期刊论文详细信息
BMC Medicine
Patient-centered activity monitoring in the self-management of chronic health conditions
Pronabesh DasMahapatra1  Carlos Rodarte1  Emil Chiauzzi1 
[1] PatientsLikeMe, Inc., 155 Second Street, Cambridge 02141, MA, USA
关键词: Wearables;    Sensors;    Physical activity;    Multiple sclerosis;    Chronic disease;    Activity monitoring;   
Others  :  1160626
DOI  :  10.1186/s12916-015-0319-2
 received in 2014-11-23, accepted in 2015-03-10,  发布年份 2015
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【 摘 要 】

Background

As activity tracking devices become smaller, cheaper, and more consumer-accessible, they will be used more extensively across a wide variety of contexts. The expansion of activity tracking and personal data collection offers the potential for patient engagement in the management of chronic diseases. Consumer wearable devices for activity tracking have shown promise in post-surgery recovery in cardiac patients, pulmonary rehabilitation, and activity counseling in diabetic patients, among others. Unfortunately, the data generated by wearable devices is seldom integrated into programmatic self-management chronic disease regimens. In addition, there is lack of evidence supporting sustained use or effects on health outcomes, as studies have primarily focused on establishing the feasibility of monitoring activity and the association of measured activity with short-term benefits.

Discussion

Monitoring devices can make a direct and real-time impact on self-management, but the validity and reliability of measurements need to be established. In order for patients to become engaged in wearable data gathering, key patient-centered issues relating to usefulness in care, motivation, the safety and privacy of information, and clinical integration need to be addressed. Because the successful usage of wearables requires an ability to comprehend and utilize personal health data, the user experience should account for individual differences in numeracy skills and apply evidence-based behavioral science principles to promote continued engagement.

Summary

Activity monitoring has the potential to engage patients as advocates in their personalized care, as well as offer health care providers real world assessments of their patients’ daily activity patterns. This potential will be realized as the voice of the chronic disease patients is accounted for in the design of devices, measurements are validated against existing clinical assessments, devices become part of the treatment ‘prescription’, behavior change programs are used to engage patients in self-management, and best practices for clinical integration are defined.

【 授权许可】

   
2015 Chiauzzi et al.; licensee BioMed Central.

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【 参考文献 】
  • [1]Fox S, Duggan M. Tracking for health. Pew Internet & American Life Project. 2013. http://www.pewinternet.org/2013/01/28/tracking-for-health. Accessed 29 Sept 2014.
  • [2]Wang T. Future of biosensing wearables. Rock Health. 2014. http://rockhealth.com/resources/rock-reports/future-biosensing-wearables. Accessed 29 Sept 2014.
  • [3]Sarasohn-Kahn J. Making sense of sensors: how new technologies can change patient care. California Healthcare Foundation. 2013. http://www.chcf.org/publications/2013/02/making-sense-sensors. Accessed 29 Sept 2014.
  • [4]Lyons EJ, Lewis ZH, Mayrsohn BG, Rowland JL: Behavior change techniques implemented in electronic lifestyle activity monitors: a systematic content analysis. J Med Internet Res 2014, 16:192.
  • [5]Ledger D, McCaffrey D. How the science of human behavior change offers the secret to long-term engagement. Endeavour Partners 2014. http://endeavourpartners.net/assets/Endeavour-Partners-Wearables-and-the-Science-of-Human-Behavior-Change-Part-1-January-20141.pdf. Accessed 8 Oct 2014.
  • [6]Lauritzen J, Muñoz A, Sevillano JL, Civit A: The usefulness of activity trackers in elderly with reduced mobility: a case study. Stud Health Technol Inform 2013, 192:759-62.
  • [7]Shammas L, Zentek T, von Haaren B, Schlesinger S, Hey S, Rashid A: Home-based system for physical activity monitoring in patients with multiple sclerosis (Pilot study). Biomed Eng Online 2014, 13:10. BioMed Central Full Text
  • [8]Blikman LJ, van Meeteren J, Horemans HL, Kortenhorst IC, Beckerman H, Stam HJ, et al.: Is physical behavior affected in fatigued persons with multiple sclerosis? Arch Phys Med Rehabil 2014, 14:1063-106.
  • [9]Cook DJ, Thompson JE, Prinsen SK, Dearani JA, Deschamps C: Functional recovery in the elderly after major surgery: assessment of mobility recovery using wireless technology. Ann Thorac Surg 2013, 96:1057-61.
  • [10]Benzo R: Activity monitoring in chronic obstructive pulmonary disease. J Cardiopulm Rehabil Prev 2009, 29:341-7.
  • [11]Vaes AW, Cheung A, Atakhorrami M, Groenen MT, Amft O, Franssen FM, et al.: Effect of ‘activity monitor-based’ counseling on physical activity and health-related outcomes in patients with chronic diseases: a systematic review and meta-analysis. Ann Med 2013, 45:397-412.
  • [12]Allet L, Knols RH, Shirato K, de Bruin ED: Wearable systems for monitoring mobility-related activities in chronic disease: a systematic review. Sensors 2010, 10:9026-52.
  • [13]Barwais FA, Cuddihy TF, Tomson LM: Physical activity, sedentary behavior and total wellness changes among sedentary adults: a 4-week randomized controlled trial. Health Qual Life Outcomes 2013, 11:183. BioMed Central Full Text
  • [14]Freak-Poli RL, Wolfe R, Walls H, Backholer K, Peeters A: Participant characteristics associated with greater reductions in waist circumference during a four-month, pedometer-based, workplace health program. BMC Public Health 2011, 11:824. BioMed Central Full Text
  • [15]Tudor-Locke C, Lutes L: Why do pedometers work? A reflection upon the factors related to successfully increasing physical activity. Sports Med 2009, 39:981-93.
  • [16]Patel S, Park H, Bonato P, Chan L, Rodgers M: A review of wearable sensors and systems with application in rehabilitation. J Neuroeng Rehabil 2012, 9:21. BioMed Central Full Text
  • [17]Wicks P, Vaughan T, Heywood J: Subjects no more: what happens when trial participants realize they hold the power? Br Med J 2014, 348:g368.
  • [18]PricewaterhouseCoopers. The wearable future. 2014. http://www.pwc.com/us/en/industry/entertainment-media/publications/consumer-intelligence-series. Accessed 9 Feb 2015.
  • [19]Health Data Exploration Project. Personal data for the public good: new opportunities to enrich understanding of individual and population health. California Institute for Telecommunications and Information Technology. 2014. http://www.rwjf.org/content/dam/farm/reports/reports/2014/rwjf411080. Accessed 20 Oct 2014.
  • [20]Takacs J, Pollock CL, Guenther JR, Bahar M, Napier C, Hunt MA: Validation of the Fitbit One activity monitor device during treadmill walking. J Sci Med Sport 2014, 17:472-6.
  • [21]Adam NJ, Spierer DK, Gu J, Bronner S: Comparison of steps and energy expenditure assessment in adults of Fitbit Tracker and Ultra to the Actical and indirect calorimetry. J Med Eng Technol 2013, 37:456-62.
  • [22]Lee JM, Kim Y, Welk GJ: Validity of consumer-based physical activity monitors. Med Sci Sports Exerc 2014, 46:1840-8.
  • [23]Wile DJ, Ranawaya R, Kiss ZH: Smart watch accelerometry for analysis and diagnosis of tremor. J Neurosci Methods 2014, 230:1-4.
  • [24]Albinali F, Intille S, Haskell W, Rosenberger M. Using wearable activity type detection to improve physical activity energy expenditure estimation. In Proceedings of the 12th Association for Computing Machinery international Conference on Ubiquitous Computing: 26–29 September 2010.
  • [25]Vooijs M, Alpay LL, Snoeck-Stroband JB, Beerthuizen T, Siemonsma PC, Abbink JJ, et al.: Validity and usability of low-cost accelerometers for internet-based self-monitoring of physical activity in patients with chronic obstructive pulmonary disease. Interact J Med Res 2014, 3:e14.
  • [26]National Center for Education Statistics. 2003 National Assessment of Adult Literacy. US Department of Education. 2003. http://nces.ed.gov/pubs2003/2003495rev.pdf. Accessed 29 Sept 2014.
  • [27]Rothman RL, Montori VM, Cherrington A, Pignone MP: Perspective: the role of numeracy in health care. J Health Commun 2008, 13:583-95.
  • [28]Fogg BJ, Cuellar G, Danielson DR: Motivating, influencing, and persuading users. In The human-computer interaction handbook: fundamentals, evolving technologies, and emerging applications. 2nd edition. Edited by Jacko JA, Sears A. Lawrence Erlbaum Associates, New York; 2007:133-44.
  • [29]Nelson R, Hayes SC: Theoretical explanations for reactivity in self-monitoring. Behav Modif 1981, 5:3-14.
  • [30]Patel MS, Asch DA, Volpp KG: Wearable devices as facilitators, not drivers, of health behavior change. JAMA 2015, 313:459-60.
  • [31]Swan M: Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking. Int J Environ Res Public Health 2009, 6:492-525.
  • [32]Grajales F, Clifford D, Loupos P, Okun S, Quattrone S, Simon M, et al. Social networking sites and the continuously learning health system: a survey. Institute of Medicine. 2014. http://www.iom.edu/~/media/Files/Perspectives-Files/2014/Discussion-Papers/VSRT-PatientDataSharing.pdf. Accessed 10 Oct 2014.
  • [33]Patankar T. Accenture interactive: four in five consumers cite privacy concerns for wearable tech adoption, according to 2014 State of the Internet of Things Study. Accenture. 2014. http://newsroom.accenture.com/news/four-in-five-consumers-cite-privacy-concerns-for-wearable-tech-adoption-according-to-2014-state-of-the-internet-of-things-study-from-accenture-interactive.htm. Accessed 11 Feb 2015.
  • [34]Boonstra A, Broekhuis M: Barriers to the acceptance of electronic medical records by physicians from systematic review to taxonomy and interventions. BMC Health Serv Res 2010, 10:231. BioMed Central Full Text
  • [35]ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories: ATS statement: guidelines for the six-minute walk test Am J Respir Crit Care Med 2002, 166:111-7.
  • [36]Deloitte Centre for Health Solutions. Healthcare and life sciences predictions 2020: a bold future? Deloitte Touche Tohmatsu Limited. 2014. http://www2.deloitte.com/content/dam/Deloitte/global/Documents/Life-Sciences-Health-Care/gx-lshc-healthcare-and-life-sciences-predictions-2020.pdf. Accessed 10 Feb 2015.
  • [37]Center for Sustainable Health: Project Honeybee. http://sustainablehealth.org/honeybee 2015. Accessed 10 Feb 2015.
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