Abstract—Many older adults in the US prefer to live independently for as long as they are able, despite the onset of conditions such as frailty and dementia. Sensor networks have emerged in the last decade, together with telehealth and internet based electronic health records (EHR), as a possible solution to older adult health monitoring. Many commercial solutions for EHRs, telehealth monitoring and sensor networks are available but, as far as we know, no integrated system exists. In this paper we present an integrated eldercare EHR system (IEEHR) that merges health data with sensor and telehealth (vital signs) measurements. The benefit of an EEHR system is three fold: provides physicians a wider gamut of tools for chronic disease management, reduces nursing workload and allows the development of health context aware algorithms for predictive health assessment. In this paper we present the integrated EEHR system we are developing at TigerPlace, an assisted living community in Columbia, Missouri. Several examples of possible applications are also presented. Index Terms—Eldercare, Electronic Health Records, Sensor Networks, Telemedicine, Predictive Health Assessment I. INTRODUCTION ANY older adults in the US prefer to live independently for as long as they are able, despite the onset of conditions such as frailty and dementia. Elderly patients are particularly at-risk for late assessment of physical or cognitive changes due to many factors: their impression that such changes are simply a normal part of aging; their reluctance to admit to a problem; their fear of being institutionalized; and even the failure of physicians to fully assess their function due to the belief that no intervention is possible [1].Solutions are needed to enable independent living while enhancing safety and peace of mind for the elder adults’ families [3], [2]. Sensor networks, telehealth and internet based EHRs have emerged in the last decade as possible solutions to older adult health monitoring. Elderly monitoring using sensor networks has traditionally evolved from home security solutions and it mostly involves motion detectors, such as GE QuietCare, and/or video cameras, such as the solutions M.P. is with the Health Management and Informatics Department, University of Missouri, Columbia, MO 65211, USA (corresponding author, phone: 573-882-1266; fax: 573-882-6158; e-mail: popescum@missouri.edu). G.C. is with CyberSense, LLC, USA, email: george@cybersense.us R.O. is with the Carolinas Medical Center, Charlotte, NC. M.S. is with the Electrical and Computer Engineering Department, University of Missouri, Columbia, email: sckubicm@missouri.edu M.R. is with the University of Missouri Sinclair School of Nursing. offered by Acadian Monitoring Services, Inc., (http://www.americaonwatchnetwork.com.) Telehealth solutions are mostly used by nursing organizations to monitor selected patients with chronic diseases such as diabetes, PTSD and depression. Many suppliers of telehealth equipment (blood pressure, blood oxygen, blood sugar and weight monitoring together with the data transmission hub) are available such as Honeywell’s (http://www.honeywell.com) Genesis suite, Bayes’ (http://bayer.com) Viterion products and Tunstall’s (http://www.tunstall.co.uk) ADLife system. Commercial nursing electronic medical records (EMR) systems are offered by many companies such as: SigmaCare (http://www.sigmacare.com), HealthMEDX (http://www.healthmedx.com), Mobile Physician Technologies (http://www.par3emr.com) and AOD Software (http://www.aodsoftware.com). In spite of the crowded EMR software market only 1% of the US skilled nursing facilities have adopted an EMR as opposed to 18% of the US hospitals [4]. Several academic monitoring environments such as MIT’s PlaceLab [5], Georgia Tech’s Aware House [6] and Honeywell’s Independent Lifestyle Assistant [7] have been demonstrated. Many other monitoring solutions for older adults such as the ones found in [8], [9], [10] and [1], employed a variety of sensors and algorithms to detect activity patterns and assess medication compliance, fall risk or dementia. In this paper we present an integrated eldercare EHR system (IEEHR) that merges health data with sensors and telehealth (vital signs) measurements. The benefit of an IEEHR system is three fold: provides physicians more tools for chronic disease management, reduces nursing workload and allows the development of health context aware algorithms for predictive health assessment. As far as we know, none of the existing monitoring solutions has considered the health context of the resident in developing monitoring algorithms. For example, a hospitalization may change the normal behavior, while a medication change may affect sleep patterns or fall risk. The IEEHR we develop at an aging in place facility, TigerPlace, situated in Columbia, Missouri [12], allows us to introduce health context aware monitoring algorithms able to detect and predict early signs of illness and functional decline based on telehealth and sensor data. The structure of the paper is as follows: in section II we present the architecture of our IEEHR, in section III we describe in more details the EHR component, in section IV An Eldercare Electronic Health Record System for Predictive Health Assessment Mihail Popescu, George Chronis, Rohan Ohol, Marjorie Skubic, Marilyn Rantz M 2011 IEEE 13th International Conference on e-Health Networking, Applications and Services 978-1-61284-696-5/11/$26.00 ©2011 IEEE 193