Smart Homes and Ambient Assisted Living Applications: From Data to KnowledgeEmpowering or Overwhelming Older Adults?

Summary

Objectives

As health care systems face limited resources and workforce shortages to address the complex needs of older adult populations, innovative approaches utilizing information technology can support aging. Smart Home and Ambient Assisted Living (SHAAL) systems utilize advanced and ubiquitous technologies including sensors and other devices that are integrated in the residential infrastructure or wearable, to capture data describing activities of daily living and health related events. This paper highlights how data from SHAAL systems can lead to information and knowledge that ultimately improves clinical outcomes and quality of life for older adults as well as quality of health care services.

Methods

We conducted are view of personal health record applications specifically for older adults and approaches to using information to improve elder care. We present a framework that show cases how data captured from SHAAL systems can be processed to provide meaningful information that becomes part of a personal health record.

Results

Synthesis and visualization of information resulting from SHAAL systems can lead to knowledge and support education, delivery of tailored interventions and if needed, transitions in care. Such actions can involve multiple stakeholders as part of shared decision making.

Conclusion

SHAAL systems have the potential to support aging and improve quality of life and decision making for older adults and their families. The framework presented in this paper demonstrates how emphasis needs to be placed into extracting meaningful information from new innovative systems that will support decision making. The challenge for informatics designers and researchers is to facilitate an evolution of SHAAL systems expanding beyond demonstration projects to actual interventions that will improve health care for older adults.

Keywords

Smart homes - ambient assisted living - shared decision making - personal health record - gerontology - geriatrics

• References

• 1 US Department of Health and Human Services-Administration on Aging (2005). 65+ in the United States: 2005. Available at http://www.census.gov/prod/2006pubs/p23-209.pdf
• 2 W.M. Kellogg Foundation. Timelye Opportunities: What Works in Community Care for the Elderly. Monograph Item Nr. MO747. 1997
• 3 Demiris G, Hensel BK. Technologies for an aging society: a systematic review of “smart home” applications. Yearb Med Inform 2008; 33-40.
• 4 Abowd GD, Mynatt ED. Charting Past, Present and Future Research in Ubiquitous Computing. ACM Trans Comput Hum Interact 2000; 07 (01) 29-58.
• 5 Marsh J. House Calls. Rochester Review 2002; 64 (03) 22-6.
• 6 Kidd CD, Orr R, Abowd GD, Atkeson CG, Essa IA, MacIntyre B. et al. The Aware Home: A Living Laboratory for Ubiquitous Computing Research. Proceedings of CoBuild. 1999
• 7 Cash M. Assistive technology and people with dementia. Rev Clin Gerontol 2003; 13 (04) 313-9.
• 8 Ackoff RL. From Data to Wisdom. Journal of Applied Systems Analysis 1989; 16: 3-9.
• 9 Bonander J, Gates S. Public Health in an Era of Personal Health Records: Opportunities for Innovation and New Partnerships. J Med Internet Res 2010; 12 (03) e33 Retrieved from: http://www.jmir.org/2010/3/e33/
• 10 National Alliance for Health Information Technology. Defining Key Health Information Technology Terms 2008. Available online at: http://www.nahit.org/images/pdfs/HITTermsFinalReport_051508.pdf
• 11 Kahn JS, Aulakh V, Bosworth A. What it takes: Characteristics of the ideal personal health record. Health Aff 2009; 28: 369-76.
• 12 Hassol A, Walker JM, Kidder D, Rokita K, Young D, Pierdon S. et al. Patient experiences and attitudes about access to a patient electronic health care record and linked web messaging. J Am Med Inform Assoc 2004; 11 (06) 505-13.
• 13 Demiris G. Information Technology and Systems in Home Health Care. In: National Research Council of the National Academies: The Role of Human Factors in Home Health Care. The National Academies Press; 2010: 173-99.
• 14 Tang PC, Ash JS, Bates DW, Overhage JM, Sands DZ. Personal health records: definitions, benefits, and strategies for overcoming barriers to adoption. J Am Med Inform Assoc 2006; 13 (02) 121-6.
• 15 Witry MJ, Doucette WR, Daly JM, Levy BT, Chrischilles EA. Family Physician Perceptions of Personal Health Records. Perspectives in Health Information Management 2010; 7 (Winter): 1d.
• 16 Weitzman ER, Kaci L, Mandl KD. Acceptability of a personally controlled health record in a communitybased setting: implications for policy and design. J Med Internet Res 2009; 11 (02) e14 Retrieved from: http://www.jmir.org.offcampus.lib.washington.edu/2009/2/e14/
• 17 Kim EH, Stolyar A, Lober WB, Herbaugh AL, Shinstrom SE, Zierler BK. et al. Challenges to Using an Electronic Personal Health Record by a Low-Income Elderly Population. J Med Internet Res 2009; 11 (04) e44 Retrieved from: http://www.jmir.org/2009/4/e44/
• 18 McInnes DK, Gifford AL, Kazis LE, Wagner TH. Disparities in health-related internet use by US veterans: results from a national survey. Inform Prim Care 2010; 18 (01) 59-68.
• 19 Nazi KM. Veterans’ voices: use of the American Customer Satisfaction Index (ACSI) Survey to identify My HealtheVet personal health record users’ characteristics, needs, and preferences. J Am Med Inform Assoc 2010; Mar-Apr; 17 (02) 203-11.
• 20 Pagliari C, Detmer D, Singleton P. Potential of electronic personal health records. BMJ 2007; Aug 18; 335 (7615): 330-3.
• 21 Weitzman ER, Kaci L, Mandl KD. Sharing medical data for health research: the early personal health record experience. J Med Internet Res 2010; May 25; 12 (02) e14 Retrieved from: http://www.jmir.org/2010/2/e14/
• 22 Fonda SJ, Kedziora RJ, Vigersky RA, Bursell SE. Combining iGoogle and personal health records to create a prototype personal health application for diabetes self-management. Telemed J E Health 2010; 16 (04) 480-9.
• 23 Hoerbst A, Kohl CD, Knaup P, Ammenwerth E. Attitudes and behaviors related to the introduction of electronic health records among Austrian and German citizens. Int J Med Inform 2010; 79 (02) 81-9.
• 24 Brundage M, Feldman-Stewart D, Leis A. et al. Communicating quality of life information to cancer patients: a study of six presentation formats. Journal of Clinical Oncology 2005; 23 (28) 6949-56.
• 25 Hoeke JO, Bonke B, van Strik R, Gelsema ES. Evaluation of techniques for the presentation of laboratory data: support of pattern recognition. Methods Inf Med 2000; 39 (01) 88-92.
• 26 Elting LS, Martin CG, Cantor SB, Rubenstein EB. Influence of data display formats on physician investigators’ decisions to stop clinical trials: prospective trial with repeated measures. BMJ 1999; 318 (7197): 1527-31.
• 27 Curran CR. Data display techniques. Appl Nurs Res Aug 1999; 12 (03) 153-8.
• 28 Berton J. Semiology of Graphs. Madison, WI: University of Wisconsin Press; 1983
• 29 Carpenter PA, Shaw PA. A model of the perceptual and conceptual processes in graph comprehension. J Expl Psychol 1998; 04: 75-100.
• 30 Shaw PA, Mayer RE, Hagarty M. Graphs as aids to knowledge construction: Signaling techniques for guiding the process of graph comprehension. Journal of Educational Psychology 1999; 91: 690-72.
• 31 Standing L, Conezio J, Haber R. Perception and memory for pictures: Single0trial learning of 2500 visual stimuli. Psychonomic Science 1970; 19: 73-4.
• 32 Tufte ER. The visual display of quantitative information. Cheshire, CT: Graphics Press; 1983
• 33 Cleveland WS, McGill R. Graphical perception: Theory, experimentation and application to the development of graphical methods. J Am Stat Assoc 1984; 79: 531-54.
• 34 Stewart M. Studies of health outcomes and patientcentered communication. In: Stewart M, Brown JB, Weston WW, McWhinney IR, McWilliam C, Freeman TR. editors. Patient-Centered Medicine: Transforming the Clinical Methods. Thousand Oaks, CA: Sage; 1995
• 35 Savage R, Armstrong D. Effect of a general practitioner’s consulting style on patient satisfaction: a controlled study. BMJ 1990; 301: 968-70.
• 36 Kinmonth AL, Woodcock A, Griffin S, Spiegal N, Campbell MJ. Randomized controlled trial of patient-centered care of diabetes in general practice: impact on current wellbeing and future disease risk. BMJ 1998; 317: 1202-8.
• 37 Stewart M, Brown JB, Weston WW, McWhinney IR, McWilliam C, Freeman TR. Patient Centered Medicine: Transforming the Clinical Method. Thousand Oaks, CA: Sage; 1995
• 38 Roter D. Which facets of communication have strong effects on outcome-a meta analysis. In Stewart M. editor. Communicating with medical patients. Thousand Oaks, CA: Sage; 1989
• 39 Mead N, Bower P. Patient centredness: a conceptual framework and review of the empirical literature. Soc Sci Med 2000; 51: 1087-110.
• 40 Mead N, Bower P. Measuring patient centredness: a comparison of three observation based instruments. Patient Educ Couns 2000; 39: 71-80.
• 41 Richards T. Partnership with patients. BMJ 1998; 316: 85-6.
• 42 Coulter A, Entwistle V, Gilbert D. Sharing decisions with patients: is the information good enough?. BMJ 1999; 318: 318-22.
• 43 Coulter A. Paternalism or partnership?. BMJ 1999; 319: 719-94.
• 44 Charles CA, Whelan T, Gafni A, Willan A, Farrell S. Shared Treatment Decision Making: What does it mean to physicians?. J Clin Oncol 2003; 21 (05) 932-6.
• 45 Charles CA, Gafni A, Whelan T. Decision-making in the physician-patient encounter: revisiting the shared treatment decision making model. Social Science and Medicine 1999; 49: 651-61.
• 46 Guadagnoli E, Ward P. Patient satisfaction in decision making. Social Science and Medicine 1998; 47: 329-39.
• 47 International Medical Informatics Association Working Group on Smart Homes and Ambient Assisted Living. http://www.health-smarthomes.org