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Patient-centered Applications: Use of Information Technology to Promote Disease Management and Wellness. A White Paper by the AMIA Knowledge in Motion Working Group
Open accessAbstract
Advances in information technology (IT) have introduced new design approaches that support health care delivery and patient education. Such advances enable a fundamental redesign of health care processes based on the use and integration of electronic communication at all levels. Healthcare IT has the potential to empower patients and support a transition from a role in which the patient is the passive recipient of care services to an active role in which the patient is informed, has choices, and is involved in the decision-making process. New IT tools can enhance and supplement communication between health care professionals and patients. As a result, many informatics researchers and system designers who previously focused on designing IT applications that addressed the needs of health care providers and institutions are shifting toward patient-centered applications. Previous data models included episodic patient encounters as one type of health care transaction but did not capture the life course of the individual patient or consistently take an approach to ensure continuity of care. New technologies and advances in informatics research will enable support of patients as active consumers in a health care delivery system that is evolving from an institution-centric to a patient-centric model.1 Information technology tools can support interventions focusing on disease management and wellness. A disease management intervention is defined as “a set of coordinated health care interventions and communications for populations with conditions in which patient self-care efforts are significant.”2 Disease management programs aim to support patient-specific care plans and the provider-patient relationship via evidence-based guidelines. They focus on prevention of deterioration and/or complications. In the context of consumer empowerment, the paradigm of disease management can be extended to wellness management, where the focus is on the maintenance and improvement of the health status of any individual. Patient-centered applications are defined as systems that enable a partnership among practitioners, patients, and their families (when appropriate) to ensure that procedures and decisions respect patients' needs and preferences. Developers should solicit patients' input regarding the education and support that patients require to make decisions and participate in their own care.3 Such applications bridge clinical and nonclinical sectors and include both individual and population health-oriented tools. They encompass different communication channels such as web-based systems, portable monitoring tools, and mobile devices. The Knowledge in Motion Working Group of the American Medical Informatics Association coalesced from the merger of three previous working groups: Internet, Telehealth, and Mobile Computing. The working group produced this white paper to define the key principles and challenges for designers, policy makers, and evaluators of patient-centered technologies designed for disease prevention and management. The paper reviews current and emerging trends; highlights challenges related to design, evaluation, reimbursement, and usability; and reaches conclusions for next steps that will advance the domain. The Internet provides a platform for consumers to access health information. The number of web-based patient education sites that provide access to information related to patients' conditions has been increasing. The web enables patients communication between patients and health care providers4 or among patients and/or community members. Internet technologies have been utilized for disease management in many clinical areas, e.g., in asthma and diabetes management, where frequent monitoring can lead to early detection of potentially critical situations and timely intervention. In this context, a distinction needs to be made between applications that support pure self-care (without involvement of a health care provider) and applications that provide IT- enabled provider support of self care or disease co-management (vs. the traditional model of provider-administered and controlled care delivery). One example of IT-enabled self care is the home asthma telemonitoring5 system, which provides patients with continuous individualized help in the daily routine of asthma self-care. Extensive evaluations of the CHESS system (Comprehensive Health Enhancement Support System), an interactive computer system containing information, social support, and problem-solving tools for different patient groups (e.g., breast cancer patients, HIV patients), show the potential of web-based applications to increase disease knowledge, education, and social support.6 Most Internet-based health intervention studies have measured immediate, IT-focused nonclinical outcomes of Internet utilization for disease management, including features accessed by the patients,7 patient experience and satisfaction,8 or general health portal reliability.9 I
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Citations
Cites
The productivity paradox of information technology
Brynjolfsson, E. (1993) · Communications of the ACM · doi:10.1145/163298.163309 · Cited by 2,604
Eysenbach, G., Powell, J., Englesakis, M., Rizo, C., & Stern, A. (2004) · BMJ · doi:10.1136/bmj.328.7449.1166 · Cited by 1,268
College Smoking-Cessation Using Cell Phone Text Messaging
Obermayer, J. L., Riley, W. T., Asif, O., & Jean-Mary, J. (2004) · Journal of American College Health · doi:10.3200/jach.53.2.71-78 · Cited by 321
Kazanjian, A., & Green, C. J. (2002) · Computers in Biology and Medicine · doi:10.1016/s0010-4825(02)00013-6 · Cited by 60
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Healthcare in the pocket: Mapping the space of mobile-phone health interventions
Klasnja, P., & Pratt, W. (2012) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2011.08.017 · Cited by 970
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Archer, N., Fevrier-Thomas, U., Lokker, C., McKibbon, K. A., & Straus, S. E. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000105 · Cited by 573
Burke, L. E., Ma, J., Azar, K. M. J., Bennett, G. G., Peterson, E. D., Zheng, Y., Riley, W., Stephens, J., Shah, S. H., Suffoletto, B., et al. (2015) · Circulation · doi:10.1161/cir.0000000000000232 · Cited by 516
Unraveling the meaning of patient engagement: A concept analysis
Higgins, T., Larson, E., & Schnall, R. (2017) · Patient Education and Counseling · doi:10.1016/j.pec.2016.09.002 · Cited by 317
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Stinson, J. N., Lalloo, C., Harris, L., Isaac, L., Campbell, F., Brown, S., Ruskin, D., Gordon, A., Galonski, M., Pink, L. R., et al. (2014) · Pain Research and Management · doi:10.1155/2014/935278 · Cited by 149
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“Individuals' tendencies to carry their phones with them everywhere means that such interventions can provide significantly more touch points, reaching individuals at nearly any time or place [20].”
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Metadata
- Authors
- Demiris, G., Afrin, L. B., Speedie, S., Courtney, K. L., Sondhi, M., Vimarlund, V., Lovis, C., Goossen, W., & Lynch, C.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-01-01
- Volume
- 15
- Issue
- 1
- Pages
- 8-13
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- OpenAlex
- W2164053020
- Cited by
- 310
- References
- 4
- FWCI
- 13.32
- Type
- journal article
- Language
- en
- Open access
- green
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