, 272 01 Kladno, Czech Republic; (J.B.); (V.R.)
| | - Jana Berežná
- Department of Biomedical Technology, Czech Technical University in Prague, 272 01 Kladno, Czech Republic; (J.B.); (V.R.)
| | - Miroslav Barták
- Department of Master Study Programs, Faculty of Health Studies, J. E. Purkyne University in Ústí nad Labem, 400 96 Ústí nad Labem, Czech Republic;
| | - Vladimír Rogalewicz
- Department of Biomedical Technology, Czech Technical University in Prague, 272 01 Kladno, Czech Republic; (J.B.); (V.R.)
| | - Lucie Severová
- Department of Economic Theories, Faculty of Economics and Management, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague, Czech Republic; (P.H.); (L.S.)
| | - Roman Svoboda
- Department of Economic Theories, Faculty of Economics and Management, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague, Czech Republic; (P.H.); (L.S.)
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Bhavnani SP. Digital Health: Opportunities and Challenges to Develop the Next-Generation Technology-Enabled Models of Cardiovascular Care. Methodist Debakey Cardiovasc J 2021; 16:296-303. [PMID: 33500758 DOI: 10.14797/mdcj-16-4-296] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The wide gap between the development of new healthcare technologies and their integration into clinical practice argues for a deeper understanding of how effective quality improvement can be designed to meet the needs of patients and their clinical teams. The COVID-19 pandemic has forced us to address this gap and create long-term strategies to bridge it. On the one hand, it has enabled the rapid implementation of telehealth. On the other hand, it has raised important questions about our preparedness to adopt and employ new digital tools as part of a new process of care. While healthcare organizations are seeking to improve the quality of care by integrating innovations in digital health, they must also address key issues such as patient experience, develop clinical decision support systems that analyze digital health data trends, and create efficient clinical workflows. Given the breadth of such requirements, embracing new technologies as a core competency of a modern healthcare system introduces a host of questions, such as "How best do patients participate in digital health programs that promote behavioral changes and mitigate risk?" and "What type of data analytics are required that enable a deeper understanding of disease phenotypes and corresponding treatment decisions?" This review presents the challenges in implementing digital health technology and discusses how patient-centered digital health programs are designed within real-world models of remote monitoring. It also provides a framework for developing new devices and wearables for the next generation of data-driven, technology-enabled cardiovascular care.
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Krishnaswami A, Beavers C, Dorsch MP, Dodson JA, Masterson Creber R, Kitsiou S, Goyal P, Maurer MS, Wenger NK, Croy DS, Alexander KP, Batsis JA, Turakhia MP, Forman DE, Bernacki GM, Kirkpatrick JN, Orr NM, Peterson ED, Rich MW, Freeman AM, Bhavnani SP. Gerotechnology for Older Adults With Cardiovascular Diseases: JACC State-of-the-Art Review. J Am Coll Cardiol 2020; 76:2650-2670. [PMID: 33243384 PMCID: PMC10436190 DOI: 10.1016/j.jacc.2020.09.606] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 08/18/2020] [Accepted: 09/21/2020] [Indexed: 12/19/2022]
Abstract
The growing population of older adults (age ≥65 years) is expected to lead to higher rates of cardiovascular disease. The expansion of digital health (encompassing telehealth, telemedicine, mobile health, and remote patient monitoring), Internet access, and cellular technologies provides an opportunity to enhance patient care and improve health outcomes-opportunities that are particularly relevant during the current coronavirus disease-2019 pandemic. Insufficient dexterity, visual impairment, and cognitive dysfunction, found commonly in older adults should be taken into consideration in the development and utilization of existing technologies. If not implemented strategically and appropriately, these can lead to inequities propagating digital divides among older adults, across disease severities and socioeconomic distributions. A systematic approach, therefore, is needed to study and implement digital health strategies in older adults. This review will focus on current knowledge of the benefits, barriers, and use of digital health in older adults for cardiovascular disease management.
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Affiliation(s)
- Ashok Krishnaswami
- Division of Cardiology, Kaiser Permanente Medical Center, San Jose, California.
| | - Craig Beavers
- Division of Pharmacy, University of Kentucky, Lexington, Kentucky
| | - Michael P Dorsch
- College of Pharmacy, University of Michigan, Ann Arbor, Michigan
| | - John A Dodson
- NYU Langone Health, NYU Grossman School of Medicine, New York, New York
| | - Ruth Masterson Creber
- Weill Cornell Medicine, Department of Population Health Sciences, Division of Health Informatics, New York, New York
| | - Spyros Kitsiou
- Department of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, Illinois
| | - Parag Goyal
- Department of Medicine, Weill Cornell Medicine, New York, New York
| | - Mathew S Maurer
- Division of Cardiology, Columbia University Medical Center, New York, New York
| | - Nanette K Wenger
- Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia
| | | | - Karen P Alexander
- Division of Cardiology, Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina
| | - John A Batsis
- Department of Medicine, Geisel School of Medicine and The Dartmouth Institute for Health Policy & Clinical Practice, Dartmouth College and Dartmouth-Hitchcock, Lebanon, New Hampshire; Division of Geriatric Medicine, School of Medicine, Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill. Chapel Hill, North Carolina
| | - Mintu P Turakhia
- Center for Digital Health, Stanford University, Stanford, California; Palo Alto Veterans Administration Health Care System, Palo Alto, California
| | - Daniel E Forman
- Division of Geriatric Cardiology, University of Pittsburgh, Geriatric Research, Education and Clinical Center; VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania
| | - Gwen M Bernacki
- Cardiovascular Division, Department of Medicine, Cambia Palliative Care Center of Excellence, University of Washington, Seattle, Washington
| | - James N Kirkpatrick
- Cardiovascular Division, Department of Medicine, Department of Bioethics and Humanities, University of Washington, Seattle, Washington
| | - Nicole M Orr
- Post-Acute Cardiology Care, LCC, Darien, Connecticut; Division of Cardiology, Tufts Medical Center, Boston, Massachusetts
| | - Eric D Peterson
- Division of Cardiology, Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina
| | - Michael W Rich
- Cardiovascular Division, Washington University, St. Louis, Missouri
| | - Andrew M Freeman
- Division of Cardiology, Department of Medicine, National Jewish Health, Denver, Colorado
| | - Sanjeev P Bhavnani
- Prebys Cardiovascular Institute, Scripps Clinic & Research Foundation, San Diego, California
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Cohoon TJ, Bhavnani SP. Toward precision health: applying artificial intelligence analytics to digital health biometric datasets. Per Med 2020; 17:307-316. [PMID: 32588726 DOI: 10.2217/pme-2019-0113] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The rapid development of digital health devices has enabled patients to engage in their care to an unprecedented degree and holds the possibility of significantly improving the diagnosis, treatment and monitoring of many medical conditions. Combined with the emergence of artificial intelligence algorithms, biometric datasets produced from these digital health devices present new opportunities to create precision-based, personalized approaches for healthcare delivery. For effective implementation of such innovations to patient care, clinicians will require an understanding of the types of datasets produced from digital health technologies; the types of analytic methods including feature selection, convolution neural networking, and deep learning that can be used to analyze digital data; and how the interpretation of these findings are best translated to patient care. In this perspective, we aim to provide the groundwork for clinicians to be able to apply artificial intelligence to this transformation of healthcare.
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Affiliation(s)
- Travis J Cohoon
- Department of Medicine, Scripps Clinic, San Diego, CA 92037, USA
| | - Sanjeev P Bhavnani
- Division of Cardiology, Healthcare Innovation & Practice Transformation Laboratory, Scripps Clinic, San Diego, CA 92037, USA
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